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qgis/QGIS | 15a77662d4bb712184f6aa60d0bd663010a76a75 | python/plugins/db_manager/db_plugins/postgis/connector.py | python | PostGisDBConnector.renamesSchema | (self, schema, new_schema) | Renames a schema in database | Renames a schema in database | [
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] | def renamesSchema(self, schema, new_schema):
"""Renames a schema in database """
sql = u"ALTER SCHEMA %s RENAME TO %s" % (self.quoteId(schema), self.quoteId(new_schema))
self._execute_and_commit(sql) | [
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JumpingYang001/webrtc | c03d6e965e1f54aeadd670e491eabe5fdb8db968 | tools_webrtc/vim/webrtc.ycm_extra_conf.py | python | GetClangOptionsFromNinjaForFilename | (webrtc_root, filename) | return GetClangOptionsFromCommandLine(clang_line, out_dir,
additional_flags) | Returns the Clang command line options needed for building |filename|.
Command line options are based on the command used by ninja for building
|filename|. If |filename| is a .h file, uses its companion .cc or .cpp file.
If a suitable companion file can't be located or if ninja doesn't know about
|filename|, then uses default source files in WebRTC for determining the
commandline.
Args:
webrtc_root: (String) Path to src/.
filename: (String) Absolute path to source file being edited.
Returns:
(List of Strings) The list of command line flags for this source file. Can
be empty. | Returns the Clang command line options needed for building |filename|. | [
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] | def GetClangOptionsFromNinjaForFilename(webrtc_root, filename):
"""Returns the Clang command line options needed for building |filename|.
Command line options are based on the command used by ninja for building
|filename|. If |filename| is a .h file, uses its companion .cc or .cpp file.
If a suitable companion file can't be located or if ninja doesn't know about
|filename|, then uses default source files in WebRTC for determining the
commandline.
Args:
webrtc_root: (String) Path to src/.
filename: (String) Absolute path to source file being edited.
Returns:
(List of Strings) The list of command line flags for this source file. Can
be empty.
"""
if not webrtc_root:
return []
# Generally, everyone benefits from including WebRTC's src/, because all of
# WebRTC's includes are relative to that.
additional_flags = ['-I' + os.path.join(webrtc_root)]
# Version of Clang used to compile WebRTC can be newer then version of
# libclang that YCM uses for completion. So it's possible that YCM's libclang
# doesn't know about some used warning options, which causes compilation
# warnings (and errors, because of '-Werror');
additional_flags.append('-Wno-unknown-warning-option')
sys.path.append(os.path.join(webrtc_root, 'tools', 'vim'))
from ninja_output import GetNinjaOutputDirectory
out_dir = GetNinjaOutputDirectory(webrtc_root)
basename, extension = os.path.splitext(filename)
if extension == '.h':
candidates = [basename + ext for ext in _HEADER_ALTERNATES]
else:
candidates = [filename]
clang_line = None
buildable_extension = extension
for candidate in candidates:
clang_line = GetClangCommandLineFromNinjaForSource(out_dir, candidate)
if clang_line:
buildable_extension = os.path.splitext(candidate)[1]
break
additional_flags += _EXTENSION_FLAGS.get(buildable_extension, [])
if not clang_line:
# If ninja didn't know about filename or it's companion files, then try a
# default build target. It is possible that the file is new, or build.ninja
# is stale.
clang_line = GetClangCommandLineFromNinjaForSource(
out_dir, GetDefaultSourceFile(webrtc_root, filename))
if not clang_line:
return additional_flags
return GetClangOptionsFromCommandLine(clang_line, out_dir,
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smilehao/xlua-framework | a03801538be2b0e92d39332d445b22caca1ef61f | ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/build/lib/google/protobuf/descriptor.py | python | ServiceDescriptor.CopyToProto | (self, proto) | Copies this to a descriptor_pb2.ServiceDescriptorProto.
Args:
proto: An empty descriptor_pb2.ServiceDescriptorProto. | Copies this to a descriptor_pb2.ServiceDescriptorProto. | [
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] | def CopyToProto(self, proto):
"""Copies this to a descriptor_pb2.ServiceDescriptorProto.
Args:
proto: An empty descriptor_pb2.ServiceDescriptorProto.
"""
# This function is overriden to give a better doc comment.
super(ServiceDescriptor, self).CopyToProto(proto) | [
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/debug/lib/debug_data.py | python | DebugDumpDir.run_feed_keys_info | (self) | return output[0] if len(output) == 1 else output | Get a str representation of the feed_dict used in the Session.run() call.
Returns:
If the information is available from one `Session.run` call, a `str`
obtained from `repr(feed_dict)`.
If the information is available from multiple `Session.run` calls, a
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"""Get a str representation of the feed_dict used in the Session.run() call.
Returns:
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obtained from `repr(feed_dict)`.
If the information is available from multiple `Session.run` calls, a
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"""
output = self._run_feed_keys_info
return output[0] if len(output) == 1 else output | [
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moderngl/moderngl | 32fe79927e02b0fa893b3603d677bdae39771e14 | moderngl/program.py | python | Program.__getitem__ | (self, key) | return self._members[key] | Get a member such as uniforms, uniform blocks, subroutines,
attributes and varyings by name.
.. code-block:: python
# Get a uniform
uniform = program['color']
# Uniform values can be set on the returned object
# or the `__setitem__` shortcut can be used.
program['color'].value = 1.0, 1.0, 1.0, 1.0
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] | def __getitem__(self, key) -> Union[Uniform, UniformBlock, Subroutine, Attribute, Varying]:
"""Get a member such as uniforms, uniform blocks, subroutines,
attributes and varyings by name.
.. code-block:: python
# Get a uniform
uniform = program['color']
# Uniform values can be set on the returned object
# or the `__setitem__` shortcut can be used.
program['color'].value = 1.0, 1.0, 1.0, 1.0
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return self._members[key] | [
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facebookresearch/habitat-sim | 63b6c71d9ca8adaefb140b198196f5d0ca1f1e34 | src_python/habitat_sim/registry.py | python | _Registry.get_pose_extractor | (cls, name: str) | return cls._get_impl("pose_extractor", name) | r"""Retrieve the pose_extractor registered under ``name``
:param name: The name provided to `register_pose_extractor` | r"""Retrieve the pose_extractor registered under ``name`` | [
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r"""Retrieve the pose_extractor registered under ``name``
:param name: The name provided to `register_pose_extractor`
"""
return cls._get_impl("pose_extractor", name) | [
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trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/seacas/scripts/exomerge2.py | python | ExodusModel.rename_element_block | (self, element_block_id, new_element_block_id) | Change an element block id or name.
This function can be used to change either the element block id or
name. If 'new_element_block_id' is an integer, it will change the id.
If it is a string, it will change the name.
Example:
>>> model.rename_element_block(1, 100)
>>> model.rename_element_block(1, 'block_1') | Change an element block id or name. | [
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"""
Change an element block id or name.
This function can be used to change either the element block id or
name. If 'new_element_block_id' is an integer, it will change the id.
If it is a string, it will change the name.
Example:
>>> model.rename_element_block(1, 100)
>>> model.rename_element_block(1, 'block_1')
"""
[element_block_id] = self._format_element_block_id_list(
[element_block_id],
single=True)
# if we're just changing the name
if type(new_element_block_id) is str:
# if the same name already, just exit
if (self.element_blocks[element_block_id][0] ==
new_element_block_id):
return
# if the name already exists, issue a warning
if self.element_block_exists(new_element_block_id):
self._exists_warning('"' + new_element_block_id + '"',
'element block')
# rename it
self.element_blocks[
element_block_id][0] = new_element_block_id
return
assert type(new_element_block_id) is int
# rename the block
self._rename_entity('element block',
element_block_id,
new_element_block_id,
self.get_element_block_ids,
self.element_blocks)
# adjust side sets
for side_set_id in self.get_side_set_ids():
members = self.get_side_set_members(side_set_id)
new_members = []
for member in members:
if member[0] == element_block_id:
member = list(member)
member[0] = new_element_block_id
member = tuple(member)
new_members.append(member)
members[:] = new_members | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/dashboard/dashboard/start_try_job.py | python | _CanDownloadBuilds | (master_name) | return master_name.startswith('ChromiumPerf') | Checks whether bisecting using archives is supported. | Checks whether bisecting using archives is supported. | [
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"""Checks whether bisecting using archives is supported."""
return master_name.startswith('ChromiumPerf') | [
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apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | scripts/Python/static-binding/lldb.py | python | SBAddress.__get_load_addr_property__ | (self) | return self.GetLoadAddress (target) | Get the load address for a lldb.SBAddress using the current target. | Get the load address for a lldb.SBAddress using the current target. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/groupby/ops.py | python | BaseGrouper.groups | (self) | dict {group name -> group labels} | dict {group name -> group labels} | [
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to_groupby = zip(*(ping.grouping_vector for ping in self.groupings))
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facebookarchive/LogDevice | ce7726050edc49a1e15d9160e81c890736b779e2 | build/fbcode_builder/getdeps/builder.py | python | CargoBuilder._resolve_crate_to_path | (crate, git_conf) | Tries to find <crate> in git_conf["inst_dir"] by searching a [package]
keyword followed by name = "<crate>". | Tries to find <crate> in git_conf["inst_dir"] by searching a [package]
keyword followed by name = "<crate>". | [
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"""
source_dir = git_conf["source_dir"]
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moflow/moflow | 2dfb27c799c90c6caf1477508eca3eec616ef7d2 | bap/libtracewrap/libtrace/protobuf/python/mox.py | python | MockAnything.__getattr__ | (self, method_name) | return self._CreateMockMethod(method_name) | Intercept method calls on this object.
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Args:
# method name: the name of the method being called.
method_name: str
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"""Intercept method calls on this object.
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state (record or replay). The call will be recorded or replayed
by the MockMethod's __call__.
Args:
# method name: the name of the method being called.
method_name: str
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/_extends/parse/standard_method.py | python | ms_len | (data) | return data.__len__() | Implementation of `len`. | Implementation of `len`. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/importlib-metadata/py3/importlib_metadata/_meta.py | python | PackageMetadata.get_all | (self, name: str, failobj: _T = ...) | Return all values associated with a possibly multi-valued key. | Return all values associated with a possibly multi-valued key. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | GBSpan.__eq__ | (*args, **kwargs) | return _core_.GBSpan___eq__(*args, **kwargs) | __eq__(self, PyObject other) -> bool
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/nn_ops.py | python | softmax_v2 | (logits, axis=None, name=None) | return _wrap_2d_function(logits, gen_nn_ops.softmax, axis, name) | Computes softmax activations.
Used for multi-class predictions. The sum of all outputs generated by softmax
is 1.
This function performs the equivalent of
```python
softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis, keepdims=True)
```
Example usage:
>>> softmax = tf.nn.softmax([-1, 0., 1.])
>>> softmax
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numpy=array([0.09003057, 0.24472848, 0.66524094], dtype=float32)>
>>> sum(softmax)
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Args:
logits: A non-empty `Tensor`. Must be one of the following types: `half`,
`float32`, `float64`.
axis: The dimension softmax would be performed on. The default is -1 which
indicates the last dimension.
name: A name for the operation (optional).
Returns:
A `Tensor`. Has the same type and shape as `logits`.
Raises:
InvalidArgumentError: if `logits` is empty or `axis` is beyond the last
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"""Computes softmax activations.
Used for multi-class predictions. The sum of all outputs generated by softmax
is 1.
This function performs the equivalent of
```python
softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis, keepdims=True)
```
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name: A name for the operation (optional).
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A `Tensor`. Has the same type and shape as `logits`.
Raises:
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"""
if axis is None:
axis = -1
return _wrap_2d_function(logits, gen_nn_ops.softmax, axis, name) | [
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domino-team/openwrt-cc | 8b181297c34d14d3ca521cc9f31430d561dbc688 | package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/tools/gyp/pylib/gyp/input.py | python | TurnIntIntoStrInList | (the_list) | Given list the_list, recursively converts all integers into strings. | Given list the_list, recursively converts all integers into strings. | [
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"""
for index in xrange(0, len(the_list)):
item = the_list[index]
if type(item) is int:
the_list[index] = str(item)
elif type(item) is dict:
TurnIntIntoStrInDict(item)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/customtreectrl.py | python | CustomTreeCtrl.GetItemType | (self, item) | return item.GetType() | Returns the item type.
:param `item`: an instance of :class:`GenericTreeItem`.
:return: An integer representing the item type.
:see: :meth:`~CustomTreeCtrl.SetItemType` for a description of valid item types. | Returns the item type. | [
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Returns the item type.
:param `item`: an instance of :class:`GenericTreeItem`.
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:see: :meth:`~CustomTreeCtrl.SetItemType` for a description of valid item types.
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livecode/livecode | 4606a10ea10b16d5071d0f9f263ccdd7ede8b31d | gyp/pylib/gyp/generator/analyzer.py | python | _AddBuildTargets | (target, roots, add_if_no_ancestor, result) | Recurses through all targets that depend on |target|, adding all targets
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roots: set of root targets.
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return
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target.in_roots = not target.back_deps and target in roots
for back_dep_target in target.back_deps:
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target.added_to_compile_targets |= back_dep_target.added_to_compile_targets
target.in_roots |= back_dep_target.in_roots
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result.add(target)
target.added_to_compile_targets = True | [
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bh107/bohrium | 5b83e7117285fefc7779ed0e9acb0f8e74c7e068 | bridge/npbackend/bohrium/summations.py | python | argmax | (a, axis=None, out=None) | Returns the indices of the maximum values along an axis.
Parameters
----------
a : array_like
Input array.
axis : int, optional
By default, the index is into the flattened array, otherwise
along the specified axis.
out : array, optional
If provided, the result will be inserted into this array. It should
be of the appropriate shape and dtype.
Returns
-------
index_array : ndarray of ints
Array of indices into the array. It has the same shape as `a.shape`
with the dimension along `axis` removed.
See Also
--------
ndarray.argmax, argmin
amax : The maximum value along a given axis.
unravel_index : Convert a flat index into an index tuple.
Notes
-----
In case of multiple occurrences of the maximum values, the indices
corresponding to the first occurrence are returned.
Examples
--------
>>> a = np.arange(6).reshape(2,3)
>>> a
array([[0, 1, 2],
[3, 4, 5]])
>>> np.argmax(a)
5
>>> np.argmax(a, axis=0)
array([1, 1, 1])
>>> np.argmax(a, axis=1)
array([2, 2])
>>> b = np.arange(6)
>>> b[1] = 5
>>> b
array([0, 5, 2, 3, 4, 5])
>>> np.argmax(b) # Only the first occurrence is returned.
1 | Returns the indices of the maximum values along an axis.
Parameters
----------
a : array_like
Input array.
axis : int, optional
By default, the index is into the flattened array, otherwise
along the specified axis.
out : array, optional
If provided, the result will be inserted into this array. It should
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Returns
-------
index_array : ndarray of ints
Array of indices into the array. It has the same shape as `a.shape`
with the dimension along `axis` removed.
See Also
--------
ndarray.argmax, argmin
amax : The maximum value along a given axis.
unravel_index : Convert a flat index into an index tuple.
Notes
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In case of multiple occurrences of the maximum values, the indices
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Examples
--------
>>> a = np.arange(6).reshape(2,3)
>>> a
array([[0, 1, 2],
[3, 4, 5]])
>>> np.argmax(a)
5
>>> np.argmax(a, axis=0)
array([1, 1, 1])
>>> np.argmax(a, axis=1)
array([2, 2])
>>> b = np.arange(6)
>>> b[1] = 5
>>> b
array([0, 5, 2, 3, 4, 5])
>>> np.argmax(b) # Only the first occurrence is returned.
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"""
Returns the indices of the maximum values along an axis.
Parameters
----------
a : array_like
Input array.
axis : int, optional
By default, the index is into the flattened array, otherwise
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out : array, optional
If provided, the result will be inserted into this array. It should
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Returns
-------
index_array : ndarray of ints
Array of indices into the array. It has the same shape as `a.shape`
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See Also
--------
ndarray.argmax, argmin
amax : The maximum value along a given axis.
unravel_index : Convert a flat index into an index tuple.
Notes
-----
In case of multiple occurrences of the maximum values, the indices
corresponding to the first occurrence are returned.
Examples
--------
>>> a = np.arange(6).reshape(2,3)
>>> a
array([[0, 1, 2],
[3, 4, 5]])
>>> np.argmax(a)
5
>>> np.argmax(a, axis=0)
array([1, 1, 1])
>>> np.argmax(a, axis=1)
array([2, 2])
>>> b = np.arange(6)
>>> b[1] = 5
>>> b
array([0, 5, 2, 3, 4, 5])
>>> np.argmax(b) # Only the first occurrence is returned.
1
"""
if not bhary.check(a):
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ret = reorganization.flatnonzero(a == max(a))[0]
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warnings.warn("Bohrium does not support the 'axis' argument, "
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return numpy.argmax(a.copy2numpy(), axis=axis)
if out is None:
return ret
else:
out[...] = ret
return out | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tkinter/__init__.py | python | Text.window_names | (self) | return self.tk.splitlist(
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/io/netcdf.py | python | netcdf_file.flush | (self) | Perform a sync-to-disk flush if the `netcdf_file` object is in write mode.
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/linalg/_interpolative_backend.py | python | idz_diffsnorm | (m, n, matveca, matveca2, matvec, matvec2, its=20) | return _id.idz_diffsnorm(m, n, matveca, matveca2, matvec, matvec2, its) | Estimate spectral norm of the difference of two complex matrices by the
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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/adapters.py | python | HTTPAdapter.add_headers | (self, request, **kwargs) | Add any headers needed by the connection. As of v2.0 this does
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apache/trafodion | 8455c839ad6b6d7b6e04edda5715053095b78046 | core/sqf/src/seatrans/hbase-trx/src/main/python/thrift1/gen-py/hbase/Hbase.py | python | Iface.scannerGetList | (self, id, nbRows) | Returns, starting at the scanner's current row value nbRows worth of
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martinmoene/span-lite | 8f7935ff4e502ee023990d356d6578b8293eda74 | script/create-vcpkg.py | python | portfile_path | ( args ) | return tpl_path_vcpkg_portfile.format( vcpkg=args.vcpkg_root, prj=args.project ) | Create path like vcpks/ports/_project_/portfile.cmake | Create path like vcpks/ports/_project_/portfile.cmake | [
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google/llvm-propeller | 45c226984fe8377ebfb2ad7713c680d652ba678d | clang/bindings/python/clang/cindex.py | python | TranslationUnit.get_file | (self, filename) | return File.from_name(self, filename) | Obtain a File from this translation unit. | Obtain a File from this translation unit. | [
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idaholab/moose | 9eeebc65e098b4c30f8205fb41591fd5b61eb6ff | modules/thermal_hydraulics/python/peacock/UnitConversion.py | python | Unit.to | (self, value) | return None | Convert the 'value' from the common base unit into my unit
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/internals/blocks.py | python | Block._interpolate_with_fill | (
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/internals/blocks.py#L1173-L1211 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | CommandLinkButton.SetMainLabel | (*args, **kwargs) | return _controls_.CommandLinkButton_SetMainLabel(*args, **kwargs) | SetMainLabel(self, String mainLabel) | SetMainLabel(self, String mainLabel) | [
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"""SetMainLabel(self, String mainLabel)"""
return _controls_.CommandLinkButton_SetMainLabel(*args, **kwargs) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/ttk.py | python | Notebook.add | (self, child, **kw) | Adds a new tab to the notebook.
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"""Adds a new tab to the notebook.
If window is currently managed by the notebook but hidden, it is
restored to its previous position."""
self.tk.call(self._w, "add", child, *(_format_optdict(kw))) | [
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | samples/networking/05-small-chat/AIRepository.py | python | AIRepository.deallocateChannel | (self, doID) | This method will be called whenever a client disconnects from the
server. The given doID is the ID of the client who left us. | This method will be called whenever a client disconnects from the
server. The given doID is the ID of the client who left us. | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_aarch64/python2.7/dist-packages/rosdep2/gbpdistro_support.py | python | get_owner_name | (url) | return result | Given a gbpdistro url, returns the name of the github user in the url.
If the url is not a valid github url it returns the default `ros`.
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"""
Given a gbpdistro url, returns the name of the github user in the url.
If the url is not a valid github url it returns the default `ros`.
This information is used to set the homebrew tap name, see:
https://github.com/ros-infrastructure/rosdep/pull/17
:returns: The github account in the given gbpdistro url
"""
result = 'ros'
try:
parsed = urlparse.urlparse(url)
if parsed.netloc == 'github.com':
result = parsed.path.split('/')[1]
except (ValueError, IndexError):
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return result | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/math/so3.py | python | cross_product | (w : Vector3) | return [0.,w[2],-w[1], -w[2],0.,w[0], w[1],-w[0],0.] | Returns the cross product matrix associated with w.
The matrix [w]R is the derivative of the matrix R as it rotates about
the axis w/||w|| with angular velocity ||w||. | Returns the cross product matrix associated with w. | [
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"""Returns the cross product matrix associated with w.
The matrix [w]R is the derivative of the matrix R as it rotates about
the axis w/||w|| with angular velocity ||w||.
"""
return [0.,w[2],-w[1], -w[2],0.,w[0], w[1],-w[0],0.] | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/third_party/pyserial/serial/sermsdos.py | python | Serial.getCD | (self) | Eead terminal status line | Eead terminal status line | [
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"""Eead terminal status line"""
raise NotImplementedError | [
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mavlink/MAVSDK | 42a7b2c96d55a72342c6d1657c101b557b5a0f94 | tools/generate_markdown_from_doxygen_xml.py | python | cppEnum.markdown | (self,aDisplayInclude=False) | return output_string | Markdown for the enum, with details | Markdown for the enum, with details | [
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"""
Markdown for the enum, with details
"""
output_string=''
output_string+='\n\n### enum %s {#%s}\n' % (self.name,self.id)
if aDisplayInclude:
output_string+='\n```\n#include: %s\n```\n' % (self.location)
output_string+='\n\n%s' % markdown_any_tag(self.briefdescription).strip()
output_string+='\n\n%s' % markdown_any_tag(self.detaileddescription).strip()
if len(self.enum_values)>0:
output_string+='\n\nValue | Description\n--- | ---'
for enum_value in self.enum_values:
output_string+='\n<span id="%s"></span> `%s` | %s %s' % (enum_value.id,enum_value.name, markdown_any_tag(enum_value.briefdescription).strip(),markdown_any_tag(enum_value.detaileddescription).strip())
if len(self.seealso)>0:
output_string+=self.seealso
if args.debug:
output_string+='\n\n'
output_string+='<!-- inbodydescription: %s --> \n' % markdown_any_tag(self.inbodydescription).strip()
output_string+='<!-- prot: %s -->\n' % self.prot
output_string+='<!-- static: %s -->\n' % self.static
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/reduction/instruments/sans/sans_reduction_steps.py | python | Mask.add_detector_list | (self, det_list) | Mask the given detectors
@param det_list: list of detector IDs | Mask the given detectors | [
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"given",
"detectors"
] | def add_detector_list(self, det_list):
"""
Mask the given detectors
@param det_list: list of detector IDs
"""
self.detect_list.extend(det_list) | [
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SpenceKonde/megaTinyCore | 1c4a70b18a149fe6bcb551dfa6db11ca50b8997b | megaavr/tools/libs/appdirs.py | python | user_state_dir | (appname=None, appauthor=None, version=None, roaming=False) | return path | r"""Return full path to the user-specific state dir for this application.
"appname" is the name of application.
If None, just the system directory is returned.
"appauthor" (only used on Windows) is the name of the
appauthor or distributing body for this application. Typically
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sync'd on login. See
<http://technet.microsoft.com/en-us/library/cc766489(WS.10).aspx>
for a discussion of issues.
Typical user state directories are:
Mac OS X: same as user_data_dir
Unix: ~/.local/state/<AppName> # or in $XDG_STATE_HOME, if defined
Win *: same as user_data_dir
For Unix, we follow this Debian proposal <https://wiki.debian.org/XDGBaseDirectorySpecification#state>
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r"""Return full path to the user-specific state dir for this application.
"appname" is the name of application.
If None, just the system directory is returned.
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"""
if system in ["win32", "darwin"]:
path = user_data_dir(appname, appauthor, None, roaming)
else:
path = os.getenv('XDG_STATE_HOME', os.path.expanduser("~/.local/state"))
if appname:
path = os.path.join(path, appname)
if appname and version:
path = os.path.join(path, version)
return path | [
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rdkit/rdkit | ede860ae316d12d8568daf5ee800921c3389c84e | rdkit/DataStructs/TopNContainer.py | python | TopNContainer.GetPts | (self) | return self.best | returns our set of points | returns our set of points | [
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""" returns our set of points """
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generalized-intelligence/GAAS | 29ab17d3e8a4ba18edef3a57c36d8db6329fac73 | deprecated/algorithms/sfm/OpenSfM/opensfm/dataset.py | python | DataSet.open_image_file | (self, image) | return open(self._image_file(image), 'rb') | Open image file and return file object. | Open image file and return file object. | [
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"""Open image file and return file object."""
return open(self._image_file(image), 'rb') | [
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ideawu/ssdb-rocks | a3cbb322cafb2f493252829c608e2239df98c9ac | deps/rocksdb-master/linters/cpp_linter/cpplint.py | python | Search | (pattern, s) | return _regexp_compile_cache[pattern].search(s) | Searches the string for the pattern, caching the compiled regexp. | Searches the string for the pattern, caching the compiled regexp. | [
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] | def Search(pattern, s):
"""Searches the string for the pattern, caching the compiled regexp."""
if pattern not in _regexp_compile_cache:
_regexp_compile_cache[pattern] = sre_compile.compile(pattern)
return _regexp_compile_cache[pattern].search(s) | [
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sfzhang15/FaceBoxes | b52cc92f9362d3adc08d54666aeb9ebb62fdb7da | python/caffe/pycaffe.py | python | _Net_blobs | (self) | return self._blobs_dict | An OrderedDict (bottom to top, i.e., input to output) of network
blobs indexed by name | An OrderedDict (bottom to top, i.e., input to output) of network
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"""
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"""
if not hasattr(self, '_blobs_dict'):
self._blobs_dict = OrderedDict(zip(self._blob_names, self._blobs))
return self._blobs_dict | [
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msftguy/ssh-rd | a5f3a79daeac5844edebf01916c9613563f1c390 | _3rd/boost_1_48_0/tools/build/v2/build/property_set.py | python | empty | () | return create () | Returns PropertySet with empty set of properties. | Returns PropertySet with empty set of properties. | [
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lrjconan/GRAN | 43cb4433e6f69401c3a4a6e946ea75da6ec35d72 | model/gran_mixture_bernoulli.py | python | GRANMixtureBernoulli._inference | (self,
A_pad=None,
edges=None,
node_idx_gnn=None,
node_idx_feat=None,
att_idx=None) | return log_theta, log_alpha | generate adj in row-wise auto-regressive fashion | generate adj in row-wise auto-regressive fashion | [
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node_idx_gnn=None,
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""" generate adj in row-wise auto-regressive fashion """
B, C, N_max, _ = A_pad.shape
H = self.hidden_dim
K = self.block_size
A_pad = A_pad.view(B * C * N_max, -1)
if self.dimension_reduce:
node_feat = self.decoder_input(A_pad) # BCN_max X H
else:
node_feat = A_pad # BCN_max X N_max
### GNN inference
# pad zero as node feature for newly generated nodes (1st row)
node_feat = F.pad(
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att_idx = att_idx.view(-1, 1)
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idx_new_node = (att_idx[[edges[:, 0]]] >
0).long() + (att_idx[[edges[:, 1]]] > 0).long()
idx_new_node = idx_new_node.byte().squeeze()
att_edge_feat[idx_new_node, :] = torch.randn(
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att_edge_feat.shape[1]).to(node_feat.device)
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# create one-hot feature
att_edge_feat = torch.zeros(edges.shape[0],
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# scatter with empty index seems to cause problem on CPU but not on GPU
att_edge_feat = att_edge_feat.scatter(1, att_idx[[edges[:, 0]]], 1)
att_edge_feat = att_edge_feat.scatter(
1, att_idx[[edges[:, 1]]] + self.att_edge_dim, 1)
# GNN inference
# N.B.: node_feat is shared by multiple subgraphs within the same batch
node_state = self.decoder(
node_feat[node_idx_feat], edges, edge_feat=att_edge_feat)
### Pairwise predict edges
diff = node_state[node_idx_gnn[:, 0], :] - node_state[node_idx_gnn[:, 1], :]
log_theta = self.output_theta(diff) # B X (tt+K)K
log_alpha = self.output_alpha(diff) # B X (tt+K)K
log_theta = log_theta.view(-1, self.num_mix_component) # B X CN(N-1)/2 X K
log_alpha = log_alpha.view(-1, self.num_mix_component) # B X CN(N-1)/2 X K
return log_theta, log_alpha | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/lib/format.py | python | read_array_header_1_0 | (fp) | return _read_array_header(fp, version=(1, 0)) | Read an array header from a filelike object using the 1.0 file format
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/framework/ops.py | python | RegisterShape.__call__ | (self, f) | return f | Registers "f" as the shape function for "op_type". | Registers "f" as the shape function for "op_type". | [
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hpi-xnor/BMXNet | ed0b201da6667887222b8e4b5f997c4f6b61943d | python/mxnet/executor_manager.py | python | DataParallelExecutorGroup.backward | (self) | Perform a backward pass on each executor. | Perform a backward pass on each executor. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_windows.py | python | Dialog_SetLayoutAdapter | (*args, **kwargs) | return _windows_.Dialog_SetLayoutAdapter(*args, **kwargs) | Dialog_SetLayoutAdapter(DialogLayoutAdapter adapter) -> DialogLayoutAdapter | Dialog_SetLayoutAdapter(DialogLayoutAdapter adapter) -> DialogLayoutAdapter | [
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cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | FWCore/ParameterSet/python/SequenceTypes.py | python | _ModuleSequenceType.dumpPython | (self, options=PrintOptions()) | return s + "\n" | Returns a string which is the python representation of the object | Returns a string which is the python representation of the object | [
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devpack/android-python27 | d42dd67565e104cf7b0b50eb473f615db3e69901 | python-build-with-qt/sip-4.11.2/sipconfig.py | python | Makefile.generate_target_default | (self, mfile) | The default implementation of the default target.
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/telemetry/third_party/web-page-replay/third_party/ipaddr/ipaddr.py | python | _BaseNet.overlaps | (self, other) | return self.network in other or self.broadcast in other or (
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_gdi.py | python | FontMapper_GetDefaultConfigPath | (*args) | return _gdi_.FontMapper_GetDefaultConfigPath(*args) | FontMapper_GetDefaultConfigPath() -> String | FontMapper_GetDefaultConfigPath() -> String | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | chrome/tools/webforms_aggregator.py | python | Crawler.__init__ | (self, url, logging_level=None) | Init crawler URL, links lists, logger, and creates a cookie temp file.
The cookie temp file is needed for session cookies.
Args:
url: the initial "seed" url of the site.
logging_level: the desired verbosity level, default is None. | Init crawler URL, links lists, logger, and creates a cookie temp file. | [
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"""Init crawler URL, links lists, logger, and creates a cookie temp file.
The cookie temp file is needed for session cookies.
Args:
url: the initial "seed" url of the site.
logging_level: the desired verbosity level, default is None.
"""
if logging_level:
self.logger.setLevel(logging_level)
self.url_error = False
url_parsed = urlparse.urlparse(url)
if not url_parsed[0].startswith('http'):
self.logger.error(
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self.url_error = True
return
# Example: if url is 'http://www.example.com?name=john' then value [1] or
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if not url_parsed[1]:
self.logger.error('Error: "%s" is not a valid url', url)
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return
self._url = url
self._domain = ''
# Http links that contain a clue from LINK_CLUES.
self._clues_general_links = []
# Http links that do not contain any clue from LINK_CLUES.
self._general_links = []
# Https links that contain a clue from LINK_CLUES.
self._clues_secure_links = []
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self._secure_links = []
# All links downloaded and parsed so far.
self._links_visited = []
self._retrievers_list = []
self._cookie_file = tempfile.NamedTemporaryFile(
suffix='.cookie', delete=False)
self._cookie_file.close()
self._cookie_file = self._cookie_file.name | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/dtypes/common.py | python | is_string_dtype | (arr_or_dtype) | return _is_dtype(arr_or_dtype, condition) | Check whether the provided array or dtype is of the string dtype.
Parameters
----------
arr_or_dtype : array-like
The array or dtype to check.
Returns
-------
boolean
Whether or not the array or dtype is of the string dtype.
Examples
--------
>>> is_string_dtype(str)
True
>>> is_string_dtype(object)
True
>>> is_string_dtype(int)
False
>>>
>>> is_string_dtype(np.array(['a', 'b']))
True
>>> is_string_dtype(pd.Series([1, 2]))
False | Check whether the provided array or dtype is of the string dtype. | [
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] | def is_string_dtype(arr_or_dtype) -> bool:
"""
Check whether the provided array or dtype is of the string dtype.
Parameters
----------
arr_or_dtype : array-like
The array or dtype to check.
Returns
-------
boolean
Whether or not the array or dtype is of the string dtype.
Examples
--------
>>> is_string_dtype(str)
True
>>> is_string_dtype(object)
True
>>> is_string_dtype(int)
False
>>>
>>> is_string_dtype(np.array(['a', 'b']))
True
>>> is_string_dtype(pd.Series([1, 2]))
False
"""
# TODO: gh-15585: consider making the checks stricter.
def condition(dtype) -> bool:
return dtype.kind in ("O", "S", "U") and not is_excluded_dtype(dtype)
def is_excluded_dtype(dtype) -> bool:
"""
These have kind = "O" but aren't string dtypes so need to be explicitly excluded
"""
is_excluded_checks = (is_period_dtype, is_interval_dtype)
return any(is_excluded(dtype) for is_excluded in is_excluded_checks)
return _is_dtype(arr_or_dtype, condition) | [
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intel-iot-devkit/how-to-code-samples | b4ea616f36bbfa2e042beb1698f968cfd651d79f | smart-stove-top/python/iot_smart_stove_top/scheduler.py | python | ms | (mills) | return mills * 0.001 | Converts milliseconds to seconds | Converts milliseconds to seconds | [
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"""
Converts milliseconds to seconds
"""
return mills * 0.001 | [
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hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/module/base_module.py | python | BaseModule.iter_predict | (self, eval_data, num_batch=None, reset=True, sparse_row_id_fn=None) | Iterates over predictions.
Examples
--------
>>> for pred, i_batch, batch in module.iter_predict(eval_data):
... # pred is a list of outputs from the module
... # i_batch is a integer
... # batch is the data batch from the data iterator
Parameters
----------
eval_data : DataIter
Evaluation data to run prediction on.
num_batch : int
Default is ``None``, indicating running all the batches in the data iterator.
reset : bool
Default is ``True``, indicating whether we should reset the data iter before start
doing prediction.
sparse_row_id_fn : A callback function
The function takes `data_batch` as an input and returns a dict of
str -> NDArray. The resulting dict is used for pulling row_sparse
parameters from the kvstore, where the str key is the name of the param,
and the value is the row id of the param to pull. | Iterates over predictions. | [
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"."
] | def iter_predict(self, eval_data, num_batch=None, reset=True, sparse_row_id_fn=None):
"""Iterates over predictions.
Examples
--------
>>> for pred, i_batch, batch in module.iter_predict(eval_data):
... # pred is a list of outputs from the module
... # i_batch is a integer
... # batch is the data batch from the data iterator
Parameters
----------
eval_data : DataIter
Evaluation data to run prediction on.
num_batch : int
Default is ``None``, indicating running all the batches in the data iterator.
reset : bool
Default is ``True``, indicating whether we should reset the data iter before start
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"""
assert self.binded and self.params_initialized
if reset:
eval_data.reset()
for nbatch, eval_batch in enumerate(eval_data):
if num_batch is not None and nbatch == num_batch:
break
self.prepare(eval_batch, sparse_row_id_fn=sparse_row_id_fn)
self.forward(eval_batch, is_train=False)
pad = eval_batch.pad
outputs = [out[0:out.shape[0]-pad] for out in self.get_outputs()]
yield (outputs, nbatch, eval_batch) | [
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/tools/inspector_protocol/markupsafe/_native.py | python | escape | (s) | return Markup(text_type(s)
.replace('&', '&')
.replace('>', '>')
.replace('<', '<')
.replace("'", ''')
.replace('"', '"')
) | Convert the characters &, <, >, ' and " in string s to HTML-safe
sequences. Use this if you need to display text that might contain
such characters in HTML. Marks return value as markup string. | Convert the characters &, <, >, ' and " in string s to HTML-safe
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such characters in HTML. Marks return value as markup string. | [
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"""Convert the characters &, <, >, ' and " in string s to HTML-safe
sequences. Use this if you need to display text that might contain
such characters in HTML. Marks return value as markup string.
"""
if hasattr(s, '__html__'):
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supercollider/supercollider | 42715a73ce2de4720174583e9b66a4510fe289a3 | external_libraries/simplejson-2.3.2/encoder.py | python | JSONEncoder.iterencode | (self, o, _one_shot=False) | Encode the given object and yield each string
representation as available.
For example::
for chunk in JSONEncoder().iterencode(bigobject):
mysocket.write(chunk) | Encode the given object and yield each string
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"""Encode the given object and yield each string
representation as available.
For example::
for chunk in JSONEncoder().iterencode(bigobject):
mysocket.write(chunk)
"""
if self.check_circular:
markers = {}
else:
markers = None
if self.ensure_ascii:
_encoder = encode_basestring_ascii
else:
_encoder = encode_basestring
if self.encoding != 'utf-8':
def _encoder(o, _orig_encoder=_encoder, _encoding=self.encoding):
if isinstance(o, str):
o = o.decode(_encoding)
return _orig_encoder(o)
def floatstr(o, allow_nan=self.allow_nan,
_repr=FLOAT_REPR, _inf=PosInf, _neginf=-PosInf):
# Check for specials. Note that this type of test is processor
# and/or platform-specific, so do tests which don't depend on
# the internals.
if o != o:
text = 'NaN'
elif o == _inf:
text = 'Infinity'
elif o == _neginf:
text = '-Infinity'
else:
return _repr(o)
if not allow_nan:
raise ValueError(
"Out of range float values are not JSON compliant: " +
repr(o))
return text
key_memo = {}
if (_one_shot and c_make_encoder is not None
and self.indent is None):
_iterencode = c_make_encoder(
markers, self.default, _encoder, self.indent,
self.key_separator, self.item_separator, self.sort_keys,
self.skipkeys, self.allow_nan, key_memo, self.use_decimal,
self.namedtuple_as_object, self.tuple_as_array)
else:
_iterencode = _make_iterencode(
markers, self.default, _encoder, self.indent, floatstr,
self.key_separator, self.item_separator, self.sort_keys,
self.skipkeys, _one_shot, self.use_decimal,
self.namedtuple_as_object, self.tuple_as_array)
try:
return _iterencode(o, 0)
finally:
key_memo.clear() | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/cmd.py | python | Cmd.parseline | (self, line) | return cmd, arg, line | Parse the line into a command name and a string containing
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/dataset/vision/py_transforms.py | python | RandomSharpness.__call__ | (self, img) | return util.random_sharpness(img, self.degrees) | Call method.
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img (PIL Image): Image to be sharpness adjusted.
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/ops/nn_grad.py | python | _TopKGrad | (op, grad, _) | return [array_ops.reshape(
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/apiclient/googleapiclient/schema.py | python | _SchemaToStruct.emitEnd | (self, text, comment) | Add text and comment to the output with line terminator.
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/build/waf-1.7.13/waflib/Utils.py | python | h_list | (lst) | return md5(repr(lst).encode()).digest() | Hashes lists of ordered data.
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Hashes lists of ordered data.
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deepmind/open_spiel | 4ca53bea32bb2875c7385d215424048ae92f78c8 | open_spiel/python/egt/alpharank_visualizer.py | python | NetworkPlot.__init__ | (self,
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payoff_tables: List of game payoff tables, one for each agent identity.
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rhos: Fixation probabilities.
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payoff_tables: List of game payoff tables, one for each agent identity.
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rho_m: Neutral fixation probability.
pi: Stationary distribution of fixation Markov chain defined by rhos.
state_labels: Labels corresponding to Markov states. For the
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num_top_profiles: Set to (int) to show only the graph nodes corresponding
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"""
self.fig = plt.figure(figsize=(10, 10))
self.num_populations = len(payoff_tables)
payoffs_are_hpt_format = utils.check_payoffs_are_hpt(payoff_tables)
self.num_strats_per_population = (
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self.rho_m = rho_m
self.pi = pi
self.num_profiles = len(pi)
self.state_labels = state_labels
self.first_run = True
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self.nodes_to_skip = list(self.pi.argsort()[:self.num_profiles -
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self.nodes_to_skip = []
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_windows.py | python | FontData.SetChosenFont | (*args, **kwargs) | return _windows_.FontData_SetChosenFont(*args, **kwargs) | SetChosenFont(self, Font font)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/botocore/vendored/requests/packages/urllib3/_collections.py | python | HTTPHeaderDict.from_httplib | (cls, message) | return cls(headers) | Read headers from a Python 2 httplib message object. | Read headers from a Python 2 httplib message object. | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/summary/event_file_inspector.py | python | get_field_to_observations_map | (generator, query_for_tag='') | return field_to_obs | Return a field to `Observations` dict for the event generator.
Args:
generator: A generator over event protos.
query_for_tag: A string that if specified, only create observations for
events with this tag name.
Returns:
A dict mapping keys in `TRACKED_FIELDS` to an `Observation` list. | Return a field to `Observations` dict for the event generator. | [
"Return",
"a",
"field",
"to",
"Observations",
"dict",
"for",
"the",
"event",
"generator",
"."
] | def get_field_to_observations_map(generator, query_for_tag=''):
"""Return a field to `Observations` dict for the event generator.
Args:
generator: A generator over event protos.
query_for_tag: A string that if specified, only create observations for
events with this tag name.
Returns:
A dict mapping keys in `TRACKED_FIELDS` to an `Observation` list.
"""
def increment(stat, event, tag=''):
assert stat in TRACKED_FIELDS
field_to_obs[stat].append(Observation(step=event.step,
wall_time=event.wall_time,
tag=tag)._asdict())
field_to_obs = dict([(t, []) for t in TRACKED_FIELDS])
for event in generator:
## Process the event
if event.HasField('graph_def') and (not query_for_tag):
increment('graph', event)
if event.HasField('session_log') and (not query_for_tag):
status = event.session_log.status
if status == SessionLog.START:
increment('sessionlog:start', event)
elif status == SessionLog.STOP:
increment('sessionlog:stop', event)
elif status == SessionLog.CHECKPOINT:
increment('sessionlog:checkpoint', event)
elif event.HasField('summary'):
for value in event.summary.value:
if query_for_tag and value.tag != query_for_tag:
continue
for proto_name, display_name in SUMMARY_TYPE_TO_FIELD.items():
if value.HasField(proto_name):
increment(display_name, event, value.tag)
return field_to_obs | [
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apitrace/apitrace | 764c9786b2312b656ce0918dff73001c6a85f46f | specs/debug.py | python | excepthook | (type, value, tb) | Automatically start the debugger on an exception.
See also:
- http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/65287 | Automatically start the debugger on an exception. | [
"Automatically",
"start",
"the",
"debugger",
"on",
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"exception",
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] | def excepthook(type, value, tb):
"""
Automatically start the debugger on an exception.
See also:
- http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/65287
"""
if hasattr(sys, 'ps1') \
or not (sys.stdin.isatty() and sys.stdout.isatty() and sys.stderr.isatty()) \
or type == SyntaxError or type == KeyboardInterrupt:
# we are in interactive mode or we don't have a tty-like
# device, so we call the default hook
oldexcepthook(type, value, tb)
else:
import traceback, pdb
# we are NOT in interactive mode, print the exception...
traceback.print_exception(type, value, tb)
print()
# ...then start the debugger in post-mortem mode.
pdb.pm() | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/tensor/linalg.py | python | lu_unpack | (x, y, unpack_ludata=True, unpack_pivots=True, name=None) | return p, l, u | r"""
Unpack L U and P to single matrix tensor .
unpack L and U matrix from LU, unpack permutation matrix P from Pivtos .
P mat can be get by pivots:
# ones = eye(rows) #eye matrix of rank rows
# for i in range(cols):
# swap(ones[i], ones[pivots[i]])
Args:
x (Tensor): The LU tensor get from paddle.linalg.lu, which is combined by L and U.
y (Tensor): Pivots get from paddle.linalg.lu.
unpack_ludata (bool,optional): whether to unpack L and U from x. Default: True.
unpack_pivots (bool, optional): whether to unpack permutation matrix P from Pivtos. Default: True.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
P (Tensor): Permutation matrix P of lu factorization.
L (Tensor): The lower triangular matrix tensor of lu factorization.
U (Tensor): The upper triangular matrix tensor of lu factorization.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]).astype('float64')
lu,p,info = paddle.linalg.lu(x, get_infos=True)
# >>> lu:
# Tensor(shape=[3, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[5. , 6. ],
# [0.20000000, 0.80000000],
# [0.60000000, 0.50000000]])
# >>> p
# Tensor(shape=[2], dtype=int32, place=CUDAPlace(0), stop_gradient=True,
# [3, 3])
# >>> info
# Tensor(shape=[], dtype=int32, place=CUDAPlace(0), stop_gradient=True,
# 0)
P,L,U = paddle.linalg.lu_unpack(lu,p)
# >>> P
# (Tensor(shape=[3, 3], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[0., 1., 0.],
# [0., 0., 1.],
# [1., 0., 0.]]),
# >>> L
# Tensor(shape=[3, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[1. , 0. ],
# [0.20000000, 1. ],
# [0.60000000, 0.50000000]]),
# >>> U
# Tensor(shape=[2, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[5. , 6. ],
# [0. , 0.80000000]]))
# one can verify : X = P @ L @ U ; | r"""
Unpack L U and P to single matrix tensor .
unpack L and U matrix from LU, unpack permutation matrix P from Pivtos . | [
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"from",
"LU",
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"matrix",
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"from",
"Pivtos",
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] | def lu_unpack(x, y, unpack_ludata=True, unpack_pivots=True, name=None):
r"""
Unpack L U and P to single matrix tensor .
unpack L and U matrix from LU, unpack permutation matrix P from Pivtos .
P mat can be get by pivots:
# ones = eye(rows) #eye matrix of rank rows
# for i in range(cols):
# swap(ones[i], ones[pivots[i]])
Args:
x (Tensor): The LU tensor get from paddle.linalg.lu, which is combined by L and U.
y (Tensor): Pivots get from paddle.linalg.lu.
unpack_ludata (bool,optional): whether to unpack L and U from x. Default: True.
unpack_pivots (bool, optional): whether to unpack permutation matrix P from Pivtos. Default: True.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
P (Tensor): Permutation matrix P of lu factorization.
L (Tensor): The lower triangular matrix tensor of lu factorization.
U (Tensor): The upper triangular matrix tensor of lu factorization.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]).astype('float64')
lu,p,info = paddle.linalg.lu(x, get_infos=True)
# >>> lu:
# Tensor(shape=[3, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[5. , 6. ],
# [0.20000000, 0.80000000],
# [0.60000000, 0.50000000]])
# >>> p
# Tensor(shape=[2], dtype=int32, place=CUDAPlace(0), stop_gradient=True,
# [3, 3])
# >>> info
# Tensor(shape=[], dtype=int32, place=CUDAPlace(0), stop_gradient=True,
# 0)
P,L,U = paddle.linalg.lu_unpack(lu,p)
# >>> P
# (Tensor(shape=[3, 3], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[0., 1., 0.],
# [0., 0., 1.],
# [1., 0., 0.]]),
# >>> L
# Tensor(shape=[3, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[1. , 0. ],
# [0.20000000, 1. ],
# [0.60000000, 0.50000000]]),
# >>> U
# Tensor(shape=[2, 2], dtype=float64, place=CUDAPlace(0), stop_gradient=True,
# [[5. , 6. ],
# [0. , 0.80000000]]))
# one can verify : X = P @ L @ U ;
"""
if in_dygraph_mode():
P, L, U = _C_ops.lu_unpack(x, y, 'unpack_ludata', unpack_ludata,
'unpack_pivots', unpack_pivots)
return P, L, U
check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'lu_unpack')
helper = LayerHelper('lu_unpack', **locals())
p = helper.create_variable_for_type_inference(dtype=x.dtype)
l = helper.create_variable_for_type_inference(dtype=x.dtype)
u = helper.create_variable_for_type_inference(dtype=x.dtype)
attrs = dict()
attrs['unpack_ludata'] = unpack_ludata
attrs['unpack_pivots'] = unpack_pivots
helper.append_op(
type='lu_unpack',
inputs={'X': x,
'Pivots': y},
outputs={'Pmat': p,
'L': l,
'U': u},
attrs=attrs)
return p, l, u | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/robotsim.py | python | Appearance.setTexture1D_channels | (self, format: str, np_array2: "ndarray") | return _robotsim.Appearance_setTexture1D_channels(self, format, np_array2) | r"""
Sets a 1D texture of the given width, given a 2D array of channels. Valid format
strings are.
Args:
format (str)
np_array2 (:obj:`unsigned char *`)
* "": turn off texture mapping
* rgb8: unsigned byte RGB colors with red in the 1st column, green in the 2nd,
blue in the 3rd
* bgr8: unsigned byte RGB colors with blue in the 1st column, green in the
2nd, green in the 3rd
* rgba8: unsigned byte RGBA colors with red in the 1st column and alpha in the
4th
* bgra8: unsigned byte RGBA colors with blue in the 1st column and alpha in
the 4th
* l8: unsigned byte grayscale colors, one channel | r"""
Sets a 1D texture of the given width, given a 2D array of channels. Valid format
strings are. | [
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] | def setTexture1D_channels(self, format: str, np_array2: "ndarray") ->None:
r"""
Sets a 1D texture of the given width, given a 2D array of channels. Valid format
strings are.
Args:
format (str)
np_array2 (:obj:`unsigned char *`)
* "": turn off texture mapping
* rgb8: unsigned byte RGB colors with red in the 1st column, green in the 2nd,
blue in the 3rd
* bgr8: unsigned byte RGB colors with blue in the 1st column, green in the
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* rgba8: unsigned byte RGBA colors with red in the 1st column and alpha in the
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* bgra8: unsigned byte RGBA colors with blue in the 1st column and alpha in
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* l8: unsigned byte grayscale colors, one channel
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return _robotsim.Appearance_setTexture1D_channels(self, format, np_array2) | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/SimpleXMLRPCServer.py | python | CGIXMLRPCRequestHandler.handle_request | (self, request_text = None) | Handle a single XML-RPC request passed through a CGI post method.
If no XML data is given then it is read from stdin. The resulting
XML-RPC response is printed to stdout along with the correct HTTP
headers. | Handle a single XML-RPC request passed through a CGI post method. | [
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] | def handle_request(self, request_text = None):
"""Handle a single XML-RPC request passed through a CGI post method.
If no XML data is given then it is read from stdin. The resulting
XML-RPC response is printed to stdout along with the correct HTTP
headers.
"""
if request_text is None and \
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self.handle_get()
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# POST data is normally available through stdin
try:
length = int(os.environ.get('CONTENT_LENGTH', None))
except (TypeError, ValueError):
length = -1
if request_text is None:
request_text = sys.stdin.read(length)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/s3transfer/futures.py | python | TransferMeta.size | (self) | return self._size | The size of the transfer request if known | The size of the transfer request if known | [
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return self._size | [
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/s3transfer/futures.py#L110-L112 | |
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/tools/gyp/pylib/gyp/generator/msvs.py | python | CalculateVariables | (default_variables, params) | Generated variables that require params to be known. | Generated variables that require params to be known. | [
"Generated",
"variables",
"that",
"require",
"params",
"to",
"be",
"known",
"."
] | def CalculateVariables(default_variables, params):
"""Generated variables that require params to be known."""
generator_flags = params.get('generator_flags', {})
# Select project file format version (if unset, default to auto detecting).
msvs_version = MSVSVersion.SelectVisualStudioVersion(
generator_flags.get('msvs_version', 'auto'))
# Stash msvs_version for later (so we don't have to probe the system twice).
params['msvs_version'] = msvs_version
# Set a variable so conditions can be based on msvs_version.
default_variables['MSVS_VERSION'] = msvs_version.ShortName()
# To determine processor word size on Windows, in addition to checking
# PROCESSOR_ARCHITECTURE (which reflects the word size of the current
# process), it is also necessary to check PROCESSOR_ARCITEW6432 (which
# contains the actual word size of the system when running thru WOW64).
if (os.environ.get('PROCESSOR_ARCHITECTURE', '').find('64') >= 0 or
os.environ.get('PROCESSOR_ARCHITEW6432', '').find('64') >= 0):
default_variables['MSVS_OS_BITS'] = 64
else:
default_variables['MSVS_OS_BITS'] = 32 | [
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trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | cmake/std/trilinosprhelpers/TrilinosPRConfigurationBase.py | python | TrilinosPRConfigurationBase.validate_branch_constraints | (self) | return 0 | Verify that the source branch is allowed.
For the `master` branch, we only allow the source branch to be
a protected branch named with the scheme `master_merge_YYYYMMDD_HHMMSS` | Verify that the source branch is allowed. | [
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] | def validate_branch_constraints(self):
"""
Verify that the source branch is allowed.
For the `master` branch, we only allow the source branch to be
a protected branch named with the scheme `master_merge_YYYYMMDD_HHMMSS`
"""
print("")
print("Validate target branch constraints:")
print("--- Target branch is '{}'".format(self.args.target_branch_name))
re_master_merge_source = "master_merge_[0-9]{8}_[0-9]{6}"
if "master" == self.args.target_branch_name:
print("--- Target branch is 'master'. Checking source branch constraints...")
if not re.match(re_master_merge_source, self.args.source_branch_name):
message = "+" + "="*78 + "+\n"
message += "ERROR: Source branch is NOT trilinos/Trilinos::master_merge_YYYYMMDD_HHMMSS\n"
message += " This violates Trilinos policy for pull requests into the master\n"
message += " branch.\n"
message += " Source branch provided is {}\n".format(self.args.source_branch_name)
message += " Perhaps you forgot to set `develop` as the target in your PR?\n"
message += "+" + "="*78 + "+\n"
#print(message)
sys.exit(message)
print("--- target branch constraints OK")
print("")
return 0 | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/tensor_forest/python/ops/training_ops.py | python | _ScatterAddNdimShape | (unused_op) | return [] | Shape function for ScatterAddNdim Op. | Shape function for ScatterAddNdim Op. | [
"Shape",
"function",
"for",
"ScatterAddNdim",
"Op",
"."
] | def _ScatterAddNdimShape(unused_op):
"""Shape function for ScatterAddNdim Op."""
return [] | [
"def",
"_ScatterAddNdimShape",
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] | https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/contrib/tensor_forest/python/ops/training_ops.py#L95-L97 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/boto3/resources/collection.py | python | CollectionManager.iterator | (self, **kwargs) | return self._collection_cls(self._model, self._parent,
self._handler, **kwargs) | Get a resource collection iterator from this manager.
:rtype: :py:class:`ResourceCollection`
:return: An iterable representing the collection of resources | Get a resource collection iterator from this manager. | [
"Get",
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] | def iterator(self, **kwargs):
"""
Get a resource collection iterator from this manager.
:rtype: :py:class:`ResourceCollection`
:return: An iterable representing the collection of resources
"""
return self._collection_cls(self._model, self._parent,
self._handler, **kwargs) | [
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protocolbuffers/protobuf | b5ab0b7a18b7336c60130f4ddb2d97c51792f896 | python/google/protobuf/internal/well_known_types.py | python | Timestamp.ToJsonString | (self) | return result + '.%09dZ' % nanos | Converts Timestamp to RFC 3339 date string format.
Returns:
A string converted from timestamp. The string is always Z-normalized
and uses 3, 6 or 9 fractional digits as required to represent the
exact time. Example of the return format: '1972-01-01T10:00:20.021Z' | Converts Timestamp to RFC 3339 date string format. | [
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] | def ToJsonString(self):
"""Converts Timestamp to RFC 3339 date string format.
Returns:
A string converted from timestamp. The string is always Z-normalized
and uses 3, 6 or 9 fractional digits as required to represent the
exact time. Example of the return format: '1972-01-01T10:00:20.021Z'
"""
nanos = self.nanos % _NANOS_PER_SECOND
total_sec = self.seconds + (self.nanos - nanos) // _NANOS_PER_SECOND
seconds = total_sec % _SECONDS_PER_DAY
days = (total_sec - seconds) // _SECONDS_PER_DAY
dt = datetime(1970, 1, 1) + timedelta(days, seconds)
result = dt.isoformat()
if (nanos % 1e9) == 0:
# If there are 0 fractional digits, the fractional
# point '.' should be omitted when serializing.
return result + 'Z'
if (nanos % 1e6) == 0:
# Serialize 3 fractional digits.
return result + '.%03dZ' % (nanos / 1e6)
if (nanos % 1e3) == 0:
# Serialize 6 fractional digits.
return result + '.%06dZ' % (nanos / 1e3)
# Serialize 9 fractional digits.
return result + '.%09dZ' % nanos | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/stc.py | python | StyledTextCtrl.GetCaretPeriod | (*args, **kwargs) | return _stc.StyledTextCtrl_GetCaretPeriod(*args, **kwargs) | GetCaretPeriod(self) -> int
Get the time in milliseconds that the caret is on and off. | GetCaretPeriod(self) -> int | [
"GetCaretPeriod",
"(",
"self",
")",
"-",
">",
"int"
] | def GetCaretPeriod(*args, **kwargs):
"""
GetCaretPeriod(self) -> int
Get the time in milliseconds that the caret is on and off.
"""
return _stc.StyledTextCtrl_GetCaretPeriod(*args, **kwargs) | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/logging/handlers.py | python | BufferingHandler.close | (self) | Close the handler.
This version just flushes and chains to the parent class' close(). | Close the handler. | [
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] | def close(self):
"""
Close the handler.
This version just flushes and chains to the parent class' close().
"""
self.flush()
logging.Handler.close(self) | [
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facebook/openr | ed38bdfd6bf290084bfab4821b59f83e7b59315d | openr/py/openr/cli/clis/config.py | python | ConfigPrefixManagerCli.config_prefix_manager | (cli_opts) | Dump prefix manager config | Dump prefix manager config | [
"Dump",
"prefix",
"manager",
"config"
] | def config_prefix_manager(cli_opts): # noqa: B902
"""Dump prefix manager config"""
config.ConfigPrefixManagerCmd(cli_opts).run() | [
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echronos/echronos | c996f1d2c8af6c6536205eb319c1bf1d4d84569c | external_tools/ply_info/example/ansic/cparse.py | python | p_init_declarator_1 | (t) | init_declarator : declarator | init_declarator : declarator | [
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rapidsai/cudf | d5b2448fc69f17509304d594f029d0df56984962 | python/cudf/versioneer.py | python | get_version | () | return get_versions()["version"] | Get the short version string for this project. | Get the short version string for this project. | [
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] | def get_version():
"""Get the short version string for this project."""
return get_versions()["version"] | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/cloudsearch2/layer1.py | python | CloudSearchConnection.describe_scaling_parameters | (self, domain_name) | return self._make_request(
action='DescribeScalingParameters',
verb='POST',
path='/', params=params) | Gets the scaling parameters configured for a domain. A
domain's scaling parameters specify the desired search
instance type and replication count. For more information, see
`Configuring Scaling Options`_ in the Amazon CloudSearch
Developer Guide .
:type domain_name: string
:param domain_name: A string that represents the name of a domain.
Domain names are unique across the domains owned by an account
within an AWS region. Domain names start with a letter or number
and can contain the following characters: a-z (lowercase), 0-9, and
- (hyphen). | Gets the scaling parameters configured for a domain. A
domain's scaling parameters specify the desired search
instance type and replication count. For more information, see
`Configuring Scaling Options`_ in the Amazon CloudSearch
Developer Guide . | [
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"""
Gets the scaling parameters configured for a domain. A
domain's scaling parameters specify the desired search
instance type and replication count. For more information, see
`Configuring Scaling Options`_ in the Amazon CloudSearch
Developer Guide .
:type domain_name: string
:param domain_name: A string that represents the name of a domain.
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"""
params = {'DomainName': domain_name, }
return self._make_request(
action='DescribeScalingParameters',
verb='POST',
path='/', params=params) | [
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rodeofx/OpenWalter | 6116fbe3f04f1146c854afbfbdbe944feaee647e | walter/maya/scripts/walterPanel/walterMayaTraverser.py | python | WalterMayaImplementation.findShadersPlug | (self, layersAssignation, layerName) | return self.getChildMPlug(requestedAssignation, 'shaderConnections') | Return MPlug node.layersAssignation[i].shaderConnections for requested
layer. | Return MPlug node.layersAssignation[i].shaderConnections for requested
layer. | [
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] | def findShadersPlug(self, layersAssignation, layerName):
"""
Return MPlug node.layersAssignation[i].shaderConnections for requested
layer.
"""
# Requested render layer
layerDepend = self.getDependNode(layerName)
if not layerDepend:
return
# Get MObject of the requested render layer to be able to comare it with
# connected layers
layerObject = layerDepend.object()
requestedAssignation = None
for i in range(layersAssignation.numElements()):
# Get walterStandin.layersAssignation[i]
currentLayerCompound = layersAssignation.elementByPhysicalIndex(i)
# Get walterStandin.layersAssignation[i].layer
layerPlug = self.getChildMPlug(currentLayerCompound, 'layer')
if not layerPlug or layerPlug.isNull:
continue
connection = layerPlug.connectedTo(True, False)
if not connection:
continue
# Compare the saved MObject with the first connected node. We
# consider we have only one connection.
if layerObject == connection[0].node():
# Save walterStandin.layersAssignation[i]
requestedAssignation = currentLayerCompound
break
if not requestedAssignation:
return
# Get walterStandin.layersAssignation[i].shaderConnections
return self.getChildMPlug(requestedAssignation, 'shaderConnections') | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/ftplib.py | python | FTP.getwelcome | (self) | return self.welcome | Get the welcome message from the server.
(this is read and squirreled away by connect()) | Get the welcome message from the server.
(this is read and squirreled away by connect()) | [
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'''Get the welcome message from the server.
(this is read and squirreled away by connect())'''
if self.debugging:
print('*welcome*', self.sanitize(self.welcome))
return self.welcome | [
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Jyouhou/UnrealText | dc8460a8dff37c61d5bf290b013674bb0c42d429 | code/DataGenerator/ClientWrapper.py | python | WrappedClient.randomizeEnv | (self, env_type='All') | env_type = 'All', 'light_int', 'light_dir', 'light-color', 'fog' | env_type = 'All', 'light_int', 'light_dir', 'light-color', 'fog' | [
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"""
env_type = 'All', 'light_int', 'light_dir', 'light-color', 'fog'
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yyzybb537/libgo | 4af17b7c67643c4d54aa354dcc77963ea07847d0 | third_party/boost.context/tools/build/src/build/targets.py | python | ProjectTarget.targets_to_build | (self) | return result | Computes and returns a list of AbstractTarget instances which
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result = []
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self.build_main_targets ()
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/io.py | python | RawIOBase.write | (self, b) | Write the given buffer to the IO stream.
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/plat-mac/lib-scriptpackages/Netscape/Standard_Suite.py | python | Standard_Suite_Events.get | (self, _object, _attributes={}, **_arguments) | get: Get the data for an object
Required argument: the object whose data is to be returned
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: The data from the object | get: Get the data for an object
Required argument: the object whose data is to be returned
Keyword argument _attributes: AppleEvent attribute dictionary
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/cryptography/hazmat/primitives/asymmetric/rsa.py | python | rsa_recover_prime_factors | (n, e, d) | return (p, q) | Compute factors p and q from the private exponent d. We assume that n has
no more than two factors. This function is adapted from code in PyCrypto. | Compute factors p and q from the private exponent d. We assume that n has
no more than two factors. This function is adapted from code in PyCrypto. | [
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"""
Compute factors p and q from the private exponent d. We assume that n has
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"""
# See 8.2.2(i) in Handbook of Applied Cryptography.
ktot = d * e - 1
# The quantity d*e-1 is a multiple of phi(n), even,
# and can be represented as t*2^s.
t = ktot
while t % 2 == 0:
t = t // 2
# Cycle through all multiplicative inverses in Zn.
# The algorithm is non-deterministic, but there is a 50% chance
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# See "Digitalized Signatures and Public Key Functions as Intractable
# as Factorization", M. Rabin, 1979
spotted = False
a = 2
while not spotted and a < _MAX_RECOVERY_ATTEMPTS:
k = t
# Cycle through all values a^{t*2^i}=a^k
while k < ktot:
cand = pow(a, k, n)
# Check if a^k is a non-trivial root of unity (mod n)
if cand != 1 and cand != (n - 1) and pow(cand, 2, n) == 1:
# We have found a number such that (cand-1)(cand+1)=0 (mod n).
# Either of the terms divides n.
p = gcd(cand + 1, n)
spotted = True
break
k *= 2
# This value was not any good... let's try another!
a += 2
if not spotted:
raise ValueError("Unable to compute factors p and q from exponent d.")
# Found !
q, r = divmod(n, p)
assert r == 0
p, q = sorted((p, q), reverse=True)
return (p, q) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/mailbox.py | python | Maildir._refresh | (self) | Update table of contents mapping. | Update table of contents mapping. | [
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"""Update table of contents mapping."""
# If it has been less than two seconds since the last _refresh() call,
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# been modified, because os.path.mtime() has a 2 sec resolution in the
# most common worst case (FAT) and a 1 sec resolution typically. This
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# extra delta to our wait. The default is one tenth second, but is an
# instance variable and so can be adjusted if dealing with a
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if time.time() - self._last_read > 2 + self._skewfactor:
refresh = False
for subdir in self._toc_mtimes:
mtime = os.path.getmtime(self._paths[subdir])
if mtime > self._toc_mtimes[subdir]:
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self._toc_mtimes[subdir] = mtime
if not refresh:
return
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self._toc = {}
for subdir in self._toc_mtimes:
path = self._paths[subdir]
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p = os.path.join(path, entry)
if os.path.isdir(p):
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uniq = entry.split(self.colon)[0]
self._toc[uniq] = os.path.join(subdir, entry)
self._last_read = time.time() | [
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hakuna-m/wubiuefi | caec1af0a09c78fd5a345180ada1fe45e0c63493 | src/pypack/altgraph/ObjectGraph.py | python | ObjectGraph.filterStack | (self, filters) | return len(visited)-1, len(removes), len(orphans) | Filter the ObjectGraph in-place by removing all edges to nodes that
do not match every filter in the given filter list
Returns a tuple containing the number of:
(nodes_visited, nodes_removed, nodes_orphaned) | Filter the ObjectGraph in-place by removing all edges to nodes that
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"""
Filter the ObjectGraph in-place by removing all edges to nodes that
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visited, removes, orphans = filter_stack(self.graph, self, filters)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/aui.py | python | AuiPaneInfo.CloseButton | (*args, **kwargs) | return _aui.AuiPaneInfo_CloseButton(*args, **kwargs) | CloseButton(self, bool visible=True) -> AuiPaneInfo | CloseButton(self, bool visible=True) -> AuiPaneInfo | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/telemetry/core/platform/__init__.py | python | Platform.IsApplicationRunning | (self, application) | return self._platform_backend.IsApplicationLaunchning(application) | Returns whether an application is currently running. | Returns whether an application is currently running. | [
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apache/arrow | af33dd1157eb8d7d9bfac25ebf61445b793b7943 | python/pyarrow/filesystem.py | python | FileSystem.cat | (self, path) | Return contents of file as a bytes object.
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BitMEX/api-connectors | 37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812 | auto-generated/python/swagger_client/models/execution.py | python | Execution.peg_offset_value | (self) | return self._peg_offset_value | Gets the peg_offset_value of this Execution. # noqa: E501
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/resmokelib/logging/handlers.py | python | HTTPHandler.post | (self, endpoint, data=None, headers=None, timeout_secs=_TIMEOUT_SECS) | return response.text | Send a POST request to the specified endpoint with the supplied data.
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/tpu/ops/tpu_ops.py | python | collective_permute | (x, source_target_pairs, name=None) | return gen_tpu_ops.collective_permute(x, source_target_pairs, name=name) | Permute the input tensor across replicas given source_target_pairs.
For each source_target_pair <a, b>, we send replica a's input to replica b.
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For example, suppose there are 4 TPU instances: `[A, B, C, D]`. Passing
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x: The local tensor to be permuted.
source_target_pairs: 2d int lists with shape [num_pairs, 2].
source_target_pairs[i][0] represents the source replica id and
source_target_pairs[i][1] represents the target replica id.
name: Optional op name.
Returns:
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SequoiaDB/SequoiaDB | 2894ed7e5bd6fe57330afc900cf76d0ff0df9f64 | tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py | python | xpathParserContext.xpathIdFunction | (self, nargs) | Implement the id() XPath function node-set id(object) The
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