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wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/stc.py
|
python
|
StyledTextCtrl.AutoCompSetCancelAtStart
|
(*args, **kwargs)
|
return _stc.StyledTextCtrl_AutoCompSetCancelAtStart(*args, **kwargs)
|
AutoCompSetCancelAtStart(self, bool cancel)
Should the auto-completion list be cancelled if the user backspaces to a
position before where the box was created.
|
AutoCompSetCancelAtStart(self, bool cancel)
|
[
"AutoCompSetCancelAtStart",
"(",
"self",
"bool",
"cancel",
")"
] |
def AutoCompSetCancelAtStart(*args, **kwargs):
"""
AutoCompSetCancelAtStart(self, bool cancel)
Should the auto-completion list be cancelled if the user backspaces to a
position before where the box was created.
"""
return _stc.StyledTextCtrl_AutoCompSetCancelAtStart(*args, **kwargs)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/stc.py#L3103-L3110
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/grid.py
|
python
|
Grid.SetDefaultCellAlignment
|
(*args, **kwargs)
|
return _grid.Grid_SetDefaultCellAlignment(*args, **kwargs)
|
SetDefaultCellAlignment(self, int horiz, int vert)
|
SetDefaultCellAlignment(self, int horiz, int vert)
|
[
"SetDefaultCellAlignment",
"(",
"self",
"int",
"horiz",
"int",
"vert",
")"
] |
def SetDefaultCellAlignment(*args, **kwargs):
"""SetDefaultCellAlignment(self, int horiz, int vert)"""
return _grid.Grid_SetDefaultCellAlignment(*args, **kwargs)
|
[
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/grid.py#L1958-L1960
|
|
reverbrain/elliptics
|
4b4f9b8094d7616c1ec50eb8605edb059b9f228e
|
bindings/python/src/route.py
|
python
|
RouteList.get_address_backend_routes
|
(self, address, backend_id)
|
return tuple(route for route in self.routes if (route.address, route.backend_id) == (address, backend_id))
|
Returns all routes for specified @address and @backend_id
|
Returns all routes for specified
|
[
"Returns",
"all",
"routes",
"for",
"specified"
] |
def get_address_backend_routes(self, address, backend_id):
"""
Returns all routes for specified @address and @backend_id
"""
return tuple(route for route in self.routes if (route.address, route.backend_id) == (address, backend_id))
|
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https://github.com/reverbrain/elliptics/blob/4b4f9b8094d7616c1ec50eb8605edb059b9f228e/bindings/python/src/route.py#L309-L313
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/io_ops.py
|
python
|
_restore_slice
|
(file_pattern, tensor_name, shape_and_slice, tensor_type,
name="restore_slice", preferred_shard=-1)
|
return gen_io_ops.restore_slice(
file_pattern, tensor_name, shape_and_slice, base_type,
preferred_shard, name=name)
|
Restore a tensor slice from a set of files with a given pattern.
Example usage:
RestoreSlice("/foo/bar-?????-of-?????", "w", "10 10 0,2:-", DT_FLOAT)
Args:
file_pattern: the file pattern used to match a set of checkpoint files.
tensor_name: the name of the tensor to restore.
shape_and_slice: the shape-and-slice spec of the slice.
tensor_type: the type of the tensor to restore.
name: string. Optional name for the op.
preferred_shard: Int. Optional shard to open first in the checkpoint file.
Returns:
A tensor of type "tensor_type".
|
Restore a tensor slice from a set of files with a given pattern.
|
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"."
] |
def _restore_slice(file_pattern, tensor_name, shape_and_slice, tensor_type,
name="restore_slice", preferred_shard=-1):
"""Restore a tensor slice from a set of files with a given pattern.
Example usage:
RestoreSlice("/foo/bar-?????-of-?????", "w", "10 10 0,2:-", DT_FLOAT)
Args:
file_pattern: the file pattern used to match a set of checkpoint files.
tensor_name: the name of the tensor to restore.
shape_and_slice: the shape-and-slice spec of the slice.
tensor_type: the type of the tensor to restore.
name: string. Optional name for the op.
preferred_shard: Int. Optional shard to open first in the checkpoint file.
Returns:
A tensor of type "tensor_type".
"""
base_type = dtypes.as_dtype(tensor_type).base_dtype
return gen_io_ops.restore_slice(
file_pattern, tensor_name, shape_and_slice, base_type,
preferred_shard, name=name)
|
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/io_ops.py#L75-L96
|
|
greearb/xorp.ct
|
b8942f69e9cb69a35adcaa58f3dd6b9a16629e6a
|
xorp/bgp/harness/harness.py
|
python
|
stop
|
()
|
Stop collecting data into the log file
|
Stop collecting data into the log file
|
[
"Stop",
"collecting",
"data",
"into",
"the",
"log",
"file"
] |
def stop():
"""
Stop collecting data into the log file
"""
coord("peer1 dump sent mrtd ipv4 traffic")
coord("peer1 dump recv mrtd ipv4 traffic")
|
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"\"peer1 dump sent mrtd ipv4 traffic\"",
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https://github.com/greearb/xorp.ct/blob/b8942f69e9cb69a35adcaa58f3dd6b9a16629e6a/xorp/bgp/harness/harness.py#L103-L109
|
||
sdhash/sdhash
|
b9eff63e4e5867e910f41fd69032bbb1c94a2a5e
|
external/tools/build/v2/build/build_request.py
|
python
|
expand_no_defaults
|
(property_sets)
|
return [property_set.create(p) for p in product]
|
Expand the given build request by combining all property_sets which don't
specify conflicting non-free features.
|
Expand the given build request by combining all property_sets which don't
specify conflicting non-free features.
|
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"free",
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] |
def expand_no_defaults (property_sets):
""" Expand the given build request by combining all property_sets which don't
specify conflicting non-free features.
"""
# First make all features and subfeatures explicit
expanded_property_sets = [ps.expand_subfeatures() for ps in property_sets]
# Now combine all of the expanded property_sets
product = __x_product (expanded_property_sets)
return [property_set.create(p) for p in product]
|
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https://github.com/sdhash/sdhash/blob/b9eff63e4e5867e910f41fd69032bbb1c94a2a5e/external/tools/build/v2/build/build_request.py#L16-L26
|
|
neoml-lib/neoml
|
a0d370fba05269a1b2258cef126f77bbd2054a3e
|
NeoML/Python/neoml/Blob.py
|
python
|
asblob
|
(math_engine, data, shape=None, copy=False)
|
return Blob(PythonWrapper.tensor(math_engine._internal, shape, dtype, np_data, bool(copy)))
|
Organizes the data from a memory buffer into a blob.
:param neoml.MathEngine.MathEngine math_engine: the math engine that works with this blob.
:param data: a pointer to the data.
:type data: object
:param shape: the target blob dimensions. If none are specified,
a one-element blob will be assumed.
:type shape: array of int, default=None
:param copy: specifies if the data should be copied to another memory block
or kept in the same place if possible, making the data parameter
point to the body of the newly-created blob.
Not copying may be impossible if the blob is in GPU memory.
:type copy: bool, default=False
|
Organizes the data from a memory buffer into a blob.
|
[
"Organizes",
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"into",
"a",
"blob",
"."
] |
def asblob(math_engine, data, shape=None, copy=False):
"""Organizes the data from a memory buffer into a blob.
:param neoml.MathEngine.MathEngine math_engine: the math engine that works with this blob.
:param data: a pointer to the data.
:type data: object
:param shape: the target blob dimensions. If none are specified,
a one-element blob will be assumed.
:type shape: array of int, default=None
:param copy: specifies if the data should be copied to another memory block
or kept in the same place if possible, making the data parameter
point to the body of the newly-created blob.
Not copying may be impossible if the blob is in GPU memory.
:type copy: bool, default=False
"""
if shape is None:
shape = np.ones(7, np.int32)
else:
shape = np.array(shape, dtype=np.int32, copy=False)
if len(shape) != 7:
raise ValueError('The `shape` must have 7 dimension sizes.')
np_data = np.array(data, copy=False, order='C')
if len(np_data.shape) > 7:
raise ValueError('The `shape` must have not more then 7 dimensions.')
if np.prod(np_data.shape) != np.prod(shape):
raise ValueError('The blob must have as many elements as ndarray')
dtype = 'none'
if np_data.dtype == np.float32:
dtype = 'float32'
elif np_data.dtype == np.int32:
dtype = 'int32'
else:
raise ValueError('The `dtype` must be one of {`float32`, `int32`}.')
if type(math_engine) is MathEngine.GpuMathEngine:
copy = True
return Blob(PythonWrapper.tensor(math_engine._internal, shape, dtype, np_data, bool(copy)))
|
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https://github.com/neoml-lib/neoml/blob/a0d370fba05269a1b2258cef126f77bbd2054a3e/NeoML/Python/neoml/Blob.py#L294-L339
|
|
kamyu104/LeetCode-Solutions
|
77605708a927ea3b85aee5a479db733938c7c211
|
Python/max-chunks-to-make-sorted.py
|
python
|
Solution2.maxChunksToSorted
|
(self, arr)
|
return len(increasing_stk)
|
:type arr: List[int]
:rtype: int
|
:type arr: List[int]
:rtype: int
|
[
":",
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":",
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] |
def maxChunksToSorted(self, arr):
"""
:type arr: List[int]
:rtype: int
"""
result, increasing_stk = 0, []
for num in arr:
max_num = num if not increasing_stk else max(increasing_stk[-1], num)
while increasing_stk and increasing_stk[-1] > num:
increasing_stk.pop()
increasing_stk.append(max_num)
return len(increasing_stk)
|
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https://github.com/kamyu104/LeetCode-Solutions/blob/77605708a927ea3b85aee5a479db733938c7c211/Python/max-chunks-to-make-sorted.py#L22-L33
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
Framework/PythonInterface/plugins/algorithms/EnggEstimateFocussedBackground.py
|
python
|
EnggEstimateFocussedBackground.doIterativeSmoothing
|
(self, y, nwindow, maxdepth, depth=0)
|
Iterative smoothing procedure to estimate the background in powder diffraction as published in
Bruckner J. Appl. Cryst. (2000). 33, 977-979
:param y: signal to smooth
:param n: size of window for convolution
:param maxdepth: max depth of recursion (i.e. number of iterations)
:param depth: current iteration
:return:
|
Iterative smoothing procedure to estimate the background in powder diffraction as published in
Bruckner J. Appl. Cryst. (2000). 33, 977-979
:param y: signal to smooth
:param n: size of window for convolution
:param maxdepth: max depth of recursion (i.e. number of iterations)
:param depth: current iteration
:return:
|
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def doIterativeSmoothing(self, y, nwindow, maxdepth, depth=0):
"""
Iterative smoothing procedure to estimate the background in powder diffraction as published in
Bruckner J. Appl. Cryst. (2000). 33, 977-979
:param y: signal to smooth
:param n: size of window for convolution
:param maxdepth: max depth of recursion (i.e. number of iterations)
:param depth: current iteration
:return:
"""
# smooth with hat function
yy = np.copy(y)
yy = np.convolve(yy, np.ones(nwindow) / nwindow, mode="same")
# normalise end values effected by convolution
ends = np.convolve(np.ones(nwindow), np.ones(nwindow) / nwindow, mode='same')
yy[0:nwindow // 2] = yy[0:nwindow // 2] / ends[0:nwindow // 2]
yy[-nwindow // 2:] = yy[-nwindow // 2:] / ends[-nwindow // 2:]
if depth < maxdepth:
# compare pt by pt with original and keep lowest
idx = yy > y
yy[idx] = y[idx]
return self.doIterativeSmoothing(yy, nwindow, maxdepth, depth + 1)
else:
return yy
|
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/PythonInterface/plugins/algorithms/EnggEstimateFocussedBackground.py#L119-L142
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/scipy/signal/signaltools.py
|
python
|
decimate
|
(x, q, n=None, ftype='iir', axis=-1, zero_phase=None)
|
return y[sl]
|
Downsample the signal after applying an anti-aliasing filter.
By default, an order 8 Chebyshev type I filter is used. A 30 point FIR
filter with Hamming window is used if `ftype` is 'fir'.
Parameters
----------
x : ndarray
The signal to be downsampled, as an N-dimensional array.
q : int
The downsampling factor. For downsampling factors higher than 13, it is
recommended to call `decimate` multiple times.
n : int, optional
The order of the filter (1 less than the length for 'fir'). Defaults to
8 for 'iir' and 30 for 'fir'.
ftype : str {'iir', 'fir'} or ``dlti`` instance, optional
If 'iir' or 'fir', specifies the type of lowpass filter. If an instance
of an `dlti` object, uses that object to filter before downsampling.
axis : int, optional
The axis along which to decimate.
zero_phase : bool, optional
Prevent phase shift by filtering with `filtfilt` instead of `lfilter`
when using an IIR filter, and shifting the outputs back by the filter's
group delay when using an FIR filter. A value of ``True`` is
recommended, since a phase shift is generally not desired. Using
``None`` defaults to ``False`` for backwards compatibility. This
default will change to ``True`` in a future release, so it is best to
set this argument explicitly.
.. versionadded:: 0.18.0
Returns
-------
y : ndarray
The down-sampled signal.
See Also
--------
resample : Resample up or down using the FFT method.
resample_poly : Resample using polyphase filtering and an FIR filter.
Notes
-----
The ``zero_phase`` keyword was added in 0.18.0.
The possibility to use instances of ``dlti`` as ``ftype`` was added in
0.18.0.
|
Downsample the signal after applying an anti-aliasing filter.
|
[
"Downsample",
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"after",
"applying",
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"anti",
"-",
"aliasing",
"filter",
"."
] |
def decimate(x, q, n=None, ftype='iir', axis=-1, zero_phase=None):
"""
Downsample the signal after applying an anti-aliasing filter.
By default, an order 8 Chebyshev type I filter is used. A 30 point FIR
filter with Hamming window is used if `ftype` is 'fir'.
Parameters
----------
x : ndarray
The signal to be downsampled, as an N-dimensional array.
q : int
The downsampling factor. For downsampling factors higher than 13, it is
recommended to call `decimate` multiple times.
n : int, optional
The order of the filter (1 less than the length for 'fir'). Defaults to
8 for 'iir' and 30 for 'fir'.
ftype : str {'iir', 'fir'} or ``dlti`` instance, optional
If 'iir' or 'fir', specifies the type of lowpass filter. If an instance
of an `dlti` object, uses that object to filter before downsampling.
axis : int, optional
The axis along which to decimate.
zero_phase : bool, optional
Prevent phase shift by filtering with `filtfilt` instead of `lfilter`
when using an IIR filter, and shifting the outputs back by the filter's
group delay when using an FIR filter. A value of ``True`` is
recommended, since a phase shift is generally not desired. Using
``None`` defaults to ``False`` for backwards compatibility. This
default will change to ``True`` in a future release, so it is best to
set this argument explicitly.
.. versionadded:: 0.18.0
Returns
-------
y : ndarray
The down-sampled signal.
See Also
--------
resample : Resample up or down using the FFT method.
resample_poly : Resample using polyphase filtering and an FIR filter.
Notes
-----
The ``zero_phase`` keyword was added in 0.18.0.
The possibility to use instances of ``dlti`` as ``ftype`` was added in
0.18.0.
"""
if not isinstance(q, int):
raise TypeError("q must be an integer")
if n is not None and not isinstance(n, int):
raise TypeError("n must be an integer")
if ftype == 'fir':
if n is None:
n = 30
system = dlti(firwin(n+1, 1. / q, window='hamming'), 1.)
elif ftype == 'iir':
if n is None:
n = 8
system = dlti(*cheby1(n, 0.05, 0.8 / q))
elif isinstance(ftype, dlti):
system = ftype._as_tf() # Avoids copying if already in TF form
n = np.max((system.num.size, system.den.size)) - 1
else:
raise ValueError('invalid ftype')
if zero_phase is None:
warnings.warn(" Note: Decimate's zero_phase keyword argument will "
"default to True in a future release. Until then, "
"decimate defaults to one-way filtering for backwards "
"compatibility. Ideally, always set this argument "
"explicitly.", FutureWarning)
zero_phase = False
sl = [slice(None)] * x.ndim
if len(system.den) == 1: # FIR case
if zero_phase:
y = resample_poly(x, 1, q, axis=axis, window=system.num)
else:
# upfirdn is generally faster than lfilter by a factor equal to the
# downsampling factor, since it only calculates the needed outputs
n_out = x.shape[axis] // q + bool(x.shape[axis] % q)
y = upfirdn(system.num, x, up=1, down=q, axis=axis)
sl[axis] = slice(None, n_out, None)
else: # IIR case
if zero_phase:
y = filtfilt(system.num, system.den, x, axis=axis)
else:
y = lfilter(system.num, system.den, x, axis=axis)
sl[axis] = slice(None, None, q)
return y[sl]
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/signal/signaltools.py#L3314-L3411
|
|
ApolloAuto/apollo-platform
|
86d9dc6743b496ead18d597748ebabd34a513289
|
ros/third_party/lib_x86_64/python2.7/dist-packages/geographic_msgs/msg/_RouteSegment.py
|
python
|
RouteSegment.__init__
|
(self, *args, **kwds)
|
Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
The available fields are:
id,start,end,props
:param args: complete set of field values, in .msg order
:param kwds: use keyword arguments corresponding to message field names
to set specific fields.
|
Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
|
[
"Constructor",
".",
"Any",
"message",
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"that",
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"implicitly",
"/",
"explicitly",
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"cannot",
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"in",
"-",
"order",
"arguments",
"and",
"keyword",
"arguments",
"."
] |
def __init__(self, *args, **kwds):
"""
Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
The available fields are:
id,start,end,props
:param args: complete set of field values, in .msg order
:param kwds: use keyword arguments corresponding to message field names
to set specific fields.
"""
if args or kwds:
super(RouteSegment, self).__init__(*args, **kwds)
#message fields cannot be None, assign default values for those that are
if self.id is None:
self.id = uuid_msgs.msg.UniqueID()
if self.start is None:
self.start = uuid_msgs.msg.UniqueID()
if self.end is None:
self.end = uuid_msgs.msg.UniqueID()
if self.props is None:
self.props = []
else:
self.id = uuid_msgs.msg.UniqueID()
self.start = uuid_msgs.msg.UniqueID()
self.end = uuid_msgs.msg.UniqueID()
self.props = []
|
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https://github.com/ApolloAuto/apollo-platform/blob/86d9dc6743b496ead18d597748ebabd34a513289/ros/third_party/lib_x86_64/python2.7/dist-packages/geographic_msgs/msg/_RouteSegment.py#L51-L80
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/PIL/ImageFont.py
|
python
|
FreeTypeFont.font_variant
|
(
self, font=None, size=None, index=None, encoding=None, layout_engine=None
)
|
return FreeTypeFont(
font=self.path if font is None else font,
size=self.size if size is None else size,
index=self.index if index is None else index,
encoding=self.encoding if encoding is None else encoding,
layout_engine=layout_engine or self.layout_engine,
)
|
Create a copy of this FreeTypeFont object,
using any specified arguments to override the settings.
Parameters are identical to the parameters used to initialize this
object.
:return: A FreeTypeFont object.
|
Create a copy of this FreeTypeFont object,
using any specified arguments to override the settings.
|
[
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"copy",
"of",
"this",
"FreeTypeFont",
"object",
"using",
"any",
"specified",
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"the",
"settings",
"."
] |
def font_variant(
self, font=None, size=None, index=None, encoding=None, layout_engine=None
):
"""
Create a copy of this FreeTypeFont object,
using any specified arguments to override the settings.
Parameters are identical to the parameters used to initialize this
object.
:return: A FreeTypeFont object.
"""
return FreeTypeFont(
font=self.path if font is None else font,
size=self.size if size is None else size,
index=self.index if index is None else index,
encoding=self.encoding if encoding is None else encoding,
layout_engine=layout_engine or self.layout_engine,
)
|
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/PIL/ImageFont.py#L479-L497
|
|
scribusproject/scribus
|
41ec7c775a060912cf251682a8b1437f753f80f4
|
scribus/plugins/scriptplugin_py2x/scripts/CalendarWizard.py
|
python
|
ScClassicCalendar.createMonthCalendar
|
(self, month, cal)
|
Create a page and draw one month calendar on it
|
Create a page and draw one month calendar on it
|
[
"Create",
"a",
"page",
"and",
"draw",
"one",
"month",
"calendar",
"on",
"it"
] |
def createMonthCalendar(self, month, cal):
""" Create a page and draw one month calendar on it """
self.createLayout()
self.createHeader(localization[self.lang][0][month])
rowCnt = 2
for week in cal:
colCnt = 0
for day in week:
cel = createText(self.marginl + colCnt * self.colSize,
self.calHeight + rowCnt * self.rowSize,
self.colSize, self.rowSize)
setLineColor("Black", cel) # comment this out if you do not want border to cells
colCnt += 1
if day.month == month + 1:
setText(str(day.day), cel)
setStyle(self.pStyleDate, cel)
rowCnt += 1
|
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https://github.com/scribusproject/scribus/blob/41ec7c775a060912cf251682a8b1437f753f80f4/scribus/plugins/scriptplugin_py2x/scripts/CalendarWizard.py#L437-L453
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/AWSPythonSDK/1.5.8/botocore/vendored/requests/cookies.py
|
python
|
morsel_to_cookie
|
(morsel)
|
return create_cookie(
comment=morsel['comment'],
comment_url=bool(morsel['comment']),
discard=False,
domain=morsel['domain'],
expires=expires,
name=morsel.key,
path=morsel['path'],
port=None,
rest={'HttpOnly': morsel['httponly']},
rfc2109=False,
secure=bool(morsel['secure']),
value=morsel.value,
version=morsel['version'] or 0,
)
|
Convert a Morsel object into a Cookie containing the one k/v pair.
|
Convert a Morsel object into a Cookie containing the one k/v pair.
|
[
"Convert",
"a",
"Morsel",
"object",
"into",
"a",
"Cookie",
"containing",
"the",
"one",
"k",
"/",
"v",
"pair",
"."
] |
def morsel_to_cookie(morsel):
"""Convert a Morsel object into a Cookie containing the one k/v pair."""
expires = None
if morsel['max-age']:
expires = time.time() + morsel['max-age']
elif morsel['expires']:
time_template = '%a, %d-%b-%Y %H:%M:%S GMT'
expires = time.mktime(
time.strptime(morsel['expires'], time_template)) - time.timezone
return create_cookie(
comment=morsel['comment'],
comment_url=bool(morsel['comment']),
discard=False,
domain=morsel['domain'],
expires=expires,
name=morsel.key,
path=morsel['path'],
port=None,
rest={'HttpOnly': morsel['httponly']},
rfc2109=False,
secure=bool(morsel['secure']),
value=morsel.value,
version=morsel['version'] or 0,
)
|
[
"def",
"morsel_to_cookie",
"(",
"morsel",
")",
":",
"expires",
"=",
"None",
"if",
"morsel",
"[",
"'max-age'",
"]",
":",
"expires",
"=",
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"time",
"(",
")",
"+",
"morsel",
"[",
"'max-age'",
"]",
"elif",
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"[",
"'expires'",
"]",
":",
"time_template",
"=",
"'%a, %d-%b-%Y %H:%M:%S GMT'",
"expires",
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"mktime",
"(",
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",",
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"create_cookie",
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"]",
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"]",
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"expires",
",",
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"]",
",",
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"=",
"None",
",",
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"{",
"'HttpOnly'",
":",
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"[",
"'httponly'",
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"}",
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"version",
"=",
"morsel",
"[",
"'version'",
"]",
"or",
"0",
",",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/botocore/vendored/requests/cookies.py#L413-L437
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/propgrid.py
|
python
|
PropertyGrid.GetEditorControl
|
(*args, **kwargs)
|
return _propgrid.PropertyGrid_GetEditorControl(*args, **kwargs)
|
GetEditorControl(self) -> Window
|
GetEditorControl(self) -> Window
|
[
"GetEditorControl",
"(",
"self",
")",
"-",
">",
"Window"
] |
def GetEditorControl(*args, **kwargs):
"""GetEditorControl(self) -> Window"""
return _propgrid.PropertyGrid_GetEditorControl(*args, **kwargs)
|
[
"def",
"GetEditorControl",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_propgrid",
".",
"PropertyGrid_GetEditorControl",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/propgrid.py#L2380-L2382
|
|
happynear/caffe-windows
|
967eedf25009e334b7f6f933bb5e17aaaff5bef6
|
scripts/cpp_lint.py
|
python
|
CheckAccess
|
(filename, clean_lines, linenum, nesting_state, error)
|
Checks for improper use of DISALLOW* macros.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: The function to call with any errors found.
|
Checks for improper use of DISALLOW* macros.
|
[
"Checks",
"for",
"improper",
"use",
"of",
"DISALLOW",
"*",
"macros",
"."
] |
def CheckAccess(filename, clean_lines, linenum, nesting_state, error):
"""Checks for improper use of DISALLOW* macros.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum] # get rid of comments and strings
matched = Match((r'\s*(DISALLOW_COPY_AND_ASSIGN|'
r'DISALLOW_EVIL_CONSTRUCTORS|'
r'DISALLOW_IMPLICIT_CONSTRUCTORS)'), line)
if not matched:
return
if nesting_state.stack and isinstance(nesting_state.stack[-1], _ClassInfo):
if nesting_state.stack[-1].access != 'private':
error(filename, linenum, 'readability/constructors', 3,
'%s must be in the private: section' % matched.group(1))
else:
# Found DISALLOW* macro outside a class declaration, or perhaps it
# was used inside a function when it should have been part of the
# class declaration. We could issue a warning here, but it
# probably resulted in a compiler error already.
pass
|
[
"def",
"CheckAccess",
"(",
"filename",
",",
"clean_lines",
",",
"linenum",
",",
"nesting_state",
",",
"error",
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":",
"line",
"=",
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"elided",
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"linenum",
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"# get rid of comments and strings",
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"Match",
"(",
"(",
"r'\\s*(DISALLOW_COPY_AND_ASSIGN|'",
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",",
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"'readability/constructors'",
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",",
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"matched",
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"group",
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"else",
":",
"# Found DISALLOW* macro outside a class declaration, or perhaps it",
"# was used inside a function when it should have been part of the",
"# class declaration. We could issue a warning here, but it",
"# probably resulted in a compiler error already.",
"pass"
] |
https://github.com/happynear/caffe-windows/blob/967eedf25009e334b7f6f933bb5e17aaaff5bef6/scripts/cpp_lint.py#L2490-L2518
|
||
hpi-xnor/BMXNet-v2
|
af2b1859eafc5c721b1397cef02f946aaf2ce20d
|
python/mxnet/symbol/symbol.py
|
python
|
Symbol.argmin
|
(self, *args, **kwargs)
|
return op.argmin(self, *args, **kwargs)
|
Convenience fluent method for :py:func:`argmin`.
The arguments are the same as for :py:func:`argmin`, with
this array as data.
|
Convenience fluent method for :py:func:`argmin`.
|
[
"Convenience",
"fluent",
"method",
"for",
":",
"py",
":",
"func",
":",
"argmin",
"."
] |
def argmin(self, *args, **kwargs):
"""Convenience fluent method for :py:func:`argmin`.
The arguments are the same as for :py:func:`argmin`, with
this array as data.
"""
return op.argmin(self, *args, **kwargs)
|
[
"def",
"argmin",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"op",
".",
"argmin",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/hpi-xnor/BMXNet-v2/blob/af2b1859eafc5c721b1397cef02f946aaf2ce20d/python/mxnet/symbol/symbol.py#L2054-L2060
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/itanium_mangler.py
|
python
|
mangle_templated_ident
|
(identifier, parameters)
|
return mangle_identifier(identifier, template_params)
|
Mangle templated identifier.
|
Mangle templated identifier.
|
[
"Mangle",
"templated",
"identifier",
"."
] |
def mangle_templated_ident(identifier, parameters):
"""
Mangle templated identifier.
"""
template_params = ('I%sE' % ''.join(map(mangle_type_or_value, parameters))
if parameters else '')
return mangle_identifier(identifier, template_params)
|
[
"def",
"mangle_templated_ident",
"(",
"identifier",
",",
"parameters",
")",
":",
"template_params",
"=",
"(",
"'I%sE'",
"%",
"''",
".",
"join",
"(",
"map",
"(",
"mangle_type_or_value",
",",
"parameters",
")",
")",
"if",
"parameters",
"else",
"''",
")",
"return",
"mangle_identifier",
"(",
"identifier",
",",
"template_params",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/itanium_mangler.py#L183-L189
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/difflib.py
|
python
|
SequenceMatcher.get_opcodes
|
(self)
|
return answer
|
Return list of 5-tuples describing how to turn a into b.
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
tuple preceding it, and likewise for j1 == the previous j2.
The tags are strings, with these meanings:
'replace': a[i1:i2] should be replaced by b[j1:j2]
'delete': a[i1:i2] should be deleted.
Note that j1==j2 in this case.
'insert': b[j1:j2] should be inserted at a[i1:i1].
Note that i1==i2 in this case.
'equal': a[i1:i2] == b[j1:j2]
>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
... print(("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2])))
delete a[0:1] (q) b[0:0] ()
equal a[1:3] (ab) b[0:2] (ab)
replace a[3:4] (x) b[2:3] (y)
equal a[4:6] (cd) b[3:5] (cd)
insert a[6:6] () b[5:6] (f)
|
Return list of 5-tuples describing how to turn a into b.
|
[
"Return",
"list",
"of",
"5",
"-",
"tuples",
"describing",
"how",
"to",
"turn",
"a",
"into",
"b",
"."
] |
def get_opcodes(self):
"""Return list of 5-tuples describing how to turn a into b.
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
tuple preceding it, and likewise for j1 == the previous j2.
The tags are strings, with these meanings:
'replace': a[i1:i2] should be replaced by b[j1:j2]
'delete': a[i1:i2] should be deleted.
Note that j1==j2 in this case.
'insert': b[j1:j2] should be inserted at a[i1:i1].
Note that i1==i2 in this case.
'equal': a[i1:i2] == b[j1:j2]
>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
... print(("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2])))
delete a[0:1] (q) b[0:0] ()
equal a[1:3] (ab) b[0:2] (ab)
replace a[3:4] (x) b[2:3] (y)
equal a[4:6] (cd) b[3:5] (cd)
insert a[6:6] () b[5:6] (f)
"""
if self.opcodes is not None:
return self.opcodes
i = j = 0
self.opcodes = answer = []
for ai, bj, size in self.get_matching_blocks():
# invariant: we've pumped out correct diffs to change
# a[:i] into b[:j], and the next matching block is
# a[ai:ai+size] == b[bj:bj+size]. So we need to pump
# out a diff to change a[i:ai] into b[j:bj], pump out
# the matching block, and move (i,j) beyond the match
tag = ''
if i < ai and j < bj:
tag = 'replace'
elif i < ai:
tag = 'delete'
elif j < bj:
tag = 'insert'
if tag:
answer.append( (tag, i, ai, j, bj) )
i, j = ai+size, bj+size
# the list of matching blocks is terminated by a
# sentinel with size 0
if size:
answer.append( ('equal', ai, i, bj, j) )
return answer
|
[
"def",
"get_opcodes",
"(",
"self",
")",
":",
"if",
"self",
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"opcodes",
"is",
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"(",
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"'equal'",
",",
"ai",
",",
"i",
",",
"bj",
",",
"j",
")",
")",
"return",
"answer"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/difflib.py#L517-L570
|
|
trailofbits/sienna-locomotive
|
09bc1a0bea7d7a33089422c62e0d3c715ecb7ce0
|
sl2/harness/state.py
|
python
|
get_target_dir
|
(_config)
|
return dir_name
|
Gets (or creates) the path to a target directory for the current
config file.
|
Gets (or creates) the path to a target directory for the current
config file.
|
[
"Gets",
"(",
"or",
"creates",
")",
"the",
"path",
"to",
"a",
"target",
"directory",
"for",
"the",
"current",
"config",
"file",
"."
] |
def get_target_dir(_config):
"""
Gets (or creates) the path to a target directory for the current
config file.
"""
slug = get_target_slug(_config)
dir_name = os.path.join(config.sl2_targets_dir, slug)
if not os.path.isdir(dir_name):
os.makedirs(dir_name)
arg_file = os.path.join(dir_name, "arguments.txt")
if not os.path.exists(arg_file):
with open(arg_file, "w") as argfile:
argfile.write(stringify_program_array(_config["target_application_path"], _config["target_args"]))
# Primes the db for checksec for this target if it doesn't already exist
db.TargetConfig.bySlug(slug, _config["target_application_path"])
return dir_name
|
[
"def",
"get_target_dir",
"(",
"_config",
")",
":",
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"=",
"get_target_slug",
"(",
"_config",
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",",
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"[",
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")",
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"db",
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"(",
"slug",
",",
"_config",
"[",
"\"target_application_path\"",
"]",
")",
"return",
"dir_name"
] |
https://github.com/trailofbits/sienna-locomotive/blob/09bc1a0bea7d7a33089422c62e0d3c715ecb7ce0/sl2/harness/state.py#L119-L137
|
|
SoarGroup/Soar
|
a1c5e249499137a27da60533c72969eef3b8ab6b
|
scons/scons-local-4.1.0/SCons/Tool/__init__.py
|
python
|
ToolInitializer.apply_tools
|
(self, env)
|
Searches the list of associated Tool modules for one that
exists, and applies that to the construction environment.
|
Searches the list of associated Tool modules for one that
exists, and applies that to the construction environment.
|
[
"Searches",
"the",
"list",
"of",
"associated",
"Tool",
"modules",
"for",
"one",
"that",
"exists",
"and",
"applies",
"that",
"to",
"the",
"construction",
"environment",
"."
] |
def apply_tools(self, env):
"""
Searches the list of associated Tool modules for one that
exists, and applies that to the construction environment.
"""
for t in self.tools:
tool = SCons.Tool.Tool(t)
if tool.exists(env):
env.Tool(tool)
return
|
[
"def",
"apply_tools",
"(",
"self",
",",
"env",
")",
":",
"for",
"t",
"in",
"self",
".",
"tools",
":",
"tool",
"=",
"SCons",
".",
"Tool",
".",
"Tool",
"(",
"t",
")",
"if",
"tool",
".",
"exists",
"(",
"env",
")",
":",
"env",
".",
"Tool",
"(",
"tool",
")",
"return"
] |
https://github.com/SoarGroup/Soar/blob/a1c5e249499137a27da60533c72969eef3b8ab6b/scons/scons-local-4.1.0/SCons/Tool/__init__.py#L640-L649
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_windows.py
|
python
|
ColourData.GetColour
|
(*args, **kwargs)
|
return _windows_.ColourData_GetColour(*args, **kwargs)
|
GetColour(self) -> Colour
Gets the colour (pre)selected by the dialog.
|
GetColour(self) -> Colour
|
[
"GetColour",
"(",
"self",
")",
"-",
">",
"Colour"
] |
def GetColour(*args, **kwargs):
"""
GetColour(self) -> Colour
Gets the colour (pre)selected by the dialog.
"""
return _windows_.ColourData_GetColour(*args, **kwargs)
|
[
"def",
"GetColour",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_windows_",
".",
"ColourData_GetColour",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_windows.py#L2941-L2947
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/mapreduce/mapreduce/api/map_job/abstract_datastore_input_reader.py
|
python
|
AbstractDatastoreInputReader._get_raw_entity_kind
|
(cls, entity_kind_or_model_classpath)
|
return entity_kind_or_model_classpath
|
Returns the entity kind to use with low level datastore calls.
Args:
entity_kind_or_model_classpath: user specified entity kind or model
classpath.
Returns:
the entity kind in str to use with low level datastore calls.
|
Returns the entity kind to use with low level datastore calls.
|
[
"Returns",
"the",
"entity",
"kind",
"to",
"use",
"with",
"low",
"level",
"datastore",
"calls",
"."
] |
def _get_raw_entity_kind(cls, entity_kind_or_model_classpath):
"""Returns the entity kind to use with low level datastore calls.
Args:
entity_kind_or_model_classpath: user specified entity kind or model
classpath.
Returns:
the entity kind in str to use with low level datastore calls.
"""
return entity_kind_or_model_classpath
|
[
"def",
"_get_raw_entity_kind",
"(",
"cls",
",",
"entity_kind_or_model_classpath",
")",
":",
"return",
"entity_kind_or_model_classpath"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/mapreduce/mapreduce/api/map_job/abstract_datastore_input_reader.py#L311-L321
|
|
bairdzhang/smallhardface
|
76fa1d87a9602d9b13d7a7fe693fc7aec91cab80
|
caffe/python/caffe/io.py
|
python
|
Transformer.set_mean
|
(self, in_, mean)
|
Set the mean to subtract for centering the data.
Parameters
----------
in_ : which input to assign this mean.
mean : mean ndarray (input dimensional or broadcastable)
|
Set the mean to subtract for centering the data.
|
[
"Set",
"the",
"mean",
"to",
"subtract",
"for",
"centering",
"the",
"data",
"."
] |
def set_mean(self, in_, mean):
"""
Set the mean to subtract for centering the data.
Parameters
----------
in_ : which input to assign this mean.
mean : mean ndarray (input dimensional or broadcastable)
"""
self.__check_input(in_)
ms = mean.shape
if mean.ndim == 1:
# broadcast channels
if ms[0] != self.inputs[in_][1]:
raise ValueError('Mean channels incompatible with input.')
mean = mean[:, np.newaxis, np.newaxis]
else:
# elementwise mean
if len(ms) == 2:
ms = (1,) + ms
if len(ms) != 3:
raise ValueError('Mean shape invalid')
if ms != self.inputs[in_][1:]:
raise ValueError('Mean shape incompatible with input shape.')
self.mean[in_] = mean
|
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"[",
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] |
https://github.com/bairdzhang/smallhardface/blob/76fa1d87a9602d9b13d7a7fe693fc7aec91cab80/caffe/python/caffe/io.py#L236-L260
|
||
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/contrib/layers/python/layers/layers.py
|
python
|
_sparse_inner_flatten
|
(inputs, new_rank)
|
return flattened
|
Helper function for `inner_flatten`.
|
Helper function for `inner_flatten`.
|
[
"Helper",
"function",
"for",
"inner_flatten",
"."
] |
def _sparse_inner_flatten(inputs, new_rank):
"""Helper function for `inner_flatten`."""
inputs_rank = inputs.dense_shape.get_shape().as_list()[0]
if inputs_rank < new_rank:
raise ValueError(
'Inputs has rank less than new_rank. {} must have rank at least'
' {}. Received rank {}, shape {}'.format(inputs, new_rank, inputs_rank,
inputs.get_shape()))
outer_dimensions = inputs.dense_shape[:new_rank - 1]
inner_dimensions = inputs.dense_shape[new_rank - 1:]
new_shape = array_ops.concat((outer_dimensions,
[math_ops.reduce_prod(inner_dimensions)]), 0)
flattened = sparse_ops.sparse_reshape(inputs, new_shape)
return flattened
|
[
"def",
"_sparse_inner_flatten",
"(",
"inputs",
",",
"new_rank",
")",
":",
"inputs_rank",
"=",
"inputs",
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"dense_shape",
".",
"get_shape",
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")",
".",
"as_list",
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"0",
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"inputs_rank",
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"new_rank",
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"'Inputs has rank less than new_rank. {} must have rank at least'",
"' {}. Received rank {}, shape {}'",
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"sparse_ops",
".",
"sparse_reshape",
"(",
"inputs",
",",
"new_shape",
")",
"return",
"flattened"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/layers/python/layers/layers.py#L1460-L1474
|
|
eldar/deepcut-cnn
|
928bf2f224fce132f6e4404b4c95fb017297a5e0
|
python/caffe/detector.py
|
python
|
Detector.detect_windows
|
(self, images_windows)
|
return detections
|
Do windowed detection over given images and windows. Windows are
extracted then warped to the input dimensions of the net.
Parameters
----------
images_windows: (image filename, window list) iterable.
context_crop: size of context border to crop in pixels.
Returns
-------
detections: list of {filename: image filename, window: crop coordinates,
predictions: prediction vector} dicts.
|
Do windowed detection over given images and windows. Windows are
extracted then warped to the input dimensions of the net.
|
[
"Do",
"windowed",
"detection",
"over",
"given",
"images",
"and",
"windows",
".",
"Windows",
"are",
"extracted",
"then",
"warped",
"to",
"the",
"input",
"dimensions",
"of",
"the",
"net",
"."
] |
def detect_windows(self, images_windows):
"""
Do windowed detection over given images and windows. Windows are
extracted then warped to the input dimensions of the net.
Parameters
----------
images_windows: (image filename, window list) iterable.
context_crop: size of context border to crop in pixels.
Returns
-------
detections: list of {filename: image filename, window: crop coordinates,
predictions: prediction vector} dicts.
"""
# Extract windows.
window_inputs = []
for image_fname, windows in images_windows:
image = caffe.io.load_image(image_fname).astype(np.float32)
for window in windows:
window_inputs.append(self.crop(image, window))
# Run through the net (warping windows to input dimensions).
in_ = self.inputs[0]
caffe_in = np.zeros((len(window_inputs), window_inputs[0].shape[2])
+ self.blobs[in_].data.shape[2:],
dtype=np.float32)
for ix, window_in in enumerate(window_inputs):
caffe_in[ix] = self.transformer.preprocess(in_, window_in)
out = self.forward_all(**{in_: caffe_in})
predictions = out[self.outputs[0]].squeeze(axis=(2, 3))
# Package predictions with images and windows.
detections = []
ix = 0
for image_fname, windows in images_windows:
for window in windows:
detections.append({
'window': window,
'prediction': predictions[ix],
'filename': image_fname
})
ix += 1
return detections
|
[
"def",
"detect_windows",
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"# Extract windows.",
"window_inputs",
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".",
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"float32",
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"=",
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"squeeze",
"(",
"axis",
"=",
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",",
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"detections",
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"[",
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"image_fname",
",",
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",",
"'filename'",
":",
"image_fname",
"}",
")",
"ix",
"+=",
"1",
"return",
"detections"
] |
https://github.com/eldar/deepcut-cnn/blob/928bf2f224fce132f6e4404b4c95fb017297a5e0/python/caffe/detector.py#L56-L99
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/framework/convert_to_constants.py
|
python
|
_populate_if_op
|
(output_node, input_node, function_data)
|
Updates the type attributes and function names of If or StatelessIf.
Args:
output_node: TensorFlow NodeDef.
input_node: TensorFlow NodeDef.
function_data: Map of function names to the list of types and shapes that
correspond with the function arguments.
|
Updates the type attributes and function names of If or StatelessIf.
|
[
"Updates",
"the",
"type",
"attributes",
"and",
"function",
"names",
"of",
"If",
"or",
"StatelessIf",
"."
] |
def _populate_if_op(output_node, input_node, function_data):
"""Updates the type attributes and function names of If or StatelessIf.
Args:
output_node: TensorFlow NodeDef.
input_node: TensorFlow NodeDef.
function_data: Map of function names to the list of types and shapes that
correspond with the function arguments.
"""
output_node.CopyFrom(input_node)
then_func = input_node.attr["then_branch"].func.name
output_node.attr["then_branch"].func.name = _get_new_function_name(then_func)
output_node.attr["else_branch"].func.name = _get_new_function_name(
input_node.attr["else_branch"].func.name)
output_node.attr["Tin"].list.CopyFrom(
attr_value_pb2.AttrValue.ListValue(
type=function_data[then_func]["types"]))
|
[
"def",
"_populate_if_op",
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"output_node",
",",
"input_node",
",",
"function_data",
")",
":",
"output_node",
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"CopyFrom",
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"input_node",
")",
"then_func",
"=",
"input_node",
".",
"attr",
"[",
"\"then_branch\"",
"]",
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"[",
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"(",
"type",
"=",
"function_data",
"[",
"then_func",
"]",
"[",
"\"types\"",
"]",
")",
")"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/framework/convert_to_constants.py#L303-L319
|
||
wallix/redemption
|
fb4ceefb39e11e1ae250bce17e878e1dc7d195d2
|
tools/icap_validator/fake_validator.py
|
python
|
read_session_msg
|
(client_socket)
|
return False, received_message, message_type
|
Read session client socket received data, parse the header to return read
message type and True if no error is detected
|
Read session client socket received data, parse the header to return read
message type and True if no error is detected
|
[
"Read",
"session",
"client",
"socket",
"received",
"data",
"parse",
"the",
"header",
"to",
"return",
"read",
"message",
"type",
"and",
"True",
"if",
"no",
"error",
"is",
"detected"
] |
def read_session_msg(client_socket):
"""
Read session client socket received data, parse the header to return read
message type and True if no error is detected
"""
message_type = -1
received_message = b""
ok, header_received = read_session_socket(client_socket, 5)
if ok:
message_type, message_len = struct.unpack_from(">BI", header_received)
ok, received_message = read_session_socket(client_socket, message_len)
if ok:
return True, received_message, message_type
return False, received_message, message_type
|
[
"def",
"read_session_msg",
"(",
"client_socket",
")",
":",
"message_type",
"=",
"-",
"1",
"received_message",
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"received_message",
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"False",
",",
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",",
"message_type"
] |
https://github.com/wallix/redemption/blob/fb4ceefb39e11e1ae250bce17e878e1dc7d195d2/tools/icap_validator/fake_validator.py#L28-L43
|
|
tfwu/FaceDetection-ConvNet-3D
|
f9251c48eb40c5aec8fba7455115c355466555be
|
python/mxnet/metric.py
|
python
|
CompositeEvalMetric.get_metric
|
(self, index)
|
Get a child metric.
|
Get a child metric.
|
[
"Get",
"a",
"child",
"metric",
"."
] |
def get_metric(self, index):
"""Get a child metric."""
try:
return self.metrics[index]
except IndexError:
return ValueError("Metric index {} is out of range 0 and {}".format(
index, len(self.metrics)))
|
[
"def",
"get_metric",
"(",
"self",
",",
"index",
")",
":",
"try",
":",
"return",
"self",
".",
"metrics",
"[",
"index",
"]",
"except",
"IndexError",
":",
"return",
"ValueError",
"(",
"\"Metric index {} is out of range 0 and {}\"",
".",
"format",
"(",
"index",
",",
"len",
"(",
"self",
".",
"metrics",
")",
")",
")"
] |
https://github.com/tfwu/FaceDetection-ConvNet-3D/blob/f9251c48eb40c5aec8fba7455115c355466555be/python/mxnet/metric.py#L95-L101
|
||
llvm-mirror/lldb
|
d01083a850f577b85501a0902b52fd0930de72c7
|
third_party/Python/module/pexpect-4.6/pexpect/pty_spawn.py
|
python
|
spawn.terminate
|
(self, force=False)
|
This forces a child process to terminate. It starts nicely with
SIGHUP and SIGINT. If "force" is True then moves onto SIGKILL. This
returns True if the child was terminated. This returns False if the
child could not be terminated.
|
This forces a child process to terminate. It starts nicely with
SIGHUP and SIGINT. If "force" is True then moves onto SIGKILL. This
returns True if the child was terminated. This returns False if the
child could not be terminated.
|
[
"This",
"forces",
"a",
"child",
"process",
"to",
"terminate",
".",
"It",
"starts",
"nicely",
"with",
"SIGHUP",
"and",
"SIGINT",
".",
"If",
"force",
"is",
"True",
"then",
"moves",
"onto",
"SIGKILL",
".",
"This",
"returns",
"True",
"if",
"the",
"child",
"was",
"terminated",
".",
"This",
"returns",
"False",
"if",
"the",
"child",
"could",
"not",
"be",
"terminated",
"."
] |
def terminate(self, force=False):
'''This forces a child process to terminate. It starts nicely with
SIGHUP and SIGINT. If "force" is True then moves onto SIGKILL. This
returns True if the child was terminated. This returns False if the
child could not be terminated. '''
if not self.isalive():
return True
try:
self.kill(signal.SIGHUP)
time.sleep(self.delayafterterminate)
if not self.isalive():
return True
self.kill(signal.SIGCONT)
time.sleep(self.delayafterterminate)
if not self.isalive():
return True
self.kill(signal.SIGINT)
time.sleep(self.delayafterterminate)
if not self.isalive():
return True
if force:
self.kill(signal.SIGKILL)
time.sleep(self.delayafterterminate)
if not self.isalive():
return True
else:
return False
return False
except OSError:
# I think there are kernel timing issues that sometimes cause
# this to happen. I think isalive() reports True, but the
# process is dead to the kernel.
# Make one last attempt to see if the kernel is up to date.
time.sleep(self.delayafterterminate * 10)
if not self.isalive():
return True
else:
return False
|
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"self",
".",
"kill",
"(",
"signal",
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"SIGCONT",
")",
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"sleep",
"(",
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"delayafterterminate",
")",
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"(",
")",
":",
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"kill",
"(",
"signal",
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")",
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".",
"isalive",
"(",
")",
":",
"return",
"True",
"else",
":",
"return",
"False",
"return",
"False",
"except",
"OSError",
":",
"# I think there are kernel timing issues that sometimes cause",
"# this to happen. I think isalive() reports True, but the",
"# process is dead to the kernel.",
"# Make one last attempt to see if the kernel is up to date.",
"time",
".",
"sleep",
"(",
"self",
".",
"delayafterterminate",
"*",
"10",
")",
"if",
"not",
"self",
".",
"isalive",
"(",
")",
":",
"return",
"True",
"else",
":",
"return",
"False"
] |
https://github.com/llvm-mirror/lldb/blob/d01083a850f577b85501a0902b52fd0930de72c7/third_party/Python/module/pexpect-4.6/pexpect/pty_spawn.py#L609-L647
|
||
BlzFans/wke
|
b0fa21158312e40c5fbd84682d643022b6c34a93
|
cygwin/lib/python2.6/textwrap.py
|
python
|
TextWrapper.wrap
|
(self, text)
|
return self._wrap_chunks(chunks)
|
wrap(text : string) -> [string]
Reformat the single paragraph in 'text' so it fits in lines of
no more than 'self.width' columns, and return a list of wrapped
lines. Tabs in 'text' are expanded with string.expandtabs(),
and all other whitespace characters (including newline) are
converted to space.
|
wrap(text : string) -> [string]
|
[
"wrap",
"(",
"text",
":",
"string",
")",
"-",
">",
"[",
"string",
"]"
] |
def wrap(self, text):
"""wrap(text : string) -> [string]
Reformat the single paragraph in 'text' so it fits in lines of
no more than 'self.width' columns, and return a list of wrapped
lines. Tabs in 'text' are expanded with string.expandtabs(),
and all other whitespace characters (including newline) are
converted to space.
"""
text = self._munge_whitespace(text)
chunks = self._split(text)
if self.fix_sentence_endings:
self._fix_sentence_endings(chunks)
return self._wrap_chunks(chunks)
|
[
"def",
"wrap",
"(",
"self",
",",
"text",
")",
":",
"text",
"=",
"self",
".",
"_munge_whitespace",
"(",
"text",
")",
"chunks",
"=",
"self",
".",
"_split",
"(",
"text",
")",
"if",
"self",
".",
"fix_sentence_endings",
":",
"self",
".",
"_fix_sentence_endings",
"(",
"chunks",
")",
"return",
"self",
".",
"_wrap_chunks",
"(",
"chunks",
")"
] |
https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/textwrap.py#L308-L321
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_misc.py
|
python
|
PlatformInformation.SetLinuxDistributionInfo
|
(*args, **kwargs)
|
return _misc_.PlatformInformation_SetLinuxDistributionInfo(*args, **kwargs)
|
SetLinuxDistributionInfo(self, LinuxDistributionInfo di)
|
SetLinuxDistributionInfo(self, LinuxDistributionInfo di)
|
[
"SetLinuxDistributionInfo",
"(",
"self",
"LinuxDistributionInfo",
"di",
")"
] |
def SetLinuxDistributionInfo(*args, **kwargs):
"""SetLinuxDistributionInfo(self, LinuxDistributionInfo di)"""
return _misc_.PlatformInformation_SetLinuxDistributionInfo(*args, **kwargs)
|
[
"def",
"SetLinuxDistributionInfo",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_misc_",
".",
"PlatformInformation_SetLinuxDistributionInfo",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_misc.py#L1178-L1180
|
|
hughperkins/tf-coriander
|
970d3df6c11400ad68405f22b0c42a52374e94ca
|
tensorflow/python/framework/errors.py
|
python
|
OpError.node_def
|
(self)
|
return self._node_def
|
The `NodeDef` proto representing the op that failed.
|
The `NodeDef` proto representing the op that failed.
|
[
"The",
"NodeDef",
"proto",
"representing",
"the",
"op",
"that",
"failed",
"."
] |
def node_def(self):
"""The `NodeDef` proto representing the op that failed."""
return self._node_def
|
[
"def",
"node_def",
"(",
"self",
")",
":",
"return",
"self",
".",
"_node_def"
] |
https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/python/framework/errors.py#L83-L85
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/tools/python3/src/Lib/ipaddress.py
|
python
|
ip_interface
|
(address)
|
Take an IP string/int and return an object of the correct type.
Args:
address: A string or integer, the IP address. Either IPv4 or
IPv6 addresses may be supplied; integers less than 2**32 will
be considered to be IPv4 by default.
Returns:
An IPv4Interface or IPv6Interface object.
Raises:
ValueError: if the string passed isn't either a v4 or a v6
address.
Notes:
The IPv?Interface classes describe an Address on a particular
Network, so they're basically a combination of both the Address
and Network classes.
|
Take an IP string/int and return an object of the correct type.
|
[
"Take",
"an",
"IP",
"string",
"/",
"int",
"and",
"return",
"an",
"object",
"of",
"the",
"correct",
"type",
"."
] |
def ip_interface(address):
"""Take an IP string/int and return an object of the correct type.
Args:
address: A string or integer, the IP address. Either IPv4 or
IPv6 addresses may be supplied; integers less than 2**32 will
be considered to be IPv4 by default.
Returns:
An IPv4Interface or IPv6Interface object.
Raises:
ValueError: if the string passed isn't either a v4 or a v6
address.
Notes:
The IPv?Interface classes describe an Address on a particular
Network, so they're basically a combination of both the Address
and Network classes.
"""
try:
return IPv4Interface(address)
except (AddressValueError, NetmaskValueError):
pass
try:
return IPv6Interface(address)
except (AddressValueError, NetmaskValueError):
pass
raise ValueError('%r does not appear to be an IPv4 or IPv6 interface' %
address)
|
[
"def",
"ip_interface",
"(",
"address",
")",
":",
"try",
":",
"return",
"IPv4Interface",
"(",
"address",
")",
"except",
"(",
"AddressValueError",
",",
"NetmaskValueError",
")",
":",
"pass",
"try",
":",
"return",
"IPv6Interface",
"(",
"address",
")",
"except",
"(",
"AddressValueError",
",",
"NetmaskValueError",
")",
":",
"pass",
"raise",
"ValueError",
"(",
"'%r does not appear to be an IPv4 or IPv6 interface'",
"%",
"address",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/ipaddress.py#L87-L119
|
||
apache/qpid-proton
|
6bcdfebb55ea3554bc29b1901422532db331a591
|
python/proton/_transport.py
|
python
|
Transport.pop
|
(self, size: int)
|
Removes ``size`` bytes of output from the pending output queue
following the transport's head pointer.
Calls to this function may alter the transport's head pointer as
well as the number of pending bytes reported by
:meth:`pending`.
:param size: Number of bytes to remove.
|
Removes ``size`` bytes of output from the pending output queue
following the transport's head pointer.
|
[
"Removes",
"size",
"bytes",
"of",
"output",
"from",
"the",
"pending",
"output",
"queue",
"following",
"the",
"transport",
"s",
"head",
"pointer",
"."
] |
def pop(self, size: int) -> None:
"""
Removes ``size`` bytes of output from the pending output queue
following the transport's head pointer.
Calls to this function may alter the transport's head pointer as
well as the number of pending bytes reported by
:meth:`pending`.
:param size: Number of bytes to remove.
"""
pn_transport_pop(self._impl, size)
|
[
"def",
"pop",
"(",
"self",
",",
"size",
":",
"int",
")",
"->",
"None",
":",
"pn_transport_pop",
"(",
"self",
".",
"_impl",
",",
"size",
")"
] |
https://github.com/apache/qpid-proton/blob/6bcdfebb55ea3554bc29b1901422532db331a591/python/proton/_transport.py#L345-L356
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_internal/vcs/versioncontrol.py
|
python
|
VersionControl.make_rev_args
|
(username, password)
|
return []
|
Return the RevOptions "extra arguments" to use in obtain().
|
Return the RevOptions "extra arguments" to use in obtain().
|
[
"Return",
"the",
"RevOptions",
"extra",
"arguments",
"to",
"use",
"in",
"obtain",
"()",
"."
] |
def make_rev_args(username, password):
# type: (Optional[str], Optional[HiddenText]) -> CommandArgs
"""
Return the RevOptions "extra arguments" to use in obtain().
"""
return []
|
[
"def",
"make_rev_args",
"(",
"username",
",",
"password",
")",
":",
"# type: (Optional[str], Optional[HiddenText]) -> CommandArgs",
"return",
"[",
"]"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_internal/vcs/versioncontrol.py#L449-L454
|
|
borglab/gtsam
|
a5bee157efce6a0563704bce6a5d188c29817f39
|
wrap/gtwrap/template_instantiator/helpers.py
|
python
|
instantiate_name
|
(original_name: str,
instantiations: Sequence[parser.Typename])
|
return "{}{}".format(original_name, "".join(instantiated_names))
|
Concatenate instantiated types with `original_name` to form a new
instantiated name.
NOTE: To avoid conflicts, we should include the instantiation's
namespaces, but that is too verbose.
|
Concatenate instantiated types with `original_name` to form a new
instantiated name.
|
[
"Concatenate",
"instantiated",
"types",
"with",
"original_name",
"to",
"form",
"a",
"new",
"instantiated",
"name",
"."
] |
def instantiate_name(original_name: str,
instantiations: Sequence[parser.Typename]):
"""
Concatenate instantiated types with `original_name` to form a new
instantiated name.
NOTE: To avoid conflicts, we should include the instantiation's
namespaces, but that is too verbose.
"""
instantiated_names = []
for inst in instantiations:
# Ensure the first character of the type is capitalized
name = inst.instantiated_name()
# Using `capitalize` on the complete name causes other caps to be lower case
instantiated_names.append(name.replace(name[0], name[0].capitalize()))
return "{}{}".format(original_name, "".join(instantiated_names))
|
[
"def",
"instantiate_name",
"(",
"original_name",
":",
"str",
",",
"instantiations",
":",
"Sequence",
"[",
"parser",
".",
"Typename",
"]",
")",
":",
"instantiated_names",
"=",
"[",
"]",
"for",
"inst",
"in",
"instantiations",
":",
"# Ensure the first character of the type is capitalized",
"name",
"=",
"inst",
".",
"instantiated_name",
"(",
")",
"# Using `capitalize` on the complete name causes other caps to be lower case",
"instantiated_names",
".",
"append",
"(",
"name",
".",
"replace",
"(",
"name",
"[",
"0",
"]",
",",
"name",
"[",
"0",
"]",
".",
"capitalize",
"(",
")",
")",
")",
"return",
"\"{}{}\"",
".",
"format",
"(",
"original_name",
",",
"\"\"",
".",
"join",
"(",
"instantiated_names",
")",
")"
] |
https://github.com/borglab/gtsam/blob/a5bee157efce6a0563704bce6a5d188c29817f39/wrap/gtwrap/template_instantiator/helpers.py#L196-L212
|
|
maidsafe-archive/MaidSafe
|
defd65e1c8cfb6a1cbdeaaa0eee31d065421792d
|
tools/cpplint.py
|
python
|
CheckEmptyLoopBody
|
(filename, clean_lines, linenum, error)
|
Loop for empty loop body with only a single semicolon.
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.
|
Loop for empty loop body with only a single semicolon.
|
[
"Loop",
"for",
"empty",
"loop",
"body",
"with",
"only",
"a",
"single",
"semicolon",
"."
] |
def CheckEmptyLoopBody(filename, clean_lines, linenum, error):
"""Loop for empty loop body with only a single semicolon.
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.
"""
# Search for loop keywords at the beginning of the line. Because only
# whitespaces are allowed before the keywords, this will also ignore most
# do-while-loops, since those lines should start with closing brace.
line = clean_lines.elided[linenum]
if Match(r'\s*(for|while)\s*\(', line):
# Find the end of the conditional expression
(end_line, end_linenum, end_pos) = CloseExpression(
clean_lines, linenum, line.find('('))
# Output warning if what follows the condition expression is a semicolon.
# No warning for all other cases, including whitespace or newline, since we
# have a separate check for semicolons preceded by whitespace.
if end_pos >= 0 and Match(r';', end_line[end_pos:]):
error(filename, end_linenum, 'whitespace/empty_loop_body', 5,
'Empty loop bodies should use {} or continue')
|
[
"def",
"CheckEmptyLoopBody",
"(",
"filename",
",",
"clean_lines",
",",
"linenum",
",",
"error",
")",
":",
"# Search for loop keywords at the beginning of the line. Because only",
"# whitespaces are allowed before the keywords, this will also ignore most",
"# do-while-loops, since those lines should start with closing brace.",
"line",
"=",
"clean_lines",
".",
"elided",
"[",
"linenum",
"]",
"if",
"Match",
"(",
"r'\\s*(for|while)\\s*\\('",
",",
"line",
")",
":",
"# Find the end of the conditional expression",
"(",
"end_line",
",",
"end_linenum",
",",
"end_pos",
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"CloseExpression",
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"clean_lines",
",",
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",",
"line",
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"(",
"'('",
")",
")",
"# Output warning if what follows the condition expression is a semicolon.",
"# No warning for all other cases, including whitespace or newline, since we",
"# have a separate check for semicolons preceded by whitespace.",
"if",
"end_pos",
">=",
"0",
"and",
"Match",
"(",
"r';'",
",",
"end_line",
"[",
"end_pos",
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")",
":",
"error",
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"filename",
",",
"end_linenum",
",",
"'whitespace/empty_loop_body'",
",",
"5",
",",
"'Empty loop bodies should use {} or continue'",
")"
] |
https://github.com/maidsafe-archive/MaidSafe/blob/defd65e1c8cfb6a1cbdeaaa0eee31d065421792d/tools/cpplint.py#L2652-L2676
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/setuptools/py2/setuptools/command/egg_info.py
|
python
|
egg_info.write_or_delete_file
|
(self, what, filename, data, force=False)
|
Write `data` to `filename` or delete if empty
If `data` is non-empty, this routine is the same as ``write_file()``.
If `data` is empty but not ``None``, this is the same as calling
``delete_file(filename)`. If `data` is ``None``, then this is a no-op
unless `filename` exists, in which case a warning is issued about the
orphaned file (if `force` is false), or deleted (if `force` is true).
|
Write `data` to `filename` or delete if empty
|
[
"Write",
"data",
"to",
"filename",
"or",
"delete",
"if",
"empty"
] |
def write_or_delete_file(self, what, filename, data, force=False):
"""Write `data` to `filename` or delete if empty
If `data` is non-empty, this routine is the same as ``write_file()``.
If `data` is empty but not ``None``, this is the same as calling
``delete_file(filename)`. If `data` is ``None``, then this is a no-op
unless `filename` exists, in which case a warning is issued about the
orphaned file (if `force` is false), or deleted (if `force` is true).
"""
if data:
self.write_file(what, filename, data)
elif os.path.exists(filename):
if data is None and not force:
log.warn(
"%s not set in setup(), but %s exists", what, filename
)
return
else:
self.delete_file(filename)
|
[
"def",
"write_or_delete_file",
"(",
"self",
",",
"what",
",",
"filename",
",",
"data",
",",
"force",
"=",
"False",
")",
":",
"if",
"data",
":",
"self",
".",
"write_file",
"(",
"what",
",",
"filename",
",",
"data",
")",
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"os",
".",
"path",
".",
"exists",
"(",
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":",
"if",
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"None",
"and",
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"force",
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"warn",
"(",
"\"%s not set in setup(), but %s exists\"",
",",
"what",
",",
"filename",
")",
"return",
"else",
":",
"self",
".",
"delete_file",
"(",
"filename",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/setuptools/py2/setuptools/command/egg_info.py#L242-L260
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/gsutil/third_party/boto/boto/vpc/__init__.py
|
python
|
VPCConnection.get_all_route_tables
|
(self, route_table_ids=None, filters=None,
dry_run=False)
|
return self.get_list('DescribeRouteTables', params,
[('item', RouteTable)])
|
Retrieve information about your routing tables. You can filter results
to return information only about those route tables that match your
search parameters. Otherwise, all route tables associated with your
account are returned.
:type route_table_ids: list
:param route_table_ids: A list of strings with the desired route table
IDs.
:type filters: list of tuples or dict
:param filters: A list of tuples or dict containing filters. Each tuple
or dict item consists of a filter key and a filter value.
:type dry_run: bool
:param dry_run: Set to True if the operation should not actually run.
:rtype: list
:return: A list of :class:`boto.vpc.routetable.RouteTable`
|
Retrieve information about your routing tables. You can filter results
to return information only about those route tables that match your
search parameters. Otherwise, all route tables associated with your
account are returned.
|
[
"Retrieve",
"information",
"about",
"your",
"routing",
"tables",
".",
"You",
"can",
"filter",
"results",
"to",
"return",
"information",
"only",
"about",
"those",
"route",
"tables",
"that",
"match",
"your",
"search",
"parameters",
".",
"Otherwise",
"all",
"route",
"tables",
"associated",
"with",
"your",
"account",
"are",
"returned",
"."
] |
def get_all_route_tables(self, route_table_ids=None, filters=None,
dry_run=False):
"""
Retrieve information about your routing tables. You can filter results
to return information only about those route tables that match your
search parameters. Otherwise, all route tables associated with your
account are returned.
:type route_table_ids: list
:param route_table_ids: A list of strings with the desired route table
IDs.
:type filters: list of tuples or dict
:param filters: A list of tuples or dict containing filters. Each tuple
or dict item consists of a filter key and a filter value.
:type dry_run: bool
:param dry_run: Set to True if the operation should not actually run.
:rtype: list
:return: A list of :class:`boto.vpc.routetable.RouteTable`
"""
params = {}
if route_table_ids:
self.build_list_params(params, route_table_ids, "RouteTableId")
if filters:
self.build_filter_params(params, filters)
if dry_run:
params['DryRun'] = 'true'
return self.get_list('DescribeRouteTables', params,
[('item', RouteTable)])
|
[
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",",
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"[",
"(",
"'item'",
",",
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")",
"]",
")"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/vpc/__init__.py#L196-L226
|
|
etternagame/etterna
|
8775f74ac9c353320128609d4b4150672e9a6d04
|
extern/fmt/support/docopt.py
|
python
|
transform
|
(pattern)
|
return Either(*[Required(*e) for e in result])
|
Expand pattern into an (almost) equivalent one, but with single Either.
Example: ((-a | -b) (-c | -d)) => (-a -c | -a -d | -b -c | -b -d)
Quirks: [-a] => (-a), (-a...) => (-a -a)
|
Expand pattern into an (almost) equivalent one, but with single Either.
|
[
"Expand",
"pattern",
"into",
"an",
"(",
"almost",
")",
"equivalent",
"one",
"but",
"with",
"single",
"Either",
"."
] |
def transform(pattern):
"""Expand pattern into an (almost) equivalent one, but with single Either.
Example: ((-a | -b) (-c | -d)) => (-a -c | -a -d | -b -c | -b -d)
Quirks: [-a] => (-a), (-a...) => (-a -a)
"""
result = []
groups = [[pattern]]
while groups:
children = groups.pop(0)
parents = [Required, Optional, OptionsShortcut, Either, OneOrMore]
if any(t in map(type, children) for t in parents):
child = [c for c in children if type(c) in parents][0]
children.remove(child)
if type(child) is Either:
for c in child.children:
groups.append([c] + children)
elif type(child) is OneOrMore:
groups.append(child.children * 2 + children)
else:
groups.append(child.children + children)
else:
result.append(children)
return Either(*[Required(*e) for e in result])
|
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https://github.com/etternagame/etterna/blob/8775f74ac9c353320128609d4b4150672e9a6d04/extern/fmt/support/docopt.py#L72-L96
|
|
BitMEX/api-connectors
|
37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812
|
auto-generated/python/swagger_client/models/margin.py
|
python
|
Margin.taxable_margin
|
(self)
|
return self._taxable_margin
|
Gets the taxable_margin of this Margin. # noqa: E501
:return: The taxable_margin of this Margin. # noqa: E501
:rtype: float
|
Gets the taxable_margin of this Margin. # noqa: E501
|
[
"Gets",
"the",
"taxable_margin",
"of",
"this",
"Margin",
".",
"#",
"noqa",
":",
"E501"
] |
def taxable_margin(self):
"""Gets the taxable_margin of this Margin. # noqa: E501
:return: The taxable_margin of this Margin. # noqa: E501
:rtype: float
"""
return self._taxable_margin
|
[
"def",
"taxable_margin",
"(",
"self",
")",
":",
"return",
"self",
".",
"_taxable_margin"
] |
https://github.com/BitMEX/api-connectors/blob/37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812/auto-generated/python/swagger_client/models/margin.py#L631-L638
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/stc.py
|
python
|
StyledTextCtrl.AutoCompSetFillUps
|
(*args, **kwargs)
|
return _stc.StyledTextCtrl_AutoCompSetFillUps(*args, **kwargs)
|
AutoCompSetFillUps(self, String characterSet)
Define a set of characters that when typed will cause the autocompletion to
choose the selected item.
|
AutoCompSetFillUps(self, String characterSet)
|
[
"AutoCompSetFillUps",
"(",
"self",
"String",
"characterSet",
")"
] |
def AutoCompSetFillUps(*args, **kwargs):
"""
AutoCompSetFillUps(self, String characterSet)
Define a set of characters that when typed will cause the autocompletion to
choose the selected item.
"""
return _stc.StyledTextCtrl_AutoCompSetFillUps(*args, **kwargs)
|
[
"def",
"AutoCompSetFillUps",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_stc",
".",
"StyledTextCtrl_AutoCompSetFillUps",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/stc.py#L3120-L3127
|
|
deepmind/open_spiel
|
4ca53bea32bb2875c7385d215424048ae92f78c8
|
open_spiel/python/algorithms/cfr_br.py
|
python
|
CFRBRSolver._compute_best_responses
|
(self)
|
Computes each player best-response against the pool of other players.
|
Computes each player best-response against the pool of other players.
|
[
"Computes",
"each",
"player",
"best",
"-",
"response",
"against",
"the",
"pool",
"of",
"other",
"players",
"."
] |
def _compute_best_responses(self):
"""Computes each player best-response against the pool of other players."""
def policy_fn(state):
key = state.information_state_string()
return self._get_infostate_policy(key)
current_policy = policy.tabular_policy_from_callable(self._game, policy_fn)
for player_id in range(self._game.num_players()):
self._best_responses[player_id] = exploitability.best_response(
self._game, current_policy, player_id)
|
[
"def",
"_compute_best_responses",
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"(",
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",",
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",",
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")"
] |
https://github.com/deepmind/open_spiel/blob/4ca53bea32bb2875c7385d215424048ae92f78c8/open_spiel/python/algorithms/cfr_br.py#L99-L110
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/_core.py
|
python
|
Window.GetFont
|
(*args, **kwargs)
|
return _core_.Window_GetFont(*args, **kwargs)
|
GetFont(self) -> Font
Returns the default font used for this window.
|
GetFont(self) -> Font
|
[
"GetFont",
"(",
"self",
")",
"-",
">",
"Font"
] |
def GetFont(*args, **kwargs):
"""
GetFont(self) -> Font
Returns the default font used for this window.
"""
return _core_.Window_GetFont(*args, **kwargs)
|
[
"def",
"GetFont",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core_",
".",
"Window_GetFont",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_core.py#L10990-L10996
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/py/py/_io/terminalwriter.py
|
python
|
TerminalWriter.width_of_current_line
|
(self)
|
return self._width_of_current_line
|
Return an estimate of the width so far in the current line.
.. versionadded:: 1.6.0
:rtype: int
|
Return an estimate of the width so far in the current line.
|
[
"Return",
"an",
"estimate",
"of",
"the",
"width",
"so",
"far",
"in",
"the",
"current",
"line",
"."
] |
def width_of_current_line(self):
"""Return an estimate of the width so far in the current line.
.. versionadded:: 1.6.0
:rtype: int
"""
return self._width_of_current_line
|
[
"def",
"width_of_current_line",
"(",
"self",
")",
":",
"return",
"self",
".",
"_width_of_current_line"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/py/py/_io/terminalwriter.py#L192-L199
|
|
grpc/grpc
|
27bc6fe7797e43298dc931b96dc57322d0852a9f
|
src/python/grpcio/grpc/_channel.py
|
python
|
_separate_channel_options
|
(options)
|
return python_options, core_options
|
Separates core channel options from Python channel options.
|
Separates core channel options from Python channel options.
|
[
"Separates",
"core",
"channel",
"options",
"from",
"Python",
"channel",
"options",
"."
] |
def _separate_channel_options(options):
"""Separates core channel options from Python channel options."""
core_options = []
python_options = []
for pair in options:
if pair[0] == grpc.experimental.ChannelOptions.SingleThreadedUnaryStream:
python_options.append(pair)
else:
core_options.append(pair)
return python_options, core_options
|
[
"def",
"_separate_channel_options",
"(",
"options",
")",
":",
"core_options",
"=",
"[",
"]",
"python_options",
"=",
"[",
"]",
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"if",
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"[",
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".",
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":",
"core_options",
".",
"append",
"(",
"pair",
")",
"return",
"python_options",
",",
"core_options"
] |
https://github.com/grpc/grpc/blob/27bc6fe7797e43298dc931b96dc57322d0852a9f/src/python/grpcio/grpc/_channel.py#L1450-L1459
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
tools/auto_bisect/source_control.py
|
python
|
GetCommitTime
|
(git_revision, cwd=None)
|
return int(output)
|
Returns commit time for the given revision in UNIX timestamp.
|
Returns commit time for the given revision in UNIX timestamp.
|
[
"Returns",
"commit",
"time",
"for",
"the",
"given",
"revision",
"in",
"UNIX",
"timestamp",
"."
] |
def GetCommitTime(git_revision, cwd=None):
"""Returns commit time for the given revision in UNIX timestamp."""
cmd = ['log', '--format=%ct', '-1', git_revision]
output = bisect_utils.CheckRunGit(cmd, cwd=cwd)
return int(output)
|
[
"def",
"GetCommitTime",
"(",
"git_revision",
",",
"cwd",
"=",
"None",
")",
":",
"cmd",
"=",
"[",
"'log'",
",",
"'--format=%ct'",
",",
"'-1'",
",",
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"bisect_utils",
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"CheckRunGit",
"(",
"cmd",
",",
"cwd",
"=",
"cwd",
")",
"return",
"int",
"(",
"output",
")"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/auto_bisect/source_control.py#L151-L155
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/protobuf/py3/google/protobuf/internal/python_message.py
|
python
|
_AddSerializePartialToStringMethod
|
(message_descriptor, cls)
|
Helper for _AddMessageMethods().
|
Helper for _AddMessageMethods().
|
[
"Helper",
"for",
"_AddMessageMethods",
"()",
"."
] |
def _AddSerializePartialToStringMethod(message_descriptor, cls):
"""Helper for _AddMessageMethods()."""
def SerializePartialToString(self, **kwargs):
out = BytesIO()
self._InternalSerialize(out.write, **kwargs)
return out.getvalue()
cls.SerializePartialToString = SerializePartialToString
def InternalSerialize(self, write_bytes, deterministic=None):
if deterministic is None:
deterministic = (
api_implementation.IsPythonDefaultSerializationDeterministic())
else:
deterministic = bool(deterministic)
descriptor = self.DESCRIPTOR
if descriptor.GetOptions().map_entry:
# Fields of map entry should always be serialized.
descriptor.fields_by_name['key']._encoder(
write_bytes, self.key, deterministic)
descriptor.fields_by_name['value']._encoder(
write_bytes, self.value, deterministic)
else:
for field_descriptor, field_value in self.ListFields():
field_descriptor._encoder(write_bytes, field_value, deterministic)
for tag_bytes, value_bytes in self._unknown_fields:
write_bytes(tag_bytes)
write_bytes(value_bytes)
cls._InternalSerialize = InternalSerialize
|
[
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"(",
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")",
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] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/protobuf/py3/google/protobuf/internal/python_message.py#L1101-L1130
|
||
idaholab/moose
|
9eeebc65e098b4c30f8205fb41591fd5b61eb6ff
|
python/peacock/utils/TextSubWindow.py
|
python
|
TextSubWindow.sizeHint
|
(self, *args)
|
Return the saved size.
|
Return the saved size.
|
[
"Return",
"the",
"saved",
"size",
"."
] |
def sizeHint(self, *args):
"""
Return the saved size.
"""
if self._size:
return self._size
else:
return super(TextSubWindow, self).size()
|
[
"def",
"sizeHint",
"(",
"self",
",",
"*",
"args",
")",
":",
"if",
"self",
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"else",
":",
"return",
"super",
"(",
"TextSubWindow",
",",
"self",
")",
".",
"size",
"(",
")"
] |
https://github.com/idaholab/moose/blob/9eeebc65e098b4c30f8205fb41591fd5b61eb6ff/python/peacock/utils/TextSubWindow.py#L22-L29
|
||
psi4/psi4
|
be533f7f426b6ccc263904e55122899b16663395
|
psi4/driver/procrouting/response/scf_products.py
|
python
|
TDRSCFEngine._combine_H1_H2
|
(self, Fx, Jx, Kx=None)
|
return H1X, H2X
|
Build the combinations:
Singlet:
H1 X = [(Ea - Ei) + 4J - K - K^T]X
H2 X = [(Ea - Ei) - K + K^T]X
Triplet:
H1 X = [(Ea - Ei) - K - K^T]X
H2 X = [(Ea - Ei) - K + K^T]X
|
Build the combinations:
Singlet:
H1 X = [(Ea - Ei) + 4J - K - K^T]X
H2 X = [(Ea - Ei) - K + K^T]X
|
[
"Build",
"the",
"combinations",
":",
"Singlet",
":",
"H1",
"X",
"=",
"[",
"(",
"Ea",
"-",
"Ei",
")",
"+",
"4J",
"-",
"K",
"-",
"K^T",
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"X",
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"=",
"[",
"(",
"Ea",
"-",
"Ei",
")",
"-",
"K",
"+",
"K^T",
"]",
"X"
] |
def _combine_H1_H2(self, Fx, Jx, Kx=None):
"""Build the combinations:
Singlet:
H1 X = [(Ea - Ei) + 4J - K - K^T]X
H2 X = [(Ea - Ei) - K + K^T]X
Triplet:
H1 X = [(Ea - Ei) - K - K^T]X
H2 X = [(Ea - Ei) - K + K^T]X
"""
H1X = []
H2X = []
if Kx is not None:
for Fxi, Jxi, Kxi in zip(Fx, Jx, Kx):
Kxit = self.vector_transpose(Kxi)
# H1x = -K singlet/triplet
H1X_so = self.vector_copy(Kxi)
H1X_so = self.vector_scale(-1.0, H1X_so)
# H1X -= K^T singlet/triplet
H1X_so = self.vector_axpy(-1.0, Kxit, H1X_so)
# H2x = K^T - K singlet/triplet
H2X_so = self.vector_axpy(-1.0, Kxi, Kxit)
if self.singlet:
# H1x += 4*J (singlet only)
H1X_so = self.vector_axpy(4.0, Jxi, H1X_so)
# transform + add Ea-Ei
H1X.append(self.vector_axpy(1.0, Fxi, self._so_to_mo(H1X_so)))
H2X.append(self.vector_axpy(1.0, Fxi, self._so_to_mo(H2X_so)))
else:
for Fxi, Jxi in zip(Fx, Jx):
if self.singlet:
H1X_so = self.vector_scale(4.0, Jxi)
H1X.append(self.vector_axpy(1.0, Fxi, self._so_to_mo(H1X_so)))
else:
H1X.append(self.vector_copy(Fxi))
H2X.append(self.vector_copy(Fxi))
return H1X, H2X
|
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"def",
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",",
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] |
https://github.com/psi4/psi4/blob/be533f7f426b6ccc263904e55122899b16663395/psi4/driver/procrouting/response/scf_products.py#L325-L364
|
|
apache/incubator-mxnet
|
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
|
python/mxnet/ndarray/numpy/_op.py
|
python
|
tril
|
(m, k=0)
|
return _api_internal.tril(m, k)
|
r"""
Lower triangle of an array.
Return a copy of an array with elements above the `k`-th diagonal zeroed.
Parameters
----------
m : ndarray, shape (M, N)
Input array.
k : int, optional
Diagonal above which to zero elements. `k = 0` (the default) is the
main diagonal, `k < 0` is below it and `k > 0` is above.
Returns
-------
tril : ndarray, shape (M, N)
Lower triangle of `m`, of same shape and data-type as `m`.
See Also
--------
triu : same thing, only for the upper triangle
Examples
--------
>>> a = np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])
>>> np.tril(a, -1)
array([[ 0., 0., 0.],
[ 4., 0., 0.],
[ 7., 8., 0.],
[10., 11., 12.]])
|
r"""
Lower triangle of an array.
|
[
"r",
"Lower",
"triangle",
"of",
"an",
"array",
"."
] |
def tril(m, k=0):
r"""
Lower triangle of an array.
Return a copy of an array with elements above the `k`-th diagonal zeroed.
Parameters
----------
m : ndarray, shape (M, N)
Input array.
k : int, optional
Diagonal above which to zero elements. `k = 0` (the default) is the
main diagonal, `k < 0` is below it and `k > 0` is above.
Returns
-------
tril : ndarray, shape (M, N)
Lower triangle of `m`, of same shape and data-type as `m`.
See Also
--------
triu : same thing, only for the upper triangle
Examples
--------
>>> a = np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])
>>> np.tril(a, -1)
array([[ 0., 0., 0.],
[ 4., 0., 0.],
[ 7., 8., 0.],
[10., 11., 12.]])
"""
return _api_internal.tril(m, k)
|
[
"def",
"tril",
"(",
"m",
",",
"k",
"=",
"0",
")",
":",
"return",
"_api_internal",
".",
"tril",
"(",
"m",
",",
"k",
")"
] |
https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/ndarray/numpy/_op.py#L2233-L2265
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/index/package_finder.py
|
python
|
PackageFinder.create
|
(
cls,
link_collector, # type: LinkCollector
selection_prefs, # type: SelectionPreferences
target_python=None, # type: Optional[TargetPython]
)
|
return cls(
candidate_prefs=candidate_prefs,
link_collector=link_collector,
target_python=target_python,
allow_yanked=selection_prefs.allow_yanked,
format_control=selection_prefs.format_control,
ignore_requires_python=selection_prefs.ignore_requires_python,
)
|
Create a PackageFinder.
:param selection_prefs: The candidate selection preferences, as a
SelectionPreferences object.
:param target_python: The target Python interpreter to use when
checking compatibility. If None (the default), a TargetPython
object will be constructed from the running Python.
|
Create a PackageFinder.
|
[
"Create",
"a",
"PackageFinder",
"."
] |
def create(
cls,
link_collector, # type: LinkCollector
selection_prefs, # type: SelectionPreferences
target_python=None, # type: Optional[TargetPython]
):
# type: (...) -> PackageFinder
"""Create a PackageFinder.
:param selection_prefs: The candidate selection preferences, as a
SelectionPreferences object.
:param target_python: The target Python interpreter to use when
checking compatibility. If None (the default), a TargetPython
object will be constructed from the running Python.
"""
if target_python is None:
target_python = TargetPython()
candidate_prefs = CandidatePreferences(
prefer_binary=selection_prefs.prefer_binary,
allow_all_prereleases=selection_prefs.allow_all_prereleases,
)
return cls(
candidate_prefs=candidate_prefs,
link_collector=link_collector,
target_python=target_python,
allow_yanked=selection_prefs.allow_yanked,
format_control=selection_prefs.format_control,
ignore_requires_python=selection_prefs.ignore_requires_python,
)
|
[
"def",
"create",
"(",
"cls",
",",
"link_collector",
",",
"# type: LinkCollector",
"selection_prefs",
",",
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",",
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",",
"ignore_requires_python",
"=",
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".",
"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/index/package_finder.py#L1245-L1305
|
|
RobotLocomotion/drake
|
0e18a34604c45ed65bc9018a54f7610f91cdad5b
|
bindings/pydrake/common/jupyter.py
|
python
|
process_ipywidget_events
|
(num_events_to_process=1)
|
Allows the kernel to process GUI events. This is required in order to
process ipywidget updates inside a simulation loop.
|
Allows the kernel to process GUI events. This is required in order to
process ipywidget updates inside a simulation loop.
|
[
"Allows",
"the",
"kernel",
"to",
"process",
"GUI",
"events",
".",
"This",
"is",
"required",
"in",
"order",
"to",
"process",
"ipywidget",
"updates",
"inside",
"a",
"simulation",
"loop",
"."
] |
def process_ipywidget_events(num_events_to_process=1):
"""
Allows the kernel to process GUI events. This is required in order to
process ipywidget updates inside a simulation loop.
"""
shell = get_ipython()
# Ok to do nothing if running from console.
if shell is None or not hasattr(shell, 'kernel'):
return
kernel = shell.kernel
events = []
old_handler = kernel.shell_handlers['execute_request']
kernel.shell_handlers['execute_request'] = lambda *e: events.append(e)
current_parent = (kernel._parent_ident, kernel._parent_header)
for _ in range(num_events_to_process):
# Ensure stdout still happens in the same cell.
kernel.set_parent(*current_parent)
kernel.do_one_iteration()
kernel.set_parent(*current_parent)
kernel.shell_handlers['execute_request'] = old_handler
def _replay_events(shell, events):
kernel = shell.kernel
sys.stdout.flush()
sys.stderr.flush()
for stream, ident, parent in events:
kernel.set_parent(ident, parent)
kernel.execute_request(stream, ident, parent)
if len(events) > 0:
loop = asyncio.get_event_loop()
if loop.is_running():
loop.call_soon(lambda: _replay_events(shell, events))
else:
warn("One of your components is attempting to use pydrake's "
"process_ipywidget_events function. However, this IPython "
"kernel is not asyncio-based. This means the following:\n"
" (1) Once your block cell is done executing, future cells "
"will *not* execute, but it may appear like they are still "
"executing ([*]).\n"
" (2) Your Jupyter UI may break. If you find your UI to be "
"unresponsive, you may need to restart the UI itself.\n"
"To avoid this behavior, avoid requesting execution of "
"future cells before or during execution of this cell.")
|
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"process_ipywidget_events",
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"# Ok to do nothing if running from console.",
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"\"kernel is not asyncio-based. This means the following:\\n\"",
"\" (1) Once your block cell is done executing, future cells \"",
"\"will *not* execute, but it may appear like they are still \"",
"\"executing ([*]).\\n\"",
"\" (2) Your Jupyter UI may break. If you find your UI to be \"",
"\"unresponsive, you may need to restart the UI itself.\\n\"",
"\"To avoid this behavior, avoid requesting execution of \"",
"\"future cells before or during execution of this cell.\"",
")"
] |
https://github.com/RobotLocomotion/drake/blob/0e18a34604c45ed65bc9018a54f7610f91cdad5b/bindings/pydrake/common/jupyter.py#L25-L71
|
||
martinmoene/string-view-lite
|
6c2ba8672db54a355a6d76c820dd46ecda254038
|
script/create-vcpkg.py
|
python
|
createControl
|
( args )
|
Create vcpkg CONTROL file
|
Create vcpkg CONTROL file
|
[
"Create",
"vcpkg",
"CONTROL",
"file"
] |
def createControl( args ):
"""Create vcpkg CONTROL file"""
output = tpl_vcpkg_control.format(
prj=args.project, ver=args.version, desc=args.description )
if args.verbose:
print( "Creating control file '{f}':".format( f=control_path( args ) ) )
if args.verbose > 1:
print( output )
os.makedirs( os.path.dirname( control_path( args ) ), exist_ok=True )
with open( control_path( args ), 'w') as f:
print( output, file=f )
|
[
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"createControl",
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"args",
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":",
"output",
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".",
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",",
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"\"Creating control file '{f}':\"",
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"True",
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")",
",",
"'w'",
")",
"as",
"f",
":",
"print",
"(",
"output",
",",
"file",
"=",
"f",
")"
] |
https://github.com/martinmoene/string-view-lite/blob/6c2ba8672db54a355a6d76c820dd46ecda254038/script/create-vcpkg.py#L122-L132
|
||
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/graph_editor/subgraph.py
|
python
|
SubGraphView.__bool__
|
(self)
|
return self._graph is not None
|
Allows for implicit boolean conversion.
|
Allows for implicit boolean conversion.
|
[
"Allows",
"for",
"implicit",
"boolean",
"conversion",
"."
] |
def __bool__(self):
"""Allows for implicit boolean conversion."""
return self._graph is not None
|
[
"def",
"__bool__",
"(",
"self",
")",
":",
"return",
"self",
".",
"_graph",
"is",
"not",
"None"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/graph_editor/subgraph.py#L518-L520
|
|
larroy/clearskies_core
|
3574ddf0edc8555454c7044126e786a6c29444dc
|
tools/gyp/pylib/gyp/generator/ninja.py
|
python
|
NinjaWriter.WriteNewNinjaRule
|
(self, name, args, description, is_cygwin, env)
|
return rule_name, args
|
Write out a new ninja "rule" statement for a given command.
Returns the name of the new rule, and a copy of |args| with variables
expanded.
|
Write out a new ninja "rule" statement for a given command.
|
[
"Write",
"out",
"a",
"new",
"ninja",
"rule",
"statement",
"for",
"a",
"given",
"command",
"."
] |
def WriteNewNinjaRule(self, name, args, description, is_cygwin, env):
"""Write out a new ninja "rule" statement for a given command.
Returns the name of the new rule, and a copy of |args| with variables
expanded."""
if self.flavor == 'win':
args = [self.msvs_settings.ConvertVSMacros(
arg, self.base_to_build, config=self.config_name)
for arg in args]
description = self.msvs_settings.ConvertVSMacros(
description, config=self.config_name)
elif self.flavor == 'mac':
# |env| is an empty list on non-mac.
args = [gyp.xcode_emulation.ExpandEnvVars(arg, env) for arg in args]
description = gyp.xcode_emulation.ExpandEnvVars(description, env)
# TODO: we shouldn't need to qualify names; we do it because
# currently the ninja rule namespace is global, but it really
# should be scoped to the subninja.
rule_name = self.name
if self.toolset == 'target':
rule_name += '.' + self.toolset
rule_name += '.' + name
rule_name = re.sub('[^a-zA-Z0-9_]', '_', rule_name)
# Remove variable references, but not if they refer to the magic rule
# variables. This is not quite right, as it also protects these for
# actions, not just for rules where they are valid. Good enough.
protect = [ '${root}', '${dirname}', '${source}', '${ext}', '${name}' ]
protect = '(?!' + '|'.join(map(re.escape, protect)) + ')'
description = re.sub(protect + r'\$', '_', description)
# gyp dictates that commands are run from the base directory.
# cd into the directory before running, and adjust paths in
# the arguments to point to the proper locations.
rspfile = None
rspfile_content = None
args = [self.ExpandSpecial(arg, self.base_to_build) for arg in args]
if self.flavor == 'win':
rspfile = rule_name + '.$unique_name.rsp'
# The cygwin case handles this inside the bash sub-shell.
run_in = '' if is_cygwin else ' ' + self.build_to_base
if is_cygwin:
rspfile_content = self.msvs_settings.BuildCygwinBashCommandLine(
args, self.build_to_base)
else:
rspfile_content = gyp.msvs_emulation.EncodeRspFileList(args)
command = ('%s gyp-win-tool action-wrapper $arch ' % sys.executable +
rspfile + run_in)
else:
env = self.ComputeExportEnvString(env)
command = gyp.common.EncodePOSIXShellList(args)
command = 'cd %s; ' % self.build_to_base + env + command
# GYP rules/actions express being no-ops by not touching their outputs.
# Avoid executing downstream dependencies in this case by specifying
# restat=1 to ninja.
self.ninja.rule(rule_name, command, description, restat=True,
rspfile=rspfile, rspfile_content=rspfile_content)
self.ninja.newline()
return rule_name, args
|
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https://github.com/larroy/clearskies_core/blob/3574ddf0edc8555454c7044126e786a6c29444dc/tools/gyp/pylib/gyp/generator/ninja.py#L1383-L1445
|
|
MythTV/mythtv
|
d282a209cb8be85d036f85a62a8ec971b67d45f4
|
mythtv/programs/scripts/internetcontent/nv_python_libs/vimeo/vimeo_api.py
|
python
|
SimpleOAuthClient._fetch_token
|
(self, oauth_request)
|
return oauth.OAuthToken.from_string(ans)
|
Sends a requests and interprets the result as a token string.
|
Sends a requests and interprets the result as a token string.
|
[
"Sends",
"a",
"requests",
"and",
"interprets",
"the",
"result",
"as",
"a",
"token",
"string",
"."
] |
def _fetch_token(self, oauth_request):
"""
Sends a requests and interprets the result as a token string.
"""
ans = self.curly.do_request(oauth_request.to_url())
return oauth.OAuthToken.from_string(ans)
|
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https://github.com/MythTV/mythtv/blob/d282a209cb8be85d036f85a62a8ec971b67d45f4/mythtv/programs/scripts/internetcontent/nv_python_libs/vimeo/vimeo_api.py#L278-L283
|
|
bundy-dns/bundy
|
3d41934996b82b0cd2fe22dd74d2abc1daba835d
|
src/lib/python/bundy/notify/notify_out.py
|
python
|
NotifyOut._prepare_select_info
|
(self)
|
return (block_timeout, valid_socks, notifying_zones)
|
Prepare the information for select(), returned
value is one tuple
(block_timeout, valid_socks, notifying_zones)
block_timeout: the timeout for select()
valid_socks: sockets list for waiting ready reading.
notifying_zones: the zones which have been triggered
for notify.
|
Prepare the information for select(), returned
value is one tuple
(block_timeout, valid_socks, notifying_zones)
block_timeout: the timeout for select()
valid_socks: sockets list for waiting ready reading.
notifying_zones: the zones which have been triggered
for notify.
|
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] |
def _prepare_select_info(self):
'''
Prepare the information for select(), returned
value is one tuple
(block_timeout, valid_socks, notifying_zones)
block_timeout: the timeout for select()
valid_socks: sockets list for waiting ready reading.
notifying_zones: the zones which have been triggered
for notify.
'''
valid_socks = []
notifying_zones = {}
min_timeout = None
for info in self._notify_infos:
sock = self._notify_infos[info].get_socket()
if sock:
valid_socks.append(sock)
# If a non null timeout is specified notify has been scheduled
# (in which case socket is still None) or sent (with a valid
# socket). In either case we need add the zone to notifying_zones
# so that we can invoke the appropriate event for the zone after
# select.
tmp_timeout = self._notify_infos[info].notify_timeout
if tmp_timeout is not None:
notifying_zones[info] = self._notify_infos[info]
if min_timeout is not None:
if tmp_timeout < min_timeout:
min_timeout = tmp_timeout
else:
min_timeout = tmp_timeout
block_timeout = None
if min_timeout is not None:
block_timeout = min_timeout - time.time()
if block_timeout < 0:
block_timeout = 0
return (block_timeout, valid_socks, notifying_zones)
|
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] |
https://github.com/bundy-dns/bundy/blob/3d41934996b82b0cd2fe22dd74d2abc1daba835d/src/lib/python/bundy/notify/notify_out.py#L335-L373
|
|
TimoSaemann/caffe-segnet-cudnn5
|
abcf30dca449245e101bf4ced519f716177f0885
|
scripts/cpp_lint.py
|
python
|
CloseExpression
|
(clean_lines, linenum, pos)
|
return (line, clean_lines.NumLines(), -1)
|
If input points to ( or { or [ or <, finds the position that closes it.
If lines[linenum][pos] points to a '(' or '{' or '[' or '<', finds the
linenum/pos that correspond to the closing of the expression.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
pos: A position on the line.
Returns:
A tuple (line, linenum, pos) pointer *past* the closing brace, or
(line, len(lines), -1) if we never find a close. Note we ignore
strings and comments when matching; and the line we return is the
'cleansed' line at linenum.
|
If input points to ( or { or [ or <, finds the position that closes it.
|
[
"If",
"input",
"points",
"to",
"(",
"or",
"{",
"or",
"[",
"or",
"<",
"finds",
"the",
"position",
"that",
"closes",
"it",
"."
] |
def CloseExpression(clean_lines, linenum, pos):
"""If input points to ( or { or [ or <, finds the position that closes it.
If lines[linenum][pos] points to a '(' or '{' or '[' or '<', finds the
linenum/pos that correspond to the closing of the expression.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
pos: A position on the line.
Returns:
A tuple (line, linenum, pos) pointer *past* the closing brace, or
(line, len(lines), -1) if we never find a close. Note we ignore
strings and comments when matching; and the line we return is the
'cleansed' line at linenum.
"""
line = clean_lines.elided[linenum]
startchar = line[pos]
if startchar not in '({[<':
return (line, clean_lines.NumLines(), -1)
if startchar == '(': endchar = ')'
if startchar == '[': endchar = ']'
if startchar == '{': endchar = '}'
if startchar == '<': endchar = '>'
# Check first line
(end_pos, num_open) = FindEndOfExpressionInLine(
line, pos, 0, startchar, endchar)
if end_pos > -1:
return (line, linenum, end_pos)
# Continue scanning forward
while linenum < clean_lines.NumLines() - 1:
linenum += 1
line = clean_lines.elided[linenum]
(end_pos, num_open) = FindEndOfExpressionInLine(
line, 0, num_open, startchar, endchar)
if end_pos > -1:
return (line, linenum, end_pos)
# Did not find endchar before end of file, give up
return (line, clean_lines.NumLines(), -1)
|
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",",
"clean_lines",
".",
"NumLines",
"(",
")",
",",
"-",
"1",
")"
] |
https://github.com/TimoSaemann/caffe-segnet-cudnn5/blob/abcf30dca449245e101bf4ced519f716177f0885/scripts/cpp_lint.py#L1254-L1297
|
|
pmq20/node-packer
|
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
|
lts/deps/v8/tools/stats-viewer.py
|
python
|
ChromeCounter.__init__
|
(self, data, name_offset, value_offset)
|
Create a new instance.
Args:
data: the shared data access object containing the counter
name_offset: the byte offset of the start of this counter's name
value_offset: the byte offset of the start of this counter's value
|
Create a new instance.
|
[
"Create",
"a",
"new",
"instance",
"."
] |
def __init__(self, data, name_offset, value_offset):
"""Create a new instance.
Args:
data: the shared data access object containing the counter
name_offset: the byte offset of the start of this counter's name
value_offset: the byte offset of the start of this counter's value
"""
self.data = data
self.name_offset = name_offset
self.value_offset = value_offset
|
[
"def",
"__init__",
"(",
"self",
",",
"data",
",",
"name_offset",
",",
"value_offset",
")",
":",
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"=",
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"self",
".",
"name_offset",
"=",
"name_offset",
"self",
".",
"value_offset",
"=",
"value_offset"
] |
https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/deps/v8/tools/stats-viewer.py#L389-L399
|
||
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
tools/cr/cr/actions/builder.py
|
python
|
Builder.Clean
|
(self, context, targets, arguments)
|
Clean temporary files built by a target.
|
Clean temporary files built by a target.
|
[
"Clean",
"temporary",
"files",
"built",
"by",
"a",
"target",
"."
] |
def Clean(self, context, targets, arguments):
"""Clean temporary files built by a target."""
raise NotImplementedError('Must be overridden.')
|
[
"def",
"Clean",
"(",
"self",
",",
"context",
",",
"targets",
",",
"arguments",
")",
":",
"raise",
"NotImplementedError",
"(",
"'Must be overridden.'",
")"
] |
https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/cr/cr/actions/builder.py#L33-L35
|
||
v8mips/v8mips
|
f0c9cc0bbfd461c7f516799d9a58e9a7395f737e
|
build/landmine_utils.py
|
python
|
platform
|
()
|
Returns a string representing the platform this build is targetted for.
Possible values: 'win', 'mac', 'linux', 'ios', 'android'
|
Returns a string representing the platform this build is targetted for.
Possible values: 'win', 'mac', 'linux', 'ios', 'android'
|
[
"Returns",
"a",
"string",
"representing",
"the",
"platform",
"this",
"build",
"is",
"targetted",
"for",
".",
"Possible",
"values",
":",
"win",
"mac",
"linux",
"ios",
"android"
] |
def platform():
"""
Returns a string representing the platform this build is targetted for.
Possible values: 'win', 'mac', 'linux', 'ios', 'android'
"""
if 'OS' in gyp_defines():
if 'android' in gyp_defines()['OS']:
return 'android'
else:
return gyp_defines()['OS']
elif IsWindows():
return 'win'
elif IsLinux():
return 'linux'
else:
return 'mac'
|
[
"def",
"platform",
"(",
")",
":",
"if",
"'OS'",
"in",
"gyp_defines",
"(",
")",
":",
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"[",
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"'win'",
"elif",
"IsLinux",
"(",
")",
":",
"return",
"'linux'",
"else",
":",
"return",
"'mac'"
] |
https://github.com/v8mips/v8mips/blob/f0c9cc0bbfd461c7f516799d9a58e9a7395f737e/build/landmine_utils.py#L68-L83
|
||
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/DirectILLReduction.py
|
python
|
DirectILLReduction.summary
|
(self)
|
return 'Data reduction workflow for the direct geometry time-of-flight spectrometers at ILL.'
|
Return a summary of the algorithm.
|
Return a summary of the algorithm.
|
[
"Return",
"a",
"summary",
"of",
"the",
"algorithm",
"."
] |
def summary(self):
"""Return a summary of the algorithm."""
return 'Data reduction workflow for the direct geometry time-of-flight spectrometers at ILL.'
|
[
"def",
"summary",
"(",
"self",
")",
":",
"return",
"'Data reduction workflow for the direct geometry time-of-flight spectrometers at ILL.'"
] |
https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/DirectILLReduction.py#L246-L248
|
|
hfinkel/llvm-project-cxxjit
|
91084ef018240bbb8e24235ff5cd8c355a9c1a1e
|
clang/bindings/python/clang/cindex.py
|
python
|
Cursor.availability
|
(self)
|
return AvailabilityKind.from_id(self._availability)
|
Retrieves the availability of the entity pointed at by the cursor.
|
Retrieves the availability of the entity pointed at by the cursor.
|
[
"Retrieves",
"the",
"availability",
"of",
"the",
"entity",
"pointed",
"at",
"by",
"the",
"cursor",
"."
] |
def availability(self):
"""
Retrieves the availability of the entity pointed at by the cursor.
"""
if not hasattr(self, '_availability'):
self._availability = conf.lib.clang_getCursorAvailability(self)
return AvailabilityKind.from_id(self._availability)
|
[
"def",
"availability",
"(",
"self",
")",
":",
"if",
"not",
"hasattr",
"(",
"self",
",",
"'_availability'",
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"self",
".",
"_availability",
"=",
"conf",
".",
"lib",
".",
"clang_getCursorAvailability",
"(",
"self",
")",
"return",
"AvailabilityKind",
".",
"from_id",
"(",
"self",
".",
"_availability",
")"
] |
https://github.com/hfinkel/llvm-project-cxxjit/blob/91084ef018240bbb8e24235ff5cd8c355a9c1a1e/clang/bindings/python/clang/cindex.py#L1620-L1627
|
|
RobotLocomotion/drake
|
0e18a34604c45ed65bc9018a54f7610f91cdad5b
|
doc/pydrake/pydrake_sphinx_extension.py
|
python
|
repair_naive_name_split
|
(objpath)
|
return out
|
Rejoins any strings with braces that were naively split across '.'.
|
Rejoins any strings with braces that were naively split across '.'.
|
[
"Rejoins",
"any",
"strings",
"with",
"braces",
"that",
"were",
"naively",
"split",
"across",
".",
"."
] |
def repair_naive_name_split(objpath):
"""Rejoins any strings with braces that were naively split across '.'.
"""
num_open = 0
out = []
cur = ''
for p in objpath:
num_open += p.count('[') - p.count(']')
assert num_open >= 0
if cur:
cur += '.'
cur += p
if num_open == 0:
out.append(cur)
cur = ''
assert len(cur) == 0, (objpath, cur, out)
return out
|
[
"def",
"repair_naive_name_split",
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"objpath",
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https://github.com/RobotLocomotion/drake/blob/0e18a34604c45ed65bc9018a54f7610f91cdad5b/doc/pydrake/pydrake_sphinx_extension.py#L49-L65
|
|
CNevd/Difacto_DMLC
|
f16862e35062707b1cf7e37d04d9b6ae34bbfd28
|
dmlc-core/scripts/lint3.py
|
python
|
LintHelper.process_cpp
|
(self, path, suffix)
|
Process a cpp file.
|
Process a cpp file.
|
[
"Process",
"a",
"cpp",
"file",
"."
] |
def process_cpp(self, path, suffix):
"""Process a cpp file."""
_cpplint_state.ResetErrorCounts()
cpplint.ProcessFile(str(path), _cpplint_state.verbose_level)
_cpplint_state.PrintErrorCounts()
errors = _cpplint_state.errors_by_category.copy()
if suffix == 'h':
self.cpp_header_map[str(path)] = errors
else:
self.cpp_src_map[str(path)] = errors
|
[
"def",
"process_cpp",
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"self",
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"suffix",
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"_cpplint_state",
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"ResetErrorCounts",
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"[",
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https://github.com/CNevd/Difacto_DMLC/blob/f16862e35062707b1cf7e37d04d9b6ae34bbfd28/dmlc-core/scripts/lint3.py#L59-L68
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/beautifulsoup4/bs4/element.py
|
python
|
PageElement.find_previous
|
(self, name=None, attrs={}, text=None, **kwargs)
|
return self._find_one(
self.find_all_previous, name, attrs, text, **kwargs)
|
Returns the first item that matches the given criteria and
appears before this Tag in the document.
|
Returns the first item that matches the given criteria and
appears before this Tag in the document.
|
[
"Returns",
"the",
"first",
"item",
"that",
"matches",
"the",
"given",
"criteria",
"and",
"appears",
"before",
"this",
"Tag",
"in",
"the",
"document",
"."
] |
def find_previous(self, name=None, attrs={}, text=None, **kwargs):
"""Returns the first item that matches the given criteria and
appears before this Tag in the document."""
return self._find_one(
self.find_all_previous, name, attrs, text, **kwargs)
|
[
"def",
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",",
"name",
",",
"attrs",
",",
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",",
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")"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/beautifulsoup4/bs4/element.py#L408-L412
|
|
RamadhanAmizudin/malware
|
2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1
|
Fuzzbunch/fuzzbunch/redirection.py
|
python
|
RedirectionManager.redirect_local
|
(self, l, plugin, session_data)
|
targetip = Destination IP (on the target)
targetport = Destination Port (on the target)
redirip = IP of the LP
redirport = Port on the LP
|
targetip = Destination IP (on the target)
targetport = Destination Port (on the target)
redirip = IP of the LP
redirport = Port on the LP
|
[
"targetip",
"=",
"Destination",
"IP",
"(",
"on",
"the",
"target",
")",
"targetport",
"=",
"Destination",
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"target",
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"=",
"IP",
"of",
"the",
"LP",
"redirport",
"=",
"Port",
"on",
"the",
"LP"
] |
def redirect_local(self, l, plugin, session_data):
"""
targetip = Destination IP (on the target)
targetport = Destination Port (on the target)
redirip = IP of the LP
redirport = Port on the LP
"""
# listenaddr - name of variable containing the LP IP
# listenport - name of variable containing the LP Port
# destaddr - name of variable containing the Target IP
# destport - name of variable containing the Target Port
# targetip - IP of the target
# targetport - Port of the target
# redirip - IP of the LP
# redirport - Port of the LP
params = iDict(plugin.getParameters())
# Get the defaults for the user prompt
laddr = self.conv_param(l.listenaddr, params, session_data['params'])
lport = self.conv_param(l.listenport, params, session_data['params'])
daddr = self.conv_param(l.destaddr, params, session_data['params'])
dport = self.conv_param(l.destport, params, session_data['params'])
if None in (laddr, lport, daddr, dport):
for p,n in (laddr, l.listenaddr), (lport, l.listenport), (daddr, l.destaddr), (dport, l.destport):
if p == None:
self.io.print_warning("Parameter %s referenced by tunnel %s not found. This tunnel will "
"be ignored" % (n, l.name))
return
self.io.print_success("Local Tunnel - %s" % l.name)
#
# Get the destination IP and port for the target
#
targetip = self.prompt_redir_fake('Destination IP', daddr)
targetport = self.prompt_redir_fake('Destination Port', dport)
#
# Get the redirection addresses
#
redirip = self.prompt_redir(plugin, l.listenaddr, 'Listen IP', '127.0.0.1')
if not dport:
dport = targetport
redirport = self.prompt_redir(plugin, l.listenport, 'Listen Port', lport)
#
#
#
session_data['params'][l.listenaddr] = targetip
session_data['params'][l.listenport] = targetport
#
# Record the redirection tunnel
#
session_data['local'].append(LocalRedirection(l.protocol, redirip,
redirport, targetip,
targetport, name=l.name))
self.io.print_success("(%s) Local %s:%s -> %s:%s" %
(l.protocol, redirip, redirport, targetip, targetport))
|
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] |
https://github.com/RamadhanAmizudin/malware/blob/2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1/Fuzzbunch/fuzzbunch/redirection.py#L401-L464
|
||
jiangxiluning/FOTS.PyTorch
|
b1851c170b4f1ad18406766352cb5171648ce603
|
FOTS/utils/util.py
|
python
|
StringLabelConverter.encode
|
(self, text)
|
Support batch or single str.
Args:
text (str or list of str): texts to convert.
Returns:
torch.IntTensor [length_0 + length_1 + ... length_{n - 1}]: encoded texts.
torch.IntTensor [n]: length of each text.
|
Support batch or single str.
Args:
text (str or list of str): texts to convert.
Returns:
torch.IntTensor [length_0 + length_1 + ... length_{n - 1}]: encoded texts.
torch.IntTensor [n]: length of each text.
|
[
"Support",
"batch",
"or",
"single",
"str",
".",
"Args",
":",
"text",
"(",
"str",
"or",
"list",
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"texts",
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"IntTensor",
"[",
"n",
"]",
":",
"length",
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"each",
"text",
"."
] |
def encode(self, text):
"""Support batch or single str.
Args:
text (str or list of str): texts to convert.
Returns:
torch.IntTensor [length_0 + length_1 + ... length_{n - 1}]: encoded texts.
torch.IntTensor [n]: length of each text.
"""
if isinstance(text, str):
text = [
self.dict.get(char.lower() if self._ignore_case else char, self.dict['<other>'])
for char in text
]
length = [len(text)]
return text, length
elif isinstance(text, collections.Iterable):
length = [len(s) for s in text]
texts = []
for s in text:
text = self.encode(s)[0]
if len(text) > self.max_length:
if self.raise_over_length:
raise ValueError('{} is over length {}'.format(text, self.max_length))
else:
text = text[:self.max_length]
else:
text = text + [len(self.dict) + 1] * (self.max_length - len(text))
texts.append(text)
text = torch.tensor(texts, dtype=torch.long)
return text, length
|
[
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] |
https://github.com/jiangxiluning/FOTS.PyTorch/blob/b1851c170b4f1ad18406766352cb5171648ce603/FOTS/utils/util.py#L90-L121
|
||
wujian16/Cornell-MOE
|
df299d1be882d2af9796d7a68b3f9505cac7a53e
|
moe/optimal_learning/python/cpp_wrappers/domain.py
|
python
|
TensorProductDomain.__init__
|
(self, domain_bounds)
|
Construct a TensorProductDomain that can be used with cpp_wrappers.* functions/classes.
:param domain_bounds: the boundaries of a dim-dimensional tensor-product domain
:type domain_bounds: iterable of dim ClosedInterval
|
Construct a TensorProductDomain that can be used with cpp_wrappers.* functions/classes.
|
[
"Construct",
"a",
"TensorProductDomain",
"that",
"can",
"be",
"used",
"with",
"cpp_wrappers",
".",
"*",
"functions",
"/",
"classes",
"."
] |
def __init__(self, domain_bounds):
"""Construct a TensorProductDomain that can be used with cpp_wrappers.* functions/classes.
:param domain_bounds: the boundaries of a dim-dimensional tensor-product domain
:type domain_bounds: iterable of dim ClosedInterval
"""
self._domain_bounds = copy.deepcopy(domain_bounds)
self._domain_type = C_GP.DomainTypes.tensor_product
|
[
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".",
"tensor_product"
] |
https://github.com/wujian16/Cornell-MOE/blob/df299d1be882d2af9796d7a68b3f9505cac7a53e/moe/optimal_learning/python/cpp_wrappers/domain.py#L27-L35
|
||
D-X-Y/caffe-faster-rcnn
|
eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb
|
tools/extra/summarize.py
|
python
|
print_table
|
(table, max_width)
|
Print a simple nicely-aligned table.
table must be a list of (equal-length) lists. Columns are space-separated,
and as narrow as possible, but no wider than max_width. Text may overflow
columns; note that unlike string.format, this will not affect subsequent
columns, if possible.
|
Print a simple nicely-aligned table.
|
[
"Print",
"a",
"simple",
"nicely",
"-",
"aligned",
"table",
"."
] |
def print_table(table, max_width):
"""Print a simple nicely-aligned table.
table must be a list of (equal-length) lists. Columns are space-separated,
and as narrow as possible, but no wider than max_width. Text may overflow
columns; note that unlike string.format, this will not affect subsequent
columns, if possible."""
max_widths = [max_width] * len(table[0])
column_widths = [max(printed_len(row[j]) + 1 for row in table)
for j in range(len(table[0]))]
column_widths = [min(w, max_w) for w, max_w in zip(column_widths, max_widths)]
for row in table:
row_str = ''
right_col = 0
for cell, width in zip(row, column_widths):
right_col += width
row_str += cell + ' '
row_str += ' ' * max(right_col - printed_len(row_str), 0)
print row_str
|
[
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",",
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https://github.com/D-X-Y/caffe-faster-rcnn/blob/eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb/tools/extra/summarize.py#L41-L61
|
||
leela-zero/leela-zero
|
e3ed6310d33d75078ba74c3adf887d18439fc2e3
|
training/tf/average_weights.py
|
python
|
swa
|
(inputs, output, weights=None)
|
Average weights of the weight files.
inputs : List of filenames to use as inputs
output : String of output filename
weights : List of numbers to use for weighting the inputs
|
Average weights of the weight files.
|
[
"Average",
"weights",
"of",
"the",
"weight",
"files",
"."
] |
def swa(inputs, output, weights=None):
""" Average weights of the weight files.
inputs : List of filenames to use as inputs
output : String of output filename
weights : List of numbers to use for weighting the inputs
"""
out_weights = []
if weights == None:
weights = [1.0]*len(inputs)
if len(weights) != len(inputs):
raise ValueError("Number of weights doesn't match number of input files")
# Normalize weights
weights = [float(w)/sum(weights) for w in weights]
for count, filename in enumerate(inputs):
with open(filename, 'r') as f:
weights_in = []
for line in f:
weights_in.append(weights[count] * np.array(list(map(float, line.split(' ')))))
if count == 0:
out_weights = weights_in
else:
if len(out_weights) != len(weights_in):
raise ValueError("Nets have different sizes")
for e, w in enumerate(weights_in):
if len(w) != len(out_weights[e]):
raise ValueError("Nets have different sizes")
out_weights[e] += w
with open(output, 'w') as f:
for e, w in enumerate(out_weights):
if e == 0:
#Version
f.write('1\n')
else:
f.write(' '.join(map(str, w)) + '\n')
|
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] |
https://github.com/leela-zero/leela-zero/blob/e3ed6310d33d75078ba74c3adf887d18439fc2e3/training/tf/average_weights.py#L22-L62
|
||
timi-liuliang/echo
|
40a5a24d430eee4118314459ab7e03afcb3b8719
|
thirdparty/protobuf/python/google/protobuf/internal/python_message.py
|
python
|
_ExtensionDict.__setitem__
|
(self, extension_handle, value)
|
If extension_handle specifies a non-repeated, scalar extension
field, sets the value of that field.
|
If extension_handle specifies a non-repeated, scalar extension
field, sets the value of that field.
|
[
"If",
"extension_handle",
"specifies",
"a",
"non",
"-",
"repeated",
"scalar",
"extension",
"field",
"sets",
"the",
"value",
"of",
"that",
"field",
"."
] |
def __setitem__(self, extension_handle, value):
"""If extension_handle specifies a non-repeated, scalar extension
field, sets the value of that field.
"""
_VerifyExtensionHandle(self._extended_message, extension_handle)
if (extension_handle.label == _FieldDescriptor.LABEL_REPEATED or
extension_handle.cpp_type == _FieldDescriptor.CPPTYPE_MESSAGE):
raise TypeError(
'Cannot assign to extension "%s" because it is a repeated or '
'composite type.' % extension_handle.full_name)
# It's slightly wasteful to lookup the type checker each time,
# but we expect this to be a vanishingly uncommon case anyway.
type_checker = type_checkers.GetTypeChecker(
extension_handle)
# pylint: disable=protected-access
self._extended_message._fields[extension_handle] = (
type_checker.CheckValue(value))
self._extended_message._Modified()
|
[
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"(",
"value",
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")",
"self",
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"_extended_message",
".",
"_Modified",
"(",
")"
] |
https://github.com/timi-liuliang/echo/blob/40a5a24d430eee4118314459ab7e03afcb3b8719/thirdparty/protobuf/python/google/protobuf/internal/python_message.py#L1220-L1240
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/botocore/signers.py
|
python
|
generate_presigned_post
|
(self, Bucket, Key, Fields=None, Conditions=None,
ExpiresIn=3600)
|
return post_presigner.generate_presigned_post(
request_dict=request_dict, fields=fields, conditions=conditions,
expires_in=expires_in)
|
Builds the url and the form fields used for a presigned s3 post
:type Bucket: string
:param Bucket: The name of the bucket to presign the post to. Note that
bucket related conditions should not be included in the
``conditions`` parameter.
:type Key: string
:param Key: Key name, optionally add ${filename} to the end to
attach the submitted filename. Note that key related conditions and
fields are filled out for you and should not be included in the
``Fields`` or ``Conditions`` parameter.
:type Fields: dict
:param Fields: A dictionary of prefilled form fields to build on top
of. Elements that may be included are acl, Cache-Control,
Content-Type, Content-Disposition, Content-Encoding, Expires,
success_action_redirect, redirect, success_action_status,
and x-amz-meta-.
Note that if a particular element is included in the fields
dictionary it will not be automatically added to the conditions
list. You must specify a condition for the element as well.
:type Conditions: list
:param Conditions: A list of conditions to include in the policy. Each
element can be either a list or a structure. For example:
[
{"acl": "public-read"},
["content-length-range", 2, 5],
["starts-with", "$success_action_redirect", ""]
]
Conditions that are included may pertain to acl,
content-length-range, Cache-Control, Content-Type,
Content-Disposition, Content-Encoding, Expires,
success_action_redirect, redirect, success_action_status,
and/or x-amz-meta-.
Note that if you include a condition, you must specify
the a valid value in the fields dictionary as well. A value will
not be added automatically to the fields dictionary based on the
conditions.
:type ExpiresIn: int
:param ExpiresIn: The number of seconds the presigned post
is valid for.
:rtype: dict
:returns: A dictionary with two elements: ``url`` and ``fields``.
Url is the url to post to. Fields is a dictionary filled with
the form fields and respective values to use when submitting the
post. For example:
{'url': 'https://mybucket.s3.amazonaws.com
'fields': {'acl': 'public-read',
'key': 'mykey',
'signature': 'mysignature',
'policy': 'mybase64 encoded policy'}
}
|
Builds the url and the form fields used for a presigned s3 post
|
[
"Builds",
"the",
"url",
"and",
"the",
"form",
"fields",
"used",
"for",
"a",
"presigned",
"s3",
"post"
] |
def generate_presigned_post(self, Bucket, Key, Fields=None, Conditions=None,
ExpiresIn=3600):
"""Builds the url and the form fields used for a presigned s3 post
:type Bucket: string
:param Bucket: The name of the bucket to presign the post to. Note that
bucket related conditions should not be included in the
``conditions`` parameter.
:type Key: string
:param Key: Key name, optionally add ${filename} to the end to
attach the submitted filename. Note that key related conditions and
fields are filled out for you and should not be included in the
``Fields`` or ``Conditions`` parameter.
:type Fields: dict
:param Fields: A dictionary of prefilled form fields to build on top
of. Elements that may be included are acl, Cache-Control,
Content-Type, Content-Disposition, Content-Encoding, Expires,
success_action_redirect, redirect, success_action_status,
and x-amz-meta-.
Note that if a particular element is included in the fields
dictionary it will not be automatically added to the conditions
list. You must specify a condition for the element as well.
:type Conditions: list
:param Conditions: A list of conditions to include in the policy. Each
element can be either a list or a structure. For example:
[
{"acl": "public-read"},
["content-length-range", 2, 5],
["starts-with", "$success_action_redirect", ""]
]
Conditions that are included may pertain to acl,
content-length-range, Cache-Control, Content-Type,
Content-Disposition, Content-Encoding, Expires,
success_action_redirect, redirect, success_action_status,
and/or x-amz-meta-.
Note that if you include a condition, you must specify
the a valid value in the fields dictionary as well. A value will
not be added automatically to the fields dictionary based on the
conditions.
:type ExpiresIn: int
:param ExpiresIn: The number of seconds the presigned post
is valid for.
:rtype: dict
:returns: A dictionary with two elements: ``url`` and ``fields``.
Url is the url to post to. Fields is a dictionary filled with
the form fields and respective values to use when submitting the
post. For example:
{'url': 'https://mybucket.s3.amazonaws.com
'fields': {'acl': 'public-read',
'key': 'mykey',
'signature': 'mysignature',
'policy': 'mybase64 encoded policy'}
}
"""
bucket = Bucket
key = Key
fields = Fields
conditions = Conditions
expires_in = ExpiresIn
if fields is None:
fields = {}
if conditions is None:
conditions = []
post_presigner = S3PostPresigner(self._request_signer)
serializer = self._serializer
# We choose the CreateBucket operation model because its url gets
# serialized to what a presign post requires.
operation_model = self.meta.service_model.operation_model(
'CreateBucket')
# Create a request dict based on the params to serialize.
request_dict = serializer.serialize_to_request(
{'Bucket': bucket}, operation_model)
# Prepare the request dict by including the client's endpoint url.
prepare_request_dict(
request_dict, endpoint_url=self.meta.endpoint_url,
context={
'is_presign_request': True,
'use_global_endpoint': _should_use_global_endpoint(self),
},
)
# Append that the bucket name to the list of conditions.
conditions.append({'bucket': bucket})
# If the key ends with filename, the only constraint that can be
# imposed is if it starts with the specified prefix.
if key.endswith('${filename}'):
conditions.append(["starts-with", '$key', key[:-len('${filename}')]])
else:
conditions.append({'key': key})
# Add the key to the fields.
fields['key'] = key
return post_presigner.generate_presigned_post(
request_dict=request_dict, fields=fields, conditions=conditions,
expires_in=expires_in)
|
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/botocore/signers.py#L605-L717
|
|
lammps/lammps
|
b75c3065430a75b1b5543a10e10f46d9b4c91913
|
tools/i-pi/ipi/utils/inputvalue.py
|
python
|
InputArray.parse
|
(self, xml=None, text="")
|
Reads the data for an array from an xml file.
Args:
xml: An xml_node object containing the all the data for the parent
tag.
text: The data held between the start and end tags.
|
Reads the data for an array from an xml file.
|
[
"Reads",
"the",
"data",
"for",
"an",
"array",
"from",
"an",
"xml",
"file",
"."
] |
def parse(self, xml=None, text=""):
"""Reads the data for an array from an xml file.
Args:
xml: An xml_node object containing the all the data for the parent
tag.
text: The data held between the start and end tags.
"""
Input.parse(self, xml=xml, text=text)
self.value = read_array(self.type, self._text)
#if the shape is not specified, assume the array is linear.
if self.shape.fetch() == (0,):
self.shape.store((len(self.value),))
|
[
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https://github.com/lammps/lammps/blob/b75c3065430a75b1b5543a10e10f46d9b4c91913/tools/i-pi/ipi/utils/inputvalue.py#L954-L968
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/__init__.py
|
python
|
Misc.configure
|
(self, cnf=None, **kw)
|
return self._configure('configure', cnf, kw)
|
Configure resources of a widget.
The values for resources are specified as keyword
arguments. To get an overview about
the allowed keyword arguments call the method keys.
|
Configure resources of a widget.
|
[
"Configure",
"resources",
"of",
"a",
"widget",
"."
] |
def configure(self, cnf=None, **kw):
"""Configure resources of a widget.
The values for resources are specified as keyword
arguments. To get an overview about
the allowed keyword arguments call the method keys.
"""
return self._configure('configure', cnf, kw)
|
[
"def",
"configure",
"(",
"self",
",",
"cnf",
"=",
"None",
",",
"*",
"*",
"kw",
")",
":",
"return",
"self",
".",
"_configure",
"(",
"'configure'",
",",
"cnf",
",",
"kw",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/__init__.py#L1478-L1485
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/feature_column/serialization.py
|
python
|
deserialize_feature_columns
|
(configs, custom_objects=None)
|
return [
deserialize_feature_column(c, custom_objects, columns_by_name)
for c in configs
]
|
Deserializes a list of FeatureColumns configs.
Returns a list of FeatureColumns given a list of config dicts acquired by
`serialize_feature_columns`.
Args:
configs: A list of Dicts with the serialization of feature columns acquired
by `serialize_feature_columns`.
custom_objects: A Dict from custom_object name to the associated keras
serializable objects (FeatureColumns, classes or functions).
Returns:
FeatureColumn objects corresponding to the input configs.
Raises:
ValueError if called with input that is not a list of FeatureColumns.
|
Deserializes a list of FeatureColumns configs.
|
[
"Deserializes",
"a",
"list",
"of",
"FeatureColumns",
"configs",
"."
] |
def deserialize_feature_columns(configs, custom_objects=None):
"""Deserializes a list of FeatureColumns configs.
Returns a list of FeatureColumns given a list of config dicts acquired by
`serialize_feature_columns`.
Args:
configs: A list of Dicts with the serialization of feature columns acquired
by `serialize_feature_columns`.
custom_objects: A Dict from custom_object name to the associated keras
serializable objects (FeatureColumns, classes or functions).
Returns:
FeatureColumn objects corresponding to the input configs.
Raises:
ValueError if called with input that is not a list of FeatureColumns.
"""
columns_by_name = {}
return [
deserialize_feature_column(c, custom_objects, columns_by_name)
for c in configs
]
|
[
"def",
"deserialize_feature_columns",
"(",
"configs",
",",
"custom_objects",
"=",
"None",
")",
":",
"columns_by_name",
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"{",
"}",
"return",
"[",
"deserialize_feature_column",
"(",
"c",
",",
"custom_objects",
",",
"columns_by_name",
")",
"for",
"c",
"in",
"configs",
"]"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/feature_column/serialization.py#L170-L192
|
|
plumonito/dtslam
|
5994bb9cf7a11981b830370db206bceb654c085d
|
3rdparty/opencv-git/3rdparty/jinja2/lexer.py
|
python
|
describe_token
|
(token)
|
return _describe_token_type(token.type)
|
Returns a description of the token.
|
Returns a description of the token.
|
[
"Returns",
"a",
"description",
"of",
"the",
"token",
"."
] |
def describe_token(token):
"""Returns a description of the token."""
if token.type == 'name':
return token.value
return _describe_token_type(token.type)
|
[
"def",
"describe_token",
"(",
"token",
")",
":",
"if",
"token",
".",
"type",
"==",
"'name'",
":",
"return",
"token",
".",
"value",
"return",
"_describe_token_type",
"(",
"token",
".",
"type",
")"
] |
https://github.com/plumonito/dtslam/blob/5994bb9cf7a11981b830370db206bceb654c085d/3rdparty/opencv-git/3rdparty/jinja2/lexer.py#L164-L168
|
|
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/contrib/metrics/python/ops/metric_ops.py
|
python
|
streaming_mean_iou
|
(predictions,
labels,
num_classes,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None)
|
return metrics.mean_iou(
num_classes=num_classes, predictions=predictions, labels=labels,
weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
|
Calculate per-step mean Intersection-Over-Union (mIOU).
Mean Intersection-Over-Union is a common evaluation metric for
semantic image segmentation, which first computes the IOU for each
semantic class and then computes the average over classes.
IOU is defined as follows:
IOU = true_positive / (true_positive + false_positive + false_negative).
The predictions are accumulated in a confusion matrix, weighted by `weights`,
and mIOU is then calculated from it.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean_iou`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of prediction results for semantic labels, whose
shape is [batch size] and type `int32` or `int64`. The tensor will be
flattened, if its rank > 1.
labels: A `Tensor` of ground truth labels with shape [batch size] and of
type `int32` or `int64`. The tensor will be flattened, if its rank > 1.
num_classes: The possible number of labels the prediction task can
have. This value must be provided, since a confusion matrix of
dimension = [num_classes, num_classes] will be allocated.
weights: An optional `Tensor` whose shape is broadcastable to `predictions`.
metrics_collections: An optional list of collections that `mean_iou`
should be added to.
updates_collections: An optional list of collections `update_op` should be
added to.
name: An optional variable_scope name.
Returns:
mean_iou: A `Tensor` representing the mean intersection-over-union.
update_op: An operation that increments the confusion matrix.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
|
Calculate per-step mean Intersection-Over-Union (mIOU).
|
[
"Calculate",
"per",
"-",
"step",
"mean",
"Intersection",
"-",
"Over",
"-",
"Union",
"(",
"mIOU",
")",
"."
] |
def streaming_mean_iou(predictions,
labels,
num_classes,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Calculate per-step mean Intersection-Over-Union (mIOU).
Mean Intersection-Over-Union is a common evaluation metric for
semantic image segmentation, which first computes the IOU for each
semantic class and then computes the average over classes.
IOU is defined as follows:
IOU = true_positive / (true_positive + false_positive + false_negative).
The predictions are accumulated in a confusion matrix, weighted by `weights`,
and mIOU is then calculated from it.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean_iou`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of prediction results for semantic labels, whose
shape is [batch size] and type `int32` or `int64`. The tensor will be
flattened, if its rank > 1.
labels: A `Tensor` of ground truth labels with shape [batch size] and of
type `int32` or `int64`. The tensor will be flattened, if its rank > 1.
num_classes: The possible number of labels the prediction task can
have. This value must be provided, since a confusion matrix of
dimension = [num_classes, num_classes] will be allocated.
weights: An optional `Tensor` whose shape is broadcastable to `predictions`.
metrics_collections: An optional list of collections that `mean_iou`
should be added to.
updates_collections: An optional list of collections `update_op` should be
added to.
name: An optional variable_scope name.
Returns:
mean_iou: A `Tensor` representing the mean intersection-over-union.
update_op: An operation that increments the confusion matrix.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.mean_iou(
num_classes=num_classes, predictions=predictions, labels=labels,
weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
|
[
"def",
"streaming_mean_iou",
"(",
"predictions",
",",
"labels",
",",
"num_classes",
",",
"weights",
"=",
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",",
"metrics_collections",
"=",
"None",
",",
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"None",
",",
"name",
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"mean_iou",
"(",
"num_classes",
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"num_classes",
",",
"predictions",
"=",
"predictions",
",",
"labels",
"=",
"labels",
",",
"weights",
"=",
"weights",
",",
"metrics_collections",
"=",
"metrics_collections",
",",
"updates_collections",
"=",
"updates_collections",
",",
"name",
"=",
"name",
")"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/metrics/python/ops/metric_ops.py#L2194-L2245
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/tools/python3/src/Lib/_pydecimal.py
|
python
|
Decimal.is_qnan
|
(self)
|
return self._exp == 'n'
|
Return True if self is a quiet NaN; otherwise return False.
|
Return True if self is a quiet NaN; otherwise return False.
|
[
"Return",
"True",
"if",
"self",
"is",
"a",
"quiet",
"NaN",
";",
"otherwise",
"return",
"False",
"."
] |
def is_qnan(self):
"""Return True if self is a quiet NaN; otherwise return False."""
return self._exp == 'n'
|
[
"def",
"is_qnan",
"(",
"self",
")",
":",
"return",
"self",
".",
"_exp",
"==",
"'n'"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/_pydecimal.py#L3143-L3145
|
|
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Editor/Python/windows/Lib/site-packages/pip/_vendor/retrying.py
|
python
|
Retrying.incrementing_sleep
|
(self, previous_attempt_number, delay_since_first_attempt_ms)
|
return result
|
Sleep an incremental amount of time after each attempt, starting at
wait_incrementing_start and incrementing by wait_incrementing_increment
|
Sleep an incremental amount of time after each attempt, starting at
wait_incrementing_start and incrementing by wait_incrementing_increment
|
[
"Sleep",
"an",
"incremental",
"amount",
"of",
"time",
"after",
"each",
"attempt",
"starting",
"at",
"wait_incrementing_start",
"and",
"incrementing",
"by",
"wait_incrementing_increment"
] |
def incrementing_sleep(self, previous_attempt_number, delay_since_first_attempt_ms):
"""
Sleep an incremental amount of time after each attempt, starting at
wait_incrementing_start and incrementing by wait_incrementing_increment
"""
result = self._wait_incrementing_start + (self._wait_incrementing_increment * (previous_attempt_number - 1))
if result < 0:
result = 0
return result
|
[
"def",
"incrementing_sleep",
"(",
"self",
",",
"previous_attempt_number",
",",
"delay_since_first_attempt_ms",
")",
":",
"result",
"=",
"self",
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"_wait_incrementing_start",
"+",
"(",
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"_wait_incrementing_increment",
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"(",
"previous_attempt_number",
"-",
"1",
")",
")",
"if",
"result",
"<",
"0",
":",
"result",
"=",
"0",
"return",
"result"
] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/pip/_vendor/retrying.py#L161-L169
|
|
irods/irods
|
ed6328646cee87182098d569919004049bf4ce21
|
scripts/irods/pyparsing.py
|
python
|
ParseResults.asList
|
( self )
|
return [res.asList() if isinstance(res,ParseResults) else res for res in self.__toklist]
|
Returns the parse results as a nested list of matching tokens, all converted to strings.
|
Returns the parse results as a nested list of matching tokens, all converted to strings.
|
[
"Returns",
"the",
"parse",
"results",
"as",
"a",
"nested",
"list",
"of",
"matching",
"tokens",
"all",
"converted",
"to",
"strings",
"."
] |
def asList( self ):
"""Returns the parse results as a nested list of matching tokens, all converted to strings."""
return [res.asList() if isinstance(res,ParseResults) else res for res in self.__toklist]
|
[
"def",
"asList",
"(",
"self",
")",
":",
"return",
"[",
"res",
".",
"asList",
"(",
")",
"if",
"isinstance",
"(",
"res",
",",
"ParseResults",
")",
"else",
"res",
"for",
"res",
"in",
"self",
".",
"__toklist",
"]"
] |
https://github.com/irods/irods/blob/ed6328646cee87182098d569919004049bf4ce21/scripts/irods/pyparsing.py#L534-L536
|
|
pskun/finance_news_analysis
|
6ac13e32deede37a4cf57bba8b2897941ae3d80d
|
utils/util_func.py
|
python
|
atof
|
(f)
|
return f
|
字符串转浮点数
|
字符串转浮点数
|
[
"字符串转浮点数"
] |
def atof(f):
''' 字符串转浮点数 '''
try:
f = float(f)
except ValueError:
f = None
except TypeError:
f = None
return f
|
[
"def",
"atof",
"(",
"f",
")",
":",
"try",
":",
"f",
"=",
"float",
"(",
"f",
")",
"except",
"ValueError",
":",
"f",
"=",
"None",
"except",
"TypeError",
":",
"f",
"=",
"None",
"return",
"f"
] |
https://github.com/pskun/finance_news_analysis/blob/6ac13e32deede37a4cf57bba8b2897941ae3d80d/utils/util_func.py#L15-L23
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/distribute/one_device_strategy.py
|
python
|
OneDeviceExtended._global_batch_size
|
(self)
|
return True
|
Global and per-replica batching are equivalent for OneDeviceStrategy.
|
Global and per-replica batching are equivalent for OneDeviceStrategy.
|
[
"Global",
"and",
"per",
"-",
"replica",
"batching",
"are",
"equivalent",
"for",
"OneDeviceStrategy",
"."
] |
def _global_batch_size(self):
"""Global and per-replica batching are equivalent for OneDeviceStrategy."""
return True
|
[
"def",
"_global_batch_size",
"(",
"self",
")",
":",
"return",
"True"
] |
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/distribute/one_device_strategy.py#L466-L468
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_internal/network/lazy_wheel.py
|
python
|
LazyZipOverHTTP.mode
|
(self)
|
return 'rb'
|
Opening mode, which is always rb.
|
Opening mode, which is always rb.
|
[
"Opening",
"mode",
"which",
"is",
"always",
"rb",
"."
] |
def mode(self):
# type: () -> str
"""Opening mode, which is always rb."""
return 'rb'
|
[
"def",
"mode",
"(",
"self",
")",
":",
"# type: () -> str",
"return",
"'rb'"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_internal/network/lazy_wheel.py#L72-L75
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_core.py
|
python
|
Window.Refresh
|
(*args, **kwargs)
|
return _core_.Window_Refresh(*args, **kwargs)
|
Refresh(self, bool eraseBackground=True, Rect rect=None)
Mark the specified rectangle (or the whole window) as "dirty" so it
will be repainted. Causes an EVT_PAINT event to be generated and sent
to the window.
|
Refresh(self, bool eraseBackground=True, Rect rect=None)
|
[
"Refresh",
"(",
"self",
"bool",
"eraseBackground",
"=",
"True",
"Rect",
"rect",
"=",
"None",
")"
] |
def Refresh(*args, **kwargs):
"""
Refresh(self, bool eraseBackground=True, Rect rect=None)
Mark the specified rectangle (or the whole window) as "dirty" so it
will be repainted. Causes an EVT_PAINT event to be generated and sent
to the window.
"""
return _core_.Window_Refresh(*args, **kwargs)
|
[
"def",
"Refresh",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core_",
".",
"Window_Refresh",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_core.py#L10665-L10673
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py
|
python
|
Checkbutton.select
|
(self)
|
Put the button in on-state.
|
Put the button in on-state.
|
[
"Put",
"the",
"button",
"in",
"on",
"-",
"state",
"."
] |
def select(self):
"""Put the button in on-state."""
self.tk.call(self._w, 'select')
|
[
"def",
"select",
"(",
"self",
")",
":",
"self",
".",
"tk",
".",
"call",
"(",
"self",
".",
"_w",
",",
"'select'",
")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py#L2427-L2429
|
||
abyzovlab/CNVnator
|
c73786d6160f17b020feae928148533ca036fad2
|
pytools/io.py
|
python
|
IO.get_tree
|
(self, chr, signal)
|
return True
|
ToDo - read tree and return arrays
|
ToDo - read tree and return arrays
|
[
"ToDo",
"-",
"read",
"tree",
"and",
"return",
"arrays"
] |
def get_tree(self, chr, signal):
"""ToDo - read tree and return arrays"""
return True
|
[
"def",
"get_tree",
"(",
"self",
",",
"chr",
",",
"signal",
")",
":",
"return",
"True"
] |
https://github.com/abyzovlab/CNVnator/blob/c73786d6160f17b020feae928148533ca036fad2/pytools/io.py#L115-L117
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/gettext.py
|
python
|
test
|
(condition, true, false)
|
Implements the C expression:
condition ? true : false
Required to correctly interpret plural forms.
|
Implements the C expression:
|
[
"Implements",
"the",
"C",
"expression",
":"
] |
def test(condition, true, false):
"""
Implements the C expression:
condition ? true : false
Required to correctly interpret plural forms.
"""
if condition:
return true
else:
return false
|
[
"def",
"test",
"(",
"condition",
",",
"true",
",",
"false",
")",
":",
"if",
"condition",
":",
"return",
"true",
"else",
":",
"return",
"false"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/gettext.py#L61-L72
|
||
apple/swift-lldb
|
d74be846ef3e62de946df343e8c234bde93a8912
|
scripts/Python/static-binding/lldb.py
|
python
|
SBType.get_members_array
|
(self)
|
return members
|
An accessor function that returns a list() that contains all members (base classes and fields) in a lldb.SBType object in ascending bit offset order.
|
An accessor function that returns a list() that contains all members (base classes and fields) in a lldb.SBType object in ascending bit offset order.
|
[
"An",
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"base",
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"lldb",
".",
"SBType",
"object",
"in",
"ascending",
"bit",
"offset",
"order",
"."
] |
def get_members_array(self):
'''An accessor function that returns a list() that contains all members (base classes and fields) in a lldb.SBType object in ascending bit offset order.'''
members = []
bases = self.get_bases_array()
fields = self.get_fields_array()
vbases = self.get_vbases_array()
for base in bases:
bit_offset = base.bit_offset
added = False
for idx, member in enumerate(members):
if member.bit_offset > bit_offset:
members.insert(idx, base)
added = True
break
if not added:
members.append(base)
for vbase in vbases:
bit_offset = vbase.bit_offset
added = False
for idx, member in enumerate(members):
if member.bit_offset > bit_offset:
members.insert(idx, vbase)
added = True
break
if not added:
members.append(vbase)
for field in fields:
bit_offset = field.bit_offset
added = False
for idx, member in enumerate(members):
if member.bit_offset > bit_offset:
members.insert(idx, field)
added = True
break
if not added:
members.append(field)
return members
|
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https://github.com/apple/swift-lldb/blob/d74be846ef3e62de946df343e8c234bde93a8912/scripts/Python/static-binding/lldb.py#L12873-L12909
|
|
openmm/openmm
|
cb293447c4fc8b03976dfe11399f107bab70f3d9
|
wrappers/python/openmm/app/internal/amber_file_parser.py
|
python
|
PrmtopLoader.getDihedrals
|
(self)
|
return self._dihedralList
|
Return list of atom quads, K, phase and periodicity for each dihedral angle
|
Return list of atom quads, K, phase and periodicity for each dihedral angle
|
[
"Return",
"list",
"of",
"atom",
"quads",
"K",
"phase",
"and",
"periodicity",
"for",
"each",
"dihedral",
"angle"
] |
def getDihedrals(self):
"""Return list of atom quads, K, phase and periodicity for each dihedral angle"""
try:
return self._dihedralList
except AttributeError:
pass
forceConstant=self._raw_data["DIHEDRAL_FORCE_CONSTANT"]
phase=self._raw_data["DIHEDRAL_PHASE"]
periodicity=self._raw_data["DIHEDRAL_PERIODICITY"]
dihedralPointers = self._raw_data["DIHEDRALS_INC_HYDROGEN"] \
+self._raw_data["DIHEDRALS_WITHOUT_HYDROGEN"]
self._dihedralList=[]
forceConstConversionFactor = (units.kilocalorie_per_mole).conversion_factor_to(units.kilojoule_per_mole)
for ii in range(0,len(dihedralPointers),5):
if int(dihedralPointers[ii])<0 or int(dihedralPointers[ii+1])<0:
raise Exception("Found negative dihedral atom pointers %s"
% ((dihedralPointers[ii],
dihedralPointers[ii+1],
dihedralPointers[ii+2],
dihedralPointers[ii+3]),))
iType=int(dihedralPointers[ii+4])-1
self._dihedralList.append((int(dihedralPointers[ii])//3,
int(dihedralPointers[ii+1])//3,
abs(int(dihedralPointers[ii+2]))//3,
abs(int(dihedralPointers[ii+3]))//3,
float(forceConstant[iType])*forceConstConversionFactor,
float(phase[iType]),
int(0.5+float(periodicity[iType]))))
return self._dihedralList
|
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] |
https://github.com/openmm/openmm/blob/cb293447c4fc8b03976dfe11399f107bab70f3d9/wrappers/python/openmm/app/internal/amber_file_parser.py#L456-L484
|
|
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Code/Tools/waf-1.7.13/waflib/Build.py
|
python
|
BuildContext.add_manual_dependency
|
(self, path, value)
|
Adds a dependency from a node object to a value::
def build(bld):
bld.add_manual_dependency(
bld.path.find_resource('wscript'),
bld.root.find_resource('/etc/fstab'))
:param path: file path
:type path: string or :py:class:`waflib.Node.Node`
:param value: value to depend on
:type value: :py:class:`waflib.Node.Node`, string, or function returning a string
|
Adds a dependency from a node object to a value::
|
[
"Adds",
"a",
"dependency",
"from",
"a",
"node",
"object",
"to",
"a",
"value",
"::"
] |
def add_manual_dependency(self, path, value):
"""
Adds a dependency from a node object to a value::
def build(bld):
bld.add_manual_dependency(
bld.path.find_resource('wscript'),
bld.root.find_resource('/etc/fstab'))
:param path: file path
:type path: string or :py:class:`waflib.Node.Node`
:param value: value to depend on
:type value: :py:class:`waflib.Node.Node`, string, or function returning a string
"""
if path is None:
raise ValueError('Invalid input')
if isinstance(path, waflib.Node.Node):
node = path
elif os.path.isabs(path):
node = self.root.find_resource(path)
else:
node = self.path.find_resource(path)
if isinstance(value, list):
self.deps_man[id(node)].extend(value)
else:
self.deps_man[id(node)].append(value)
|
[
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"]",
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"(",
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] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Code/Tools/waf-1.7.13/waflib/Build.py#L434-L461
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/propgrid.py
|
python
|
PyEditor.__init__
|
(self, *args, **kwargs)
|
__init__(self) -> PyEditor
|
__init__(self) -> PyEditor
|
[
"__init__",
"(",
"self",
")",
"-",
">",
"PyEditor"
] |
def __init__(self, *args, **kwargs):
"""__init__(self) -> PyEditor"""
_propgrid.PyEditor_swiginit(self,_propgrid.new_PyEditor(*args, **kwargs))
self._SetSelf(self); self._RegisterMethods()
|
[
"def",
"__init__",
"(",
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",",
"*",
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",",
"*",
"*",
"kwargs",
")",
":",
"_propgrid",
".",
"PyEditor_swiginit",
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",",
"_propgrid",
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",",
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")",
")",
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"(",
"self",
")",
"self",
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"_RegisterMethods",
"(",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/propgrid.py#L4410-L4413
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/roc/hsadrv/driver.py
|
python
|
Stream._get_last_signal
|
(self)
|
return self._signals[-1] if self._signals else None
|
Get the last signal.
|
Get the last signal.
|
[
"Get",
"the",
"last",
"signal",
"."
] |
def _get_last_signal(self):
"""
Get the last signal.
"""
return self._signals[-1] if self._signals else None
|
[
"def",
"_get_last_signal",
"(",
"self",
")",
":",
"return",
"self",
".",
"_signals",
"[",
"-",
"1",
"]",
"if",
"self",
".",
"_signals",
"else",
"None"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/roc/hsadrv/driver.py#L1365-L1369
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/plotting/_core.py
|
python
|
boxplot_frame_groupby
|
(
grouped,
subplots=True,
column=None,
fontsize=None,
rot=0,
grid=True,
ax=None,
figsize=None,
layout=None,
sharex=False,
sharey=True,
backend=None,
**kwargs,
)
|
return plot_backend.boxplot_frame_groupby(
grouped,
subplots=subplots,
column=column,
fontsize=fontsize,
rot=rot,
grid=grid,
ax=ax,
figsize=figsize,
layout=layout,
sharex=sharex,
sharey=sharey,
**kwargs,
)
|
Make box plots from DataFrameGroupBy data.
Parameters
----------
grouped : Grouped DataFrame
subplots : bool
* ``False`` - no subplots will be used
* ``True`` - create a subplot for each group.
column : column name or list of names, or vector
Can be any valid input to groupby.
fontsize : int or str
rot : label rotation angle
grid : Setting this to True will show the grid
ax : Matplotlib axis object, default None
figsize : A tuple (width, height) in inches
layout : tuple (optional)
The layout of the plot: (rows, columns).
sharex : bool, default False
Whether x-axes will be shared among subplots.
.. versionadded:: 0.23.1
sharey : bool, default True
Whether y-axes will be shared among subplots.
.. versionadded:: 0.23.1
backend : str, default None
Backend to use instead of the backend specified in the option
``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
specify the ``plotting.backend`` for the whole session, set
``pd.options.plotting.backend``.
.. versionadded:: 1.0.0
**kwargs
All other plotting keyword arguments to be passed to
matplotlib's boxplot function.
Returns
-------
dict of key/value = group key/DataFrame.boxplot return value
or DataFrame.boxplot return value in case subplots=figures=False
Examples
--------
>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)
|
Make box plots from DataFrameGroupBy data.
|
[
"Make",
"box",
"plots",
"from",
"DataFrameGroupBy",
"data",
"."
] |
def boxplot_frame_groupby(
grouped,
subplots=True,
column=None,
fontsize=None,
rot=0,
grid=True,
ax=None,
figsize=None,
layout=None,
sharex=False,
sharey=True,
backend=None,
**kwargs,
):
"""
Make box plots from DataFrameGroupBy data.
Parameters
----------
grouped : Grouped DataFrame
subplots : bool
* ``False`` - no subplots will be used
* ``True`` - create a subplot for each group.
column : column name or list of names, or vector
Can be any valid input to groupby.
fontsize : int or str
rot : label rotation angle
grid : Setting this to True will show the grid
ax : Matplotlib axis object, default None
figsize : A tuple (width, height) in inches
layout : tuple (optional)
The layout of the plot: (rows, columns).
sharex : bool, default False
Whether x-axes will be shared among subplots.
.. versionadded:: 0.23.1
sharey : bool, default True
Whether y-axes will be shared among subplots.
.. versionadded:: 0.23.1
backend : str, default None
Backend to use instead of the backend specified in the option
``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
specify the ``plotting.backend`` for the whole session, set
``pd.options.plotting.backend``.
.. versionadded:: 1.0.0
**kwargs
All other plotting keyword arguments to be passed to
matplotlib's boxplot function.
Returns
-------
dict of key/value = group key/DataFrame.boxplot return value
or DataFrame.boxplot return value in case subplots=figures=False
Examples
--------
>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)
"""
plot_backend = _get_plot_backend(backend)
return plot_backend.boxplot_frame_groupby(
grouped,
subplots=subplots,
column=column,
fontsize=fontsize,
rot=rot,
grid=grid,
ax=ax,
figsize=figsize,
layout=layout,
sharex=sharex,
sharey=sharey,
**kwargs,
)
|
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",",
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/plotting/_core.py#L451-L538
|
|
dmlc/treelite
|
df56babb6a4a2d7c29d719c28ce53acfa7dbab3c
|
python/setup.py
|
python
|
BuildExt.build
|
(self, src_dir, build_dir, generator, build_tool=None)
|
Build the core library with CMake.
|
Build the core library with CMake.
|
[
"Build",
"the",
"core",
"library",
"with",
"CMake",
"."
] |
def build(self, src_dir, build_dir, generator, build_tool=None):
"""Build the core library with CMake."""
cmake_cmd = ['cmake', src_dir, generator]
# Flag for cross-compiling for Apple Silicon
# We use environment variable because it's the only way to pass down custom flags
# through the cibuildwheel package, which otherwise calls `python setup.py bdist_wheel`
# command.
if 'CIBW_TARGET_OSX_ARM64' in os.environ:
cmake_cmd.append("-DCMAKE_OSX_ARCHITECTURES=arm64")
self.logger.info('Run CMake command: %s', str(cmake_cmd))
subprocess.check_call(cmake_cmd, cwd=build_dir)
if system() != 'Windows':
nproc = os.cpu_count()
build_cmd = [build_tool, 'treelite', '-j' + str(nproc)]
subprocess.check_call(build_cmd, cwd=build_dir)
else:
subprocess.check_call(['cmake', '--build', '.', '--config', 'Release',
'--target', 'treelite'], cwd=build_dir)
|
[
"def",
"build",
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"self",
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"src_dir",
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"build_dir",
",",
"generator",
",",
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"=",
"None",
")",
":",
"cmake_cmd",
"=",
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"'cmake'",
",",
"src_dir",
",",
"generator",
"]",
"# Flag for cross-compiling for Apple Silicon",
"# We use environment variable because it's the only way to pass down custom flags",
"# through the cibuildwheel package, which otherwise calls `python setup.py bdist_wheel`",
"# command.",
"if",
"'CIBW_TARGET_OSX_ARM64'",
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"cmake_cmd",
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"append",
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"\"-DCMAKE_OSX_ARCHITECTURES=arm64\"",
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"'Run CMake command: %s'",
",",
"str",
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"cmake_cmd",
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",",
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"'Windows'",
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",",
"cwd",
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"build_dir",
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"else",
":",
"subprocess",
".",
"check_call",
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"[",
"'cmake'",
",",
"'--build'",
",",
"'.'",
",",
"'--config'",
",",
"'Release'",
",",
"'--target'",
",",
"'treelite'",
"]",
",",
"cwd",
"=",
"build_dir",
")"
] |
https://github.com/dmlc/treelite/blob/df56babb6a4a2d7c29d719c28ce53acfa7dbab3c/python/setup.py#L97-L117
|
||
baidu/AnyQ
|
d94d450d2aaa5f7ed73424b10aa4539835b97527
|
tools/simnet/train/paddle/losses/log_loss.py
|
python
|
LogLoss.__init__
|
(self, conf_dict)
|
initialize
|
initialize
|
[
"initialize"
] |
def __init__(self, conf_dict):
"""
initialize
"""
pass
|
[
"def",
"__init__",
"(",
"self",
",",
"conf_dict",
")",
":",
"pass"
] |
https://github.com/baidu/AnyQ/blob/d94d450d2aaa5f7ed73424b10aa4539835b97527/tools/simnet/train/paddle/losses/log_loss.py#L24-L28
|
||
Alexhuszagh/rust-lexical
|
01fcdcf8efc8850edb35d8fc65fd5f31bd0981a0
|
scripts/size.py
|
python
|
build
|
(args, level, is_lexical)
|
Build the project.
|
Build the project.
|
[
"Build",
"the",
"project",
"."
] |
def build(args, level, is_lexical):
'''Build the project.'''
os.chdir(f'{home}/lexical-size')
command = f'cargo +nightly build'
if args.no_default_features:
command = f'{command} --no-default-features'
features = args.features
if is_lexical:
if features:
features = f'{features},lexical'
else:
features = 'lexical'
if features:
command = f'{command} --features={features}'
if LEVELS[level] == 'release':
command = f'{command} --release'
subprocess.check_call(
# Use shell for faster performance.
# Spawning a new process is a **lot** slower, gives misleading info.
command,
shell=True,
stderr=subprocess.DEVNULL,
stdout=subprocess.DEVNULL,
)
|
[
"def",
"build",
"(",
"args",
",",
"level",
",",
"is_lexical",
")",
":",
"os",
".",
"chdir",
"(",
"f'{home}/lexical-size'",
")",
"command",
"=",
"f'cargo +nightly build'",
"if",
"args",
".",
"no_default_features",
":",
"command",
"=",
"f'{command} --no-default-features'",
"features",
"=",
"args",
".",
"features",
"if",
"is_lexical",
":",
"if",
"features",
":",
"features",
"=",
"f'{features},lexical'",
"else",
":",
"features",
"=",
"'lexical'",
"if",
"features",
":",
"command",
"=",
"f'{command} --features={features}'",
"if",
"LEVELS",
"[",
"level",
"]",
"==",
"'release'",
":",
"command",
"=",
"f'{command} --release'",
"subprocess",
".",
"check_call",
"(",
"# Use shell for faster performance.",
"# Spawning a new process is a **lot** slower, gives misleading info.",
"command",
",",
"shell",
"=",
"True",
",",
"stderr",
"=",
"subprocess",
".",
"DEVNULL",
",",
"stdout",
"=",
"subprocess",
".",
"DEVNULL",
",",
")"
] |
https://github.com/Alexhuszagh/rust-lexical/blob/01fcdcf8efc8850edb35d8fc65fd5f31bd0981a0/scripts/size.py#L172-L196
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/ntpath.py
|
python
|
_abspath_fallback
|
(path)
|
return normpath(path)
|
Return the absolute version of a path as a fallback function in case
`nt._getfullpathname` is not available or raises OSError. See bpo-31047 for
more.
|
Return the absolute version of a path as a fallback function in case
`nt._getfullpathname` is not available or raises OSError. See bpo-31047 for
more.
|
[
"Return",
"the",
"absolute",
"version",
"of",
"a",
"path",
"as",
"a",
"fallback",
"function",
"in",
"case",
"nt",
".",
"_getfullpathname",
"is",
"not",
"available",
"or",
"raises",
"OSError",
".",
"See",
"bpo",
"-",
"31047",
"for",
"more",
"."
] |
def _abspath_fallback(path):
"""Return the absolute version of a path as a fallback function in case
`nt._getfullpathname` is not available or raises OSError. See bpo-31047 for
more.
"""
path = os.fspath(path)
if not isabs(path):
if isinstance(path, bytes):
cwd = os.getcwdb()
else:
cwd = os.getcwd()
path = join(cwd, path)
return normpath(path)
|
[
"def",
"_abspath_fallback",
"(",
"path",
")",
":",
"path",
"=",
"os",
".",
"fspath",
"(",
"path",
")",
"if",
"not",
"isabs",
"(",
"path",
")",
":",
"if",
"isinstance",
"(",
"path",
",",
"bytes",
")",
":",
"cwd",
"=",
"os",
".",
"getcwdb",
"(",
")",
"else",
":",
"cwd",
"=",
"os",
".",
"getcwd",
"(",
")",
"path",
"=",
"join",
"(",
"cwd",
",",
"path",
")",
"return",
"normpath",
"(",
"path",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/ntpath.py#L499-L513
|
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