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catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/py3/scipy/stats/_multivariate.py
|
python
|
multivariate_normal_gen.logcdf
|
(self, x, mean=None, cov=1, allow_singular=False, maxpts=None,
abseps=1e-5, releps=1e-5)
|
return out
|
Log of the multivariate normal cumulative distribution function.
Parameters
----------
x : array_like
Quantiles, with the last axis of `x` denoting the components.
%(_mvn_doc_default_callparams)s
maxpts: integer, optional
The maximum number of points to use for integration
(default `1000000*dim`)
abseps: float, optional
Absolute error tolerance (default 1e-5)
releps: float, optional
Relative error tolerance (default 1e-5)
Returns
-------
cdf : ndarray or scalar
Log of the cumulative distribution function evaluated at `x`
Notes
-----
%(_mvn_doc_callparams_note)s
.. versionadded:: 1.0.0
|
Log of the multivariate normal cumulative distribution function.
|
[
"Log",
"of",
"the",
"multivariate",
"normal",
"cumulative",
"distribution",
"function",
"."
] |
def logcdf(self, x, mean=None, cov=1, allow_singular=False, maxpts=None,
abseps=1e-5, releps=1e-5):
"""
Log of the multivariate normal cumulative distribution function.
Parameters
----------
x : array_like
Quantiles, with the last axis of `x` denoting the components.
%(_mvn_doc_default_callparams)s
maxpts: integer, optional
The maximum number of points to use for integration
(default `1000000*dim`)
abseps: float, optional
Absolute error tolerance (default 1e-5)
releps: float, optional
Relative error tolerance (default 1e-5)
Returns
-------
cdf : ndarray or scalar
Log of the cumulative distribution function evaluated at `x`
Notes
-----
%(_mvn_doc_callparams_note)s
.. versionadded:: 1.0.0
"""
dim, mean, cov = self._process_parameters(None, mean, cov)
x = self._process_quantiles(x, dim)
# Use _PSD to check covariance matrix
_PSD(cov, allow_singular=allow_singular)
if not maxpts:
maxpts = 1000000 * dim
out = np.log(self._cdf(x, mean, cov, maxpts, abseps, releps))
return out
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py3/scipy/stats/_multivariate.py#L557-L594
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/agw/customtreectrl.py
|
python
|
CustomTreeCtrl.SetStateImageList
|
(self, imageList)
|
Sets the state image list for :class:`CustomTreeCtrl` (from which application-defined
state images are taken).
:param `imageList`: an instance of :class:`ImageList`.
|
Sets the state image list for :class:`CustomTreeCtrl` (from which application-defined
state images are taken).
|
[
"Sets",
"the",
"state",
"image",
"list",
"for",
":",
"class",
":",
"CustomTreeCtrl",
"(",
"from",
"which",
"application",
"-",
"defined",
"state",
"images",
"are",
"taken",
")",
"."
] |
def SetStateImageList(self, imageList):
"""
Sets the state image list for :class:`CustomTreeCtrl` (from which application-defined
state images are taken).
:param `imageList`: an instance of :class:`ImageList`.
"""
if self._ownsImageListState:
del self._imageListState
self._imageListState = imageList
self._ownsImageListState = False
|
[
"def",
"SetStateImageList",
"(",
"self",
",",
"imageList",
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":",
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".",
"_ownsImageListState",
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"_imageListState",
"self",
".",
"_imageListState",
"=",
"imageList",
"self",
".",
"_ownsImageListState",
"=",
"False"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/customtreectrl.py#L6114-L6126
|
||
forkineye/ESPixelStick
|
22926f1c0d1131f1369fc7cad405689a095ae3cb
|
dist/bin/esptool/serial/serialcli.py
|
python
|
Serial.cts
|
(self)
|
return self._port_handle.CtsHolding
|
Read terminal status line: Clear To Send
|
Read terminal status line: Clear To Send
|
[
"Read",
"terminal",
"status",
"line",
":",
"Clear",
"To",
"Send"
] |
def cts(self):
"""Read terminal status line: Clear To Send"""
if not self.is_open:
raise portNotOpenError
return self._port_handle.CtsHolding
|
[
"def",
"cts",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"is_open",
":",
"raise",
"portNotOpenError",
"return",
"self",
".",
"_port_handle",
".",
"CtsHolding"
] |
https://github.com/forkineye/ESPixelStick/blob/22926f1c0d1131f1369fc7cad405689a095ae3cb/dist/bin/esptool/serial/serialcli.py#L222-L226
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/datetime.py
|
python
|
tzinfo.utcoffset
|
(self, dt)
|
datetime -> timedelta, positive for east of UTC, negative for west of UTC
|
datetime -> timedelta, positive for east of UTC, negative for west of UTC
|
[
"datetime",
"-",
">",
"timedelta",
"positive",
"for",
"east",
"of",
"UTC",
"negative",
"for",
"west",
"of",
"UTC"
] |
def utcoffset(self, dt):
"datetime -> timedelta, positive for east of UTC, negative for west of UTC"
raise NotImplementedError("tzinfo subclass must override utcoffset()")
|
[
"def",
"utcoffset",
"(",
"self",
",",
"dt",
")",
":",
"raise",
"NotImplementedError",
"(",
"\"tzinfo subclass must override utcoffset()\"",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/datetime.py#L1103-L1105
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/pipes.py
|
python
|
Template.open
|
(self, file, rw)
|
t.open(file, rw) returns a pipe or file object open for
reading or writing; the file is the other end of the pipeline.
|
t.open(file, rw) returns a pipe or file object open for
reading or writing; the file is the other end of the pipeline.
|
[
"t",
".",
"open",
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"file",
"rw",
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"returns",
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"pipe",
"or",
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"reading",
"or",
"writing",
";",
"the",
"file",
"is",
"the",
"other",
"end",
"of",
"the",
"pipeline",
"."
] |
def open(self, file, rw):
"""t.open(file, rw) returns a pipe or file object open for
reading or writing; the file is the other end of the pipeline."""
if rw == 'r':
return self.open_r(file)
if rw == 'w':
return self.open_w(file)
raise ValueError, \
'Template.open: rw must be \'r\' or \'w\', not %r' % (rw,)
|
[
"def",
"open",
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"self",
",",
"file",
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"if",
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"==",
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"ValueError",
",",
"'Template.open: rw must be \\'r\\' or \\'w\\', not %r'",
"%",
"(",
"rw",
",",
")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/pipes.py#L152-L160
|
||
martinmoene/lest
|
f3e9dfe4a66c3e60dfdac7a3d3e4ddc0dcf06b26
|
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 )
|
[
"def",
"createControl",
"(",
"args",
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":",
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":",
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"(",
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",",
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"=",
"f",
")"
] |
https://github.com/martinmoene/lest/blob/f3e9dfe4a66c3e60dfdac7a3d3e4ddc0dcf06b26/script/create-vcpkg.py#L100-L110
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/_pydecimal.py
|
python
|
Context.compare_total
|
(self, a, b)
|
return a.compare_total(b)
|
Compares two operands using their abstract representation.
This is not like the standard compare, which use their numerical
value. Note that a total ordering is defined for all possible abstract
representations.
>>> ExtendedContext.compare_total(Decimal('12.73'), Decimal('127.9'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('-127'), Decimal('12'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.3'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.30'))
Decimal('0')
>>> ExtendedContext.compare_total(Decimal('12.3'), Decimal('12.300'))
Decimal('1')
>>> ExtendedContext.compare_total(Decimal('12.3'), Decimal('NaN'))
Decimal('-1')
>>> ExtendedContext.compare_total(1, 2)
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal(1), 2)
Decimal('-1')
>>> ExtendedContext.compare_total(1, Decimal(2))
Decimal('-1')
|
Compares two operands using their abstract representation.
|
[
"Compares",
"two",
"operands",
"using",
"their",
"abstract",
"representation",
"."
] |
def compare_total(self, a, b):
"""Compares two operands using their abstract representation.
This is not like the standard compare, which use their numerical
value. Note that a total ordering is defined for all possible abstract
representations.
>>> ExtendedContext.compare_total(Decimal('12.73'), Decimal('127.9'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('-127'), Decimal('12'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.3'))
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.30'))
Decimal('0')
>>> ExtendedContext.compare_total(Decimal('12.3'), Decimal('12.300'))
Decimal('1')
>>> ExtendedContext.compare_total(Decimal('12.3'), Decimal('NaN'))
Decimal('-1')
>>> ExtendedContext.compare_total(1, 2)
Decimal('-1')
>>> ExtendedContext.compare_total(Decimal(1), 2)
Decimal('-1')
>>> ExtendedContext.compare_total(1, Decimal(2))
Decimal('-1')
"""
a = _convert_other(a, raiseit=True)
return a.compare_total(b)
|
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"def",
"compare_total",
"(",
"self",
",",
"a",
",",
"b",
")",
":",
"a",
"=",
"_convert_other",
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",",
"raiseit",
"=",
"True",
")",
"return",
"a",
".",
"compare_total",
"(",
"b",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/_pydecimal.py#L4258-L4285
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/botocore/docs/params.py
|
python
|
BaseParamsDocumenter.document_params
|
(self, section, shape, include=None, exclude=None)
|
Fills out the documentation for a section given a model shape.
:param section: The section to write the documentation to.
:param shape: The shape of the operation.
:type include: Dictionary where keys are parameter names and
values are the shapes of the parameter names.
:param include: The parameter shapes to include in the documentation.
:type exclude: List of the names of the parameters to exclude.
:param exclude: The names of the parameters to exclude from
documentation.
|
Fills out the documentation for a section given a model shape.
|
[
"Fills",
"out",
"the",
"documentation",
"for",
"a",
"section",
"given",
"a",
"model",
"shape",
"."
] |
def document_params(self, section, shape, include=None, exclude=None):
"""Fills out the documentation for a section given a model shape.
:param section: The section to write the documentation to.
:param shape: The shape of the operation.
:type include: Dictionary where keys are parameter names and
values are the shapes of the parameter names.
:param include: The parameter shapes to include in the documentation.
:type exclude: List of the names of the parameters to exclude.
:param exclude: The names of the parameters to exclude from
documentation.
"""
history = []
self.traverse_and_document_shape(
section=section, shape=shape, history=history,
name=None, include=include, exclude=exclude)
|
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/botocore/docs/params.py#L18-L36
|
||
wy1iu/LargeMargin_Softmax_Loss
|
c3e9f20e4f16e2b4daf7d358a614366b9b39a6ec
|
python/caffe/coord_map.py
|
python
|
conv_params
|
(fn)
|
return (axis, np.array(params.get('stride', 1), ndmin=1),
(ks - 1) * dilation + 1,
np.array(params.get('pad', 0), ndmin=1))
|
Extract the spatial parameters that determine the coordinate mapping:
kernel size, stride, padding, and dilation.
Implementation detail: Convolution, Deconvolution, and Im2col layers
define these in the convolution_param message, while Pooling has its
own fields in pooling_param. This method deals with these details to
extract canonical parameters.
|
Extract the spatial parameters that determine the coordinate mapping:
kernel size, stride, padding, and dilation.
|
[
"Extract",
"the",
"spatial",
"parameters",
"that",
"determine",
"the",
"coordinate",
"mapping",
":",
"kernel",
"size",
"stride",
"padding",
"and",
"dilation",
"."
] |
def conv_params(fn):
"""
Extract the spatial parameters that determine the coordinate mapping:
kernel size, stride, padding, and dilation.
Implementation detail: Convolution, Deconvolution, and Im2col layers
define these in the convolution_param message, while Pooling has its
own fields in pooling_param. This method deals with these details to
extract canonical parameters.
"""
params = fn.params.get('convolution_param', fn.params)
axis = params.get('axis', 1)
ks = np.array(params['kernel_size'], ndmin=1)
dilation = np.array(params.get('dilation', 1), ndmin=1)
assert len({'pad_h', 'pad_w', 'kernel_h', 'kernel_w', 'stride_h',
'stride_w'} & set(fn.params)) == 0, \
'cropping does not support legacy _h/_w params'
return (axis, np.array(params.get('stride', 1), ndmin=1),
(ks - 1) * dilation + 1,
np.array(params.get('pad', 0), ndmin=1))
|
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https://github.com/wy1iu/LargeMargin_Softmax_Loss/blob/c3e9f20e4f16e2b4daf7d358a614366b9b39a6ec/python/caffe/coord_map.py#L18-L37
|
|
bumptop/BumpTop
|
466d23597a07ae738f4265262fa01087fc6e257c
|
trunk/win/Source/bin/jinja2/runtime.py
|
python
|
Context.get
|
(self, key, default=None)
|
Returns an item from the template context, if it doesn't exist
`default` is returned.
|
Returns an item from the template context, if it doesn't exist
`default` is returned.
|
[
"Returns",
"an",
"item",
"from",
"the",
"template",
"context",
"if",
"it",
"doesn",
"t",
"exist",
"default",
"is",
"returned",
"."
] |
def get(self, key, default=None):
"""Returns an item from the template context, if it doesn't exist
`default` is returned.
"""
try:
return self[key]
except KeyError:
return default
|
[
"def",
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"(",
"self",
",",
"key",
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"None",
")",
":",
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":",
"return",
"self",
"[",
"key",
"]",
"except",
"KeyError",
":",
"return",
"default"
] |
https://github.com/bumptop/BumpTop/blob/466d23597a07ae738f4265262fa01087fc6e257c/trunk/win/Source/bin/jinja2/runtime.py#L136-L143
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/_core.py
|
python
|
MenuBar.EnableTop
|
(*args, **kwargs)
|
return _core_.MenuBar_EnableTop(*args, **kwargs)
|
EnableTop(self, size_t pos, bool enable)
|
EnableTop(self, size_t pos, bool enable)
|
[
"EnableTop",
"(",
"self",
"size_t",
"pos",
"bool",
"enable",
")"
] |
def EnableTop(*args, **kwargs):
"""EnableTop(self, size_t pos, bool enable)"""
return _core_.MenuBar_EnableTop(*args, **kwargs)
|
[
"def",
"EnableTop",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core_",
".",
"MenuBar_EnableTop",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_core.py#L12292-L12294
|
|
PX4/PX4-Autopilot
|
0b9f60a0370be53d683352c63fd92db3d6586e18
|
platforms/nuttx/NuttX/tools/kconfiglib.py
|
python
|
load_allconfig
|
(kconf, filename)
|
Helper for all*config. Loads (merges) the configuration file specified by
KCONFIG_ALLCONFIG, if any. See Documentation/kbuild/kconfig.txt in the
Linux kernel.
Disables warnings for duplicated assignments within configuration files for
the duration of the call (disable_override_warnings() +
disable_redun_warnings()), and enables them at the end. The
KCONFIG_ALLCONFIG configuration file is expected to override symbols.
Exits with sys.exit() (which raises a SystemExit exception) and prints an
error to stderr if KCONFIG_ALLCONFIG is set but the configuration file
can't be opened.
kconf:
Kconfig instance to load the configuration in.
filename:
Command-specific configuration filename - "allyes.config",
"allno.config", etc.
|
Helper for all*config. Loads (merges) the configuration file specified by
KCONFIG_ALLCONFIG, if any. See Documentation/kbuild/kconfig.txt in the
Linux kernel.
|
[
"Helper",
"for",
"all",
"*",
"config",
".",
"Loads",
"(",
"merges",
")",
"the",
"configuration",
"file",
"specified",
"by",
"KCONFIG_ALLCONFIG",
"if",
"any",
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"Documentation",
"/",
"kbuild",
"/",
"kconfig",
".",
"txt",
"in",
"the",
"Linux",
"kernel",
"."
] |
def load_allconfig(kconf, filename):
"""
Helper for all*config. Loads (merges) the configuration file specified by
KCONFIG_ALLCONFIG, if any. See Documentation/kbuild/kconfig.txt in the
Linux kernel.
Disables warnings for duplicated assignments within configuration files for
the duration of the call (disable_override_warnings() +
disable_redun_warnings()), and enables them at the end. The
KCONFIG_ALLCONFIG configuration file is expected to override symbols.
Exits with sys.exit() (which raises a SystemExit exception) and prints an
error to stderr if KCONFIG_ALLCONFIG is set but the configuration file
can't be opened.
kconf:
Kconfig instance to load the configuration in.
filename:
Command-specific configuration filename - "allyes.config",
"allno.config", etc.
"""
def std_msg(e):
# "Upcasts" a _KconfigIOError to an IOError, removing the custom
# __str__() message. The standard message is better here.
return IOError(e.errno, e.strerror, e.filename)
kconf.disable_override_warnings()
kconf.disable_redun_warnings()
allconfig = os.environ.get("KCONFIG_ALLCONFIG")
if allconfig is not None:
if allconfig in ("", "1"):
try:
kconf.load_config(filename, False)
except IOError as e1:
try:
kconf.load_config("all.config", False)
except IOError as e2:
sys.exit("error: KCONFIG_ALLCONFIG is set, but neither {} "
"nor all.config could be opened: {}, {}"
.format(filename, std_msg(e1), std_msg(e2)))
else:
try:
kconf.load_config(allconfig, False)
except IOError as e:
sys.exit("error: KCONFIG_ALLCONFIG is set to '{}', which "
"could not be opened: {}"
.format(allconfig, std_msg(e)))
# API wart: It would be nice if there was a way to query and/or push/pop
# warning settings
kconf.enable_override_warnings()
kconf.enable_redun_warnings()
|
[
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"# \"Upcasts\" a _KconfigIOError to an IOError, removing the custom",
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",",
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"\"could not be opened: {}\"",
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"allconfig",
",",
"std_msg",
"(",
"e",
")",
")",
")",
"# API wart: It would be nice if there was a way to query and/or push/pop",
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"kconf",
".",
"enable_override_warnings",
"(",
")",
"kconf",
".",
"enable_redun_warnings",
"(",
")"
] |
https://github.com/PX4/PX4-Autopilot/blob/0b9f60a0370be53d683352c63fd92db3d6586e18/platforms/nuttx/NuttX/tools/kconfiglib.py#L5729-L5782
|
||
hakuna-m/wubiuefi
|
caec1af0a09c78fd5a345180ada1fe45e0c63493
|
src/pypack/modulegraph/util.py
|
python
|
imp_walk
|
(name)
|
yields namepart, tuple_or_importer for each path item
raise ImportError if a name can not be found.
|
yields namepart, tuple_or_importer for each path item
|
[
"yields",
"namepart",
"tuple_or_importer",
"for",
"each",
"path",
"item"
] |
def imp_walk(name):
"""
yields namepart, tuple_or_importer for each path item
raise ImportError if a name can not be found.
"""
if name in sys.builtin_module_names:
yield name, (None, None, ("", "", imp.C_BUILTIN))
return
paths = sys.path
res = None
for namepart in name.split('.'):
for path_item in paths:
res = _check_importer_for_path(namepart, path_item)
if hasattr(res, 'find_module'):
break
else:
break
yield namepart, res
paths = [os.path.join(path_item, namepart)]
else:
return
raise ImportError('No module named %s' % (name,))
|
[
"def",
"imp_walk",
"(",
"name",
")",
":",
"if",
"name",
"in",
"sys",
".",
"builtin_module_names",
":",
"yield",
"name",
",",
"(",
"None",
",",
"None",
",",
"(",
"\"\"",
",",
"\"\"",
",",
"imp",
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"C_BUILTIN",
")",
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"path",
"res",
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"split",
"(",
"'.'",
")",
":",
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"path",
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"]",
"else",
":",
"return",
"raise",
"ImportError",
"(",
"'No module named %s'",
"%",
"(",
"name",
",",
")",
")"
] |
https://github.com/hakuna-m/wubiuefi/blob/caec1af0a09c78fd5a345180ada1fe45e0c63493/src/pypack/modulegraph/util.py#L38-L60
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/telnetlib.py
|
python
|
Telnet.rawq_getchar
|
(self)
|
return c
|
Get next char from raw queue.
Block if no data is immediately available. Raise EOFError
when connection is closed.
|
Get next char from raw queue.
|
[
"Get",
"next",
"char",
"from",
"raw",
"queue",
"."
] |
def rawq_getchar(self):
"""Get next char from raw queue.
Block if no data is immediately available. Raise EOFError
when connection is closed.
"""
if not self.rawq:
self.fill_rawq()
if self.eof:
raise EOFError
c = self.rawq[self.irawq:self.irawq+1]
self.irawq = self.irawq + 1
if self.irawq >= len(self.rawq):
self.rawq = b''
self.irawq = 0
return c
|
[
"def",
"rawq_getchar",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"rawq",
":",
"self",
".",
"fill_rawq",
"(",
")",
"if",
"self",
".",
"eof",
":",
"raise",
"EOFError",
"c",
"=",
"self",
".",
"rawq",
"[",
"self",
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"irawq",
":",
"self",
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"irawq",
"+",
"1",
"]",
"self",
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"irawq",
"=",
"self",
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"irawq",
"+",
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"irawq",
">=",
"len",
"(",
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"rawq",
")",
":",
"self",
".",
"rawq",
"=",
"b''",
"self",
".",
"irawq",
"=",
"0",
"return",
"c"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/telnetlib.py#L494-L510
|
|
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py
|
python
|
_get_state_name
|
(i)
|
return '{}_{}'.format(rnn_common.RNNKeys.STATE_PREFIX, i)
|
Constructs the name string for state component `i`.
|
Constructs the name string for state component `i`.
|
[
"Constructs",
"the",
"name",
"string",
"for",
"state",
"component",
"i",
"."
] |
def _get_state_name(i):
"""Constructs the name string for state component `i`."""
return '{}_{}'.format(rnn_common.RNNKeys.STATE_PREFIX, i)
|
[
"def",
"_get_state_name",
"(",
"i",
")",
":",
"return",
"'{}_{}'",
".",
"format",
"(",
"rnn_common",
".",
"RNNKeys",
".",
"STATE_PREFIX",
",",
"i",
")"
] |
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py#L300-L302
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/propgrid.py
|
python
|
PropertyGrid.HasInternalFlag
|
(*args, **kwargs)
|
return _propgrid.PropertyGrid_HasInternalFlag(*args, **kwargs)
|
HasInternalFlag(self, long flag) -> bool
|
HasInternalFlag(self, long flag) -> bool
|
[
"HasInternalFlag",
"(",
"self",
"long",
"flag",
")",
"-",
">",
"bool"
] |
def HasInternalFlag(*args, **kwargs):
"""HasInternalFlag(self, long flag) -> bool"""
return _propgrid.PropertyGrid_HasInternalFlag(*args, **kwargs)
|
[
"def",
"HasInternalFlag",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_propgrid",
".",
"PropertyGrid_HasInternalFlag",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/propgrid.py#L2403-L2405
|
|
panda3d/panda3d
|
833ad89ebad58395d0af0b7ec08538e5e4308265
|
direct/src/distributed/ClientRepositoryBase.py
|
python
|
ClientRepositoryBase.setDeferInterval
|
(self, deferInterval)
|
Specifies the minimum amount of time, in seconds, that must
elapse before generating any two DistributedObjects whose
class type is marked "deferrable". Set this to 0 to indicate
no deferring will occur.
|
Specifies the minimum amount of time, in seconds, that must
elapse before generating any two DistributedObjects whose
class type is marked "deferrable". Set this to 0 to indicate
no deferring will occur.
|
[
"Specifies",
"the",
"minimum",
"amount",
"of",
"time",
"in",
"seconds",
"that",
"must",
"elapse",
"before",
"generating",
"any",
"two",
"DistributedObjects",
"whose",
"class",
"type",
"is",
"marked",
"deferrable",
".",
"Set",
"this",
"to",
"0",
"to",
"indicate",
"no",
"deferring",
"will",
"occur",
"."
] |
def setDeferInterval(self, deferInterval):
"""Specifies the minimum amount of time, in seconds, that must
elapse before generating any two DistributedObjects whose
class type is marked "deferrable". Set this to 0 to indicate
no deferring will occur."""
self.deferInterval = deferInterval
self.setHandleCUpdates(self.deferInterval == 0)
if self.deferredGenerates:
taskMgr.remove('deferredGenerate')
taskMgr.doMethodLater(self.deferInterval, self.doDeferredGenerate, 'deferredGenerate')
|
[
"def",
"setDeferInterval",
"(",
"self",
",",
"deferInterval",
")",
":",
"self",
".",
"deferInterval",
"=",
"deferInterval",
"self",
".",
"setHandleCUpdates",
"(",
"self",
".",
"deferInterval",
"==",
"0",
")",
"if",
"self",
".",
"deferredGenerates",
":",
"taskMgr",
".",
"remove",
"(",
"'deferredGenerate'",
")",
"taskMgr",
".",
"doMethodLater",
"(",
"self",
".",
"deferInterval",
",",
"self",
".",
"doDeferredGenerate",
",",
"'deferredGenerate'",
")"
] |
https://github.com/panda3d/panda3d/blob/833ad89ebad58395d0af0b7ec08538e5e4308265/direct/src/distributed/ClientRepositoryBase.py#L80-L91
|
||
seqan/seqan
|
f5f658343c366c9c3d44ba358ffc9317e78a09ed
|
util/py_lib/seqan/dddoc/html.py
|
python
|
HtmlHelper.pageLink
|
(self, txt=None, arr=None, node=None)
|
return '<a href="%s"%s>%s</a>' % (pyratemp.escape(filename), dead_attr, title)
|
The link can be given as text or as a path.
If it is given as text then also HTTP/FTP links are allowed, otherwise,
it can only be a link to an entity in the tree.
|
The link can be given as text or as a path.
|
[
"The",
"link",
"can",
"be",
"given",
"as",
"text",
"or",
"as",
"a",
"path",
"."
] |
def pageLink(self, txt=None, arr=None, node=None):
"""The link can be given as text or as a path.
If it is given as text then also HTTP/FTP links are allowed, otherwise,
it can only be a link to an entity in the tree.
"""
# Compute source file name and line.
location_candidates = []
if node and node.entry:
for entry in node.tree.entries[node.entry[0]:node.entry[1]]:
if entry.line_no_begin + 1 == entry.line_no_end:
line = entry.line_no_begin + 1
else:
line = '%s-%s' % (entry.line_no_begin + 1, entry.line_no_end)
location_candidates.append((entry.filename, line))
# Now, switch between txt and arr.
is_dead = False
if txt:
# Split out titles from "$reference|$title".
title = None
if '|' in txt:
txt, title = txt.split('|', 1)
# Handle the different link types.
if txt.startswith('glos:'):
return self._glossaryLink(txt)
elif txt.split(':')[0] in ['http', 'https', 'ftp']:
if not title: title = txt
return '<a href="%s" target="_top">%s</a>' % (pyratemp.escape(txt), pyratemp.escape(title))
elif txt.startswith('nolink:'):
if not title: title = txt[len('nolink:'):]
return self.translateMarkup(title, node=node)
else:
# Is not a special link, compute two-element path and title. We
# will use the link generation code shared with paths as arrays.
lst = core.splitKeys(txt[txt.startswith('.'):], '.') # The startswith removes one leading dot if any.
lst = core.cleanPath(lst)
if len(lst) == 1: # Is link to index.
cat, subcat = 'indexpage', lst[0]
if not title:
if self.tree.find(['globals', 'indexes', subcat]):
title = self.tree.find(['globals', 'indexes', subcat]).text()
else:
title = subcat
if not self.tree.find(subcat):
is_dead = True
self.error_logger.invalidReference(txt, location_candidates)
else:
cat, subcat = lst[0], lst[1]
if not title: title = lst[-1]
if not self.tree.find([cat, subcat]):
is_dead = True
self.error_logger.invalidReference(txt, location_candidates)
else:
# Code for array paths.
cat, subcat, title = arr[0], arr[1], arr[1]
# Shared link generation code.
title = self.translateId(title)
filename = cat.upper() + escapeFiles(subcat) + ".html"
dead_attr = {True: ' class="dead"', False: ''}[is_dead]
return '<a href="%s"%s>%s</a>' % (pyratemp.escape(filename), dead_attr, title)
|
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"cat",
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"upper",
"(",
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"+",
"\".html\"",
"dead_attr",
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"' class=\"dead\"'",
",",
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",",
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",",
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https://github.com/seqan/seqan/blob/f5f658343c366c9c3d44ba358ffc9317e78a09ed/util/py_lib/seqan/dddoc/html.py#L577-L636
|
|
ComputationalRadiationPhysics/picongpu
|
59e9b53605f9a5c1bf271eeb055bc74370a99052
|
lib/python/picongpu/plugins/plot_mpl/base_visualizer.py
|
python
|
Visualizer._check_and_fix_run_dirs
|
(self, run_directories)
|
return run_directories
|
Check variable type for the run_directories and change
to list of tuples if necessary.
This can be overridden in derived classes to e.g. restrict
to single simulation visualization.
Returns
-------
a list of tuples, each of the form
(simulation_label, path_to_simulation).
|
Check variable type for the run_directories and change
to list of tuples if necessary.
This can be overridden in derived classes to e.g. restrict
to single simulation visualization.
|
[
"Check",
"variable",
"type",
"for",
"the",
"run_directories",
"and",
"change",
"to",
"list",
"of",
"tuples",
"if",
"necessary",
".",
"This",
"can",
"be",
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"classes",
"to",
"e",
".",
"g",
".",
"restrict",
"to",
"single",
"simulation",
"visualization",
"."
] |
def _check_and_fix_run_dirs(self, run_directories):
"""
Check variable type for the run_directories and change
to list of tuples if necessary.
This can be overridden in derived classes to e.g. restrict
to single simulation visualization.
Returns
-------
a list of tuples, each of the form
(simulation_label, path_to_simulation).
"""
# silently convert str to list of length 1
if not isinstance(run_directories, list):
run_directories = [run_directories]
if len(run_directories) < 1:
warn("Empty run_directories list was passed!")
return run_directories
if isinstance(run_directories[0], str):
warn("First element is str. Assuming the same for all "
"other elements. Will use enumeration for labeling!")
run_directories = list(enumerate(run_directories))
return run_directories
|
[
"def",
"_check_and_fix_run_dirs",
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"self",
",",
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"# silently convert str to list of length 1",
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https://github.com/ComputationalRadiationPhysics/picongpu/blob/59e9b53605f9a5c1bf271eeb055bc74370a99052/lib/python/picongpu/plugins/plot_mpl/base_visualizer.py#L122-L147
|
|
nasa/trick
|
7b85aa66329d62fe8816462627c09a353aac8299
|
share/trick/pymods/trick/variable_server.py
|
python
|
find_simulation
|
(host=None, port=None, user=None, pid=None,
version=None, sim_directory=None, s_main=None,
input_file=None, tag=None, timeout=None)
|
Listen for simulations on the multicast channel over which all sims broadcast
their existence. Connect to the one that matches the provided arguments that
are not None.
If there are multiple matches, connect to the first one we happen to find.
If all arguments are None, connect to the first sim we happen to find.
Such matches will be non-deterministic.
Parameters
----------
host : str
Host name of the machine on which the sim is running as reported by
Trick.
port : int
Variable Server port.
user : str
Simulation process user.
pid : int
The sim's process ID.
version : str
Trick version.
sim_directory : str
SIM_* directory. If this starts with /, it will be considered an
absolute path.
s_main : str
Filename of the S_main* executable. Not an absolute path.
input_file : str
Path to the input file relative to the simDirectory.
tag : str
Simulation tag.
timeout : positive float or None
How long to look for the sim before giving up. Pass None to wait
indefinitely.
Returns
-------
VariableServer
A VariableServer connected to the sim matching the specified
parameters.
Raises
------
socket.timeout
If a timeout occurs.
|
Listen for simulations on the multicast channel over which all sims broadcast
their existence. Connect to the one that matches the provided arguments that
are not None.
|
[
"Listen",
"for",
"simulations",
"on",
"the",
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"which",
"all",
"sims",
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"the",
"one",
"that",
"matches",
"the",
"provided",
"arguments",
"that",
"are",
"not",
"None",
"."
] |
def find_simulation(host=None, port=None, user=None, pid=None,
version=None, sim_directory=None, s_main=None,
input_file=None, tag=None, timeout=None):
"""
Listen for simulations on the multicast channel over which all sims broadcast
their existence. Connect to the one that matches the provided arguments that
are not None.
If there are multiple matches, connect to the first one we happen to find.
If all arguments are None, connect to the first sim we happen to find.
Such matches will be non-deterministic.
Parameters
----------
host : str
Host name of the machine on which the sim is running as reported by
Trick.
port : int
Variable Server port.
user : str
Simulation process user.
pid : int
The sim's process ID.
version : str
Trick version.
sim_directory : str
SIM_* directory. If this starts with /, it will be considered an
absolute path.
s_main : str
Filename of the S_main* executable. Not an absolute path.
input_file : str
Path to the input file relative to the simDirectory.
tag : str
Simulation tag.
timeout : positive float or None
How long to look for the sim before giving up. Pass None to wait
indefinitely.
Returns
-------
VariableServer
A VariableServer connected to the sim matching the specified
parameters.
Raises
------
socket.timeout
If a timeout occurs.
"""
clock = time.time()
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
sock.bind(('', 9265))
sock.setsockopt(
socket.IPPROTO_IP,
socket.IP_ADD_MEMBERSHIP,
struct.pack('=4sl', socket.inet_aton('224.3.14.15'), socket.INADDR_ANY))
file_interface = sock.makefile()
def candidate_matches(candidate):
for parameter, candidate_parameter in zip(
[host, port, user, pid, sim_directory,
s_main, input_file, version, tag],
candidate) :
if parameter is not None and str(parameter) != candidate_parameter:
return False
return True
# the socket will clean itself up when it's garbage-collected
while True:
if timeout is not None:
timeout -= (time.time() - clock)
if timeout < 0:
raise socket.timeout
clock = time.time()
sock.settimeout(timeout)
# 0: host
# 1: port
# 2: user
# 3: pid
# 4: SIM_*
# 5: S_main*
# 6: RUN_*
# 7: version
# 8: tag
candidate = file_interface.readline().split('\t')[:9]
if not str(sim_directory).startswith('/'):
candidate[4] = os.path.basename(candidate[4])
if candidate_matches(candidate):
return VariableServer(candidate[0], candidate[1])
|
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")"
] |
https://github.com/nasa/trick/blob/7b85aa66329d62fe8816462627c09a353aac8299/share/trick/pymods/trick/variable_server.py#L1035-L1127
|
||
bulletphysics/bullet3
|
f0f2a952e146f016096db6f85cf0c44ed75b0b9a
|
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur.py
|
python
|
Minitaur.GetControlLatency
|
(self)
|
return self._control_latency
|
Get the control latency.
Returns:
The latency (in seconds) between when the motor command is sent and when
the sensor measurements are reported back to the controller.
|
Get the control latency.
|
[
"Get",
"the",
"control",
"latency",
"."
] |
def GetControlLatency(self):
"""Get the control latency.
Returns:
The latency (in seconds) between when the motor command is sent and when
the sensor measurements are reported back to the controller.
"""
return self._control_latency
|
[
"def",
"GetControlLatency",
"(",
"self",
")",
":",
"return",
"self",
".",
"_control_latency"
] |
https://github.com/bulletphysics/bullet3/blob/f0f2a952e146f016096db6f85cf0c44ed75b0b9a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur.py#L895-L902
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py3/pandas/core/generic.py
|
python
|
NDFrame._drop_axis
|
(
self: FrameOrSeries, labels, axis, level=None, errors: str = "raise"
)
|
return result
|
Drop labels from specified axis. Used in the ``drop`` method
internally.
Parameters
----------
labels : single label or list-like
axis : int or axis name
level : int or level name, default None
For MultiIndex
errors : {'ignore', 'raise'}, default 'raise'
If 'ignore', suppress error and existing labels are dropped.
|
Drop labels from specified axis. Used in the ``drop`` method
internally.
|
[
"Drop",
"labels",
"from",
"specified",
"axis",
".",
"Used",
"in",
"the",
"drop",
"method",
"internally",
"."
] |
def _drop_axis(
self: FrameOrSeries, labels, axis, level=None, errors: str = "raise"
) -> FrameOrSeries:
"""
Drop labels from specified axis. Used in the ``drop`` method
internally.
Parameters
----------
labels : single label or list-like
axis : int or axis name
level : int or level name, default None
For MultiIndex
errors : {'ignore', 'raise'}, default 'raise'
If 'ignore', suppress error and existing labels are dropped.
"""
axis = self._get_axis_number(axis)
axis_name = self._get_axis_name(axis)
axis = self._get_axis(axis)
if axis.is_unique:
if level is not None:
if not isinstance(axis, MultiIndex):
raise AssertionError("axis must be a MultiIndex")
new_axis = axis.drop(labels, level=level, errors=errors)
else:
new_axis = axis.drop(labels, errors=errors)
result = self.reindex(**{axis_name: new_axis})
# Case for non-unique axis
else:
is_tuple_labels = is_nested_list_like(labels) or isinstance(labels, tuple)
labels = ensure_object(com.index_labels_to_array(labels))
if level is not None:
if not isinstance(axis, MultiIndex):
raise AssertionError("axis must be a MultiIndex")
indexer = ~axis.get_level_values(level).isin(labels)
# GH 18561 MultiIndex.drop should raise if label is absent
if errors == "raise" and indexer.all():
raise KeyError(f"{labels} not found in axis")
elif (
isinstance(axis, MultiIndex)
and labels.dtype == "object"
and not is_tuple_labels
):
# Set level to zero in case of MultiIndex and label is string,
# because isin can't handle strings for MultiIndexes GH#36293
# In case of tuples we get dtype object but have to use isin GH#42771
indexer = ~axis.get_level_values(0).isin(labels)
else:
indexer = ~axis.isin(labels)
# Check if label doesn't exist along axis
labels_missing = (axis.get_indexer_for(labels) == -1).any()
if errors == "raise" and labels_missing:
raise KeyError(f"{labels} not found in axis")
slicer = [slice(None)] * self.ndim
slicer[self._get_axis_number(axis_name)] = indexer
result = self.loc[tuple(slicer)]
return result
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/core/generic.py#L4158-L4221
|
|
google/syzygy
|
8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5
|
third_party/numpy/files/numpy/oldnumeric/ma.py
|
python
|
MaskedArray.__float__
|
(self)
|
return float(self.data.item())
|
Convert self to float.
|
Convert self to float.
|
[
"Convert",
"self",
"to",
"float",
"."
] |
def __float__(self):
"Convert self to float."
self.unmask()
if self._mask is not nomask:
raise MAError, 'Cannot convert masked element to a Python float.'
return float(self.data.item())
|
[
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https://github.com/google/syzygy/blob/8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5/third_party/numpy/files/numpy/oldnumeric/ma.py#L785-L790
|
|
google/orbit
|
7c0a530f402f0c3753d0bc52f8e3eb620f65d017
|
third_party/include-what-you-use/fix_includes.py
|
python
|
_NextNondeletedLine
|
(file_lines, line_number)
|
return None
|
Returns the line number of the next not-deleted line, or None.
|
Returns the line number of the next not-deleted line, or None.
|
[
"Returns",
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"line",
"number",
"of",
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"next",
"not",
"-",
"deleted",
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"or",
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"."
] |
def _NextNondeletedLine(file_lines, line_number):
"""Returns the line number of the next not-deleted line, or None."""
for line_number in range(line_number + 1, len(file_lines)):
if not file_lines[line_number].deleted:
return line_number
return None
|
[
"def",
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https://github.com/google/orbit/blob/7c0a530f402f0c3753d0bc52f8e3eb620f65d017/third_party/include-what-you-use/fix_includes.py#L818-L823
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/lite/python/convert.py
|
python
|
toco_convert_impl
|
(input_data, input_tensors, output_tensors,
enable_mlir_converter, *args, **kwargs)
|
return data
|
Convert a model using TOCO.
Typically this function is used to convert from TensorFlow GraphDef to TFLite.
Conversion can be customized by providing arguments that are forwarded to
`build_toco_convert_protos` (see documentation for details).
Args:
input_data: Input data (i.e. often `sess.graph_def`),
input_tensors: List of input tensors. Type and shape are computed using
`foo.shape` and `foo.dtype`.
output_tensors: List of output tensors (only .name is used from this).
enable_mlir_converter: Enables the MLIR converter instead of the TOCO
converter.
*args: See `build_toco_convert_protos`,
**kwargs: See `build_toco_convert_protos`.
Returns:
The converted data. For example if TFLite was the destination, then
this will be a tflite flatbuffer in a bytes array.
Raises:
Defined in `build_toco_convert_protos`.
|
Convert a model using TOCO.
|
[
"Convert",
"a",
"model",
"using",
"TOCO",
"."
] |
def toco_convert_impl(input_data, input_tensors, output_tensors,
enable_mlir_converter, *args, **kwargs):
""""Convert a model using TOCO.
Typically this function is used to convert from TensorFlow GraphDef to TFLite.
Conversion can be customized by providing arguments that are forwarded to
`build_toco_convert_protos` (see documentation for details).
Args:
input_data: Input data (i.e. often `sess.graph_def`),
input_tensors: List of input tensors. Type and shape are computed using
`foo.shape` and `foo.dtype`.
output_tensors: List of output tensors (only .name is used from this).
enable_mlir_converter: Enables the MLIR converter instead of the TOCO
converter.
*args: See `build_toco_convert_protos`,
**kwargs: See `build_toco_convert_protos`.
Returns:
The converted data. For example if TFLite was the destination, then
this will be a tflite flatbuffer in a bytes array.
Raises:
Defined in `build_toco_convert_protos`.
"""
model_flags, toco_flags, debug_info = build_toco_convert_protos(
input_tensors, output_tensors, *args, **kwargs)
debug_info_str = debug_info.SerializeToString() if debug_info else None
data = toco_convert_protos(
model_flags.SerializeToString(),
toco_flags.SerializeToString(),
input_data.SerializeToString(),
debug_info_str=debug_info_str,
enable_mlir_converter=enable_mlir_converter)
return data
|
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/lite/python/convert.py#L416-L450
|
|
oracle/graaljs
|
36a56e8e993d45fc40939a3a4d9c0c24990720f1
|
graal-nodejs/tools/cpplint.py
|
python
|
PrintCategories
|
()
|
Prints a list of all the error-categories used by error messages.
These are the categories used to filter messages via --filter.
|
Prints a list of all the error-categories used by error messages.
|
[
"Prints",
"a",
"list",
"of",
"all",
"the",
"error",
"-",
"categories",
"used",
"by",
"error",
"messages",
"."
] |
def PrintCategories():
"""Prints a list of all the error-categories used by error messages.
These are the categories used to filter messages via --filter.
"""
sys.stderr.write(''.join(' %s\n' % cat for cat in _ERROR_CATEGORIES))
sys.exit(0)
|
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https://github.com/oracle/graaljs/blob/36a56e8e993d45fc40939a3a4d9c0c24990720f1/graal-nodejs/tools/cpplint.py#L6803-L6809
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/tools/python/src/Lib/distutils/dist.py
|
python
|
Distribution._set_command_options
|
(self, command_obj, option_dict=None)
|
Set the options for 'command_obj' from 'option_dict'. Basically
this means copying elements of a dictionary ('option_dict') to
attributes of an instance ('command').
'command_obj' must be a Command instance. If 'option_dict' is not
supplied, uses the standard option dictionary for this command
(from 'self.command_options').
|
Set the options for 'command_obj' from 'option_dict'. Basically
this means copying elements of a dictionary ('option_dict') to
attributes of an instance ('command').
|
[
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"option_dict",
")",
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"attributes",
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"an",
"instance",
"(",
"command",
")",
"."
] |
def _set_command_options(self, command_obj, option_dict=None):
"""Set the options for 'command_obj' from 'option_dict'. Basically
this means copying elements of a dictionary ('option_dict') to
attributes of an instance ('command').
'command_obj' must be a Command instance. If 'option_dict' is not
supplied, uses the standard option dictionary for this command
(from 'self.command_options').
"""
command_name = command_obj.get_command_name()
if option_dict is None:
option_dict = self.get_option_dict(command_name)
if DEBUG:
self.announce(" setting options for '%s' command:" % command_name)
for (option, (source, value)) in option_dict.items():
if DEBUG:
self.announce(" %s = %s (from %s)" % (option, value,
source))
try:
bool_opts = map(translate_longopt, command_obj.boolean_options)
except AttributeError:
bool_opts = []
try:
neg_opt = command_obj.negative_opt
except AttributeError:
neg_opt = {}
try:
is_string = isinstance(value, str)
if option in neg_opt and is_string:
setattr(command_obj, neg_opt[option], not strtobool(value))
elif option in bool_opts and is_string:
setattr(command_obj, option, strtobool(value))
elif hasattr(command_obj, option):
setattr(command_obj, option, value)
else:
raise DistutilsOptionError, \
("error in %s: command '%s' has no such option '%s'"
% (source, command_name, option))
except ValueError, msg:
raise DistutilsOptionError, msg
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/distutils/dist.py#L860-L901
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scikit-learn/py2/sklearn/metrics/pairwise.py
|
python
|
euclidean_distances
|
(X, Y=None, Y_norm_squared=None, squared=False,
X_norm_squared=None)
|
return distances if squared else np.sqrt(distances, out=distances)
|
Considering the rows of X (and Y=X) as vectors, compute the
distance matrix between each pair of vectors.
For efficiency reasons, the euclidean distance between a pair of row
vector x and y is computed as::
dist(x, y) = sqrt(dot(x, x) - 2 * dot(x, y) + dot(y, y))
This formulation has two advantages over other ways of computing distances.
First, it is computationally efficient when dealing with sparse data.
Second, if one argument varies but the other remains unchanged, then
`dot(x, x)` and/or `dot(y, y)` can be pre-computed.
However, this is not the most precise way of doing this computation, and
the distance matrix returned by this function may not be exactly
symmetric as required by, e.g., ``scipy.spatial.distance`` functions.
Read more in the :ref:`User Guide <metrics>`.
Parameters
----------
X : {array-like, sparse matrix}, shape (n_samples_1, n_features)
Y : {array-like, sparse matrix}, shape (n_samples_2, n_features)
Y_norm_squared : array-like, shape (n_samples_2, ), optional
Pre-computed dot-products of vectors in Y (e.g.,
``(Y**2).sum(axis=1)``)
squared : boolean, optional
Return squared Euclidean distances.
X_norm_squared : array-like, shape = [n_samples_1], optional
Pre-computed dot-products of vectors in X (e.g.,
``(X**2).sum(axis=1)``)
Returns
-------
distances : {array, sparse matrix}, shape (n_samples_1, n_samples_2)
Examples
--------
>>> from sklearn.metrics.pairwise import euclidean_distances
>>> X = [[0, 1], [1, 1]]
>>> # distance between rows of X
>>> euclidean_distances(X, X)
array([[ 0., 1.],
[ 1., 0.]])
>>> # get distance to origin
>>> euclidean_distances(X, [[0, 0]])
array([[ 1. ],
[ 1.41421356]])
See also
--------
paired_distances : distances betweens pairs of elements of X and Y.
|
Considering the rows of X (and Y=X) as vectors, compute the
distance matrix between each pair of vectors.
|
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def euclidean_distances(X, Y=None, Y_norm_squared=None, squared=False,
X_norm_squared=None):
"""
Considering the rows of X (and Y=X) as vectors, compute the
distance matrix between each pair of vectors.
For efficiency reasons, the euclidean distance between a pair of row
vector x and y is computed as::
dist(x, y) = sqrt(dot(x, x) - 2 * dot(x, y) + dot(y, y))
This formulation has two advantages over other ways of computing distances.
First, it is computationally efficient when dealing with sparse data.
Second, if one argument varies but the other remains unchanged, then
`dot(x, x)` and/or `dot(y, y)` can be pre-computed.
However, this is not the most precise way of doing this computation, and
the distance matrix returned by this function may not be exactly
symmetric as required by, e.g., ``scipy.spatial.distance`` functions.
Read more in the :ref:`User Guide <metrics>`.
Parameters
----------
X : {array-like, sparse matrix}, shape (n_samples_1, n_features)
Y : {array-like, sparse matrix}, shape (n_samples_2, n_features)
Y_norm_squared : array-like, shape (n_samples_2, ), optional
Pre-computed dot-products of vectors in Y (e.g.,
``(Y**2).sum(axis=1)``)
squared : boolean, optional
Return squared Euclidean distances.
X_norm_squared : array-like, shape = [n_samples_1], optional
Pre-computed dot-products of vectors in X (e.g.,
``(X**2).sum(axis=1)``)
Returns
-------
distances : {array, sparse matrix}, shape (n_samples_1, n_samples_2)
Examples
--------
>>> from sklearn.metrics.pairwise import euclidean_distances
>>> X = [[0, 1], [1, 1]]
>>> # distance between rows of X
>>> euclidean_distances(X, X)
array([[ 0., 1.],
[ 1., 0.]])
>>> # get distance to origin
>>> euclidean_distances(X, [[0, 0]])
array([[ 1. ],
[ 1.41421356]])
See also
--------
paired_distances : distances betweens pairs of elements of X and Y.
"""
X, Y = check_pairwise_arrays(X, Y)
if X_norm_squared is not None:
XX = check_array(X_norm_squared)
if XX.shape == (1, X.shape[0]):
XX = XX.T
elif XX.shape != (X.shape[0], 1):
raise ValueError(
"Incompatible dimensions for X and X_norm_squared")
else:
XX = row_norms(X, squared=True)[:, np.newaxis]
if X is Y: # shortcut in the common case euclidean_distances(X, X)
YY = XX.T
elif Y_norm_squared is not None:
YY = np.atleast_2d(Y_norm_squared)
if YY.shape != (1, Y.shape[0]):
raise ValueError(
"Incompatible dimensions for Y and Y_norm_squared")
else:
YY = row_norms(Y, squared=True)[np.newaxis, :]
distances = safe_sparse_dot(X, Y.T, dense_output=True)
distances *= -2
distances += XX
distances += YY
np.maximum(distances, 0, out=distances)
if X is Y:
# Ensure that distances between vectors and themselves are set to 0.0.
# This may not be the case due to floating point rounding errors.
distances.flat[::distances.shape[0] + 1] = 0.0
return distances if squared else np.sqrt(distances, out=distances)
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scikit-learn/py2/sklearn/metrics/pairwise.py#L162-L256
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/distribute/coordinator/cluster_coordinator.py
|
python
|
Cluster.__init__
|
(self, strategy)
|
Initializes the cluster instance.
|
Initializes the cluster instance.
|
[
"Initializes",
"the",
"cluster",
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"."
] |
def __init__(self, strategy):
"""Initializes the cluster instance."""
self._num_workers = strategy._num_workers
self._num_ps = strategy._num_ps
# Ignore PS failures reported by workers due to transient connection errors.
# Transient connectivity issues between workers and PS are relayed by the
# workers to the coordinator, leading the coordinator to believe that there
# are PS failures. The difference between transient vs. permanent PS failure
# is the number of reports from the workers. When this env var is set to a
# positive integer K, the coordinator ignores up to K reports of a failed PS
# task, i.e., only when there are more than K trials of executing closures
# fail due to errors from the same PS instance do we consider the PS
# instance encounters a failure.
# TODO(b/164279603): Remove this workaround when the underlying connectivity
# issue in gRPC server is resolved.
self._transient_ps_failures_threshold = int(
os.environ.get("TF_COORDINATOR_IGNORE_TRANSIENT_PS_FAILURES", 3))
self._potential_ps_failures_lock = threading.Lock()
self._potential_ps_failures_count = [0] * self._num_ps
# Ignore worker timeouts due to transient connection errors.
# Transient connectivity issues might cause the server side to unexpectedly
# cancel RPC handling logic, leading to closure execution timeouts. When
# the _transient_timeout_threshold is set to a positive number, the cluster
# coordinator ignores DeadlineExceeded errors from workers for the specified
# times before raising the error to users.
self._transient_timeouts_threshold = int(
os.environ.get("TF_COORDINATOR_IGNORE_TRANSIENT_TIMEOUTS",
self._num_workers // 10))
self._transient_timeouts_lock = threading.Lock()
self._transient_timeouts_count = 0
self.closure_queue = _CoordinatedClosureQueue()
self.failure_handler = WorkerPreemptionHandler(context.get_server_def(),
self)
worker_device_strings = [
"/job:worker/replica:0/task:%d" % i for i in range(self._num_workers)
]
self.workers = [
Worker(i, w, self) for i, w in enumerate(worker_device_strings)
]
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/distribute/coordinator/cluster_coordinator.py#L812-L854
|
||
pytorch/pytorch
|
7176c92687d3cc847cc046bf002269c6949a21c2
|
torch/ao/quantization/_dbr/quantization_state.py
|
python
|
AutoQuantizationState._get_packed_param_name
|
(self, seen_q_op_info: SeenQOpInfo)
|
return self.idx_to_packed_weight_name.get(seen_q_op_info.idx, None)
|
If the op in seen_q_op_info has a quantized packed param, returns it.
Otherwise, returns None.
|
If the op in seen_q_op_info has a quantized packed param, returns it.
Otherwise, returns None.
|
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"."
] |
def _get_packed_param_name(self, seen_q_op_info: SeenQOpInfo) -> Optional[str]:
"""
If the op in seen_q_op_info has a quantized packed param, returns it.
Otherwise, returns None.
"""
return self.idx_to_packed_weight_name.get(seen_q_op_info.idx, None)
|
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https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/torch/ao/quantization/_dbr/quantization_state.py#L594-L599
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_ops.py
|
python
|
equal
|
(x, y, name=None)
|
return gen_math_ops.equal(x, y, name=name)
|
Returns the truth value of (x == y) element-wise.
Usage:
```python
x = tf.constant([2, 4])
y = tf.constant(2)
tf.math.equal(x, y) ==> array([True, False])
x = tf.constant([2, 4])
y = tf.constant([2, 4])
tf.math.equal(x, y) ==> array([True, True])
```
**NOTE**: `Equal` supports broadcasting. More about broadcasting [here](
https://docs.scipy.org/doc/numpy-1.13.0/user/basics.broadcasting.html)
Args:
x: A `Tensor` or `SparseTensor` or `IndexedSlices`.
y: A `Tensor` or `SparseTensor` or `IndexedSlices`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type bool with the same size as that of x or y.
|
Returns the truth value of (x == y) element-wise.
|
[
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"value",
"of",
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"x",
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"element",
"-",
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] |
def equal(x, y, name=None):
"""Returns the truth value of (x == y) element-wise.
Usage:
```python
x = tf.constant([2, 4])
y = tf.constant(2)
tf.math.equal(x, y) ==> array([True, False])
x = tf.constant([2, 4])
y = tf.constant([2, 4])
tf.math.equal(x, y) ==> array([True, True])
```
**NOTE**: `Equal` supports broadcasting. More about broadcasting [here](
https://docs.scipy.org/doc/numpy-1.13.0/user/basics.broadcasting.html)
Args:
x: A `Tensor` or `SparseTensor` or `IndexedSlices`.
y: A `Tensor` or `SparseTensor` or `IndexedSlices`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type bool with the same size as that of x or y.
"""
return gen_math_ops.equal(x, y, 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/math_ops.py#L1280-L1306
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/html2.py
|
python
|
WebView.IsBusy
|
(*args, **kwargs)
|
return _html2.WebView_IsBusy(*args, **kwargs)
|
IsBusy(self) -> bool
|
IsBusy(self) -> bool
|
[
"IsBusy",
"(",
"self",
")",
"-",
">",
"bool"
] |
def IsBusy(*args, **kwargs):
"""IsBusy(self) -> bool"""
return _html2.WebView_IsBusy(*args, **kwargs)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/html2.py#L171-L173
|
|
apache/incubator-mxnet
|
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
|
python/mxnet/_ctypes/symbol.py
|
python
|
SymbolBase._set_handle
|
(self, handle)
|
Set handle.
|
Set handle.
|
[
"Set",
"handle",
"."
] |
def _set_handle(self, handle):
"""Set handle."""
self.handle = handle
|
[
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"(",
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",",
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":",
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"handle",
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https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/_ctypes/symbol.py#L107-L109
|
||
crosslife/OpenBird
|
9e0198a1a2295f03fa1e8676e216e22c9c7d380b
|
cocos2d/tools/bindings-generator/clang/cindex.py
|
python
|
Cursor.is_bitfield
|
(self)
|
return conf.lib.clang_Cursor_isBitField(self)
|
Check if the field is a bitfield.
|
Check if the field is a bitfield.
|
[
"Check",
"if",
"the",
"field",
"is",
"a",
"bitfield",
"."
] |
def is_bitfield(self):
"""
Check if the field is a bitfield.
"""
return conf.lib.clang_Cursor_isBitField(self)
|
[
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")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_Cursor_isBitField",
"(",
"self",
")"
] |
https://github.com/crosslife/OpenBird/blob/9e0198a1a2295f03fa1e8676e216e22c9c7d380b/cocos2d/tools/bindings-generator/clang/cindex.py#L1483-L1487
|
|
arangodb/arangodb
|
0d658689c7d1b721b314fa3ca27d38303e1570c8
|
3rdParty/V8/gyp/buildtime_helpers/mac_tool.py
|
python
|
MacTool.ExecFlock
|
(self, lockfile, *cmd_list)
|
return subprocess.call(cmd_list)
|
Emulates the most basic behavior of Linux's flock(1).
|
Emulates the most basic behavior of Linux's flock(1).
|
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"flock",
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"1",
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"."
] |
def ExecFlock(self, lockfile, *cmd_list):
"""Emulates the most basic behavior of Linux's flock(1)."""
# Rely on exception handling to report errors.
fd = os.open(lockfile, os.O_RDONLY|os.O_NOCTTY|os.O_CREAT, 0o666)
fcntl.flock(fd, fcntl.LOCK_EX)
return subprocess.call(cmd_list)
|
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https://github.com/arangodb/arangodb/blob/0d658689c7d1b721b314fa3ca27d38303e1570c8/3rdParty/V8/gyp/buildtime_helpers/mac_tool.py#L248-L253
|
|
qgis/QGIS
|
15a77662d4bb712184f6aa60d0bd663010a76a75
|
python/plugins/db_manager/db_plugins/oracle/connector.py
|
python
|
OracleDBConnector.getTableGeomTypes
|
(self, table, geomCol)
|
return geomtypes, srids
|
Return all the wkbTypes for a table by requesting geometry
column.
|
Return all the wkbTypes for a table by requesting geometry
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|
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def getTableGeomTypes(self, table, geomCol):
"""Return all the wkbTypes for a table by requesting geometry
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"""
estimated = u""
if self.useEstimatedMetadata:
estimated = u"AND ROWNUM < 100"
# Grab all of geometry types from the layer
query = u"""
SELECT DISTINCT a.{0}.SDO_GTYPE As gtype,
a.{0}.SDO_SRID
FROM {1} a
WHERE a.{0} IS NOT NULL {2}
ORDER BY a.{0}.SDO_GTYPE
""".format(geomCol, table, estimated)
try:
c = self._execute(None, query)
except DbError: # handle error views or other problems
return [QgsWkbTypes.Unknown], [-1]
rows = self._fetchall(c)
c.close()
# Handle results
if len(rows) == 0:
return [QgsWkbTypes.Unknown], [-1]
# A dict to store the geomtypes
geomtypes = []
srids = []
for row in rows:
if row[1] == NULL:
srids.append(-1)
else:
srids.append(int(row[1]))
if int(row[0]) in list(OracleDBConnector.ORGeomTypes.keys()):
geomtypes.append(OracleDBConnector.ORGeomTypes[int(row[0])])
else:
geomtypes.append(QgsWkbTypes.Unknown)
return geomtypes, srids
|
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|
|
klzgrad/naiveproxy
|
ed2c513637c77b18721fe428d7ed395b4d284c83
|
src/tools/grit/grit/gather/skeleton_gatherer.py
|
python
|
SkeletonGatherer.Escape
|
(self, text)
|
return text
|
Subclasses can override. Base impl is identity.
|
Subclasses can override. Base impl is identity.
|
[
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def Escape(self, text):
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return text
|
[
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"text"
] |
https://github.com/klzgrad/naiveproxy/blob/ed2c513637c77b18721fe428d7ed395b4d284c83/src/tools/grit/grit/gather/skeleton_gatherer.py#L49-L52
|
|
sfzhang15/RefineDet
|
52b6fe23dc1a160fe710b7734576dca509bf4fae
|
scripts/cpp_lint.py
|
python
|
RemoveMultiLineComments
|
(filename, lines, error)
|
Removes multiline (c-style) comments from lines.
|
Removes multiline (c-style) comments from lines.
|
[
"Removes",
"multiline",
"(",
"c",
"-",
"style",
")",
"comments",
"from",
"lines",
"."
] |
def RemoveMultiLineComments(filename, lines, error):
"""Removes multiline (c-style) comments from lines."""
lineix = 0
while lineix < len(lines):
lineix_begin = FindNextMultiLineCommentStart(lines, lineix)
if lineix_begin >= len(lines):
return
lineix_end = FindNextMultiLineCommentEnd(lines, lineix_begin)
if lineix_end >= len(lines):
error(filename, lineix_begin + 1, 'readability/multiline_comment', 5,
'Could not find end of multi-line comment')
return
RemoveMultiLineCommentsFromRange(lines, lineix_begin, lineix_end + 1)
lineix = lineix_end + 1
|
[
"def",
"RemoveMultiLineComments",
"(",
"filename",
",",
"lines",
",",
"error",
")",
":",
"lineix",
"=",
"0",
"while",
"lineix",
"<",
"len",
"(",
"lines",
")",
":",
"lineix_begin",
"=",
"FindNextMultiLineCommentStart",
"(",
"lines",
",",
"lineix",
")",
"if",
"lineix_begin",
">=",
"len",
"(",
"lines",
")",
":",
"return",
"lineix_end",
"=",
"FindNextMultiLineCommentEnd",
"(",
"lines",
",",
"lineix_begin",
")",
"if",
"lineix_end",
">=",
"len",
"(",
"lines",
")",
":",
"error",
"(",
"filename",
",",
"lineix_begin",
"+",
"1",
",",
"'readability/multiline_comment'",
",",
"5",
",",
"'Could not find end of multi-line comment'",
")",
"return",
"RemoveMultiLineCommentsFromRange",
"(",
"lines",
",",
"lineix_begin",
",",
"lineix_end",
"+",
"1",
")",
"lineix",
"=",
"lineix_end",
"+",
"1"
] |
https://github.com/sfzhang15/RefineDet/blob/52b6fe23dc1a160fe710b7734576dca509bf4fae/scripts/cpp_lint.py#L1151-L1164
|
||
apache/trafodion
|
8455c839ad6b6d7b6e04edda5715053095b78046
|
core/sqf/src/seatrans/hbase-trx/src/main/python/thrift2/gen-py/hbase/THBaseService.py
|
python
|
Client.closeScanner
|
(self, scannerId)
|
Closes the scanner. Should be called if you need to close
the Scanner before all results are read.
Exhausted scanners are closed automatically.
Parameters:
- scannerId: the Id of the Scanner to close *
|
Closes the scanner. Should be called if you need to close
the Scanner before all results are read.
|
[
"Closes",
"the",
"scanner",
".",
"Should",
"be",
"called",
"if",
"you",
"need",
"to",
"close",
"the",
"Scanner",
"before",
"all",
"results",
"are",
"read",
"."
] |
def closeScanner(self, scannerId):
"""
Closes the scanner. Should be called if you need to close
the Scanner before all results are read.
Exhausted scanners are closed automatically.
Parameters:
- scannerId: the Id of the Scanner to close *
"""
self.send_closeScanner(scannerId)
self.recv_closeScanner()
|
[
"def",
"closeScanner",
"(",
"self",
",",
"scannerId",
")",
":",
"self",
".",
"send_closeScanner",
"(",
"scannerId",
")",
"self",
".",
"recv_closeScanner",
"(",
")"
] |
https://github.com/apache/trafodion/blob/8455c839ad6b6d7b6e04edda5715053095b78046/core/sqf/src/seatrans/hbase-trx/src/main/python/thrift2/gen-py/hbase/THBaseService.py#L681-L692
|
||
jsupancic/deep_hand_pose
|
22cbeae1a8410ff5d37c060c7315719d0a5d608f
|
scripts/cpp_lint.py
|
python
|
FileInfo.RepositoryName
|
(self)
|
return fullname
|
FullName after removing the local path to the repository.
If we have a real absolute path name here we can try to do something smart:
detecting the root of the checkout and truncating /path/to/checkout from
the name so that we get header guards that don't include things like
"C:\Documents and Settings\..." or "/home/username/..." in them and thus
people on different computers who have checked the source out to different
locations won't see bogus errors.
|
FullName after removing the local path to the repository.
|
[
"FullName",
"after",
"removing",
"the",
"local",
"path",
"to",
"the",
"repository",
"."
] |
def RepositoryName(self):
"""FullName after removing the local path to the repository.
If we have a real absolute path name here we can try to do something smart:
detecting the root of the checkout and truncating /path/to/checkout from
the name so that we get header guards that don't include things like
"C:\Documents and Settings\..." or "/home/username/..." in them and thus
people on different computers who have checked the source out to different
locations won't see bogus errors.
"""
fullname = self.FullName()
if os.path.exists(fullname):
project_dir = os.path.dirname(fullname)
if os.path.exists(os.path.join(project_dir, ".svn")):
# If there's a .svn file in the current directory, we recursively look
# up the directory tree for the top of the SVN checkout
root_dir = project_dir
one_up_dir = os.path.dirname(root_dir)
while os.path.exists(os.path.join(one_up_dir, ".svn")):
root_dir = os.path.dirname(root_dir)
one_up_dir = os.path.dirname(one_up_dir)
prefix = os.path.commonprefix([root_dir, project_dir])
return fullname[len(prefix) + 1:]
# Not SVN <= 1.6? Try to find a git, hg, or svn top level directory by
# searching up from the current path.
root_dir = os.path.dirname(fullname)
while (root_dir != os.path.dirname(root_dir) and
not os.path.exists(os.path.join(root_dir, ".git")) and
not os.path.exists(os.path.join(root_dir, ".hg")) and
not os.path.exists(os.path.join(root_dir, ".svn"))):
root_dir = os.path.dirname(root_dir)
if (os.path.exists(os.path.join(root_dir, ".git")) or
os.path.exists(os.path.join(root_dir, ".hg")) or
os.path.exists(os.path.join(root_dir, ".svn"))):
prefix = os.path.commonprefix([root_dir, project_dir])
return fullname[len(prefix) + 1:]
# Don't know what to do; header guard warnings may be wrong...
return fullname
|
[
"def",
"RepositoryName",
"(",
"self",
")",
":",
"fullname",
"=",
"self",
".",
"FullName",
"(",
")",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"fullname",
")",
":",
"project_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"fullname",
")",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"project_dir",
",",
"\".svn\"",
")",
")",
":",
"# If there's a .svn file in the current directory, we recursively look",
"# up the directory tree for the top of the SVN checkout",
"root_dir",
"=",
"project_dir",
"one_up_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"root_dir",
")",
"while",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"one_up_dir",
",",
"\".svn\"",
")",
")",
":",
"root_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"root_dir",
")",
"one_up_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"one_up_dir",
")",
"prefix",
"=",
"os",
".",
"path",
".",
"commonprefix",
"(",
"[",
"root_dir",
",",
"project_dir",
"]",
")",
"return",
"fullname",
"[",
"len",
"(",
"prefix",
")",
"+",
"1",
":",
"]",
"# Not SVN <= 1.6? Try to find a git, hg, or svn top level directory by",
"# searching up from the current path.",
"root_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"fullname",
")",
"while",
"(",
"root_dir",
"!=",
"os",
".",
"path",
".",
"dirname",
"(",
"root_dir",
")",
"and",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".git\"",
")",
")",
"and",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".hg\"",
")",
")",
"and",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".svn\"",
")",
")",
")",
":",
"root_dir",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"root_dir",
")",
"if",
"(",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".git\"",
")",
")",
"or",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".hg\"",
")",
")",
"or",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"root_dir",
",",
"\".svn\"",
")",
")",
")",
":",
"prefix",
"=",
"os",
".",
"path",
".",
"commonprefix",
"(",
"[",
"root_dir",
",",
"project_dir",
"]",
")",
"return",
"fullname",
"[",
"len",
"(",
"prefix",
")",
"+",
"1",
":",
"]",
"# Don't know what to do; header guard warnings may be wrong...",
"return",
"fullname"
] |
https://github.com/jsupancic/deep_hand_pose/blob/22cbeae1a8410ff5d37c060c7315719d0a5d608f/scripts/cpp_lint.py#L885-L928
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/lzma.py
|
python
|
LZMAFile.seekable
|
(self)
|
return self.readable() and self._buffer.seekable()
|
Return whether the file supports seeking.
|
Return whether the file supports seeking.
|
[
"Return",
"whether",
"the",
"file",
"supports",
"seeking",
"."
] |
def seekable(self):
"""Return whether the file supports seeking."""
return self.readable() and self._buffer.seekable()
|
[
"def",
"seekable",
"(",
"self",
")",
":",
"return",
"self",
".",
"readable",
"(",
")",
"and",
"self",
".",
"_buffer",
".",
"seekable",
"(",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/lzma.py#L168-L170
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/protobuf/py2/google/protobuf/text_format.py
|
python
|
_ConsumeUint32
|
(tokenizer)
|
return _ConsumeInteger(tokenizer, is_signed=False, is_long=False)
|
Consumes an unsigned 32bit integer number from tokenizer.
Args:
tokenizer: A tokenizer used to parse the number.
Returns:
The integer parsed.
Raises:
ParseError: If an unsigned 32bit integer couldn't be consumed.
|
Consumes an unsigned 32bit integer number from tokenizer.
|
[
"Consumes",
"an",
"unsigned",
"32bit",
"integer",
"number",
"from",
"tokenizer",
"."
] |
def _ConsumeUint32(tokenizer):
"""Consumes an unsigned 32bit integer number from tokenizer.
Args:
tokenizer: A tokenizer used to parse the number.
Returns:
The integer parsed.
Raises:
ParseError: If an unsigned 32bit integer couldn't be consumed.
"""
return _ConsumeInteger(tokenizer, is_signed=False, is_long=False)
|
[
"def",
"_ConsumeUint32",
"(",
"tokenizer",
")",
":",
"return",
"_ConsumeInteger",
"(",
"tokenizer",
",",
"is_signed",
"=",
"False",
",",
"is_long",
"=",
"False",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/protobuf/py2/google/protobuf/text_format.py#L1592-L1604
|
|
Cisco-Talos/moflow
|
ed71dfb0540d9e0d7a4c72f0881b58958d573728
|
BAP-0.7-moflow/libtracewrap/libtrace/protobuf/python/stubout.py
|
python
|
StubOutForTesting.SmartUnsetAll
|
(self)
|
Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
|
Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
|
[
"Reverses",
"all",
"the",
"SmartSet",
"()",
"calls",
"restoring",
"things",
"to",
"their",
"original",
"definition",
".",
"Its",
"okay",
"to",
"call",
"SmartUnsetAll",
"()",
"repeatedly",
"as",
"later",
"calls",
"have",
"no",
"effect",
"if",
"no",
"SmartSet",
"()",
"calls",
"have",
"been",
"made",
"."
] |
def SmartUnsetAll(self):
"""Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
"""
self.stubs.reverse()
for args in self.stubs:
setattr(*args)
self.stubs = []
|
[
"def",
"SmartUnsetAll",
"(",
"self",
")",
":",
"self",
".",
"stubs",
".",
"reverse",
"(",
")",
"for",
"args",
"in",
"self",
".",
"stubs",
":",
"setattr",
"(",
"*",
"args",
")",
"self",
".",
"stubs",
"=",
"[",
"]"
] |
https://github.com/Cisco-Talos/moflow/blob/ed71dfb0540d9e0d7a4c72f0881b58958d573728/BAP-0.7-moflow/libtracewrap/libtrace/protobuf/python/stubout.py#L96-L107
|
||
PlatformLab/RAMCloud
|
b1866af19124325a6dfd8cbc267e2e3ef1f965d1
|
scripts/log.py
|
python
|
createDir
|
(top, log_exists=False)
|
return subdir
|
Given a top-level log directory, create a subdirectory within that
directory to use for log files for a particular run of an application,
and make a symbolic link from "latest" to that subdirectory. Return the
path to the subdirectory.
|
Given a top-level log directory, create a subdirectory within that
directory to use for log files for a particular run of an application,
and make a symbolic link from "latest" to that subdirectory. Return the
path to the subdirectory.
|
[
"Given",
"a",
"top",
"-",
"level",
"log",
"directory",
"create",
"a",
"subdirectory",
"within",
"that",
"directory",
"to",
"use",
"for",
"log",
"files",
"for",
"a",
"particular",
"run",
"of",
"an",
"application",
"and",
"make",
"a",
"symbolic",
"link",
"from",
"latest",
"to",
"that",
"subdirectory",
".",
"Return",
"the",
"path",
"to",
"the",
"subdirectory",
"."
] |
def createDir(top, log_exists=False):
"""
Given a top-level log directory, create a subdirectory within that
directory to use for log files for a particular run of an application,
and make a symbolic link from "latest" to that subdirectory. Return the
path to the subdirectory.
"""
try:
os.mkdir(top)
except:
pass
# when a new server is started after the clusterperf test is started,
# it uses a new cluster object but is still part of the overall
# test. It has to use the same log directory that was used by the
# original cluster so that the clusterperf.py is able to gather the
# log output from the 'latest' log directory (symbolic link)
if log_exists:
subdir = '%s/latest' % (top)
return subdir
datetime = time.strftime('%Y%m%d%H%M%S')
latest = '%s/latest' % top
subdir = '%s/%s' % (top, datetime)
os.mkdir(subdir)
try:
os.remove('%s/latest' % top)
except:
pass
os.symlink(datetime, latest)
return subdir
|
[
"def",
"createDir",
"(",
"top",
",",
"log_exists",
"=",
"False",
")",
":",
"try",
":",
"os",
".",
"mkdir",
"(",
"top",
")",
"except",
":",
"pass",
"# when a new server is started after the clusterperf test is started,",
"# it uses a new cluster object but is still part of the overall",
"# test. It has to use the same log directory that was used by the",
"# original cluster so that the clusterperf.py is able to gather the",
"# log output from the 'latest' log directory (symbolic link)",
"if",
"log_exists",
":",
"subdir",
"=",
"'%s/latest'",
"%",
"(",
"top",
")",
"return",
"subdir",
"datetime",
"=",
"time",
".",
"strftime",
"(",
"'%Y%m%d%H%M%S'",
")",
"latest",
"=",
"'%s/latest'",
"%",
"top",
"subdir",
"=",
"'%s/%s'",
"%",
"(",
"top",
",",
"datetime",
")",
"os",
".",
"mkdir",
"(",
"subdir",
")",
"try",
":",
"os",
".",
"remove",
"(",
"'%s/latest'",
"%",
"top",
")",
"except",
":",
"pass",
"os",
".",
"symlink",
"(",
"datetime",
",",
"latest",
")",
"return",
"subdir"
] |
https://github.com/PlatformLab/RAMCloud/blob/b1866af19124325a6dfd8cbc267e2e3ef1f965d1/scripts/log.py#L27-L58
|
|
tangzhenyu/Scene-Text-Understanding
|
0f7ffc7aea5971a50cdc03d33d0a41075285948b
|
SynthText_Chinese/colorize3_poisson.py
|
python
|
Colorize.color_border
|
(self, col_text, col_bg)
|
return np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_HSV2RGB))
|
Decide on a color for the border:
- could be the same as text-color but lower/higher 'VALUE' component.
- could be the same as bg-color but lower/higher 'VALUE'.
- could be 'mid-way' color b/w text & bg colors.
|
Decide on a color for the border:
- could be the same as text-color but lower/higher 'VALUE' component.
- could be the same as bg-color but lower/higher 'VALUE'.
- could be 'mid-way' color b/w text & bg colors.
|
[
"Decide",
"on",
"a",
"color",
"for",
"the",
"border",
":",
"-",
"could",
"be",
"the",
"same",
"as",
"text",
"-",
"color",
"but",
"lower",
"/",
"higher",
"VALUE",
"component",
".",
"-",
"could",
"be",
"the",
"same",
"as",
"bg",
"-",
"color",
"but",
"lower",
"/",
"higher",
"VALUE",
".",
"-",
"could",
"be",
"mid",
"-",
"way",
"color",
"b",
"/",
"w",
"text",
"&",
"bg",
"colors",
"."
] |
def color_border(self, col_text, col_bg):
"""
Decide on a color for the border:
- could be the same as text-color but lower/higher 'VALUE' component.
- could be the same as bg-color but lower/higher 'VALUE'.
- could be 'mid-way' color b/w text & bg colors.
"""
choice = np.random.choice(3)
col_text = cv.cvtColor(col_text, cv.cv.CV_RGB2HSV)
col_text = np.reshape(col_text, (np.prod(col_text.shape[:2]),3))
col_text = np.mean(col_text,axis=0).astype('uint8')
vs = np.linspace(0,1)
def get_sample(x):
ps = np.abs(vs - x/255.0)
ps /= np.sum(ps)
v_rand = np.clip(np.random.choice(vs,p=ps) + 0.1*np.random.randn(),0,1)
return 255*v_rand
# first choose a color, then inc/dec its VALUE:
if choice==0:
# increase/decrease saturation:
col_text[0] = get_sample(col_text[0]) # saturation
col_text = np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_HSV2RGB))
elif choice==1:
# get the complementary color to text:
col_text = np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_HSV2RGB))
col_text = self.font_color.complement(col_text)
else:
# choose a mid-way color:
col_bg = cv.cvtColor(col_bg, cv.cv.CV_RGB2HSV)
col_bg = np.reshape(col_bg, (np.prod(col_bg.shape[:2]),3))
col_bg = np.mean(col_bg,axis=0).astype('uint8')
col_bg = np.squeeze(cv.cvtColor(col_bg[None,None,:],cv.cv.CV_HSV2RGB))
col_text = np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_HSV2RGB))
col_text = self.font_color.triangle_color(col_text,col_bg)
# now change the VALUE channel:
col_text = np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_RGB2HSV))
col_text[2] = get_sample(col_text[2]) # value
return np.squeeze(cv.cvtColor(col_text[None,None,:],cv.cv.CV_HSV2RGB))
|
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https://github.com/tangzhenyu/Scene-Text-Understanding/blob/0f7ffc7aea5971a50cdc03d33d0a41075285948b/SynthText_Chinese/colorize3_poisson.py#L247-L288
|
|
tensorflow/deepmath
|
b5b721f54de1d5d6a02d78f5da5995237f9995f9
|
deepmath/deephol/prover_util.py
|
python
|
ProverTaskGenerator.emit_error
|
(self, error_msg, *args)
|
Stores error messages for later processing.
|
Stores error messages for later processing.
|
[
"Stores",
"error",
"messages",
"for",
"later",
"processing",
"."
] |
def emit_error(self, error_msg, *args):
"""Stores error messages for later processing."""
self.errors.append('%s for log %d' % (error_msg % args, self.count_logs))
self.count_errors[error_msg] = self.count_errors.get(error_msg, 0) + 1
|
[
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https://github.com/tensorflow/deepmath/blob/b5b721f54de1d5d6a02d78f5da5995237f9995f9/deepmath/deephol/prover_util.py#L290-L293
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/Jinja2/py2/jinja2/environment.py
|
python
|
Environment.extend
|
(self, **attributes)
|
Add the items to the instance of the environment if they do not exist
yet. This is used by :ref:`extensions <writing-extensions>` to register
callbacks and configuration values without breaking inheritance.
|
Add the items to the instance of the environment if they do not exist
yet. This is used by :ref:`extensions <writing-extensions>` to register
callbacks and configuration values without breaking inheritance.
|
[
"Add",
"the",
"items",
"to",
"the",
"instance",
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"register",
"callbacks",
"and",
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"values",
"without",
"breaking",
"inheritance",
"."
] |
def extend(self, **attributes):
"""Add the items to the instance of the environment if they do not exist
yet. This is used by :ref:`extensions <writing-extensions>` to register
callbacks and configuration values without breaking inheritance.
"""
for key, value in iteritems(attributes):
if not hasattr(self, key):
setattr(self, key, value)
|
[
"def",
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"setattr",
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",",
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")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/Jinja2/py2/jinja2/environment.py#L376-L383
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/pstats.py
|
python
|
add_func_stats
|
(target, source)
|
return (cc+t_cc, nc+t_nc, tt+t_tt, ct+t_ct,
add_callers(t_callers, callers))
|
Add together all the stats for two profile entries.
|
Add together all the stats for two profile entries.
|
[
"Add",
"together",
"all",
"the",
"stats",
"for",
"two",
"profile",
"entries",
"."
] |
def add_func_stats(target, source):
"""Add together all the stats for two profile entries."""
cc, nc, tt, ct, callers = source
t_cc, t_nc, t_tt, t_ct, t_callers = target
return (cc+t_cc, nc+t_nc, tt+t_tt, ct+t_ct,
add_callers(t_callers, callers))
|
[
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"t_callers",
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/pstats.py#L499-L504
|
|
hpi-xnor/BMXNet
|
ed0b201da6667887222b8e4b5f997c4f6b61943d
|
python/mxnet/ndarray/ndarray.py
|
python
|
NDArray.copyto
|
(self, other)
|
Copies the value of this array to another array.
If ``other`` is a ``NDArray`` object, then ``other.shape`` and
``self.shape`` should be the same. This function copies the value from
``self`` to ``other``.
If ``other`` is a context, a new ``NDArray`` will be first created on
the target context, and the value of ``self`` is copied.
Parameters
----------
other : NDArray or Context
The destination array or context.
Returns
-------
NDArray, CSRNDArray or RowSparseNDArray
The copied array. If ``other`` is an ``NDArray``, then the return value
and ``other`` will point to the same ``NDArray``.
Examples
--------
>>> x = mx.nd.ones((2,3))
>>> y = mx.nd.zeros((2,3), mx.gpu(0))
>>> z = x.copyto(y)
>>> z is y
True
>>> y.asnumpy()
array([[ 1., 1., 1.],
[ 1., 1., 1.]], dtype=float32)
>>> y.copyto(mx.gpu(0))
<NDArray 2x3 @gpu(0)>
|
Copies the value of this array to another array.
|
[
"Copies",
"the",
"value",
"of",
"this",
"array",
"to",
"another",
"array",
"."
] |
def copyto(self, other):
"""Copies the value of this array to another array.
If ``other`` is a ``NDArray`` object, then ``other.shape`` and
``self.shape`` should be the same. This function copies the value from
``self`` to ``other``.
If ``other`` is a context, a new ``NDArray`` will be first created on
the target context, and the value of ``self`` is copied.
Parameters
----------
other : NDArray or Context
The destination array or context.
Returns
-------
NDArray, CSRNDArray or RowSparseNDArray
The copied array. If ``other`` is an ``NDArray``, then the return value
and ``other`` will point to the same ``NDArray``.
Examples
--------
>>> x = mx.nd.ones((2,3))
>>> y = mx.nd.zeros((2,3), mx.gpu(0))
>>> z = x.copyto(y)
>>> z is y
True
>>> y.asnumpy()
array([[ 1., 1., 1.],
[ 1., 1., 1.]], dtype=float32)
>>> y.copyto(mx.gpu(0))
<NDArray 2x3 @gpu(0)>
"""
if isinstance(other, NDArray):
if other.handle is self.handle:
warnings.warn('You are attempting to copy an array to itself', RuntimeWarning)
return
return _internal._copyto(self, out=other)
elif isinstance(other, Context):
hret = NDArray(_new_alloc_handle(self.shape, other, True, self.dtype))
return _internal._copyto(self, out=hret)
else:
raise TypeError('copyto does not support type ' + str(type(other)))
|
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https://github.com/hpi-xnor/BMXNet/blob/ed0b201da6667887222b8e4b5f997c4f6b61943d/python/mxnet/ndarray/ndarray.py#L1837-L1881
|
||
microsoft/TSS.MSR
|
0f2516fca2cd9929c31d5450e39301c9bde43688
|
TSS.Py/src/TpmTypes.py
|
python
|
TPML_PCR_SELECTION.toTpm
|
(self, buf)
|
TpmMarshaller method
|
TpmMarshaller method
|
[
"TpmMarshaller",
"method"
] |
def toTpm(self, buf):
""" TpmMarshaller method """
buf.writeObjArr(self.pcrSelections)
|
[
"def",
"toTpm",
"(",
"self",
",",
"buf",
")",
":",
"buf",
".",
"writeObjArr",
"(",
"self",
".",
"pcrSelections",
")"
] |
https://github.com/microsoft/TSS.MSR/blob/0f2516fca2cd9929c31d5450e39301c9bde43688/TSS.Py/src/TpmTypes.py#L4676-L4678
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/mapreduce/mapreduce/handlers.py
|
python
|
StartJobHandler._start_map
|
(cls,
name,
mapper_spec,
mapreduce_params,
queue_name,
eta=None,
countdown=None,
hooks_class_name=None,
_app=None,
in_xg_transaction=False)
|
return mapreduce_id
|
See control.start_map.
Requirements for this method:
1. The request that invokes this method can either be regular or
from taskqueue. So taskqueue specific headers can not be used.
2. Each invocation transactionally starts an isolated mapreduce job with
a unique id. MapreduceState should be immediately available after
returning. See control.start_map's doc on transactional.
3. Method should be lightweight.
|
See control.start_map.
|
[
"See",
"control",
".",
"start_map",
"."
] |
def _start_map(cls,
name,
mapper_spec,
mapreduce_params,
queue_name,
eta=None,
countdown=None,
hooks_class_name=None,
_app=None,
in_xg_transaction=False):
# pylint: disable=g-doc-args
# pylint: disable=g-doc-return-or-yield
"""See control.start_map.
Requirements for this method:
1. The request that invokes this method can either be regular or
from taskqueue. So taskqueue specific headers can not be used.
2. Each invocation transactionally starts an isolated mapreduce job with
a unique id. MapreduceState should be immediately available after
returning. See control.start_map's doc on transactional.
3. Method should be lightweight.
"""
# Validate input reader.
mapper_input_reader_class = mapper_spec.input_reader_class()
mapper_input_reader_class.validate(mapper_spec)
# Validate output writer.
mapper_output_writer_class = mapper_spec.output_writer_class()
if mapper_output_writer_class:
mapper_output_writer_class.validate(mapper_spec)
# Create a new id and mr spec.
mapreduce_id = model.MapreduceState.new_mapreduce_id()
mapreduce_spec = model.MapreduceSpec(
name,
mapreduce_id,
mapper_spec.to_json(),
mapreduce_params,
hooks_class_name)
# Validate mapper handler.
ctx = context.Context(mapreduce_spec, None)
context.Context._set(ctx)
try:
# pylint: disable=pointless-statement
mapper_spec.handler
finally:
context.Context._set(None)
# Save states and enqueue task.
if in_xg_transaction:
propagation = db.MANDATORY
else:
propagation = db.INDEPENDENT
@db.transactional(propagation=propagation)
def _txn():
cls._create_and_save_state(mapreduce_spec, _app)
cls._add_kickoff_task(mapreduce_params["base_path"], mapreduce_spec, eta,
countdown, queue_name)
_txn()
return mapreduce_id
|
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"=",
"propagation",
")",
"def",
"_txn",
"(",
")",
":",
"cls",
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"_create_and_save_state",
"(",
"mapreduce_spec",
",",
"_app",
")",
"cls",
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"_add_kickoff_task",
"(",
"mapreduce_params",
"[",
"\"base_path\"",
"]",
",",
"mapreduce_spec",
",",
"eta",
",",
"countdown",
",",
"queue_name",
")",
"_txn",
"(",
")",
"return",
"mapreduce_id"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/mapreduce/mapreduce/handlers.py#L1701-L1763
|
|
microsoft/TSS.MSR
|
0f2516fca2cd9929c31d5450e39301c9bde43688
|
TSS.Py/src/TpmTypes.py
|
python
|
HMACResponse.initFromTpm
|
(self, buf)
|
TpmMarshaller method
|
TpmMarshaller method
|
[
"TpmMarshaller",
"method"
] |
def initFromTpm(self, buf):
""" TpmMarshaller method """
self.outHMAC = buf.readSizedByteBuf()
|
[
"def",
"initFromTpm",
"(",
"self",
",",
"buf",
")",
":",
"self",
".",
"outHMAC",
"=",
"buf",
".",
"readSizedByteBuf",
"(",
")"
] |
https://github.com/microsoft/TSS.MSR/blob/0f2516fca2cd9929c31d5450e39301c9bde43688/TSS.Py/src/TpmTypes.py#L11703-L11705
|
||
apache/incubator-mxnet
|
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
|
python/mxnet/ndarray/ndarray.py
|
python
|
NDArray.__gt__
|
(self, other)
|
return greater(self, other)
|
x.__gt__(y) <=> x>y <=> mx.nd.greater(x, y)
|
x.__gt__(y) <=> x>y <=> mx.nd.greater(x, y)
|
[
"x",
".",
"__gt__",
"(",
"y",
")",
"<",
"=",
">",
"x",
">",
"y",
"<",
"=",
">",
"mx",
".",
"nd",
".",
"greater",
"(",
"x",
"y",
")"
] |
def __gt__(self, other):
"""x.__gt__(y) <=> x>y <=> mx.nd.greater(x, y) """
return greater(self, other)
|
[
"def",
"__gt__",
"(",
"self",
",",
"other",
")",
":",
"return",
"greater",
"(",
"self",
",",
"other",
")"
] |
https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/ndarray/ndarray.py#L433-L435
|
|
SoarGroup/Soar
|
a1c5e249499137a27da60533c72969eef3b8ab6b
|
scons/scons-local-4.1.0/SCons/Tool/ilink32.py
|
python
|
generate
|
(env)
|
Add Builders and construction variables for Borland ilink to an
Environment.
|
Add Builders and construction variables for Borland ilink to an
Environment.
|
[
"Add",
"Builders",
"and",
"construction",
"variables",
"for",
"Borland",
"ilink",
"to",
"an",
"Environment",
"."
] |
def generate(env):
"""Add Builders and construction variables for Borland ilink to an
Environment."""
SCons.Tool.createSharedLibBuilder(env)
SCons.Tool.createProgBuilder(env)
env['LINK'] = '$CC'
env['LINKFLAGS'] = SCons.Util.CLVar('')
env['LINKCOM'] = '$LINK -q $LINKFLAGS -e$TARGET $SOURCES $LIBS'
env['LIBDIRPREFIX']=''
env['LIBDIRSUFFIX']=''
env['LIBLINKPREFIX']=''
env['LIBLINKSUFFIX']='$LIBSUFFIX'
|
[
"def",
"generate",
"(",
"env",
")",
":",
"SCons",
".",
"Tool",
".",
"createSharedLibBuilder",
"(",
"env",
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".",
"Tool",
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"createProgBuilder",
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"env",
")",
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"[",
"'LINK'",
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"=",
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"[",
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"=",
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"'LIBLINKPREFIX'",
"]",
"=",
"''",
"env",
"[",
"'LIBLINKSUFFIX'",
"]",
"=",
"'$LIBSUFFIX'"
] |
https://github.com/SoarGroup/Soar/blob/a1c5e249499137a27da60533c72969eef3b8ab6b/scons/scons-local-4.1.0/SCons/Tool/ilink32.py#L36-L48
|
||
mindspore-ai/mindspore
|
fb8fd3338605bb34fa5cea054e535a8b1d753fab
|
mindspore/python/mindspore/ops/composite/multitype_ops/mul_impl.py
|
python
|
_scalar_mul_tensor
|
(x, y)
|
return F.tensor_mul(x, y)
|
Returns x * y where x is a scalar and y is a tensor. x and y have same dtype.
Outputs:
Tensor, has the same dtype as x.
|
Returns x * y where x is a scalar and y is a tensor. x and y have same dtype.
|
[
"Returns",
"x",
"*",
"y",
"where",
"x",
"is",
"a",
"scalar",
"and",
"y",
"is",
"a",
"tensor",
".",
"x",
"and",
"y",
"have",
"same",
"dtype",
"."
] |
def _scalar_mul_tensor(x, y):
"""
Returns x * y where x is a scalar and y is a tensor. x and y have same dtype.
Outputs:
Tensor, has the same dtype as x.
"""
return F.tensor_mul(x, y)
|
[
"def",
"_scalar_mul_tensor",
"(",
"x",
",",
"y",
")",
":",
"return",
"F",
".",
"tensor_mul",
"(",
"x",
",",
"y",
")"
] |
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/ops/composite/multitype_ops/mul_impl.py#L77-L84
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/computation/scope.py
|
python
|
Scope.ntemps
|
(self)
|
return len(self.temps)
|
The number of temporary variables in this scope
|
The number of temporary variables in this scope
|
[
"The",
"number",
"of",
"temporary",
"variables",
"in",
"this",
"scope"
] |
def ntemps(self) -> int:
"""The number of temporary variables in this scope"""
return len(self.temps)
|
[
"def",
"ntemps",
"(",
"self",
")",
"->",
"int",
":",
"return",
"len",
"(",
"self",
".",
"temps",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/computation/scope.py#L298-L300
|
|
D-X-Y/caffe-faster-rcnn
|
eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb
|
examples/pycaffe/layers/pascal_multilabel_datalayers.py
|
python
|
BatchLoader.load_next_image
|
(self)
|
return self.transformer.preprocess(im), multilabel
|
Load the next image in a batch.
|
Load the next image in a batch.
|
[
"Load",
"the",
"next",
"image",
"in",
"a",
"batch",
"."
] |
def load_next_image(self):
"""
Load the next image in a batch.
"""
# Did we finish an epoch?
if self._cur == len(self.indexlist):
self._cur = 0
shuffle(self.indexlist)
# Load an image
index = self.indexlist[self._cur] # Get the image index
image_file_name = index + '.jpg'
im = np.asarray(Image.open(
osp.join(self.pascal_root, 'JPEGImages', image_file_name)))
im = scipy.misc.imresize(im, self.im_shape) # resize
# do a simple horizontal flip as data augmentation
flip = np.random.choice(2)*2-1
im = im[:, ::flip, :]
# Load and prepare ground truth
multilabel = np.zeros(20).astype(np.float32)
anns = load_pascal_annotation(index, self.pascal_root)
for label in anns['gt_classes']:
# in the multilabel problem we don't care how MANY instances
# there are of each class. Only if they are present.
# The "-1" is b/c we are not interested in the background
# class.
multilabel[label - 1] = 1
self._cur += 1
return self.transformer.preprocess(im), multilabel
|
[
"def",
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":",
"# Did we finish an epoch?",
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"self",
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"flip",
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"multilabel",
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"20",
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".",
"astype",
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"float32",
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"self",
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"pascal_root",
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"for",
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"'gt_classes'",
"]",
":",
"# in the multilabel problem we don't care how MANY instances",
"# there are of each class. Only if they are present.",
"# The \"-1\" is b/c we are not interested in the background",
"# class.",
"multilabel",
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"label",
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"+=",
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"self",
".",
"transformer",
".",
"preprocess",
"(",
"im",
")",
",",
"multilabel"
] |
https://github.com/D-X-Y/caffe-faster-rcnn/blob/eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb/examples/pycaffe/layers/pascal_multilabel_datalayers.py#L106-L137
|
|
windystrife/UnrealEngine_NVIDIAGameWorks
|
b50e6338a7c5b26374d66306ebc7807541ff815e
|
Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/file_util.py
|
python
|
backup_file
|
(name)
|
Rename the file to a name that includes the current time stamp.
|
Rename the file to a name that includes the current time stamp.
|
[
"Rename",
"the",
"file",
"to",
"a",
"name",
"that",
"includes",
"the",
"current",
"time",
"stamp",
"."
] |
def backup_file(name):
""" Rename the file to a name that includes the current time stamp. """
move_file(name, name+'.'+time.strftime('%Y-%m-%d-%H-%M-%S'))
|
[
"def",
"backup_file",
"(",
"name",
")",
":",
"move_file",
"(",
"name",
",",
"name",
"+",
"'.'",
"+",
"time",
".",
"strftime",
"(",
"'%Y-%m-%d-%H-%M-%S'",
")",
")"
] |
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/file_util.py#L43-L45
|
||
google/iree
|
1224bbdbe65b0d1fdf40e7324f60f68beeaf7c76
|
integrations/tensorflow/iree-dialects/python/iree/compiler/dialects/iree_pydm/importer/importer.py
|
python
|
ExpressionImporter.get_call_result
|
(self, args: Sequence[ir.Value])
|
Perfoms a call against the expression result, returning the value.
|
Perfoms a call against the expression result, returning the value.
|
[
"Perfoms",
"a",
"call",
"against",
"the",
"expression",
"result",
"returning",
"the",
"value",
"."
] |
def get_call_result(self, args: Sequence[ir.Value]) -> ir.Value:
"""Perfoms a call against the expression result, returning the value."""
if isinstance(self._result, ir.Value):
return self.fctx.ic.abort(
f"TODO: User defined function call not supported")
else:
# Intrinsic.
return self._result.emit_call(self.fctx, args=args, keywords=[])
|
[
"def",
"get_call_result",
"(",
"self",
",",
"args",
":",
"Sequence",
"[",
"ir",
".",
"Value",
"]",
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"ir",
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"Value",
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"if",
"isinstance",
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",",
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"Value",
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"fctx",
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"abort",
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"f\"TODO: User defined function call not supported\"",
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":",
"# Intrinsic.",
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"(",
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".",
"fctx",
",",
"args",
"=",
"args",
",",
"keywords",
"=",
"[",
"]",
")"
] |
https://github.com/google/iree/blob/1224bbdbe65b0d1fdf40e7324f60f68beeaf7c76/integrations/tensorflow/iree-dialects/python/iree/compiler/dialects/iree_pydm/importer/importer.py#L506-L513
|
||
facebook/redex
|
fac189a289bca2647061f9e364016afc1096500d
|
tools/python/file_extract.py
|
python
|
FileExtract.get_sint8
|
(self, fail_value=0)
|
return self._unpack("b", s) if s else fail_value
|
Extract a int8_t from the current file position.
|
Extract a int8_t from the current file position.
|
[
"Extract",
"a",
"int8_t",
"from",
"the",
"current",
"file",
"position",
"."
] |
def get_sint8(self, fail_value=0):
"""Extract a int8_t from the current file position."""
s = self.read_size(1)
return self._unpack("b", s) if s else fail_value
|
[
"def",
"get_sint8",
"(",
"self",
",",
"fail_value",
"=",
"0",
")",
":",
"s",
"=",
"self",
".",
"read_size",
"(",
"1",
")",
"return",
"self",
".",
"_unpack",
"(",
"\"b\"",
",",
"s",
")",
"if",
"s",
"else",
"fail_value"
] |
https://github.com/facebook/redex/blob/fac189a289bca2647061f9e364016afc1096500d/tools/python/file_extract.py#L318-L321
|
|
microsoft/checkedc-clang
|
a173fefde5d7877b7750e7ce96dd08cf18baebf2
|
compiler-rt/lib/sanitizer_common/scripts/cpplint.py
|
python
|
CheckMakePairUsesDeduction
|
(filename, clean_lines, linenum, error)
|
Check that make_pair's template arguments are deduced.
G++ 4.6 in C++11 mode fails badly if make_pair's template arguments are
specified explicitly, and such use isn't intended in any case.
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.
|
Check that make_pair's template arguments are deduced.
|
[
"Check",
"that",
"make_pair",
"s",
"template",
"arguments",
"are",
"deduced",
"."
] |
def CheckMakePairUsesDeduction(filename, clean_lines, linenum, error):
"""Check that make_pair's template arguments are deduced.
G++ 4.6 in C++11 mode fails badly if make_pair's template arguments are
specified explicitly, and such use isn't intended in any case.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum]
match = _RE_PATTERN_EXPLICIT_MAKEPAIR.search(line)
if match:
error(filename, linenum, 'build/explicit_make_pair',
4, # 4 = high confidence
'For C++11-compatibility, omit template arguments from make_pair'
' OR use pair directly OR if appropriate, construct a pair directly')
|
[
"def",
"CheckMakePairUsesDeduction",
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",",
"clean_lines",
",",
"linenum",
",",
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"4",
",",
"# 4 = high confidence",
"'For C++11-compatibility, omit template arguments from make_pair'",
"' OR use pair directly OR if appropriate, construct a pair directly'",
")"
] |
https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/compiler-rt/lib/sanitizer_common/scripts/cpplint.py#L5600-L5618
|
||
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/examples/learn/text_classification.py
|
python
|
estimator_spec_for_softmax_classification
|
(
logits, labels, mode)
|
return tf.estimator.EstimatorSpec(
mode=mode, loss=loss, eval_metric_ops=eval_metric_ops)
|
Returns EstimatorSpec instance for softmax classification.
|
Returns EstimatorSpec instance for softmax classification.
|
[
"Returns",
"EstimatorSpec",
"instance",
"for",
"softmax",
"classification",
"."
] |
def estimator_spec_for_softmax_classification(
logits, labels, mode):
"""Returns EstimatorSpec instance for softmax classification."""
predicted_classes = tf.argmax(logits, 1)
if mode == tf.estimator.ModeKeys.PREDICT:
return tf.estimator.EstimatorSpec(
mode=mode,
predictions={
'class': predicted_classes,
'prob': tf.nn.softmax(logits)
})
onehot_labels = tf.one_hot(labels, MAX_LABEL, 1, 0)
loss = tf.losses.softmax_cross_entropy(
onehot_labels=onehot_labels, logits=logits)
if mode == tf.estimator.ModeKeys.TRAIN:
optimizer = tf.train.AdamOptimizer(learning_rate=0.01)
train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step())
return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
eval_metric_ops = {
'accuracy': tf.metrics.accuracy(
labels=labels, predictions=predicted_classes)
}
return tf.estimator.EstimatorSpec(
mode=mode, loss=loss, eval_metric_ops=eval_metric_ops)
|
[
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"eval_metric_ops",
")"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/examples/learn/text_classification.py#L37-L62
|
|
adobe/chromium
|
cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7
|
native_client_sdk/src/build_tools/make_nacl_tools.py
|
python
|
Install
|
(options, tools=[], runtimes=[])
|
Install the NaCl tools and runtimes into the SDK staging area.
Assumes that all necessary artifacts are built into the NaCl scons-out/staging
directory, and copies them from there into the SDK staging area under
toolchain.
Args:
options: The build options object. This is populated from command-line
args at start-up.
tools: A list of tool names, these should *not* have any executable
suffix - this utility adds that (e.g. '.exe' on Windows).
runtimes: A list of IRT runtimes. These artifacts should *not* have any
suffix attached - this utility adds the '.nexe' suffix along with an
ISA-specific string (e.g. '_x86_32').
|
Install the NaCl tools and runtimes into the SDK staging area.
|
[
"Install",
"the",
"NaCl",
"tools",
"and",
"runtimes",
"into",
"the",
"SDK",
"staging",
"area",
"."
] |
def Install(options, tools=[], runtimes=[]):
'''Install the NaCl tools and runtimes into the SDK staging area.
Assumes that all necessary artifacts are built into the NaCl scons-out/staging
directory, and copies them from there into the SDK staging area under
toolchain.
Args:
options: The build options object. This is populated from command-line
args at start-up.
tools: A list of tool names, these should *not* have any executable
suffix - this utility adds that (e.g. '.exe' on Windows).
runtimes: A list of IRT runtimes. These artifacts should *not* have any
suffix attached - this utility adds the '.nexe' suffix along with an
ISA-specific string (e.g. '_x86_32').
'''
# TODO(bradnelson): add an 'install' alias to the main build for this.
nacl_dir = os.path.join(options.nacl_dir, 'native_client')
tool_build_path_32 = os.path.join(nacl_dir,
'scons-out',
'%s-x86-32' % (options.variant),
'staging')
tool_build_path_64 = os.path.join(nacl_dir,
'scons-out',
'%s-x86-64' % (options.variant),
'staging')
for nacl_tool in tools:
shutil.copy(os.path.join(tool_build_path_32,
'%s%s' % (nacl_tool, options.exe_suffix)),
os.path.join(options.toolchain,
'bin',
'%s_x86_32%s' % (nacl_tool, options.exe_suffix)))
shutil.copy(os.path.join(tool_build_path_64,
'%s%s' % (nacl_tool, options.exe_suffix)),
os.path.join(options.toolchain,
'bin',
'%s_x86_64%s' % (nacl_tool, options.exe_suffix)))
irt_build_path_32 = os.path.join(nacl_dir,
'scons-out',
'nacl_irt-x86-32',
'staging')
irt_build_path_64 = os.path.join(nacl_dir,
'scons-out',
'nacl_irt-x86-64',
'staging')
for nacl_irt in runtimes:
shutil.copy(os.path.join(irt_build_path_32,
'%s%s' % (nacl_irt, NEXE_SUFFIX)),
os.path.join(options.toolchain,
'runtime',
'%s_x86_32%s' % (nacl_irt, NEXE_SUFFIX)))
shutil.copy(os.path.join(irt_build_path_64,
'%s%s' % (nacl_irt, NEXE_SUFFIX)),
os.path.join(options.toolchain,
'runtime',
'%s_x86_64%s' % (nacl_irt, NEXE_SUFFIX)))
|
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"'%s%s'",
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"'%s%s'",
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"nacl_irt",
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"NEXE_SUFFIX",
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")",
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"'%s_x86_64%s'",
"%",
"(",
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",",
"NEXE_SUFFIX",
")",
")",
")"
] |
https://github.com/adobe/chromium/blob/cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7/native_client_sdk/src/build_tools/make_nacl_tools.py#L86-L143
|
||
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Editor/Python/windows/Lib/site-packages/setuptools/_vendor/six.py
|
python
|
remove_move
|
(name)
|
Remove item from six.moves.
|
Remove item from six.moves.
|
[
"Remove",
"item",
"from",
"six",
".",
"moves",
"."
] |
def remove_move(name):
"""Remove item from six.moves."""
try:
delattr(_MovedItems, name)
except AttributeError:
try:
del moves.__dict__[name]
except KeyError:
raise AttributeError("no such move, %r" % (name,))
|
[
"def",
"remove_move",
"(",
"name",
")",
":",
"try",
":",
"delattr",
"(",
"_MovedItems",
",",
"name",
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"except",
"AttributeError",
":",
"try",
":",
"del",
"moves",
".",
"__dict__",
"[",
"name",
"]",
"except",
"KeyError",
":",
"raise",
"AttributeError",
"(",
"\"no such move, %r\"",
"%",
"(",
"name",
",",
")",
")"
] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/setuptools/_vendor/six.py#L491-L499
|
||
ros-perception/image_pipeline
|
cd4aa7ab38726d88e8e0144aa0d45ad2f236535a
|
camera_calibration/src/camera_calibration/calibrator.py
|
python
|
_get_circles
|
(img, board, pattern)
|
return (ok, corners)
|
Get circle centers for a symmetric or asymmetric grid
|
Get circle centers for a symmetric or asymmetric grid
|
[
"Get",
"circle",
"centers",
"for",
"a",
"symmetric",
"or",
"asymmetric",
"grid"
] |
def _get_circles(img, board, pattern):
"""
Get circle centers for a symmetric or asymmetric grid
"""
h = img.shape[0]
w = img.shape[1]
if len(img.shape) == 3 and img.shape[2] == 3:
mono = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
else:
mono = img
flag = cv2.CALIB_CB_SYMMETRIC_GRID
if pattern == Patterns.ACircles:
flag = cv2.CALIB_CB_ASYMMETRIC_GRID
mono_arr = numpy.array(mono)
(ok, corners) = cv2.findCirclesGrid(mono_arr, (board.n_cols, board.n_rows), flags=flag)
# In symmetric case, findCirclesGrid does not detect the target if it's turned sideways. So we try
# again with dimensions swapped - not so efficient.
# TODO Better to add as second board? Corner ordering will change.
if not ok and pattern == Patterns.Circles:
(ok, corners) = cv2.findCirclesGrid(mono_arr, (board.n_rows, board.n_cols), flags=flag)
return (ok, corners)
|
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"def",
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"img",
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",",
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"0",
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https://github.com/ros-perception/image_pipeline/blob/cd4aa7ab38726d88e8e0144aa0d45ad2f236535a/camera_calibration/src/camera_calibration/calibrator.py#L265-L288
|
|
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
third_party/markdown/treeprocessors.py
|
python
|
PrettifyTreeprocessor._prettifyETree
|
(self, elem)
|
Recursively add linebreaks to ElementTree children.
|
Recursively add linebreaks to ElementTree children.
|
[
"Recursively",
"add",
"linebreaks",
"to",
"ElementTree",
"children",
"."
] |
def _prettifyETree(self, elem):
""" Recursively add linebreaks to ElementTree children. """
i = "\n"
if util.isBlockLevel(elem.tag) and elem.tag not in ['code', 'pre']:
if (not elem.text or not elem.text.strip()) \
and len(elem) and util.isBlockLevel(elem[0].tag):
elem.text = i
for e in elem:
if util.isBlockLevel(e.tag):
self._prettifyETree(e)
if not elem.tail or not elem.tail.strip():
elem.tail = i
if not elem.tail or not elem.tail.strip():
elem.tail = i
|
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/markdown/treeprocessors.py#L360-L374
|
||
NVIDIA/thrust
|
627dccb359a635afdd69e95a6cc59698f23f70e2
|
internal/benchmark/compare_benchmark_results.py
|
python
|
sample_variance
|
(X, u = None)
|
return sum(imap(lambda X_i: (X_i - u) ** 2, X)) / (len(X) - 1)
|
Computes the sample variance of the sequence `X`.
Let:
* `n = len(X)`.
* `u` denote the arithmetic mean of `X`.
* `s` denote the sample standard deviation of `X`.
.. math::
v = \frac{\sum_{i = 0}^{n - 1} (X_i - u)^2}{n - 1}
Args:
X (`Iterable`) : The sequence of values.
u (number) : The arithmetic mean of `X`.
|
Computes the sample variance of the sequence `X`.
|
[
"Computes",
"the",
"sample",
"variance",
"of",
"the",
"sequence",
"X",
"."
] |
def sample_variance(X, u = None):
"""Computes the sample variance of the sequence `X`.
Let:
* `n = len(X)`.
* `u` denote the arithmetic mean of `X`.
* `s` denote the sample standard deviation of `X`.
.. math::
v = \frac{\sum_{i = 0}^{n - 1} (X_i - u)^2}{n - 1}
Args:
X (`Iterable`) : The sequence of values.
u (number) : The arithmetic mean of `X`.
"""
if u is None: u = arithmetic_mean(X)
return sum(imap(lambda X_i: (X_i - u) ** 2, X)) / (len(X) - 1)
|
[
"def",
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https://github.com/NVIDIA/thrust/blob/627dccb359a635afdd69e95a6cc59698f23f70e2/internal/benchmark/compare_benchmark_results.py#L356-L374
|
|
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
tools/site_compare/command_line.py
|
python
|
Command.ParseNextArgument
|
(self)
|
Find the next argument in the command line and parse it.
|
Find the next argument in the command line and parse it.
|
[
"Find",
"the",
"next",
"argument",
"in",
"the",
"command",
"line",
"and",
"parse",
"it",
"."
] |
def ParseNextArgument(self):
"""Find the next argument in the command line and parse it."""
arg = None
value = None
argstr = self.cmdline.rargs.pop(0)
# First check: is this a literal argument?
if argstr.lower() in self.arg_dict:
arg = self.arg_dict[argstr.lower()]
if arg.type in Command.Argument.TYPES_WITH_VALUES:
if len(self.cmdline.rargs):
value = self.cmdline.rargs.pop(0)
# Second check: is this of the form "arg=val" or "arg:val"?
if arg is None:
delimiter_pos = -1
for delimiter in [':', '=']:
pos = argstr.find(delimiter)
if pos >= 0:
if delimiter_pos < 0 or pos < delimiter_pos:
delimiter_pos = pos
if delimiter_pos >= 0:
testarg = argstr[:delimiter_pos]
testval = argstr[delimiter_pos+1:]
if testarg.lower() in self.arg_dict:
arg = self.arg_dict[testarg.lower()]
argstr = testarg
value = testval
# Third check: does this begin an argument?
if arg is None:
for key in self.arg_dict.iterkeys():
if (len(key) < len(argstr) and
self.arg_dict[key].type in Command.Argument.TYPES_WITH_VALUES and
argstr[:len(key)].lower() == key):
value = argstr[len(key):]
argstr = argstr[:len(key)]
arg = self.arg_dict[argstr]
# Fourth check: do we have any positional arguments available?
if arg is None:
for positional_arg in [
testarg for testarg in self.args if testarg.positional]:
if not positional_arg.present:
arg = positional_arg
value = argstr
argstr = positional_arg.names[0]
break
# Push the retrieved argument/value onto the largs stack
if argstr: self.cmdline.largs.append(argstr)
if value: self.cmdline.largs.append(value)
# If we've made it this far and haven't found an arg, give up
if arg is None:
raise ParseError("Unknown argument: '%s'" % argstr)
# Convert the value, if necessary
if arg.type in Command.Argument.TYPES_WITH_VALUES and value is None:
raise ParseError("Argument '%s' requires a value" % argstr)
if value is not None:
value = self.StringToValue(value, arg.type, argstr)
arg.argstr = argstr
arg.value = value
arg.present = True
|
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/site_compare/command_line.py#L339-L408
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/_core.py
|
python
|
AcceleratorEntry.GetFlags
|
(*args, **kwargs)
|
return _core_.AcceleratorEntry_GetFlags(*args, **kwargs)
|
GetFlags(self) -> int
Get the AcceleratorEntry's flags.
|
GetFlags(self) -> int
|
[
"GetFlags",
"(",
"self",
")",
"-",
">",
"int"
] |
def GetFlags(*args, **kwargs):
"""
GetFlags(self) -> int
Get the AcceleratorEntry's flags.
"""
return _core_.AcceleratorEntry_GetFlags(*args, **kwargs)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_core.py#L8932-L8938
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/floatcanvas/FloatCanvas.py
|
python
|
ScaledBitmap2._DrawEntireBitmap
|
(self, dc , WorldToPixel, ScaleWorldToPixel, HTdc)
|
this is pretty much the old code
Scales and Draws the entire bitmap.
|
this is pretty much the old code
|
[
"this",
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"pretty",
"much",
"the",
"old",
"code"
] |
def _DrawEntireBitmap(self, dc , WorldToPixel, ScaleWorldToPixel, HTdc):
"""
this is pretty much the old code
Scales and Draws the entire bitmap.
"""
XY = WorldToPixel(self.XY)
H = int(round(ScaleWorldToPixel(self.Height)[0]))
W = int(round(H * (self.bmpWidth / self.bmpHeight)))
if W == 0 or H == 0: # nothing to draw
return
else:
if (self.ScaledBitmap is None) or (self.ScaledBitmap[0] != (0, 0, self.bmpWidth, self.bmpHeight, W, H) ):
#if True: #fixme: (self.ScaledBitmap is None) or (H <> self.ScaledHeight) :
self.ScaledHeight = H
Img = self.Image.Scale(W, H, quality=self._scale_quality)
bmp = wx.BitmapFromImage(Img)
self.ScaledBitmap = ((0, 0, self.bmpWidth, self.bmpHeight , W, H), bmp)# this defines the cached bitmap
else:
bmp = self.ScaledBitmap[1]
XY = self.ShiftFun(XY[0], XY[1], W, H)
dc.DrawBitmapPoint(bmp, XY, True)
if HTdc and self.HitAble:
HTdc.SetPen(self.HitPen)
HTdc.SetBrush(self.HitBrush)
HTdc.DrawRectanglePointSize(XY, (W, H) )
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/floatcanvas/FloatCanvas.py#L2085-L2111
|
||
thalium/icebox
|
99d147d5b9269222225443ce171b4fd46d8985d4
|
third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2class.py
|
python
|
loadACatalog
|
(filename)
|
return catalog(_obj=ret)
|
Load the catalog and build the associated data structures.
This can be either an XML Catalog or an SGML Catalog It
will recurse in SGML CATALOG entries. On the other hand XML
Catalogs are not handled recursively.
|
Load the catalog and build the associated data structures.
This can be either an XML Catalog or an SGML Catalog It
will recurse in SGML CATALOG entries. On the other hand XML
Catalogs are not handled recursively.
|
[
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] |
def loadACatalog(filename):
"""Load the catalog and build the associated data structures.
This can be either an XML Catalog or an SGML Catalog It
will recurse in SGML CATALOG entries. On the other hand XML
Catalogs are not handled recursively. """
ret = libxml2mod.xmlLoadACatalog(filename)
if ret is None:raise treeError('xmlLoadACatalog() failed')
return catalog(_obj=ret)
|
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https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2class.py#L189-L196
|
|
apache/qpid-proton
|
6bcdfebb55ea3554bc29b1901422532db331a591
|
python/proton/_endpoints.py
|
python
|
Connection.user
|
(self)
|
return utf82unicode(pn_connection_get_user(self._impl))
|
The authentication username for a client connection.
It is necessary to set the username and password before binding
the connection to a transport and it isn't allowed to change
after the binding.
If not set then no authentication will be negotiated unless the
client sasl layer is explicitly created (this would be for something
like Kerberos where the credentials are implicit in the environment,
or to explicitly use the ``ANONYMOUS`` SASL mechanism)
|
The authentication username for a client connection.
|
[
"The",
"authentication",
"username",
"for",
"a",
"client",
"connection",
"."
] |
def user(self) -> Optional[str]:
"""The authentication username for a client connection.
It is necessary to set the username and password before binding
the connection to a transport and it isn't allowed to change
after the binding.
If not set then no authentication will be negotiated unless the
client sasl layer is explicitly created (this would be for something
like Kerberos where the credentials are implicit in the environment,
or to explicitly use the ``ANONYMOUS`` SASL mechanism)
"""
return utf82unicode(pn_connection_get_user(self._impl))
|
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"utf82unicode",
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"pn_connection_get_user",
"(",
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")"
] |
https://github.com/apache/qpid-proton/blob/6bcdfebb55ea3554bc29b1901422532db331a591/python/proton/_endpoints.py#L243-L255
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
Framework/PythonInterface/mantid/fitfunctions.py
|
python
|
FunctionWrapper.constrain
|
(self, expressions)
|
Add constraints
:param expressions: string of tie expressions
|
Add constraints
|
[
"Add",
"constraints"
] |
def constrain(self, expressions):
"""
Add constraints
:param expressions: string of tie expressions
"""
self.fun.addConstraints( expressions )
|
[
"def",
"constrain",
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",",
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/PythonInterface/mantid/fitfunctions.py#L320-L326
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/uuid.py
|
python
|
_windll_getnode
|
()
|
Get the hardware address on Windows using ctypes.
|
Get the hardware address on Windows using ctypes.
|
[
"Get",
"the",
"hardware",
"address",
"on",
"Windows",
"using",
"ctypes",
"."
] |
def _windll_getnode():
"""Get the hardware address on Windows using ctypes."""
_buffer = ctypes.create_string_buffer(16)
if _UuidCreate(_buffer) == 0:
return UUID(bytes=_buffer.raw).node
|
[
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] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/uuid.py#L448-L452
|
||
ROCmSoftwarePlatform/hipCaffe
|
4ec5d482515cce532348553b6db6d00d015675d5
|
python/caffe/classifier.py
|
python
|
Classifier.predict
|
(self, inputs, oversample=True)
|
return predictions
|
Predict classification probabilities of inputs.
Parameters
----------
inputs : iterable of (H x W x K) input ndarrays.
oversample : boolean
average predictions across center, corners, and mirrors
when True (default). Center-only prediction when False.
Returns
-------
predictions: (N x C) ndarray of class probabilities for N images and C
classes.
|
Predict classification probabilities of inputs.
|
[
"Predict",
"classification",
"probabilities",
"of",
"inputs",
"."
] |
def predict(self, inputs, oversample=True):
"""
Predict classification probabilities of inputs.
Parameters
----------
inputs : iterable of (H x W x K) input ndarrays.
oversample : boolean
average predictions across center, corners, and mirrors
when True (default). Center-only prediction when False.
Returns
-------
predictions: (N x C) ndarray of class probabilities for N images and C
classes.
"""
# Scale to standardize input dimensions.
input_ = np.zeros((len(inputs),
self.image_dims[0],
self.image_dims[1],
inputs[0].shape[2]),
dtype=np.float32)
for ix, in_ in enumerate(inputs):
input_[ix] = caffe.io.resize_image(in_, self.image_dims)
if oversample:
# Generate center, corner, and mirrored crops.
input_ = caffe.io.oversample(input_, self.crop_dims)
else:
# Take center crop.
center = np.array(self.image_dims) / 2.0
crop = np.tile(center, (1, 2))[0] + np.concatenate([
-self.crop_dims / 2.0,
self.crop_dims / 2.0
])
crop = crop.astype(int)
input_ = input_[:, crop[0]:crop[2], crop[1]:crop[3], :]
# Classify
caffe_in = np.zeros(np.array(input_.shape)[[0, 3, 1, 2]],
dtype=np.float32)
for ix, in_ in enumerate(input_):
caffe_in[ix] = self.transformer.preprocess(self.inputs[0], in_)
out = self.forward_all(**{self.inputs[0]: caffe_in})
predictions = out[self.outputs[0]]
# For oversampling, average predictions across crops.
if oversample:
predictions = predictions.reshape((len(predictions) / 10, 10, -1))
predictions = predictions.mean(1)
return predictions
|
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"(",
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"return",
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https://github.com/ROCmSoftwarePlatform/hipCaffe/blob/4ec5d482515cce532348553b6db6d00d015675d5/python/caffe/classifier.py#L47-L98
|
|
moderngl/moderngl
|
32fe79927e02b0fa893b3603d677bdae39771e14
|
moderngl/program.py
|
python
|
Program.geometry_output
|
(self)
|
return self._geom[1]
|
int: The geometry output primitive.
The GeometryShader's output primitive if the GeometryShader exists.
This can only be ``POINTS``, ``LINE_STRIP`` and ``TRIANGLE_STRIP``
(from ``layout(output_primitive, max_vertices = vert_count) out;``)
|
int: The geometry output primitive.
|
[
"int",
":",
"The",
"geometry",
"output",
"primitive",
"."
] |
def geometry_output(self) -> int:
'''
int: The geometry output primitive.
The GeometryShader's output primitive if the GeometryShader exists.
This can only be ``POINTS``, ``LINE_STRIP`` and ``TRIANGLE_STRIP``
(from ``layout(output_primitive, max_vertices = vert_count) out;``)
'''
return self._geom[1]
|
[
"def",
"geometry_output",
"(",
"self",
")",
"->",
"int",
":",
"return",
"self",
".",
"_geom",
"[",
"1",
"]"
] |
https://github.com/moderngl/moderngl/blob/32fe79927e02b0fa893b3603d677bdae39771e14/moderngl/program.py#L167-L176
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/agw/ribbon/panel.py
|
python
|
RibbonPanel.GetBestSizeForParentSize
|
(self, parentSize)
|
return self.GetSize()
|
Finds the best width and height given the parent's width and height.
|
Finds the best width and height given the parent's width and height.
|
[
"Finds",
"the",
"best",
"width",
"and",
"height",
"given",
"the",
"parent",
"s",
"width",
"and",
"height",
"."
] |
def GetBestSizeForParentSize(self, parentSize):
""" Finds the best width and height given the parent's width and height. """
if len(self.GetChildren()) == 1:
win = self.GetChildren()[0]
if isinstance(win, RibbonControl):
temp_dc = wx.ClientDC(self)
childSize = win.GetBestSizeForParentSize(parentSize)
clientParentSize = self._art.GetPanelClientSize(temp_dc, self, wx.Size(*parentSize), None)
overallSize = self._art.GetPanelSize(temp_dc, self, wx.Size(*clientParentSize), None)
return overallSize
return self.GetSize()
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/ribbon/panel.py#L493-L506
|
|
hughperkins/tf-coriander
|
970d3df6c11400ad68405f22b0c42a52374e94ca
|
tensorflow/contrib/layers/python/layers/layers.py
|
python
|
flatten
|
(inputs,
outputs_collections=None,
scope=None)
|
Flattens the input while maintaining the batch_size.
Assumes that the first dimension represents the batch.
Args:
inputs: a tensor of size [batch_size, ...].
outputs_collections: collection to add the outputs.
scope: Optional scope for name_scope.
Returns:
a flattened tensor with shape [batch_size, k].
Raises:
ValueError: if inputs.shape is wrong.
|
Flattens the input while maintaining the batch_size.
|
[
"Flattens",
"the",
"input",
"while",
"maintaining",
"the",
"batch_size",
"."
] |
def flatten(inputs,
outputs_collections=None,
scope=None):
"""Flattens the input while maintaining the batch_size.
Assumes that the first dimension represents the batch.
Args:
inputs: a tensor of size [batch_size, ...].
outputs_collections: collection to add the outputs.
scope: Optional scope for name_scope.
Returns:
a flattened tensor with shape [batch_size, k].
Raises:
ValueError: if inputs.shape is wrong.
"""
with ops.name_scope(scope, 'Flatten', [inputs]) as sc:
inputs = ops.convert_to_tensor(inputs)
inputs_shape = inputs.get_shape()
inputs_rank = inputs_shape.ndims
if (inputs_rank is None) or (inputs_rank < 2):
raise ValueError('Inputs must have a least 2 dimensions.')
dims = inputs_shape[1:]
if not dims.is_fully_defined():
raise ValueError('Inputs 2nd dimension must be defined.')
k = dims.num_elements()
outputs = array_ops.reshape(inputs, [-1, k])
return utils.collect_named_outputs(outputs_collections, sc, outputs)
|
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https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/contrib/layers/python/layers/layers.py#L751-L779
|
||
microsoft/CNTK
|
e9396480025b9ca457d26b6f33dd07c474c6aa04
|
bindings/python/cntk/device.py
|
python
|
cpu
|
()
|
return cntk_py.DeviceDescriptor.cpu_device()
|
Returns CPU device descriptor
Returns:
:class:`~cntk.device.DeviceDescriptor`: CPU device descriptor
|
Returns CPU device descriptor
|
[
"Returns",
"CPU",
"device",
"descriptor"
] |
def cpu():
'''
Returns CPU device descriptor
Returns:
:class:`~cntk.device.DeviceDescriptor`: CPU device descriptor
'''
return cntk_py.DeviceDescriptor.cpu_device()
|
[
"def",
"cpu",
"(",
")",
":",
"return",
"cntk_py",
".",
"DeviceDescriptor",
".",
"cpu_device",
"(",
")"
] |
https://github.com/microsoft/CNTK/blob/e9396480025b9ca457d26b6f33dd07c474c6aa04/bindings/python/cntk/device.py#L78-L85
|
|
smilehao/xlua-framework
|
a03801538be2b0e92d39332d445b22caca1ef61f
|
ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/stubout.py
|
python
|
StubOutForTesting.SmartUnsetAll
|
(self)
|
Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
|
Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
|
[
"Reverses",
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"SmartSet",
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"things",
"to",
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"()",
"repeatedly",
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"later",
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"have",
"no",
"effect",
"if",
"no",
"SmartSet",
"()",
"calls",
"have",
"been",
"made",
"."
] |
def SmartUnsetAll(self):
"""Reverses all the SmartSet() calls, restoring things to their original
definition. Its okay to call SmartUnsetAll() repeatedly, as later calls
have no effect if no SmartSet() calls have been made.
"""
self.stubs.reverse()
for args in self.stubs:
setattr(*args)
self.stubs = []
|
[
"def",
"SmartUnsetAll",
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"self",
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":",
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":",
"setattr",
"(",
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"args",
")",
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".",
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"=",
"[",
"]"
] |
https://github.com/smilehao/xlua-framework/blob/a03801538be2b0e92d39332d445b22caca1ef61f/ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/stubout.py#L96-L107
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/ipython/py3/IPython/core/display.py
|
python
|
_display_mimetype
|
(mimetype, objs, raw=False, metadata=None)
|
internal implementation of all display_foo methods
Parameters
----------
mimetype : str
The mimetype to be published (e.g. 'image/png')
*objs : object
The Python objects to display, or if raw=True raw text data to
display.
raw : bool
Are the data objects raw data or Python objects that need to be
formatted before display? [default: False]
metadata : dict (optional)
Metadata to be associated with the specific mimetype output.
|
internal implementation of all display_foo methods
|
[
"internal",
"implementation",
"of",
"all",
"display_foo",
"methods"
] |
def _display_mimetype(mimetype, objs, raw=False, metadata=None):
"""internal implementation of all display_foo methods
Parameters
----------
mimetype : str
The mimetype to be published (e.g. 'image/png')
*objs : object
The Python objects to display, or if raw=True raw text data to
display.
raw : bool
Are the data objects raw data or Python objects that need to be
formatted before display? [default: False]
metadata : dict (optional)
Metadata to be associated with the specific mimetype output.
"""
if metadata:
metadata = {mimetype: metadata}
if raw:
# turn list of pngdata into list of { 'image/png': pngdata }
objs = [ {mimetype: obj} for obj in objs ]
display(*objs, raw=raw, metadata=metadata, include=[mimetype])
|
[
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/ipython/py3/IPython/core/display.py#L53-L74
|
||
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
Framework/DataObjects/scripts/analysis.py
|
python
|
plot_results_with_slope
|
(results, x_field, y_field, x_scale=1.)
|
Function to plot Y vs X of anything. It accesses the members of "results" to plot them.
other_field is used to separate by another field, and make separate line plots for each
@param x_scale :: multiply x by this amount
|
Function to plot Y vs X of anything. It accesses the members of "results" to plot them.
other_field is used to separate by another field, and make separate line plots for each
|
[
"Function",
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"plot",
"Y",
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"anything",
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"separate",
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"another",
"field",
"and",
"make",
"separate",
"line",
"plots",
"for",
"each"
] |
def plot_results_with_slope(results, x_field, y_field, x_scale=1.):
""" Function to plot Y vs X of anything. It accesses the members of "results" to plot them.
other_field is used to separate by another field, and make separate line plots for each
@param x_scale :: multiply x by this amount
"""
figure()
data = []
for _ in results:
x = eval('par.%s' % x_field)
y = eval('par.%s' % y_field)
data.append( (x,y) )
data.sort()
xs = [x*x_scale for (x,y) in data]
ys = [y for (x,y) in data]
# Now get the slope
gradient, intercept, r_value, p_value, std_err = stats.linregress(xs,ys)
plot(xs,ys, marker='.', label="y = %.3gx + %.3g" % (gradient, intercept))
title("%s vs %s" % (y_field, x_field))
xlabel("%s x %s" % (x_field, x_scale) )
ylabel(y_field)
legend(loc='best')
savefig("%s_vs_%s.png" % (y_field, x_field))
|
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/DataObjects/scripts/analysis.py#L67-L93
|
||
ceph/ceph
|
959663007321a369c83218414a29bd9dbc8bda3a
|
qa/tasks/exec_on_cleanup.py
|
python
|
task
|
(ctx, config)
|
Execute commands on a given role
tasks:
- ceph:
- kclient: [client.a]
- exec:
client.a:
- "echo 'module libceph +p' > /sys/kernel/debug/dynamic_debug/control"
- "echo 'module ceph +p' > /sys/kernel/debug/dynamic_debug/control"
- interactive:
It stops and fails with the first command that does not return on success. It means
that if the first command fails, the second won't run at all.
To avoid confusion it is recommended to explicitly enclose the commands in
double quotes. For instance if the command is false (without double quotes) it will
be interpreted as a boolean by the YAML parser.
:param ctx: Context
:param config: Configuration
|
Execute commands on a given role
|
[
"Execute",
"commands",
"on",
"a",
"given",
"role"
] |
def task(ctx, config):
"""
Execute commands on a given role
tasks:
- ceph:
- kclient: [client.a]
- exec:
client.a:
- "echo 'module libceph +p' > /sys/kernel/debug/dynamic_debug/control"
- "echo 'module ceph +p' > /sys/kernel/debug/dynamic_debug/control"
- interactive:
It stops and fails with the first command that does not return on success. It means
that if the first command fails, the second won't run at all.
To avoid confusion it is recommended to explicitly enclose the commands in
double quotes. For instance if the command is false (without double quotes) it will
be interpreted as a boolean by the YAML parser.
:param ctx: Context
:param config: Configuration
"""
try:
yield
finally:
log.info('Executing custom commands...')
assert isinstance(config, dict), "task exec got invalid config"
testdir = teuthology.get_testdir(ctx)
if 'all' in config and len(config) == 1:
a = config['all']
roles = teuthology.all_roles(ctx.cluster)
config = dict((id_, a) for id_ in roles)
for role, ls in config.items():
(remote,) = ctx.cluster.only(role).remotes.keys()
log.info('Running commands on role %s host %s', role, remote.name)
for c in ls:
c.replace('$TESTDIR', testdir)
remote.run(
args=[
'sudo',
'TESTDIR={tdir}'.format(tdir=testdir),
'bash',
'-c',
c],
)
|
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",",
"'bash'",
",",
"'-c'",
",",
"c",
"]",
",",
")"
] |
https://github.com/ceph/ceph/blob/959663007321a369c83218414a29bd9dbc8bda3a/qa/tasks/exec_on_cleanup.py#L12-L60
|
||
mindspore-ai/mindspore
|
fb8fd3338605bb34fa5cea054e535a8b1d753fab
|
mindspore/python/mindspore/_checkparam.py
|
python
|
Validator.check_equal_int
|
(arg_value, value, arg_name=None, prim_name=None)
|
return check_number(arg_value, value, Rel.EQ, int, arg_name, prim_name)
|
Checks input integer value `arg_value` compare to `value`.
Usage:
- number = check_int(number, 0, Rel.GE, "number", None) # number >= 0
|
Checks input integer value `arg_value` compare to `value`.
|
[
"Checks",
"input",
"integer",
"value",
"arg_value",
"compare",
"to",
"value",
"."
] |
def check_equal_int(arg_value, value, arg_name=None, prim_name=None):
"""
Checks input integer value `arg_value` compare to `value`.
Usage:
- number = check_int(number, 0, Rel.GE, "number", None) # number >= 0
"""
return check_number(arg_value, value, Rel.EQ, int, arg_name, prim_name)
|
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"def",
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",",
"Rel",
".",
"EQ",
",",
"int",
",",
"arg_name",
",",
"prim_name",
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https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/_checkparam.py#L253-L260
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/dtypes/cast.py
|
python
|
construct_1d_object_array_from_listlike
|
(values)
|
return result
|
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Parameters
----------
values : any iterable which has a len()
Raises
------
TypeError
* If `values` does not have a len()
Returns
-------
1-dimensional numpy array of dtype object
|
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
|
[
"Transform",
"any",
"list",
"-",
"like",
"object",
"in",
"a",
"1",
"-",
"dimensional",
"numpy",
"array",
"of",
"object",
"dtype",
"."
] |
def construct_1d_object_array_from_listlike(values):
"""
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Parameters
----------
values : any iterable which has a len()
Raises
------
TypeError
* If `values` does not have a len()
Returns
-------
1-dimensional numpy array of dtype object
"""
# numpy will try to interpret nested lists as further dimensions, hence
# making a 1D array that contains list-likes is a bit tricky:
result = np.empty(len(values), dtype="object")
result[:] = values
return result
|
[
"def",
"construct_1d_object_array_from_listlike",
"(",
"values",
")",
":",
"# numpy will try to interpret nested lists as further dimensions, hence",
"# making a 1D array that contains list-likes is a bit tricky:",
"result",
"=",
"np",
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"empty",
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"(",
"values",
")",
",",
"dtype",
"=",
"\"object\"",
")",
"result",
"[",
":",
"]",
"=",
"values",
"return",
"result"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/dtypes/cast.py#L1458-L1480
|
|
windystrife/UnrealEngine_NVIDIAGameWorks
|
b50e6338a7c5b26374d66306ebc7807541ff815e
|
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/multiprocessing/managers.py
|
python
|
Server.create
|
(self, c, typeid, *args, **kwds)
|
Create a new shared object and return its id
|
Create a new shared object and return its id
|
[
"Create",
"a",
"new",
"shared",
"object",
"and",
"return",
"its",
"id"
] |
def create(self, c, typeid, *args, **kwds):
'''
Create a new shared object and return its id
'''
self.mutex.acquire()
try:
callable, exposed, method_to_typeid, proxytype = \
self.registry[typeid]
if callable is None:
assert len(args) == 1 and not kwds
obj = args[0]
else:
obj = callable(*args, **kwds)
if exposed is None:
exposed = public_methods(obj)
if method_to_typeid is not None:
assert type(method_to_typeid) is dict
exposed = list(exposed) + list(method_to_typeid)
ident = '%x' % id(obj) # convert to string because xmlrpclib
# only has 32 bit signed integers
util.debug('%r callable returned object with id %r', typeid, ident)
self.id_to_obj[ident] = (obj, set(exposed), method_to_typeid)
if ident not in self.id_to_refcount:
self.id_to_refcount[ident] = 0
# increment the reference count immediately, to avoid
# this object being garbage collected before a Proxy
# object for it can be created. The caller of create()
# is responsible for doing a decref once the Proxy object
# has been created.
self.incref(c, ident)
return ident, tuple(exposed)
finally:
self.mutex.release()
|
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] |
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/multiprocessing/managers.py#L373-L409
|
||
LiquidPlayer/LiquidCore
|
9405979363f2353ac9a71ad8ab59685dd7f919c9
|
deps/node-10.15.3/tools/gyp/pylib/gyp/xcode_emulation.py
|
python
|
XcodeSettings.GetInstallNameBase
|
(self)
|
return install_base
|
Return DYLIB_INSTALL_NAME_BASE for this target.
|
Return DYLIB_INSTALL_NAME_BASE for this target.
|
[
"Return",
"DYLIB_INSTALL_NAME_BASE",
"for",
"this",
"target",
"."
] |
def GetInstallNameBase(self):
"""Return DYLIB_INSTALL_NAME_BASE for this target."""
# Xcode sets this for shared_libraries, and for nonbundled loadable_modules.
if (self.spec['type'] != 'shared_library' and
(self.spec['type'] != 'loadable_module' or self._IsBundle())):
return None
install_base = self.GetPerTargetSetting(
'DYLIB_INSTALL_NAME_BASE',
default='/Library/Frameworks' if self._IsBundle() else '/usr/local/lib')
return install_base
|
[
"def",
"GetInstallNameBase",
"(",
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")",
":",
"# Xcode sets this for shared_libraries, and for nonbundled loadable_modules.",
"if",
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"'type'",
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".",
"_IsBundle",
"(",
")",
"else",
"'/usr/local/lib'",
")",
"return",
"install_base"
] |
https://github.com/LiquidPlayer/LiquidCore/blob/9405979363f2353ac9a71ad8ab59685dd7f919c9/deps/node-10.15.3/tools/gyp/pylib/gyp/xcode_emulation.py#L756-L765
|
|
gwaldron/osgearth
|
4c521857d59a69743e4a9cedba00afe570f984e8
|
src/third_party/tinygltf/deps/cpplint.py
|
python
|
Search
|
(pattern, s)
|
return _regexp_compile_cache[pattern].search(s)
|
Searches the string for the pattern, caching the compiled regexp.
|
Searches the string for the pattern, caching the compiled regexp.
|
[
"Searches",
"the",
"string",
"for",
"the",
"pattern",
"caching",
"the",
"compiled",
"regexp",
"."
] |
def Search(pattern, s):
"""Searches the string for the pattern, caching the compiled regexp."""
if pattern not in _regexp_compile_cache:
_regexp_compile_cache[pattern] = sre_compile.compile(pattern)
return _regexp_compile_cache[pattern].search(s)
|
[
"def",
"Search",
"(",
"pattern",
",",
"s",
")",
":",
"if",
"pattern",
"not",
"in",
"_regexp_compile_cache",
":",
"_regexp_compile_cache",
"[",
"pattern",
"]",
"=",
"sre_compile",
".",
"compile",
"(",
"pattern",
")",
"return",
"_regexp_compile_cache",
"[",
"pattern",
"]",
".",
"search",
"(",
"s",
")"
] |
https://github.com/gwaldron/osgearth/blob/4c521857d59a69743e4a9cedba00afe570f984e8/src/third_party/tinygltf/deps/cpplint.py#L585-L589
|
|
gnina/gnina
|
b9ae032f52fc7a8153987bde09c0efa3620d8bb6
|
caffe/python/caffe/io.py
|
python
|
Transformer.set_input_scale
|
(self, in_, scale)
|
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
|
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
|
[
"Set",
"the",
"scale",
"of",
"preprocessed",
"inputs",
"s",
".",
"t",
".",
"the",
"blob",
"=",
"blob",
"*",
"scale",
".",
"N",
".",
"B",
".",
"input_scale",
"is",
"done",
"AFTER",
"mean",
"subtraction",
"and",
"other",
"preprocessing",
"while",
"raw_scale",
"is",
"done",
"BEFORE",
"."
] |
def set_input_scale(self, in_, scale):
"""
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
"""
self.__check_input(in_)
self.input_scale[in_] = scale
|
[
"def",
"set_input_scale",
"(",
"self",
",",
"in_",
",",
"scale",
")",
":",
"self",
".",
"__check_input",
"(",
"in_",
")",
"self",
".",
"input_scale",
"[",
"in_",
"]",
"=",
"scale"
] |
https://github.com/gnina/gnina/blob/b9ae032f52fc7a8153987bde09c0efa3620d8bb6/caffe/python/caffe/io.py#L277-L289
|
||
RoboJackets/robocup-software
|
bce13ce53ddb2ecb9696266d980722c34617dc15
|
util/run-clang-tidy.py
|
python
|
get_tidy_invocation
|
(
f,
clang_tidy_binary,
checks,
tmpdir,
build_path,
header_filter,
allow_enabling_alpha_checkers,
extra_arg,
extra_arg_before,
quiet,
config,
)
|
return start
|
Gets a command line for clang-tidy.
|
Gets a command line for clang-tidy.
|
[
"Gets",
"a",
"command",
"line",
"for",
"clang",
"-",
"tidy",
"."
] |
def get_tidy_invocation(
f,
clang_tidy_binary,
checks,
tmpdir,
build_path,
header_filter,
allow_enabling_alpha_checkers,
extra_arg,
extra_arg_before,
quiet,
config,
):
"""Gets a command line for clang-tidy."""
start = [clang_tidy_binary]
if allow_enabling_alpha_checkers is not None:
start.append("-allow-enabling-analyzer-alpha-checkers")
if header_filter is not None:
start.append("-header-filter=" + header_filter)
if checks:
start.append("-checks=" + checks)
if tmpdir is not None:
start.append("-export-fixes")
# Get a temporary file. We immediately close the handle so clang-tidy can
# overwrite it.
(handle, name) = tempfile.mkstemp(suffix=".yaml", dir=tmpdir)
os.close(handle)
start.append(name)
for arg in extra_arg:
start.append("-extra-arg=%s" % arg)
for arg in extra_arg_before:
start.append("-extra-arg-before=%s" % arg)
start.append("-p=" + build_path)
if quiet:
start.append("-quiet")
if config:
start.append("-config=" + config)
start.append(f)
return start
|
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",",
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",",
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"(",
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"+",
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":",
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"(",
"\"-quiet\"",
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"+",
"config",
")",
"start",
".",
"append",
"(",
"f",
")",
"return",
"start"
] |
https://github.com/RoboJackets/robocup-software/blob/bce13ce53ddb2ecb9696266d980722c34617dc15/util/run-clang-tidy.py#L83-L121
|
|
SoarGroup/Soar
|
a1c5e249499137a27da60533c72969eef3b8ab6b
|
scons/scons-local-4.1.0/SCons/Action.py
|
python
|
CommandAction._get_implicit_deps_lightweight
|
(self, target, source, env, executor)
|
return res
|
Lightweight dependency scanning involves only scanning the first entry
in an action string, even if it contains &&.
|
Lightweight dependency scanning involves only scanning the first entry
in an action string, even if it contains &&.
|
[
"Lightweight",
"dependency",
"scanning",
"involves",
"only",
"scanning",
"the",
"first",
"entry",
"in",
"an",
"action",
"string",
"even",
"if",
"it",
"contains",
"&&",
"."
] |
def _get_implicit_deps_lightweight(self, target, source, env, executor):
"""
Lightweight dependency scanning involves only scanning the first entry
in an action string, even if it contains &&.
"""
from SCons.Subst import SUBST_SIG
if executor:
cmd_list = env.subst_list(self.cmd_list, SUBST_SIG, executor=executor)
else:
cmd_list = env.subst_list(self.cmd_list, SUBST_SIG, target, source)
res = []
for cmd_line in cmd_list:
if cmd_line:
d = str(cmd_line[0])
m = strip_quotes.match(d)
if m:
d = m.group(1)
d = env.WhereIs(d)
if d:
res.append(env.fs.File(d))
return res
|
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",",
"target",
",",
"source",
")",
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"[",
"]",
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":",
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".",
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".",
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"(",
"d",
")",
")",
"return",
"res"
] |
https://github.com/SoarGroup/Soar/blob/a1c5e249499137a27da60533c72969eef3b8ab6b/scons/scons-local-4.1.0/SCons/Action.py#L988-L1008
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/io/excel/_util.py
|
python
|
_maybe_convert_usecols
|
(usecols)
|
return usecols
|
Convert `usecols` into a compatible format for parsing in `parsers.py`.
Parameters
----------
usecols : object
The use-columns object to potentially convert.
Returns
-------
converted : object
The compatible format of `usecols`.
|
Convert `usecols` into a compatible format for parsing in `parsers.py`.
|
[
"Convert",
"usecols",
"into",
"a",
"compatible",
"format",
"for",
"parsing",
"in",
"parsers",
".",
"py",
"."
] |
def _maybe_convert_usecols(usecols):
"""
Convert `usecols` into a compatible format for parsing in `parsers.py`.
Parameters
----------
usecols : object
The use-columns object to potentially convert.
Returns
-------
converted : object
The compatible format of `usecols`.
"""
if usecols is None:
return usecols
if is_integer(usecols):
raise ValueError(
"Passing an integer for `usecols` is no longer supported. "
"Please pass in a list of int from 0 to `usecols` "
"inclusive instead."
)
if isinstance(usecols, str):
return _range2cols(usecols)
return usecols
|
[
"def",
"_maybe_convert_usecols",
"(",
"usecols",
")",
":",
"if",
"usecols",
"is",
"None",
":",
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"(",
"usecols",
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":",
"raise",
"ValueError",
"(",
"\"Passing an integer for `usecols` is no longer supported. \"",
"\"Please pass in a list of int from 0 to `usecols` \"",
"\"inclusive instead.\"",
")",
"if",
"isinstance",
"(",
"usecols",
",",
"str",
")",
":",
"return",
"_range2cols",
"(",
"usecols",
")",
"return",
"usecols"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/io/excel/_util.py#L119-L146
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/AWSPythonSDK/1.5.8/docutils/examples.py
|
python
|
html_body
|
(input_string, source_path=None, destination_path=None,
input_encoding='unicode', output_encoding='unicode',
doctitle=True, initial_header_level=1)
|
return fragment
|
Given an input string, returns an HTML fragment as a string.
The return value is the contents of the <body> element.
Parameters (see `html_parts()` for the remainder):
- `output_encoding`: The desired encoding of the output. If a Unicode
string is desired, use the default value of "unicode" .
|
Given an input string, returns an HTML fragment as a string.
|
[
"Given",
"an",
"input",
"string",
"returns",
"an",
"HTML",
"fragment",
"as",
"a",
"string",
"."
] |
def html_body(input_string, source_path=None, destination_path=None,
input_encoding='unicode', output_encoding='unicode',
doctitle=True, initial_header_level=1):
"""
Given an input string, returns an HTML fragment as a string.
The return value is the contents of the <body> element.
Parameters (see `html_parts()` for the remainder):
- `output_encoding`: The desired encoding of the output. If a Unicode
string is desired, use the default value of "unicode" .
"""
parts = html_parts(
input_string=input_string, source_path=source_path,
destination_path=destination_path,
input_encoding=input_encoding, doctitle=doctitle,
initial_header_level=initial_header_level)
fragment = parts['html_body']
if output_encoding != 'unicode':
fragment = fragment.encode(output_encoding)
return fragment
|
[
"def",
"html_body",
"(",
"input_string",
",",
"source_path",
"=",
"None",
",",
"destination_path",
"=",
"None",
",",
"input_encoding",
"=",
"'unicode'",
",",
"output_encoding",
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",",
"doctitle",
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"True",
",",
"initial_header_level",
"=",
"1",
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"parts",
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"html_parts",
"(",
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",",
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",",
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"'unicode'",
":",
"fragment",
"=",
"fragment",
".",
"encode",
"(",
"output_encoding",
")",
"return",
"fragment"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/docutils/examples.py#L52-L73
|
|
sfzhang15/FaceBoxes
|
b52cc92f9362d3adc08d54666aeb9ebb62fdb7da
|
python/caffe/net_spec.py
|
python
|
param_name_dict
|
()
|
return dict(zip(param_type_names, param_names))
|
Find out the correspondence between layer names and parameter names.
|
Find out the correspondence between layer names and parameter names.
|
[
"Find",
"out",
"the",
"correspondence",
"between",
"layer",
"names",
"and",
"parameter",
"names",
"."
] |
def param_name_dict():
"""Find out the correspondence between layer names and parameter names."""
layer = caffe_pb2.LayerParameter()
# get all parameter names (typically underscore case) and corresponding
# type names (typically camel case), which contain the layer names
# (note that not all parameters correspond to layers, but we'll ignore that)
param_names = [f.name for f in layer.DESCRIPTOR.fields if f.name.endswith('_param')]
param_type_names = [type(getattr(layer, s)).__name__ for s in param_names]
# strip the final '_param' or 'Parameter'
param_names = [s[:-len('_param')] for s in param_names]
param_type_names = [s[:-len('Parameter')] for s in param_type_names]
return dict(zip(param_type_names, param_names))
|
[
"def",
"param_name_dict",
"(",
")",
":",
"layer",
"=",
"caffe_pb2",
".",
"LayerParameter",
"(",
")",
"# get all parameter names (typically underscore case) and corresponding",
"# type names (typically camel case), which contain the layer names",
"# (note that not all parameters correspond to layers, but we'll ignore that)",
"param_names",
"=",
"[",
"f",
".",
"name",
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"f",
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"layer",
".",
"DESCRIPTOR",
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"name",
".",
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"'_param'",
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",",
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"# strip the final '_param' or 'Parameter'",
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"-",
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"-",
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"]",
"return",
"dict",
"(",
"zip",
"(",
"param_type_names",
",",
"param_names",
")",
")"
] |
https://github.com/sfzhang15/FaceBoxes/blob/b52cc92f9362d3adc08d54666aeb9ebb62fdb7da/python/caffe/net_spec.py#L28-L40
|
|
krishauser/Klampt
|
972cc83ea5befac3f653c1ba20f80155768ad519
|
Python/klampt/robotsim.py
|
python
|
RobotPoser.setActiveDofs
|
(self, dofs: IntArray)
|
return _robotsim.RobotPoser_setActiveDofs(self, dofs)
|
r"""
Args:
dofs (:obj:`list of int`)
|
r"""
Args:
dofs (:obj:`list of int`)
|
[
"r",
"Args",
":",
"dofs",
"(",
":",
"obj",
":",
"list",
"of",
"int",
")"
] |
def setActiveDofs(self, dofs: IntArray) ->None:
r"""
Args:
dofs (:obj:`list of int`)
"""
return _robotsim.RobotPoser_setActiveDofs(self, dofs)
|
[
"def",
"setActiveDofs",
"(",
"self",
",",
"dofs",
":",
"IntArray",
")",
"->",
"None",
":",
"return",
"_robotsim",
".",
"RobotPoser_setActiveDofs",
"(",
"self",
",",
"dofs",
")"
] |
https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/klampt/robotsim.py#L3579-L3584
|
|
klzgrad/naiveproxy
|
ed2c513637c77b18721fe428d7ed395b4d284c83
|
src/build/lacros/lacros_resource_sizes.py
|
python
|
_visit_paths
|
(base_dir, paths)
|
Itemizes files specified by a list of paths.
Args:
base_dir: Base directory for all elements in |paths|.
paths: A list of filenames or directory names to specify files whose sizes
to be counted. Directories are recursed. There's no de-duping effort.
Non-existing files or directories are ignored (with warning message).
|
Itemizes files specified by a list of paths.
|
[
"Itemizes",
"files",
"specified",
"by",
"a",
"list",
"of",
"paths",
"."
] |
def _visit_paths(base_dir, paths):
"""Itemizes files specified by a list of paths.
Args:
base_dir: Base directory for all elements in |paths|.
paths: A list of filenames or directory names to specify files whose sizes
to be counted. Directories are recursed. There's no de-duping effort.
Non-existing files or directories are ignored (with warning message).
"""
for path in paths:
full_path = os.path.join(base_dir, path)
if os.path.exists(full_path):
if os.path.isdir(full_path):
for dirpath, _, filenames in os.walk(full_path):
for filename in filenames:
yield os.path.join(dirpath, filename)
else: # Assume is file.
yield full_path
else:
logging.critical('Not found: %s', path)
|
[
"def",
"_visit_paths",
"(",
"base_dir",
",",
"paths",
")",
":",
"for",
"path",
"in",
"paths",
":",
"full_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"base_dir",
",",
"path",
")",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"full_path",
")",
":",
"if",
"os",
".",
"path",
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"isdir",
"(",
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")",
":",
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"dirpath",
",",
"_",
",",
"filenames",
"in",
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"walk",
"(",
"full_path",
")",
":",
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":",
"yield",
"os",
".",
"path",
".",
"join",
"(",
"dirpath",
",",
"filename",
")",
"else",
":",
"# Assume is file.",
"yield",
"full_path",
"else",
":",
"logging",
".",
"critical",
"(",
"'Not found: %s'",
",",
"path",
")"
] |
https://github.com/klzgrad/naiveproxy/blob/ed2c513637c77b18721fe428d7ed395b4d284c83/src/build/lacros/lacros_resource_sizes.py#L118-L137
|
||
miyosuda/TensorFlowAndroidDemo
|
35903e0221aa5f109ea2dbef27f20b52e317f42d
|
jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/estimator.py
|
python
|
BaseEstimator._get_train_ops
|
(self, features, targets)
|
Method that builds model graph and returns trainer ops.
Expected to be overriden by sub-classes that require custom support.
Args:
features: `Tensor` or `dict` of `Tensor` objects.
targets: `Tensor` or `dict` of `Tensor` objects.
Returns:
Tuple of train `Operation` and loss `Tensor`.
|
Method that builds model graph and returns trainer ops.
|
[
"Method",
"that",
"builds",
"model",
"graph",
"and",
"returns",
"trainer",
"ops",
"."
] |
def _get_train_ops(self, features, targets):
"""Method that builds model graph and returns trainer ops.
Expected to be overriden by sub-classes that require custom support.
Args:
features: `Tensor` or `dict` of `Tensor` objects.
targets: `Tensor` or `dict` of `Tensor` objects.
Returns:
Tuple of train `Operation` and loss `Tensor`.
"""
pass
|
[
"def",
"_get_train_ops",
"(",
"self",
",",
"features",
",",
"targets",
")",
":",
"pass"
] |
https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/estimator.py#L351-L363
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/msw/_misc.py
|
python
|
DateTime.SetToNextWeekDay
|
(*args, **kwargs)
|
return _misc_.DateTime_SetToNextWeekDay(*args, **kwargs)
|
SetToNextWeekDay(self, int weekday) -> DateTime
|
SetToNextWeekDay(self, int weekday) -> DateTime
|
[
"SetToNextWeekDay",
"(",
"self",
"int",
"weekday",
")",
"-",
">",
"DateTime"
] |
def SetToNextWeekDay(*args, **kwargs):
"""SetToNextWeekDay(self, int weekday) -> DateTime"""
return _misc_.DateTime_SetToNextWeekDay(*args, **kwargs)
|
[
"def",
"SetToNextWeekDay",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_misc_",
".",
"DateTime_SetToNextWeekDay",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_misc.py#L3853-L3855
|
|
microsoft/TSS.MSR
|
0f2516fca2cd9929c31d5450e39301c9bde43688
|
TSS.Py/src/TpmTypes.py
|
python
|
TPM2_CertifyCreation_REQUEST.fromTpm
|
(buf)
|
return buf.createObj(TPM2_CertifyCreation_REQUEST)
|
Returns new TPM2_CertifyCreation_REQUEST object constructed from its
marshaled representation in the given TpmBuffer buffer
|
Returns new TPM2_CertifyCreation_REQUEST object constructed from its
marshaled representation in the given TpmBuffer buffer
|
[
"Returns",
"new",
"TPM2_CertifyCreation_REQUEST",
"object",
"constructed",
"from",
"its",
"marshaled",
"representation",
"in",
"the",
"given",
"TpmBuffer",
"buffer"
] |
def fromTpm(buf):
""" Returns new TPM2_CertifyCreation_REQUEST object constructed from its
marshaled representation in the given TpmBuffer buffer
"""
return buf.createObj(TPM2_CertifyCreation_REQUEST)
|
[
"def",
"fromTpm",
"(",
"buf",
")",
":",
"return",
"buf",
".",
"createObj",
"(",
"TPM2_CertifyCreation_REQUEST",
")"
] |
https://github.com/microsoft/TSS.MSR/blob/0f2516fca2cd9929c31d5450e39301c9bde43688/TSS.Py/src/TpmTypes.py#L12563-L12567
|
|
etotheipi/BitcoinArmory
|
2a6fc5355bb0c6fe26e387ccba30a5baafe8cd98
|
qt4reactor.py
|
python
|
QtEventReactor.iterate
|
(self, delay=None)
|
See twisted.internet.interfaces.IReactorCore.iterate.
|
See twisted.internet.interfaces.IReactorCore.iterate.
|
[
"See",
"twisted",
".",
"internet",
".",
"interfaces",
".",
"IReactorCore",
".",
"iterate",
"."
] |
def iterate(self, delay=None):
"""See twisted.internet.interfaces.IReactorCore.iterate.
"""
self.runUntilCurrent()
self.doEvents()
self.doIteration(delay)
|
[
"def",
"iterate",
"(",
"self",
",",
"delay",
"=",
"None",
")",
":",
"self",
".",
"runUntilCurrent",
"(",
")",
"self",
".",
"doEvents",
"(",
")",
"self",
".",
"doIteration",
"(",
"delay",
")"
] |
https://github.com/etotheipi/BitcoinArmory/blob/2a6fc5355bb0c6fe26e387ccba30a5baafe8cd98/qt4reactor.py#L326-L331
|
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