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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/share/gdb/python/gdb/FrameDecorator.py | python | SymValueWrapper.value | (self) | return self.val | Return the value associated with this symbol, or None | Return the value associated with this symbol, or None | [
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FeatherCoin/Feathercoin | 8dad11707024149029bb9bfdd7bc5e10385e0e77 | contrib/devtools/security-check.py | python | check_PE_NX | (executable) | return (bits & IMAGE_DLL_CHARACTERISTICS_NX_COMPAT) == IMAGE_DLL_CHARACTERISTICS_NX_COMPAT | NX: DllCharacteristics bit 0x100 signifies nxcompat (DEP) | NX: DllCharacteristics bit 0x100 signifies nxcompat (DEP) | [
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'''NX: DllCharacteristics bit 0x100 signifies nxcompat (DEP)'''
(arch,bits) = get_PE_dll_characteristics(executable)
return (bits & IMAGE_DLL_CHARACTERISTICS_NX_COMPAT) == IMAGE_DLL_CHARACTERISTICS_NX_COMPAT | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/predictor/contrib_estimator_predictor.py | python | ContribEstimatorPredictor.__init__ | (self,
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prediction_input_fn: a function that takes no arguments and returns an
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input_alternative_key: Optional. Specify the input alternative used for
prediction.
output_alternative_key: Specify the output alternative used for
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graph: Optional. The Tensorflow `graph` in which prediction should be
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"""Initialize a `ContribEstimatorPredictor`.
Args:
estimator: an instance of `tf.contrib.learn.Estimator`.
prediction_input_fn: a function that takes no arguments and returns an
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input_alternative_key: Optional. Specify the input alternative used for
prediction.
output_alternative_key: Specify the output alternative used for
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multi-headed models.
graph: Optional. The Tensorflow `graph` in which prediction should be
done.
"""
self._graph = graph or ops.Graph()
with self._graph.as_default():
input_fn_ops = prediction_input_fn()
# pylint: disable=protected-access
model_fn_ops = estimator._get_predict_ops(input_fn_ops.features)
# pylint: enable=protected-access
checkpoint_path = saver.latest_checkpoint(estimator.model_dir)
self._session = monitored_session.MonitoredSession(
session_creator=monitored_session.ChiefSessionCreator(
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input_alternative_key = (
input_alternative_key or
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input_alternatives, _ = saved_model_export_utils.get_input_alternatives(
input_fn_ops)
self._feed_tensors = input_alternatives[input_alternative_key]
(output_alternatives,
output_alternative_key) = saved_model_export_utils.get_output_alternatives(
model_fn_ops, output_alternative_key)
_, fetch_tensors = output_alternatives[output_alternative_key]
self._fetch_tensors = fetch_tensors | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/mailbox.py | python | _ProxyFile.seek | (self, offset, whence=0) | Change position. | Change position. | [
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"""Change position."""
if whence == 1:
self._file.seek(self._pos)
self._file.seek(offset, whence)
self._pos = self._file.tell() | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/wsgiref/handlers.py | python | BaseHandler.add_cgi_vars | (self) | Override in subclass to insert CGI variables in 'self.environ | Override in subclass to insert CGI variables in 'self.environ | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/compiler/pyassem.py | python | Block.getContainedGraphs | (self) | return contained | Return all graphs contained within this block.
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contained = []
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_controls.py | python | TreeItemId.IsOk | (*args, **kwargs) | return _controls_.TreeItemId_IsOk(*args, **kwargs) | IsOk(self) -> bool | IsOk(self) -> bool | [
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chipsalliance/verible | aa14e0074ff89945bf65eecfb9ef78684d996058 | verilog/tools/syntax/export_json_examples/verible_verilog_syntax.py | python | BranchNode.find_all | (self, filter_: Union[CallableFilter, KeyValueFilter, None],
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"""Find all nodes matching specified filter.
Args:
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arangodb/arangodb | 0d658689c7d1b721b314fa3ca27d38303e1570c8 | 3rdParty/V8/v7.9.317/third_party/jinja2/runtime.py | python | LoopContextBase.changed | (self, *value) | return False | Checks whether the value has changed since the last call. | Checks whether the value has changed since the last call. | [
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arangodb/arangodb | 0d658689c7d1b721b314fa3ca27d38303e1570c8 | 3rdParty/V8/gyp/msvs_emulation.py | python | MsvsSettings.GetDefFile | (self, gyp_to_build_path) | return None | Returns the .def file from sources, if any. Otherwise returns None. | Returns the .def file from sources, if any. Otherwise returns None. | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/llvmlite/ir/builder.py | python | IRBuilder.bswap | (self, cond) | Used to byte swap integer values with an even number of bytes (positive multiple of 16 bits) | Used to byte swap integer values with an even number of bytes (positive multiple of 16 bits) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/propgrid.py | python | PropertyGridInterface.Properties | (self) | This attribute is a pythonic iterator over all properties in
this `PropertyGrid` property container. It will only skip
categories and private child properties. Usage is simple::
for prop in propGrid.Properties:
print(prop)
:see: `wx.propgrid.PropertyGridInterface.Items`
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it = self.GetVIterator(PG_ITERATE_NORMAL)
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Arch/ArchCommands.py | python | survey | (callback=False) | survey(): starts survey mode, where you can click edges and faces to get their lengths or area.
Clicking on no object (on an empty area) resets the count. | survey(): starts survey mode, where you can click edges and faces to get their lengths or area.
Clicking on no object (on an empty area) resets the count. | [
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if hasattr(FreeCAD,"SurveyObserver"):
for label in FreeCAD.SurveyObserver.labels:
FreeCAD.ActiveDocument.removeObject(label)
FreeCADGui.Selection.removeObserver(FreeCAD.SurveyObserver)
del FreeCAD.SurveyObserver
FreeCADGui.Control.closeDialog()
if hasattr(FreeCAD,"SurveyDialog"):
del FreeCAD.SurveyDialog
else:
FreeCAD.SurveyObserver = _SurveyObserver(callback=survey)
FreeCADGui.Selection.addObserver(FreeCAD.SurveyObserver)
FreeCAD.SurveyDialog = SurveyTaskPanel()
FreeCADGui.Control.showDialog(FreeCAD.SurveyDialog)
else:
sel = FreeCADGui.Selection.getSelectionEx()
if hasattr(FreeCAD,"SurveyObserver"):
if not sel:
if FreeCAD.SurveyObserver.labels:
for label in FreeCAD.SurveyObserver.labels:
FreeCAD.ActiveDocument.removeObject(label)
tl = FreeCAD.SurveyObserver.totalLength
ta = FreeCAD.SurveyObserver.totalArea
FreeCAD.SurveyObserver.labels = []
FreeCAD.SurveyObserver.selection = []
FreeCAD.SurveyObserver.totalLength = 0
FreeCAD.SurveyObserver.totalArea = 0
FreeCAD.SurveyObserver.totalVolume = 0
if not FreeCAD.SurveyObserver.cancellable:
FreeCAD.Console.PrintMessage("\n---- Reset ----\n\n")
FreeCAD.SurveyObserver.cancellable = True
if hasattr(FreeCAD,"SurveyDialog"):
FreeCAD.SurveyDialog.newline(tl,ta)
else:
FreeCADGui.Selection.removeObserver(FreeCAD.SurveyObserver)
del FreeCAD.SurveyObserver
FreeCADGui.Control.closeDialog()
if hasattr(FreeCAD,"SurveyDialog"):
del FreeCAD.SurveyDialog
else:
FreeCAD.SurveyObserver.cancellable = False
basesel = FreeCAD.SurveyObserver.selection
newsels = []
for o in sel:
found = False
for eo in basesel:
if o.ObjectName == eo.ObjectName:
if o.SubElementNames == eo.SubElementNames:
found = True
if not found:
newsels.append(o)
if newsels:
for o in newsels:
if hasattr(o.Object, 'Shape'):
n = o.Object.Label
showUnit = FreeCAD.ParamGet("User parameter:BaseApp/Preferences/Mod/Arch").GetBool("surveyUnits",True)
t = ""
u = FreeCAD.Units.Quantity()
if not o.HasSubObjects:
# entire object
anno = FreeCAD.ActiveDocument.addObject("App::AnnotationLabel","surveyLabel")
if hasattr(o.Object.Shape,"CenterOfMass"):
anno.BasePosition = o.Object.Shape.CenterOfMass
else:
anno.BasePosition = o.Object.Shape.BoundBox.Center
FreeCAD.SurveyObserver.labels.append(anno.Name)
if o.Object.Shape.Solids:
u = FreeCAD.Units.Quantity(o.Object.Shape.Volume,FreeCAD.Units.Volume)
t = u.getUserPreferred()[0]
t = string_replace(t, "^3","³")
anno.LabelText = "v " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: Whole, Volume: " + utf8_decode(t) + "\n")
FreeCAD.SurveyObserver.totalVolume += u.Value
elif o.Object.Shape.Faces:
u = FreeCAD.Units.Quantity(o.Object.Shape.Area,FreeCAD.Units.Area)
t = u.getUserPreferred()[0]
t = string_replace(t, "^2","²")
anno.LabelText = "a " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: Whole, Area: " + utf8_decode(t) + "\n")
FreeCAD.SurveyObserver.totalArea += u.Value
if hasattr(FreeCAD,"SurveyDialog"):
FreeCAD.SurveyDialog.update(2,t)
else:
u = FreeCAD.Units.Quantity(o.Object.Shape.Length,FreeCAD.Units.Length)
t = u.getUserPreferred()[0]
t = t.encode("utf8")
anno.LabelText = "l " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: Whole, Length: " + utf8_decode(t) + "\n")
FreeCAD.SurveyObserver.totalLength += u.Value
if hasattr(FreeCAD,"SurveyDialog"):
FreeCAD.SurveyDialog.update(1,t)
if FreeCAD.GuiUp and t:
if showUnit:
QtGui.QApplication.clipboard().setText(t)
else:
QtGui.QApplication.clipboard().setText(str(u.Value))
else:
# single element(s)
for el in o.SubElementNames:
e = getattr(o.Object.Shape,el)
anno = FreeCAD.ActiveDocument.addObject("App::AnnotationLabel","surveyLabel")
if "Vertex" in el:
anno.BasePosition = e.Point
else:
if hasattr(e,"CenterOfMass"):
anno.BasePosition = e.CenterOfMass
else:
anno.BasePosition = e.BoundBox.Center
FreeCAD.SurveyObserver.labels.append(anno.Name)
if "Face" in el:
u = FreeCAD.Units.Quantity(e.Area,FreeCAD.Units.Area)
t = u.getUserPreferred()[0]
t = string_replace(t, "^2","²")
anno.LabelText = "a " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: " + el + ", Area: "+ utf8_decode(t) + "\n")
FreeCAD.SurveyObserver.totalArea += u.Value
if hasattr(FreeCAD,"SurveyDialog"):
FreeCAD.SurveyDialog.update(2,t)
elif "Edge" in el:
u= FreeCAD.Units.Quantity(e.Length,FreeCAD.Units.Length)
t = u.getUserPreferred()[0]
if sys.version_info.major < 3:
t = t.encode("utf8")
anno.LabelText = "l " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: " + el + ", Length: " + utf8_decode(t) + "\n")
FreeCAD.SurveyObserver.totalLength += u.Value
if hasattr(FreeCAD,"SurveyDialog"):
FreeCAD.SurveyDialog.update(1,t)
elif "Vertex" in el:
u = FreeCAD.Units.Quantity(e.Z,FreeCAD.Units.Length)
t = u.getUserPreferred()[0]
t = t.encode("utf8")
anno.LabelText = "z " + t
FreeCAD.Console.PrintMessage("Object: " + n + ", Element: " + el + ", Zcoord: " + utf8_decode(t) + "\n")
if FreeCAD.GuiUp and t:
if showUnit:
QtGui.QApplication.clipboard().setText(t)
else:
QtGui.QApplication.clipboard().setText(str(u.Value))
FreeCAD.SurveyObserver.selection.extend(newsels)
if hasattr(FreeCAD,"SurveyObserver"):
if FreeCAD.SurveyObserver.totalLength or FreeCAD.SurveyObserver.totalArea or FreeCAD.SurveyObserver.totalVolume:
msg = " Total:"
if FreeCAD.SurveyObserver.totalLength:
u = FreeCAD.Units.Quantity(FreeCAD.SurveyObserver.totalLength,FreeCAD.Units.Length)
t = u.getUserPreferred()[0]
if sys.version_info.major < 3:
t = t.encode("utf8")
msg += " Length: " + t
if FreeCAD.SurveyObserver.totalArea:
u = FreeCAD.Units.Quantity(FreeCAD.SurveyObserver.totalArea,FreeCAD.Units.Area)
t = u.getUserPreferred()[0]
t = string_replace(t, "^2","²")
msg += " Area: " + t
if FreeCAD.SurveyObserver.totalVolume:
u = FreeCAD.Units.Quantity(FreeCAD.SurveyObserver.totalVolume,FreeCAD.Units.Volume)
t = u.getUserPreferred()[0]
t = string_replace(t, "^3","³")
msg += " Volume: " + t
FreeCAD.Console.PrintMessage(msg+"\n") | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/debug/lib/debug_data.py | python | DebugDumpDir.t0 | (self) | return self._t0 | Absolute timestamp of the first dumped tensor across all devices.
Returns:
(`int`) absolute timestamp of the first dumped tensor, in microseconds. | Absolute timestamp of the first dumped tensor across all devices. | [
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Returns:
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"""
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tfwu/FaceDetection-ConvNet-3D | f9251c48eb40c5aec8fba7455115c355466555be | python/build/lib.linux-x86_64-2.7/mxnet/executor_manager.py | python | DataParallelExecutorGroup.update_metric | (self, metric, labels) | Update evaluation metric with label and current outputs | Update evaluation metric with label and current outputs | [
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""" Update evaluation metric with label and current outputs """
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labels_slice = [label[islice] for label in labels]
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NicknineTheEagle/TF2-Base | 20459c5a7fbc995b6bf54fa85c2f62a101e9fb64 | src/thirdparty/protobuf-2.3.0/python/google/protobuf/internal/wire_format.py | python | _VarUInt64ByteSizeNoTag | (uint64) | return 10 | Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
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uint64 must be unsigned.
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if uint64 <= 0x7f: return 1
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if uint64 <= 0xfffffff: return 4
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D-X-Y/caffe-faster-rcnn | eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb | scripts/cpp_lint.py | python | FindNextMultiLineCommentStart | (lines, lineix) | return len(lines) | Find the beginning marker for a multiline comment. | Find the beginning marker for a multiline comment. | [
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"""Find the beginning marker for a multiline comment."""
while lineix < len(lines):
if lines[lineix].strip().startswith('/*'):
# Only return this marker if the comment goes beyond this line
if lines[lineix].strip().find('*/', 2) < 0:
return lineix
lineix += 1
return len(lines) | [
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potassco/clingo | e0c91d8f95cc28de1c480a871f9c97c30de83d40 | libpyclingo/clingo/ast.py | python | ShowTerm | (location: Location, term: AST, body: Sequence[AST], csp: int) | return AST(p_ast[0]) | Construct an AST node of type `ASTType.ShowTerm`. | Construct an AST node of type `ASTType.ShowTerm`. | [
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'''
Construct an AST node of type `ASTType.ShowTerm`.
'''
p_ast = _ffi.new('clingo_ast_t**')
c_location = _c_location(location)
_handle_error(_lib.clingo_ast_build(
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_ffi.cast('size_t', len(body)),
_ffi.cast('int', csp)))
return AST(p_ast[0]) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/textwrap.py | python | TextWrapper._fix_sentence_endings | (self, chunks) | _fix_sentence_endings(chunks : [string])
Correct for sentence endings buried in 'chunks'. Eg. when the
original text contains "... foo.\\nBar ...", munge_whitespace()
and split() will convert that to [..., "foo.", " ", "Bar", ...]
which has one too few spaces; this method simply changes the one
space to two. | _fix_sentence_endings(chunks : [string]) | [
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"""_fix_sentence_endings(chunks : [string])
Correct for sentence endings buried in 'chunks'. Eg. when the
original text contains "... foo.\\nBar ...", munge_whitespace()
and split() will convert that to [..., "foo.", " ", "Bar", ...]
which has one too few spaces; this method simply changes the one
space to two.
"""
i = 0
patsearch = self.sentence_end_re.search
while i < len(chunks)-1:
if chunks[i+1] == " " and patsearch(chunks[i]):
chunks[i+1] = " "
i += 2
else:
i += 1 | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/cuda/cudadrv/driver.py | python | device_memset | (dst, val, size, stream=0) | Memset on the device.
If stream is not zero, asynchronous mode is used.
dst: device memory
val: byte value to be written
size: number of byte to be written
stream: a CUDA stream | Memset on the device.
If stream is not zero, asynchronous mode is used. | [
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"""Memset on the device.
If stream is not zero, asynchronous mode is used.
dst: device memory
val: byte value to be written
size: number of byte to be written
stream: a CUDA stream
"""
varargs = []
if stream:
assert isinstance(stream, Stream)
fn = driver.cuMemsetD8Async
varargs.append(stream.handle)
else:
fn = driver.cuMemsetD8
fn(device_pointer(dst), val, size, *varargs) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/factorization/python/ops/gmm.py | python | GMM.__init__ | (self,
num_clusters,
model_dir=None,
random_seed=0,
params='wmc',
initial_clusters='random',
covariance_type='full',
batch_size=128,
steps=10,
continue_training=False,
config=None,
verbose=1) | Creates a model for running GMM training and inference.
Args:
num_clusters: number of clusters to train.
model_dir: the directory to save the model results and log files.
random_seed: Python integer. Seed for PRNG used to initialize centers.
params: Controls which parameters are updated in the training process.
Can contain any combination of "w" for weights, "m" for means,
and "c" for covars.
initial_clusters: specifies how to initialize the clusters for training.
See gmm_ops.gmm for the possible values.
covariance_type: one of "full", "diag".
batch_size: See TensorFlowEstimator
steps: See TensorFlowEstimator
continue_training: See TensorFlowEstimator
config: See TensorFlowEstimator
verbose: See TensorFlowEstimator | Creates a model for running GMM training and inference. | [
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model_dir=None,
random_seed=0,
params='wmc',
initial_clusters='random',
covariance_type='full',
batch_size=128,
steps=10,
continue_training=False,
config=None,
verbose=1):
"""Creates a model for running GMM training and inference.
Args:
num_clusters: number of clusters to train.
model_dir: the directory to save the model results and log files.
random_seed: Python integer. Seed for PRNG used to initialize centers.
params: Controls which parameters are updated in the training process.
Can contain any combination of "w" for weights, "m" for means,
and "c" for covars.
initial_clusters: specifies how to initialize the clusters for training.
See gmm_ops.gmm for the possible values.
covariance_type: one of "full", "diag".
batch_size: See TensorFlowEstimator
steps: See TensorFlowEstimator
continue_training: See TensorFlowEstimator
config: See TensorFlowEstimator
verbose: See TensorFlowEstimator
"""
super(GMM, self).__init__(
model_dir=model_dir,
config=config)
self.batch_size = batch_size
self.steps = steps
self.continue_training = continue_training
self.verbose = verbose
self._num_clusters = num_clusters
self._params = params
self._training_initial_clusters = initial_clusters
self._covariance_type = covariance_type
self._training_graph = None
self._random_seed = random_seed | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_controls.py | python | ToolBarToolBase.SetToggle | (*args, **kwargs) | return _controls_.ToolBarToolBase_SetToggle(*args, **kwargs) | SetToggle(self, bool toggle) -> bool | SetToggle(self, bool toggle) -> bool | [
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"""SetToggle(self, bool toggle) -> bool"""
return _controls_.ToolBarToolBase_SetToggle(*args, **kwargs) | [
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lammps/lammps | b75c3065430a75b1b5543a10e10f46d9b4c91913 | tools/i-pi/ipi/engine/ensembles.py | python | NPTEnsemble.step | (self) | NPT time step.
Note that the barostat only propagates the centroid coordinates. If this
approximation is made a centroid virial pressure and stress estimator can
be defined, so this gives the best statistical convergence. This is
allowed as the normal mode propagation is approximately unaffected
by volume fluctuations as long as the system box is much larger than
the radius of gyration of the ring polymers. | NPT time step. | [
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] | def step(self):
"""NPT time step.
Note that the barostat only propagates the centroid coordinates. If this
approximation is made a centroid virial pressure and stress estimator can
be defined, so this gives the best statistical convergence. This is
allowed as the normal mode propagation is approximately unaffected
by volume fluctuations as long as the system box is much larger than
the radius of gyration of the ring polymers.
"""
self.ttime = -time.time()
self.thermostat.step()
self.barostat.thermostat.step()
self.rmcom()
self.ttime += time.time()
self.ptime = -time.time()
self.barostat.pstep()
self.ptime += time.time()
self.qtime = -time.time()
self.barostat.qcstep()
self.nm.free_qstep()
self.qtime += time.time()
self.ptime -= time.time()
self.barostat.pstep()
self.ptime += time.time()
self.ttime -= time.time()
self.barostat.thermostat.step()
self.thermostat.step()
self.rmcom()
self.ttime += time.time() | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/google/protobuf-py/google/protobuf/descriptor.py | python | FileDescriptor.CopyToProto | (self, proto) | Copies this to a descriptor_pb2.FileDescriptorProto.
Args:
proto: An empty descriptor_pb2.FileDescriptorProto. | Copies this to a descriptor_pb2.FileDescriptorProto. | [
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"""Copies this to a descriptor_pb2.FileDescriptorProto.
Args:
proto: An empty descriptor_pb2.FileDescriptorProto.
"""
proto.ParseFromString(self.serialized_pb) | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | tools/update-packaging/make_incremental_updates.py | python | create_add_patch_for_file | (to_marfile_entry, patch_info) | Copy the file to the working dir, add the add instruction, and add it to the list of archive files | Copy the file to the working dir, add the add instruction, and add it to the list of archive files | [
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""" Copy the file to the working dir, add the add instruction, and add it to the list of archive files """
copy_file(to_marfile_entry.abs_path, os.path.join(patch_info.work_dir, to_marfile_entry.name))
patch_info.append_add_instruction(to_marfile_entry.name)
patch_info.archive_files.append('"'+to_marfile_entry.name+'"') | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/plan/robotcspace.py | python | ClosedLoopRobotCSpace.setIKActiveDofs | (self,activeSet) | Marks that only a subset of the DOFs of the robot are to be used for solving
the IK constraint. | Marks that only a subset of the DOFs of the robot are to be used for solving
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"""Marks that only a subset of the DOFs of the robot are to be used for solving
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/shutil.py | python | unpack_archive | (filename, extract_dir=None, format=None) | Unpack an archive.
`filename` is the name of the archive.
`extract_dir` is the name of the target directory, where the archive
is unpacked. If not provided, the current working directory is used.
`format` is the archive format: one of "zip", "tar", "gztar", "bztar",
or "xztar". Or any other registered format. If not provided,
unpack_archive will use the filename extension and see if an unpacker
was registered for that extension.
In case none is found, a ValueError is raised. | Unpack an archive. | [
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] | def unpack_archive(filename, extract_dir=None, format=None):
"""Unpack an archive.
`filename` is the name of the archive.
`extract_dir` is the name of the target directory, where the archive
is unpacked. If not provided, the current working directory is used.
`format` is the archive format: one of "zip", "tar", "gztar", "bztar",
or "xztar". Or any other registered format. If not provided,
unpack_archive will use the filename extension and see if an unpacker
was registered for that extension.
In case none is found, a ValueError is raised.
"""
if extract_dir is None:
extract_dir = os.getcwd()
extract_dir = os.fspath(extract_dir)
filename = os.fspath(filename)
if format is not None:
try:
format_info = _UNPACK_FORMATS[format]
except KeyError:
raise ValueError("Unknown unpack format '{0}'".format(format)) from None
func = format_info[1]
func(filename, extract_dir, **dict(format_info[2]))
else:
# we need to look at the registered unpackers supported extensions
format = _find_unpack_format(filename)
if format is None:
raise ReadError("Unknown archive format '{0}'".format(filename))
func = _UNPACK_FORMATS[format][1]
kwargs = dict(_UNPACK_FORMATS[format][2])
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arangodb/arangodb | 0d658689c7d1b721b314fa3ca27d38303e1570c8 | 3rdParty/V8/v7.9.317/third_party/jinja2/utils.py | python | clear_caches | () | Jinja2 keeps internal caches for environments and lexers. These are
used so that Jinja2 doesn't have to recreate environments and lexers all
the time. Normally you don't have to care about that but if you are
measuring memory consumption you may want to clean the caches. | Jinja2 keeps internal caches for environments and lexers. These are
used so that Jinja2 doesn't have to recreate environments and lexers all
the time. Normally you don't have to care about that but if you are
measuring memory consumption you may want to clean the caches. | [
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"""Jinja2 keeps internal caches for environments and lexers. These are
used so that Jinja2 doesn't have to recreate environments and lexers all
the time. Normally you don't have to care about that but if you are
measuring memory consumption you may want to clean the caches.
"""
from jinja2.environment import _spontaneous_environments
from jinja2.lexer import _lexer_cache
_spontaneous_environments.clear()
_lexer_cache.clear() | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_misc.py | python | Log_DoCreateOnDemand | (*args) | return _misc_.Log_DoCreateOnDemand(*args) | Log_DoCreateOnDemand() | Log_DoCreateOnDemand() | [
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"""Log_DoCreateOnDemand()"""
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/computation/pytables.py | python | BinOp.is_in_table | (self) | return self.queryables.get(self.lhs) is not None | return True if this is a valid column name for generation (e.g. an
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"""
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return self.queryables.get(self.lhs) is not None | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | chrome/common/extensions/docs/server2/compiled_file_system.py | python | SingleFile | (fn) | return fn | A decorator which can be optionally applied to the compilation function
passed to CompiledFileSystem.Create, indicating that the function only
needs access to the file which is given in the function's callback. When
this is the case some optimisations can be done.
Note that this decorator must be listed first in any list of decorators to
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_SINGLE_FILE_FUNCTIONS.add(fn)
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/cython/Cython/Compiler/ExprNodes.py | python | BufferIndexNode.buffer_lookup_code | (self, code) | return buffer_entry, Buffer.put_buffer_lookup_code(
entry=buffer_entry,
index_signeds=[ivar.type.signed for ivar in self.indices],
index_cnames=index_temps,
directives=code.globalstate.directives,
pos=self.pos, code=code,
negative_indices=negative_indices,
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"""
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if self.is_buffer_access or self.is_memview_index:
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self.index_temps = index_temps = [self.get_index_in_temp(code,ivar) for ivar in self.indices]
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buffer_entry = self.buffer_entry()
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Source/bindings/scripts/generate_global_constructors.py | python | interface_name_to_constructors | (interface_name) | return flatten_list(global_name_to_constructors[global_name]
for global_name in global_names) | Returns constructors for an interface. | Returns constructors for an interface. | [
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] | def interface_name_to_constructors(interface_name):
"""Returns constructors for an interface."""
global_names = interface_name_to_global_names[interface_name]
return flatten_list(global_name_to_constructors[global_name]
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/botocore/docs/method.py | python | document_custom_signature | (section, name, method,
include=None, exclude=None) | Documents the signature of a custom method
:param section: The section to write the documentation to.
:param name: The name of the method
:param method: The handle to the method being documented
:type include: Dictionary where keys are parameter names and
values are the shapes of the parameter names.
:param include: The parameter shapes to include in the documentation.
:type exclude: List of the names of the parameters to exclude.
:param exclude: The names of the parameters to exclude from
documentation. | Documents the signature of a custom method | [
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] | def document_custom_signature(section, name, method,
include=None, exclude=None):
"""Documents the signature of a custom method
:param section: The section to write the documentation to.
:param name: The name of the method
:param method: The handle to the method being documented
:type include: Dictionary where keys are parameter names and
values are the shapes of the parameter names.
:param include: The parameter shapes to include in the documentation.
:type exclude: List of the names of the parameters to exclude.
:param exclude: The names of the parameters to exclude from
documentation.
"""
args, varargs, keywords, defaults = inspect.getargspec(method)
args = args[1:]
signature_params = inspect.formatargspec(
args, varargs, keywords, defaults)
signature_params = signature_params.lstrip('(')
signature_params = signature_params.rstrip(')')
section.style.start_sphinx_py_method(name, signature_params) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/robotparser.py | python | RobotFileParser.mtime | (self) | return self.last_checked | Returns the time the robots.txt file was last fetched.
This is useful for long-running web spiders that need to
check for new robots.txt files periodically. | Returns the time the robots.txt file was last fetched. | [
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"""Returns the time the robots.txt file was last fetched.
This is useful for long-running web spiders that need to
check for new robots.txt files periodically.
"""
return self.last_checked | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py2/sklearn/dummy.py | python | DummyRegressor.predict | (self, X) | return y | Perform classification on test vectors X.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Input vectors, where n_samples is the number of samples
and n_features is the number of features.
Returns
-------
y : array, shape = [n_samples] or [n_samples, n_outputs]
Predicted target values for X. | Perform classification on test vectors X. | [
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] | def predict(self, X):
"""
Perform classification on test vectors X.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Input vectors, where n_samples is the number of samples
and n_features is the number of features.
Returns
-------
y : array, shape = [n_samples] or [n_samples, n_outputs]
Predicted target values for X.
"""
check_is_fitted(self, "constant_")
X = check_array(X, accept_sparse=['csr', 'csc', 'coo'])
n_samples = X.shape[0]
y = np.ones((n_samples, 1)) * self.constant_
if self.n_outputs_ == 1 and not self.output_2d_:
y = np.ravel(y)
return y | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/wizard.py | python | WizardEvent.GetDirection | (*args, **kwargs) | return _wizard.WizardEvent_GetDirection(*args, **kwargs) | GetDirection(self) -> bool | GetDirection(self) -> bool | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Tools/Scripts/logmerge.py | python | digest_chunk | (chunk, branch=None) | return records | Digest a chunk -- extract working file name and revisions | Digest a chunk -- extract working file name and revisions | [
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lines = chunk[0]
key = 'Working file:'
keylen = len(key)
for line in lines:
if line[:keylen] == key:
working_file = line[keylen:].strip()
break
else:
working_file = None
if branch is None:
pass
elif branch == "HEAD":
branch = re.compile(r"^\d+\.\d+$")
else:
revisions = {}
key = 'symbolic names:\n'
found = 0
for line in lines:
if line == key:
found = 1
elif found:
if line[0] in '\t ':
tag, rev = line.split()
if tag[-1] == ':':
tag = tag[:-1]
revisions[tag] = rev
else:
found = 0
rev = revisions.get(branch)
branch = re.compile(r"^<>$") # <> to force a mismatch by default
if rev:
if rev.find('.0.') >= 0:
rev = rev.replace('.0.', '.')
branch = re.compile(r"^" + re.escape(rev) + r"\.\d+$")
records = []
for lines in chunk[1:]:
revline = lines[0]
dateline = lines[1]
text = lines[2:]
words = dateline.split()
author = None
if len(words) >= 3 and words[0] == 'date:':
dateword = words[1]
timeword = words[2]
if timeword[-1:] == ';':
timeword = timeword[:-1]
date = dateword + ' ' + timeword
if len(words) >= 5 and words[3] == 'author:':
author = words[4]
if author[-1:] == ';':
author = author[:-1]
else:
date = None
text.insert(0, revline)
words = revline.split()
if len(words) >= 2 and words[0] == 'revision':
rev = words[1]
else:
# No 'revision' line -- weird...
rev = None
text.insert(0, revline)
if branch:
if rev is None or not branch.match(rev):
continue
records.append((date, working_file, rev, author, text))
return records | [
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psi4/psi4 | be533f7f426b6ccc263904e55122899b16663395 | psi4/driver/procrouting/proc.py | python | select_mp2 | (name, **kwargs) | Function selecting the algorithm for a MP2 energy call
and directing to specified or best-performance default modules. | Function selecting the algorithm for a MP2 energy call
and directing to specified or best-performance default modules. | [
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] | def select_mp2(name, **kwargs):
"""Function selecting the algorithm for a MP2 energy call
and directing to specified or best-performance default modules.
"""
reference = core.get_option('SCF', 'REFERENCE')
mtd_type = core.get_global_option('MP2_TYPE')
module = core.get_global_option('QC_MODULE')
# Considering only [df]occ/dfmp2/detci/fnocc
# MP2_TYPE exists largely for py-side reasoning, so must manage it
# here rather than passing to c-side unprepared for validation
func = None
if reference == 'RHF':
if mtd_type == 'CONV':
if module == 'DETCI':
func = run_detci
elif module == 'FNOCC':
func = run_fnocc
elif module in ['', 'OCC']:
func = run_occ
elif mtd_type == 'DF':
if module == 'OCC':
func = run_dfocc
elif module in ['', 'DFMP2']:
func = run_dfmp2
elif mtd_type == 'CD':
if module in ['', 'OCC']:
func = run_dfocc
elif reference == 'UHF':
if mtd_type == 'CONV':
if module in ['', 'OCC']:
func = run_occ
elif mtd_type == 'DF':
if module == 'OCC':
func = run_dfocc
elif module in ['', 'DFMP2']:
func = run_dfmp2
elif mtd_type == 'CD':
if module in ['', 'OCC']:
func = run_dfocc
elif reference == 'ROHF':
if mtd_type == 'CONV':
if module == 'DETCI':
func = run_detci
elif module in ['', 'OCC']:
func = run_occ
elif mtd_type == 'DF':
if module == 'OCC':
func = run_dfocc
elif module in ['', 'DFMP2']:
func = run_dfmp2
elif mtd_type == 'CD':
if module in ['', 'OCC']:
func = run_dfocc
elif reference in ['RKS', 'UKS']:
if mtd_type == 'DF':
if module in ['', 'DFMP2']:
func = run_dfmp2
if module == 'DETCI':
core.print_out("""\nDETCI is ill-advised for method MP2 as it is available inefficiently as a """
"""byproduct of a CISD computation.\n DETCI ROHF MP2 will produce non-standard results.\n""")
if func is None:
raise ManagedMethodError(['select_mp2', name, 'MP2_TYPE', mtd_type, reference, module])
if kwargs.pop('probe', False):
return
else:
return func(name, **kwargs) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/protobuf/py3/google/protobuf/json_format.py | python | MessageToDict | (
message,
including_default_value_fields=False,
preserving_proto_field_name=False,
use_integers_for_enums=False,
descriptor_pool=None,
float_precision=None) | return printer._MessageToJsonObject(message) | Converts protobuf message to a dictionary.
When the dictionary is encoded to JSON, it conforms to proto3 JSON spec.
Args:
message: The protocol buffers message instance to serialize.
including_default_value_fields: If True, singular primitive fields,
repeated fields, and map fields will always be serialized. If
False, only serialize non-empty fields. Singular message fields
and oneof fields are not affected by this option.
preserving_proto_field_name: If True, use the original proto field
names as defined in the .proto file. If False, convert the field
names to lowerCamelCase.
use_integers_for_enums: If true, print integers instead of enum names.
descriptor_pool: A Descriptor Pool for resolving types. If None use the
default.
float_precision: If set, use this to specify float field valid digits.
Returns:
A dict representation of the protocol buffer message. | Converts protobuf message to a dictionary. | [
"Converts",
"protobuf",
"message",
"to",
"a",
"dictionary",
"."
] | def MessageToDict(
message,
including_default_value_fields=False,
preserving_proto_field_name=False,
use_integers_for_enums=False,
descriptor_pool=None,
float_precision=None):
"""Converts protobuf message to a dictionary.
When the dictionary is encoded to JSON, it conforms to proto3 JSON spec.
Args:
message: The protocol buffers message instance to serialize.
including_default_value_fields: If True, singular primitive fields,
repeated fields, and map fields will always be serialized. If
False, only serialize non-empty fields. Singular message fields
and oneof fields are not affected by this option.
preserving_proto_field_name: If True, use the original proto field
names as defined in the .proto file. If False, convert the field
names to lowerCamelCase.
use_integers_for_enums: If true, print integers instead of enum names.
descriptor_pool: A Descriptor Pool for resolving types. If None use the
default.
float_precision: If set, use this to specify float field valid digits.
Returns:
A dict representation of the protocol buffer message.
"""
printer = _Printer(
including_default_value_fields,
preserving_proto_field_name,
use_integers_for_enums,
descriptor_pool,
float_precision=float_precision)
# pylint: disable=protected-access
return printer._MessageToJsonObject(message) | [
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jeog/TOSDataBridge | 6a5a08ca5cf3883db1f12e9bc89ef374d098df5a | python/tosdb/__init__.py | python | VInit | (address, dllpath=None, root="C:\\", password=None, timeout=DEF_TIMEOUT) | Manage a virtual 'session' with a host system's C lib, engine, and TOS platform.
The context manager handles initialization of the virtual admin interface
and the host C Lib, then tries to connect the latter with the engine and
TOS platform on the host. On exiting the context block it automatically
cleans up the host system and closes down the connection.
with VInit(...):
# (automatically initializes, connects etc.)
# use virtual admin interface, create data blocks etc.
# (automatically cleans up, closes etc.)
VInit(address, dllpath=None, root="C:\\", password=None, timeout=DEF_TIMEOUT)
address :: (str,int) :: (address of the host system, port)
dllpath :: str :: exact path of the DLL -or-
root :: str :: directory to start walking/searching to find the DLL
password :: str :: password for authentication(None for no authentication)
timeout :: int :: timeout used by the underlying socket
throws TOSDB_VirtualizationError TOSDB_InitError | Manage a virtual 'session' with a host system's C lib, engine, and TOS platform. | [
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] | def VInit(address, dllpath=None, root="C:\\", password=None, timeout=DEF_TIMEOUT):
""" Manage a virtual 'session' with a host system's C lib, engine, and TOS platform.
The context manager handles initialization of the virtual admin interface
and the host C Lib, then tries to connect the latter with the engine and
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# (automatically initializes, connects etc.)
# use virtual admin interface, create data blocks etc.
# (automatically cleans up, closes etc.)
VInit(address, dllpath=None, root="C:\\", password=None, timeout=DEF_TIMEOUT)
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password :: str :: password for authentication(None for no authentication)
timeout :: int :: timeout used by the underlying socket
throws TOSDB_VirtualizationError TOSDB_InitError
"""
try:
admin_init(address, password, timeout)
if not vinit(dllpath, root):
raise TOSDB_InitError("failed to initilize library (virtual)")
if not vconnected():
if not vconnect(): # try again
raise TOSDB_InitError("failed to connect to library (virtual)")
yield
finally:
vclean_up()
admin_close() | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/mimetools.py | python | decode | (input, output, encoding) | Decode common content-transfer-encodings (base64, quopri, uuencode). | Decode common content-transfer-encodings (base64, quopri, uuencode). | [
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"""Decode common content-transfer-encodings (base64, quopri, uuencode)."""
if encoding == 'base64':
import base64
return base64.decode(input, output)
if encoding == 'quoted-printable':
import quopri
return quopri.decode(input, output)
if encoding in ('uuencode', 'x-uuencode', 'uue', 'x-uue'):
import uu
return uu.decode(input, output)
if encoding in ('7bit', '8bit'):
return output.write(input.read())
if encoding in decodetab:
pipethrough(input, decodetab[encoding], output)
else:
raise ValueError, \
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/win/toolchain/toolchain.py | python | CopyToFinalLocation2010 | (extracted, target_dir) | Copy all the directories we need to the target location. | Copy all the directories we need to the target location. | [
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"directories",
"we",
"need",
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"the",
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"."
] | def CopyToFinalLocation2010(extracted, target_dir):
"""Copy all the directories we need to the target location."""
sys.stdout.write('Pulling together required pieces...\n')
# Note that order is important because some of the older ones are
# overwritten by updates.
from_sdk = [(r'Windows Kits\8.0', r'win8sdk')]
PullFrom(from_sdk, extracted.sdk_path, target_dir)
from_metro_sdk = [(r'Windows Kits\8.0', r'win8sdk')]
PullFrom(from_sdk, extracted.metro_sdk_path, target_dir)
from_buildtools_x86 = [
(r'WinDDK\7600.16385.win7_wdk.100208-1538\bin\x86', r'WDK\bin'),
]
PullFrom(from_buildtools_x86, extracted.buildtools_x86, target_dir)
from_buildtools_x64 = [
(r'WinDDK\7600.16385.win7_wdk.100208-1538\bin\amd64', r'WDK\bin'),
]
PullFrom(from_buildtools_x64, extracted.buildtools_x64, target_dir)
from_libs_x86 = [
(r'WinDDK\7600.16385.win7_wdk.100208-1538\lib', r'WDK\lib'),
]
PullFrom(from_libs_x86, extracted.libs_x86, target_dir)
from_libs_x64 = [
(r'WinDDK\7600.16385.win7_wdk.100208-1538\lib', r'WDK\lib'),
]
PullFrom(from_libs_x64, extracted.libs_x64, target_dir)
from_headers = [
(r'WinDDK\7600.16385.win7_wdk.100208-1538\inc', r'WDK\inc'),
]
PullFrom(from_headers, extracted.headers, target_dir)
# The compiler update to get the SP1 compiler is a bit of a mess. See
# http://goo.gl/n1DeO. The summary is that update for the standalone compiler
# binary installs a broken set of headers. So, add an empty ammintrin.h since
# we don't actually need the contents of it (for Chromium).
from_sdk7_x86 = [
(r'Program Files\Microsoft Visual Studio 10.0', '.'),
(r'Win\System', r'VC\bin'),
]
PullFrom(from_sdk7_x86, extracted.vc_x86, target_dir)
from_sdk7_x64 =[
(r'Program Files(64)\Microsoft Visual Studio 10.0', '.'),
(r'Win\System64', r'VC\bin\amd64'),
]
PullFrom(from_sdk7_x64, extracted.vc_x64, target_dir)
from_vcupdate_x86 = [
(r'Program Files\Microsoft Visual Studio 10.0', '.'),
(r'Win\System', r'VC\bin'),
]
PullFrom(from_vcupdate_x86, extracted.update_x86, target_dir)
from_vcupdate_x64 = [
(r'Program Files(64)\Microsoft Visual Studio 10.0', '.'),
(r'Win\System64', r'VC\bin\amd64'),
]
PullFrom(from_vcupdate_x64, extracted.update_x64, target_dir)
sys.stdout.write('Stubbing ammintrin.h...\n')
open(os.path.join(target_dir, r'VC\include\ammintrin.h'), 'w').close()
from_dxsdk = [
(r'DXSDK\Include', r'DXSDK\Include'),
(r'DXSDK\Lib', r'DXSDK\Lib'),
(r'DXSDK\Redist', r'DXSDK\Redist'),
]
PullFrom(from_dxsdk, extracted.dxsdk, target_dir) | [
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] | https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/win/toolchain/toolchain.py#L426-L500 | ||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/html.py | python | HtmlRenderingInfo.__init__ | (self, *args, **kwargs) | __init__(self) -> HtmlRenderingInfo | __init__(self) -> HtmlRenderingInfo | [
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"(",
"self",
")",
"-",
">",
"HtmlRenderingInfo"
] | def __init__(self, *args, **kwargs):
"""__init__(self) -> HtmlRenderingInfo"""
_html.HtmlRenderingInfo_swiginit(self,_html.new_HtmlRenderingInfo(*args, **kwargs)) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/platform/benchmark.py | python | _global_report_benchmark | (
name, iters=None, cpu_time=None, wall_time=None,
throughput=None, extras=None, metrics=None) | Method for recording a benchmark directly.
Args:
name: The BenchmarkEntry name.
iters: (optional) How many iterations were run
cpu_time: (optional) Total cpu time in seconds
wall_time: (optional) Total wall time in seconds
throughput: (optional) Throughput (in MB/s)
extras: (optional) Dict mapping string keys to additional benchmark info.
metrics: (optional) A list of dict representing metrics generated by the
benchmark. Each dict should contain keys 'name' and'value'. A dict
can optionally contain keys 'min_value' and 'max_value'.
Raises:
TypeError: if extras is not a dict.
IOError: if the benchmark output file already exists. | Method for recording a benchmark directly. | [
"Method",
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] | def _global_report_benchmark(
name, iters=None, cpu_time=None, wall_time=None,
throughput=None, extras=None, metrics=None):
"""Method for recording a benchmark directly.
Args:
name: The BenchmarkEntry name.
iters: (optional) How many iterations were run
cpu_time: (optional) Total cpu time in seconds
wall_time: (optional) Total wall time in seconds
throughput: (optional) Throughput (in MB/s)
extras: (optional) Dict mapping string keys to additional benchmark info.
metrics: (optional) A list of dict representing metrics generated by the
benchmark. Each dict should contain keys 'name' and'value'. A dict
can optionally contain keys 'min_value' and 'max_value'.
Raises:
TypeError: if extras is not a dict.
IOError: if the benchmark output file already exists.
"""
logging.info("Benchmark [%s] iters: %d, wall_time: %g, cpu_time: %g,"
"throughput: %g, extras: %s, metrics: %s", name,
iters if iters is not None else -1,
wall_time if wall_time is not None else -1,
cpu_time if cpu_time is not None else -1,
throughput if throughput is not None else -1,
str(extras) if extras else "None",
str(metrics) if metrics else "None")
entries = test_log_pb2.BenchmarkEntries()
entry = entries.entry.add()
entry.name = name
if iters is not None:
entry.iters = iters
if cpu_time is not None:
entry.cpu_time = cpu_time
if wall_time is not None:
entry.wall_time = wall_time
if throughput is not None:
entry.throughput = throughput
if extras is not None:
if not isinstance(extras, dict):
raise TypeError("extras must be a dict")
for (k, v) in extras.items():
if isinstance(v, numbers.Number):
entry.extras[k].double_value = v
else:
entry.extras[k].string_value = str(v)
if metrics is not None:
if not isinstance(metrics, list):
raise TypeError("metrics must be a list")
for metric in metrics:
if "name" not in metric:
raise TypeError("metric must has a 'name' field")
if "value" not in metric:
raise TypeError("metric must has a 'value' field")
metric_entry = entry.metrics.add()
metric_entry.name = metric["name"]
metric_entry.value = metric["value"]
if "min_value" in metric:
metric_entry.min_value.value = metric["min_value"]
if "max_value" in metric:
metric_entry.max_value.value = metric["max_value"]
test_env = os.environ.get(TEST_REPORTER_TEST_ENV, None)
if test_env is None:
# Reporting was not requested, just print the proto
print(str(entries))
return
serialized_entry = entries.SerializeToString()
mangled_name = name.replace("/", "__")
output_path = "%s%s" % (test_env, mangled_name)
if gfile.Exists(output_path):
raise IOError("File already exists: %s" % output_path)
with gfile.GFile(output_path, "wb") as out:
out.write(serialized_entry) | [
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kushview/Element | 1cc16380caa2ab79461246ba758b9de1f46db2a5 | waflib/Logs.py | python | init_log | () | Initializes the logger :py:attr:`waflib.Logs.log` | Initializes the logger :py:attr:`waflib.Logs.log` | [
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"logger",
":",
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":",
"attr",
":",
"waflib",
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] | def init_log():
"""
Initializes the logger :py:attr:`waflib.Logs.log`
"""
global log
log = logging.getLogger('waflib')
log.handlers = []
log.filters = []
hdlr = log_handler()
hdlr.setFormatter(formatter())
log.addHandler(hdlr)
log.addFilter(log_filter())
log.setLevel(logging.DEBUG) | [
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KhronosGroup/Vulkan-Headers | b32da5329b50e3cb96229aaecba9ded032fe29cc | registry/generator.py | python | OutputGenerator.newline | (self) | Print a newline to the output file (utility function) | Print a newline to the output file (utility function) | [
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] | def newline(self):
"""Print a newline to the output file (utility function)"""
write('', file=self.outFile) | [
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hyperledger-archives/iroha | ed579f85126d0e86532a1f4f1f6ce5681bbcd3a9 | docs/permissions_compiler/rst.py | python | excerpt | (permission) | return result | Renders source file listing
:param permission: name of permission to list, used as a part of filename
:return: rst lines | Renders source file listing
:param permission: name of permission to list, used as a part of filename
:return: rst lines | [
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] | def excerpt(permission):
"""
Renders source file listing
:param permission: name of permission to list, used as a part of filename
:return: rst lines
"""
compile_time_path = [os.path.pardir, os.path.pardir, 'example', 'python', 'permissions', '{}.py'.format(permission)]
path = os.path.join(*compile_time_path)
result = []
if not os.path.isfile(path):
print(path)
return result
window = excerpt_boundaries(path)
result.extend(listing(compile_time_path, lines_range=window))
return result | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/learn/python/learn/monitors.py | python | EveryN.every_n_step_begin | (self, step) | return [] | Callback before every n'th step begins.
Args:
step: `int`, the current value of the global step.
Returns:
A `list` of tensors that will be evaluated at this step. | Callback before every n'th step begins. | [
"Callback",
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"begins",
"."
] | def every_n_step_begin(self, step): # pylint: disable=unused-argument
"""Callback before every n'th step begins.
Args:
step: `int`, the current value of the global step.
Returns:
A `list` of tensors that will be evaluated at this step.
"""
return [] | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/distributed/fleet/dataset/dataset.py | python | InMemoryDataset.load_into_memory | (self, is_shuffle=False) | :api_attr: Static Graph
Load data into memory
Args:
is_shuffle(bool): whether to use local shuffle, default is False
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
dataset = paddle.distributed.InMemoryDataset()
slots = ["slot1", "slot2", "slot3", "slot4"]
slots_vars = []
for slot in slots:
var = paddle.static.data(
name=slot, shape=[None, 1], dtype="int64", lod_level=1)
slots_vars.append(var)
dataset.init(
batch_size=1,
thread_num=2,
input_type=1,
pipe_command="cat",
use_var=slots_vars)
filelist = ["a.txt", "b.txt"]
dataset.set_filelist(filelist)
dataset.load_into_memory() | :api_attr: Static Graph
Load data into memory | [
":",
"api_attr",
":",
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] | def load_into_memory(self, is_shuffle=False):
"""
:api_attr: Static Graph
Load data into memory
Args:
is_shuffle(bool): whether to use local shuffle, default is False
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
dataset = paddle.distributed.InMemoryDataset()
slots = ["slot1", "slot2", "slot3", "slot4"]
slots_vars = []
for slot in slots:
var = paddle.static.data(
name=slot, shape=[None, 1], dtype="int64", lod_level=1)
slots_vars.append(var)
dataset.init(
batch_size=1,
thread_num=2,
input_type=1,
pipe_command="cat",
use_var=slots_vars)
filelist = ["a.txt", "b.txt"]
dataset.set_filelist(filelist)
dataset.load_into_memory()
"""
self._prepare_to_run()
if not self.use_ps_gpu:
self.dataset.load_into_memory()
elif core._is_compiled_with_heterps():
self.psgpu.set_dataset(self.dataset)
self.psgpu.load_into_memory(is_shuffle) | [
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bumptop/BumpTop | 466d23597a07ae738f4265262fa01087fc6e257c | trunk/win/Source/bin/jinja2/utils.py | python | LRUCache.keys | (self) | return list(self) | Return a list of all keys ordered by most recent usage. | Return a list of all keys ordered by most recent usage. | [
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"""Return a list of all keys ordered by most recent usage."""
return list(self) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_gdi.py | python | Locale.GetLanguageInfo | (*args, **kwargs) | return _gdi_.Locale_GetLanguageInfo(*args, **kwargs) | GetLanguageInfo(int lang) -> LanguageInfo | GetLanguageInfo(int lang) -> LanguageInfo | [
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"(",
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")",
"-",
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"""GetLanguageInfo(int lang) -> LanguageInfo"""
return _gdi_.Locale_GetLanguageInfo(*args, **kwargs) | [
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fabianschenk/REVO | eb949c0fdbcdf0be09a38464eb0592a90803947f | thirdparty/Sophus/py/sophus/se3.py | python | Se3.matrix | (self) | return (R.row_join(self.t)).col_join(sympy.Matrix(1, 4, [0, 0, 0, 1])) | returns matrix representation | returns matrix representation | [
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""" returns matrix representation """
R = self.so3.matrix()
return (R.row_join(self.t)).col_join(sympy.Matrix(1, 4, [0, 0, 0, 1])) | [
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CoolProp/CoolProp | 381c8535e5dec3eec27ad430ebbfff8bc9dfc008 | wrappers/Python/CoolProp/Plots/Common.py | python | BasePlot._set_axis_limits | (self, limits) | Set the limits of the internal axis object based on SI units,
takes [xmin, xmax, ymin, ymax] | Set the limits of the internal axis object based on SI units,
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oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/tools/inspector_protocol/jinja2/runtime.py | python | Context.super | (self, name, current) | return BlockReference(name, self, blocks, index) | Render a parent block. | Render a parent block. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/asyncio/base_events.py | python | BaseEventLoop.set_exception_handler | (self, handler) | Set handler as the new event loop exception handler.
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cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | PhysicsTools/PythonAnalysis/python/rootplot/root2matplotlib.py | python | replace | (string, replacements) | return string | Modify a string based on a list of patterns and substitutions.
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domino-team/openwrt-cc | 8b181297c34d14d3ca521cc9f31430d561dbc688 | package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/msvs_emulation.py | python | _AppendOrReturn | (append, element) | If |append| is None, simply return |element|. If |append| is not None,
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/grid.py | python | GridRangeSelectEvent.GetBottomRightCoords | (*args, **kwargs) | return _grid.GridRangeSelectEvent_GetBottomRightCoords(*args, **kwargs) | GetBottomRightCoords(self) -> GridCellCoords | GetBottomRightCoords(self) -> GridCellCoords | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/setuptools/py2/pkg_resources/_vendor/pyparsing.py | python | matchOnlyAtCol | (n) | return verifyCol | Helper method for defining parse actions that require matching at a specific
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/xml/sax/__init__.py | python | make_parser | (parser_list = []) | Creates and returns a SAX parser.
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_pytorch/pytorch_binding/pytorch_nndct/utils/logging.py | python | get_logger | () | Return logger instance. | Return logger instance. | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Fem/femtools/femutils.py | python | get_part_to_mesh | (mesh_obj) | gmsh mesh object: the Attribute is Part
netgen mesh object: the Attribute is Shape
other mesh objects: do not have a Attribute which holds the part to mesh | gmsh mesh object: the Attribute is Part
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/learn/python/learn/utils/saved_model_export_utils.py | python | BestModelSelector._get_best_eval_result | (self, event_files) | return best_eval_result | Get the best eval result from event files.
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] | def _get_best_eval_result(self, event_files):
"""Get the best eval result from event files.
Args:
event_files: Absolute pattern of event files.
Returns:
The best eval result.
"""
if not event_files:
return None
best_eval_result = None
for event_file in gfile.Glob(os.path.join(event_files)):
for event in summary_iterator.summary_iterator(event_file):
if event.HasField('summary'):
event_eval_result = {}
for value in event.summary.value:
if value.HasField('simple_value'):
event_eval_result[value.tag] = value.simple_value
if best_eval_result is None or self._compare_fn(
best_eval_result, event_eval_result):
best_eval_result = event_eval_result
return best_eval_result | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/DirectILLReduction.py | python | DirectILLReduction._convertToDistribution | (self, mainWS) | return mainWS | Convert the workspace into a distribution. | Convert the workspace into a distribution. | [
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] | def _convertToDistribution(self, mainWS):
"""Convert the workspace into a distribution."""
ConvertToDistribution(Workspace=mainWS,
EnableLogging=self._subalgLogging)
return mainWS | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/server/wsgi/serve/snippets/util/sparse_tree.py | python | _SetAbstractThroughRepeated | (parts, value, store, log) | Set value at parts, when the top of store is 'repeated'.
Complements _GeneralSetAbstract.
It is different from normal setting, in that we set corresponding field in
repeated elements (and their descendants).
In case we have pre-existing items of repeated element in store,
we set corresponding field in all the items.
If there are no items of repeated element in store, we add new item with index
value of zero and set field in that item. It is the case when corresponding
repeated snippet is only present in hard-masked snippets list.
Args:
parts: list of the elements of the path we're setting.
value: value we're setting at the path.
store: the multi-level dict representing our protobuf.
log: logging obj. | Set value at parts, when the top of store is 'repeated'. | [
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] | def _SetAbstractThroughRepeated(parts, value, store, log):
"""Set value at parts, when the top of store is 'repeated'.
Complements _GeneralSetAbstract.
It is different from normal setting, in that we set corresponding field in
repeated elements (and their descendants).
In case we have pre-existing items of repeated element in store,
we set corresponding field in all the items.
If there are no items of repeated element in store, we add new item with index
value of zero and set field in that item. It is the case when corresponding
repeated snippet is only present in hard-masked snippets list.
Args:
parts: list of the elements of the path we're setting.
value: value we're setting at the path.
store: the multi-level dict representing our protobuf.
log: logging obj.
"""
assert (parts and
parts[0] == "[]"), "expected element of path to be abstract index."
assert isinstance(store, dict)
if store:
# set field in pre-existing items of repeated element.
for index in store:
assert index.isdigit(), "expected store keys to be indexes."
substore = store.get(index, None)
if isinstance(substore, dict):
_GeneralSetAbstract(parts[1:], value, substore, log)
else:
# It breaks an invariant of the protobuf => sparse tree, to replace
# a primitive value with a subtree. Eg, trying to write
# 'a.b' = 2 to {'a': 1}. 'b' cannot be a sibling of 2. That would be
# the error we're trying to do here.
log.error(
"Programmer or data error; cannot write a subtree ([%s]) over"
" a primitive value (%s); that\'s an invariant of protobufs =>"
" sparse trees. Value ignored, but no further damage done. "
"%s" % (str(index), str(store), repr(traceback.extract_stack())))
else:
# Corresponding repeated element is only present in hard-masked snippets
# list.
# Note: hard-masked snippets list may only contain one item of repeated
# element.
key = "0" # There are no items so we set index value to zero.
store[key] = {}
substore = store[key]
_GeneralSetAbstract(parts[1:], value, substore, log) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/external/bazel_tools/tools/build_defs/docker/rewrite_json.py | python | DeepCopySkipNull | (data) | return copy.deepcopy(data) | Do a deep copy, skipping null entry. | Do a deep copy, skipping null entry. | [
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"a",
"deep",
"copy",
"skipping",
"null",
"entry",
"."
] | def DeepCopySkipNull(data):
"""Do a deep copy, skipping null entry."""
if type(data) == type(dict()):
return dict((DeepCopySkipNull(k), DeepCopySkipNull(v))
for k, v in data.iteritems() if v is not None)
return copy.deepcopy(data) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/llvmlite/binding/executionengine.py | python | ExecutionEngine.get_function_address | (self, name) | return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode("ascii")) | Return the address of the function named *name* as an integer.
It's a fatal error in LLVM if the symbol of *name* doesn't exist. | Return the address of the function named *name* as an integer. | [
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] | def get_function_address(self, name):
"""
Return the address of the function named *name* as an integer.
It's a fatal error in LLVM if the symbol of *name* doesn't exist.
"""
return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode("ascii")) | [
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okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_vendor/requests/cookies.py | python | get_cookie_header | (jar, request) | return r.get_new_headers().get('Cookie') | Produce an appropriate Cookie header string to be sent with `request`, or None.
:rtype: str | Produce an appropriate Cookie header string to be sent with `request`, or None. | [
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"""
Produce an appropriate Cookie header string to be sent with `request`, or None.
:rtype: str
"""
r = MockRequest(request)
jar.add_cookie_header(r)
return r.get_new_headers().get('Cookie') | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/PIL/PSDraw.py | python | PSDraw.end_document | (self) | Ends printing. (Write Postscript DSC footer.) | Ends printing. (Write Postscript DSC footer.) | [
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"""Ends printing. (Write Postscript DSC footer.)"""
self._fp_write("%%EndDocument\nrestore showpage\n%%End\n")
if hasattr(self.fp, "flush"):
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OpenGenus/cosmos | 1a94e8880068e51d571543be179c323936bd0936 | code/languages/python/web_programming/world_covid19_stats.py | python | world_covid19_stats | (url: str = "https://www.worldometers.info/coronavirus") | return {key.text.strip(): value.text.strip() for key, value in zip(keys, values)} | Return a dict of current worldwide COVID-19 statistics | Return a dict of current worldwide COVID-19 statistics | [
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"""
Return a dict of current worldwide COVID-19 statistics
"""
soup = BeautifulSoup(requests.get(url).text, "html.parser")
keys = soup.findAll("h1")
values = soup.findAll("div", {"class": "maincounter-number"})
keys += soup.findAll("span", {"class": "panel-title"})
values += soup.findAll("div", {"class": "number-table-main"})
return {key.text.strip(): value.text.strip() for key, value in zip(keys, values)} | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | gpu/command_buffer/build_gles2_cmd_buffer.py | python | Function.WriteServiceUnitTest | (self, file) | Writes the service implementation for a command. | Writes the service implementation for a command. | [
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"""Writes the service implementation for a command."""
self.type_handler.WriteServiceUnitTest(self, file) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py2/sklearn/decomposition/nmf.py | python | NMF.fit_transform | (self, X, y=None, W=None, H=None) | return W | Learn a NMF model for the data X and returns the transformed data.
This is more efficient than calling fit followed by transform.
Parameters
----------
X: {array-like, sparse matrix}, shape (n_samples, n_features)
Data matrix to be decomposed
W : array-like, shape (n_samples, n_components)
If init='custom', it is used as initial guess for the solution.
H : array-like, shape (n_components, n_features)
If init='custom', it is used as initial guess for the solution.
Returns
-------
W: array, shape (n_samples, n_components)
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"""Learn a NMF model for the data X and returns the transformed data.
This is more efficient than calling fit followed by transform.
Parameters
----------
X: {array-like, sparse matrix}, shape (n_samples, n_features)
Data matrix to be decomposed
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"""
X = check_array(X, accept_sparse=('csr', 'csc'))
W, H, n_iter_ = non_negative_factorization(
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tol=self.tol, max_iter=self.max_iter, alpha=self.alpha,
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shuffle=self.shuffle,
nls_max_iter=self.nls_max_iter, sparseness=self.sparseness,
beta=self.beta, eta=self.eta)
if self.solver == 'pg':
self.comp_sparseness_ = _sparseness(H.ravel())
self.data_sparseness_ = _sparseness(W.ravel())
self.reconstruction_err_ = _safe_compute_error(X, W, H)
self.n_components_ = H.shape[0]
self.components_ = H
self.n_iter_ = n_iter_
return W | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/python/ops/control_flow_ops.py | python | ZerosLikeOutsideLoop | (op, index) | Create zeros_like for the specified output of an op. | Create zeros_like for the specified output of an op. | [
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"""Create zeros_like for the specified output of an op."""
val = op.outputs[index]
if not IsSwitch(op):
return array_ops.zeros_like(val)
else:
op_ctxt = op._get_control_flow_context()
pred = op_ctxt.pred
branch = op_ctxt.branch
switch_val = switch(op.inputs[0], pred)[1 - branch]
zeros_shape = array_ops.shape(switch_val)
return array_ops.zeros(zeros_shape, dtype=val.dtype) | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/SConf.py | python | Streamer.getvalue | (self) | return self.s.getvalue() | Return everything written to orig since the Streamer was created. | Return everything written to orig since the Streamer was created. | [
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return self.s.getvalue() | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | python | _conv_block | (inputs, filters, alpha, kernel=(3, 3), strides=(1, 1)) | return Activation(relu6, name='conv1_relu')(x) | Adds an initial convolution layer (with batch normalization and relu6).
Arguments:
inputs: Input tensor of shape `(rows, cols, 3)`
(with `channels_last` data format) or
(3, rows, cols) (with `channels_first` data format).
It should have exactly 3 inputs channels,
and width and height should be no smaller than 32.
E.g. `(224, 224, 3)` would be one valid value.
filters: Integer, the dimensionality of the output space
(i.e. the number output of filters in the convolution).
alpha: controls the width of the network.
- If `alpha` < 1.0, proportionally decreases the number
of filters in each layer.
- If `alpha` > 1.0, proportionally increases the number
of filters in each layer.
- If `alpha` = 1, default number of filters from the paper
are used at each layer.
kernel: An integer or tuple/list of 2 integers, specifying the
width and height of the 2D convolution window.
Can be a single integer to specify the same value for
all spatial dimensions.
strides: An integer or tuple/list of 2 integers,
specifying the strides of the convolution along the width and height.
Can be a single integer to specify the same value for
all spatial dimensions.
Specifying any stride value != 1 is incompatible with specifying
any `dilation_rate` value != 1.
Input shape:
4D tensor with shape:
`(samples, channels, rows, cols)` if data_format='channels_first'
or 4D tensor with shape:
`(samples, rows, cols, channels)` if data_format='channels_last'.
Output shape:
4D tensor with shape:
`(samples, filters, new_rows, new_cols)` if data_format='channels_first'
or 4D tensor with shape:
`(samples, new_rows, new_cols, filters)` if data_format='channels_last'.
`rows` and `cols` values might have changed due to stride.
Returns:
Output tensor of block. | Adds an initial convolution layer (with batch normalization and relu6). | [
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"""Adds an initial convolution layer (with batch normalization and relu6).
Arguments:
inputs: Input tensor of shape `(rows, cols, 3)`
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4D tensor with shape:
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or 4D tensor with shape:
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or 4D tensor with shape:
`(samples, new_rows, new_cols, filters)` if data_format='channels_last'.
`rows` and `cols` values might have changed due to stride.
Returns:
Output tensor of block.
"""
channel_axis = 1 if K.image_data_format() == 'channels_first' else -1
filters = int(filters * alpha)
x = Conv2D(
filters,
kernel,
padding='same',
use_bias=False,
strides=strides,
name='conv1')(inputs)
x = BatchNormalization(axis=channel_axis, name='conv1_bn')(x)
return Activation(relu6, name='conv1_relu')(x) | [
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eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/python/bitstring/bitstring.py | python | Bits._readfloatle | (self, length, start) | Read bits and interpret as a little-endian float. | Read bits and interpret as a little-endian float. | [
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"""Read bits and interpret as a little-endian float."""
startbyte, offset = divmod(start + self._offset, 8)
if not offset:
if length == 32:
f, = struct.unpack('<f', bytes(self._datastore.getbyteslice(startbyte, startbyte + 4)))
elif length == 64:
f, = struct.unpack('<d', bytes(self._datastore.getbyteslice(startbyte, startbyte + 8)))
else:
if length == 32:
f, = struct.unpack('<f', self._readbytes(32, start))
elif length == 64:
f, = struct.unpack('<d', self._readbytes(64, start))
try:
return f
except NameError:
raise InterpretError("floats can only be 32 or 64 bits long, "
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/google_appengine_cloudstorage/cloudstorage/cloudstorage_api.py | python | open | (filename,
mode='r',
content_type=None,
options=None,
read_buffer_size=storage_api.ReadBuffer.DEFAULT_BUFFER_SIZE,
retry_params=None,
_account_id=None) | Opens a Google Cloud Storage file and returns it as a File-like object.
Args:
filename: A Google Cloud Storage filename of form '/bucket/filename'.
mode: 'r' for reading mode. 'w' for writing mode.
In reading mode, the file must exist. In writing mode, a file will
be created or be overrode.
content_type: The MIME type of the file. str. Only valid in writing mode.
options: A str->basestring dict to specify additional headers to pass to
GCS e.g. {'x-goog-acl': 'private', 'x-goog-meta-foo': 'foo'}.
Supported options are x-goog-acl, x-goog-meta-, cache-control,
content-disposition, and content-encoding.
Only valid in writing mode.
See https://developers.google.com/storage/docs/reference-headers
for details.
read_buffer_size: The buffer size for read. Read keeps a buffer
and prefetches another one. To minimize blocking for large files,
always read by buffer size. To minimize number of RPC requests for
small files, set a large buffer size. Max is 30MB.
retry_params: An instance of api_utils.RetryParams for subsequent calls
to GCS from this file handle. If None, the default one is used.
_account_id: Internal-use only.
Returns:
A reading or writing buffer that supports File-like interface. Buffer
must be closed after operations are done.
Raises:
errors.AuthorizationError: if authorization failed.
errors.NotFoundError: if an object that's expected to exist doesn't.
ValueError: invalid open mode or if content_type or options are specified
in reading mode. | Opens a Google Cloud Storage file and returns it as a File-like object. | [
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Raises:
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errors.NotFoundError: if an object that's expected to exist doesn't.
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"""
common.validate_file_path(filename)
api = storage_api._get_storage_api(retry_params=retry_params,
account_id=_account_id)
filename = api_utils._quote_filename(filename)
if mode == 'w':
common.validate_options(options)
return storage_api.StreamingBuffer(api, filename, content_type, options)
elif mode == 'r':
if content_type or options:
raise ValueError('Options and content_type can only be specified '
'for writing mode.')
return storage_api.ReadBuffer(api,
filename,
buffer_size=read_buffer_size)
else:
raise ValueError('Invalid mode %s.' % mode) | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/ttk.py | python | Treeview.set_children | (self, item, *newchildren) | Replaces item's child with newchildren.
Children present in item that are not present in newchildren
are detached from tree. No items in newchildren may be an
ancestor of item. | Replaces item's child with newchildren. | [
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self.tk.call(self._w, "children", item, newchildren) | [
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nasa/astrobee | 9241e67e6692810d6e275abb3165b6d02f4ca5ef | scripts/git/cpplint.py | python | FindNextMultiLineCommentEnd | (lines, lineix) | return len(lines) | We are inside a comment, find the end marker. | We are inside a comment, find the end marker. | [
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while lineix < len(lines):
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return lineix
lineix += 1
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bulletphysics/bullet3 | f0f2a952e146f016096db6f85cf0c44ed75b0b9a | examples/pybullet/gym/pybullet_envs/agents/networks.py | python | feed_forward_gaussian | (config, action_size, observations, unused_length, state=None) | return NetworkOutput(policy, mean, logstd, value, state) | Independent feed forward networks for policy and value.
The policy network outputs the mean action and the log standard deviation
is learned as independent parameter vector.
Args:
config: Configuration object.
action_size: Length of the action vector.
observations: Sequences of observations.
unused_length: Batch of sequence lengths.
state: Batch of initial recurrent states.
Returns:
NetworkOutput tuple. | Independent feed forward networks for policy and value. | [
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"""Independent feed forward networks for policy and value.
The policy network outputs the mean action and the log standard deviation
is learned as independent parameter vector.
Args:
config: Configuration object.
action_size: Length of the action vector.
observations: Sequences of observations.
unused_length: Batch of sequence lengths.
state: Batch of initial recurrent states.
Returns:
NetworkOutput tuple.
"""
mean_weights_initializer = tf.contrib.layers.variance_scaling_initializer(
factor=config.init_mean_factor)
logstd_initializer = tf.random_normal_initializer(config.init_logstd, 1e-10)
flat_observations = tf.reshape(observations, [
tf.shape(observations)[0],
tf.shape(observations)[1],
functools.reduce(operator.mul,
observations.shape.as_list()[2:], 1)
])
with tf.variable_scope('policy'):
x = flat_observations
for size in config.policy_layers:
x = tf.contrib.layers.fully_connected(x, size, tf.nn.relu)
mean = tf.contrib.layers.fully_connected(x,
action_size,
tf.tanh,
weights_initializer=mean_weights_initializer)
logstd = tf.get_variable('logstd', mean.shape[2:], tf.float32, logstd_initializer)
logstd = tf.tile(logstd[None, None],
[tf.shape(mean)[0], tf.shape(mean)[1]] + [1] * (mean.shape.ndims - 2))
with tf.variable_scope('value'):
x = flat_observations
for size in config.value_layers:
x = tf.contrib.layers.fully_connected(x, size, tf.nn.relu)
value = tf.contrib.layers.fully_connected(x, 1, None)[..., 0]
mean = tf.check_numerics(mean, 'mean')
logstd = tf.check_numerics(logstd, 'logstd')
value = tf.check_numerics(value, 'value')
policy = tf.contrib.distributions.MultivariateNormalDiag(mean, tf.exp(logstd))
return NetworkOutput(policy, mean, logstd, value, state) | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/Tix.py | python | Grid.entrycget | (self, x, y, option) | return self.tk.call(self, 'entrycget', x, y, option) | Get the option value for cell at (x,y) | Get the option value for cell at (x,y) | [
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"Get the option value for cell at (x,y)"
if option and option[0] != '-':
option = '-' + option
return self.tk.call(self, 'entrycget', x, y, option) | [
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neopenx/Dragon | 0e639a7319035ddc81918bd3df059230436ee0a1 | Dragon/python/dragon/io/blob_fetcher.py | python | BlobFetcher.__init__ | (self, **kwargs) | Construct a ``BlobFetcher``.
Parameters
----------
batch_size : int
The size of a training batch.
partition : boolean
Whether to partition batch. Default is ``False``.
prefetch : int
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batch_size : int
The size of a training batch.
partition : boolean
Whether to partition batch. Default is ``False``.
prefetch : int
The prefetch count. Default is ``5``.
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super(BlobFetcher, self).__init__()
self._batch_size = GetProperty(kwargs, 'batch_size', 100)
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if self._partition:
self._batch_size = int(self._batch_size / kwargs['group_size'])
self.Q_in = self.Q_out = None
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snap-stanford/snap-python | d53c51b0a26aa7e3e7400b014cdf728948fde80a | setup/snap.py | python | TStr.GetHex | (self) | return _snap.TStr_GetHex(self) | GetHex(TStr self) -> TStr
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"""
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Source/ThirdParty/CEF3/cef_source/tools/cef_parser.py | python | obj_function.get_capi_proto | (self, defined_structs = [], prefix = None) | return result | Return the prototype of the C API function. | Return the prototype of the C API function. | [
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parts = self.get_capi_parts(defined_structs, prefix)
result = parts['retval']+' '+parts['name']+ \
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AndroidAdvanceWithGeektime/Chapter01 | da2bc56d708fa74035c64564b134189045f51213 | breakpad-build/src/main/cpp/external/libbreakpad/src/tools/python/filter_syms.py | python | SymbolFileParser._AdjustPath | (self, path) | return path[len(filter(path.startswith,
self.ignored_prefixes + [''])[0]):] | Adjusts the supplied path after performing path de-duplication.
This may be used to perform secondary adjustments, such as removing a
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sc0ty/subsync | be5390d00ff475b6543eb0140c7e65b34317d95b | subsync/assets/downloader.py | python | AssetDownloader.run | (self, timeout=None) | return True | Start downloader (asynchronously).
Could be called multiple times, has no effect if downloader is already
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Parameters
----------
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timeout: float, optional
How often `onUpdate` callback should be called (in seconds).
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GJDuck/LowFat | ecf6a0f0fa1b73a27a626cf493cc39e477b6faea | llvm-4.0.0.src/projects/compiler-rt/lib/sanitizer_common/scripts/cpplint.py | python | CheckSectionSpacing | (filename, clean_lines, class_info, linenum, error) | Checks for additional blank line issues related to sections.
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Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/math/symbolic_io.py | python | exprToStr | (expr,parseCompatible=True,expandSubexprs='auto') | Converts an Expression to a printable or parseable string.
Args:
expr (Expression): the Expression to convert
parseCompatible (bool, optional): if True, the result is readable via exprFromStr()
expandSubexprs (str or bool, optional): whether to expand subexpressions. Can be:
* 'auto': if parseCompatible, equivalent to False.
if parseCompatible=False, equivalent to True.
* True: expands all common subexpressions
* False: does not expand common subexpressions.
* 'show': Internally used.
Returns:
(str): a printable or parsable string representing expr. | Converts an Expression to a printable or parseable string. | [
"Converts",
"an",
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] | def exprToStr(expr,parseCompatible=True,expandSubexprs='auto'):
"""Converts an Expression to a printable or parseable string.
Args:
expr (Expression): the Expression to convert
parseCompatible (bool, optional): if True, the result is readable via exprFromStr()
expandSubexprs (str or bool, optional): whether to expand subexpressions. Can be:
* 'auto': if parseCompatible, equivalent to False.
if parseCompatible=False, equivalent to True.
* True: expands all common subexpressions
* False: does not expand common subexpressions.
* 'show': Internally used.
Returns:
(str): a printable or parsable string representing expr.
"""
if isinstance(expr,ConstantExpression):
if isinstance(expr.value,slice):
start,stop,step = expr.value.start,expr.value.stop,expr.value.step
return "%s:%s%s"%(("" if start is None else str(start)),
("" if (stop is None or stop > 900000000000) else str(stop)),
("" if step is None else ":"+str(step)))
try:
jsonval = _to_jsonobj(expr.value)
except:
return str(expr.value)
if parseCompatible:
return json.dumps(jsonval)
else:
#Note: DOESNT WORK IN Python 3
#original_float_repr = encoder.FLOAT_REPR
encoder.FLOAT_REPR = lambda o:format(o,'.14g')
try:
if _json_complex(jsonval):
res = json.dumps(jsonval,sort_keys=True, indent=4, separators=(',', ': '))
else:
res = json.dumps(jsonval,sort_keys=True)
except Exception:
print("Unable to dump constant expression",expr.value,"of type",expr.value.__class__.__name__)
def print_recursive(v,indent=0):
if hasattr(v,'__iter__'):
print(indent*' ',"Sub objects have type",[a.__class__.__name__ for a in v])
for a in v:
print_recursive(a,indent+2)
print_recursive(expr.value)
return "___JSON_ENCODE_ERROR___"
#encoder.FLOAT_REPR = original_float_repr
return res
elif isinstance(expr,VariableExpression):
if parseCompatible:
return VAR_PREFIX+expr.var.name
else:
return str(expr.var)
elif isinstance(expr,UserDataExpression):
return USER_DATA_PREFIX+expr.name
elif isinstance(expr,OperatorExpression):
if expandSubexprs == 'auto':
expandSubexprs = not parseCompatible
if expandSubexprs:
astr = []
for i,a in enumerate(expr.args):
a._parent = (weakref.ref(expr),i)
astr.append(exprToStr(a,parseCompatible,expandSubexprs))
if not isinstance(a,OperatorExpression) and expandSubexprs == 'show' and ('id' in a._cache or 'name' in a._cache):
#tagged subexprs need parenthesies
if astr[-1][-1] != ')':
astr[-1] = '('+astr[-1]+')'
astr[-1] = astr[-1] + NAMED_EXPRESSION_TAG + a._cache.get('id',a._cache.get('name'))
a._parent = None
res = _prettyPrintExpr(expr,astr,parseCompatible)
if expandSubexprs == 'show' and ('id' in expr._cache or 'name' in expr._cache):
#tagged subexprs need parenthesies
if res[-1] != ')':
res = '('+res+')'
return res + NAMED_EXPRESSION_TAG + expr._cache.get('id',expr._cache.get('name'))
oldparent = expr._parent
iscomplex = expr.depth() >= 0 and (expr.functionInfo.name in _operator_precedence)
expr._parent = oldparent
if iscomplex and (expr._parent is not None and not isinstance(expr._parent,str)):
if parseCompatible:
return '(' + res + ')'
else:
parent = expr._parent[0]()
if parent.functionInfo.name in _operator_precedence:
expr_precedence = _operator_precedence[expr.functionInfo.name]
parent_precedence = _operator_precedence[parent.functionInfo.name]
#if - is the first in a summation, don't parenthesize it
if expr._parent[1] == 0 and expr.functionInfo.name == 'neg' and parent.functionInfo.name in ['sum','add','sub']:
return res
if expr_precedence > parent_precedence:
return '(' + res + ')'
if expr_precedence == parent_precedence:
if expr.functionInfo is parent.functionInfo and expr.functionInfo.properties.get('associative',False):
return res
else:
return '(' + res + ')'
return res
else:
if not parseCompatible:
taggedexpr = _make_tagged(expr,"")
else:
taggedexpr = _make_tagged(expr)
res = exprToStr(taggedexpr,parseCompatible,'show')
if taggedexpr is not expr:
expr._clearCache('id',deep=True)
return res
elif isinstance(expr,_TaggedExpression):
return NAMED_EXPRESSION_PREFIX+expr.name
elif is_const(expr):
return str(expr)
else:
raise ValueError("Unknown type "+expr.__class__.__name__) | [
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/traci/_vehicle.py | python | VehicleDomain.setVehicleClass | (self, vehID, clazz) | setVehicleClass(string, string) -> None
Sets the vehicle class for this vehicle. | setVehicleClass(string, string) -> None | [
"setVehicleClass",
"(",
"string",
"string",
")",
"-",
">",
"None"
] | def setVehicleClass(self, vehID, clazz):
"""setVehicleClass(string, string) -> None
Sets the vehicle class for this vehicle.
"""
self._setCmd(tc.VAR_VEHICLECLASS, vehID, "s", clazz) | [
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genn-team/genn | 75e1eb218cafa228bf36ae4613d1ce26e877b12c | pygenn/genn_model.py | python | create_var_ref | (pop, var_name) | return (genn_wrapper.create_var_ref(pop.pop, var_name), pop) | This helper function creates a Models::VarReference
pointing to a neuron or current source variable
for initialising variable references.
Args:
pop -- population, either a NeuronGroup or CurrentSource object
var_name -- name of variable in population to reference | This helper function creates a Models::VarReference
pointing to a neuron or current source variable
for initialising variable references. | [
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] | def create_var_ref(pop, var_name):
"""This helper function creates a Models::VarReference
pointing to a neuron or current source variable
for initialising variable references.
Args:
pop -- population, either a NeuronGroup or CurrentSource object
var_name -- name of variable in population to reference
"""
return (genn_wrapper.create_var_ref(pop.pop, var_name), pop) | [
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netket/netket | 0d534e54ecbf25b677ea72af6b85947979420652 | netket/optimizer/qgt/qgt_jacobian_pytree.py | python | QGTJacobianPyTree | (
vstate=None,
*,
mode: str = None,
holomorphic: bool = None,
rescale_shift=False,
**kwargs,
) | return QGTJacobianPyTreeT(
O=O, scale=scale, params=vstate.parameters, mode=mode, **kwargs
) | Semi-lazy representation of an S Matrix where the Jacobian O_k is precomputed
and stored as a PyTree.
The matrix of gradients O is computed on initialisation, but not S,
which can be computed by calling :code:`to_dense`.
The details on how the ⟨S⟩⁻¹⟨F⟩ system is solved are contaianed in
the field `sr`.
Args:
vstate: The variational state
mode: "real", "complex" or "holomorphic": specifies the implementation
used to compute the jacobian. "real" discards the imaginary part
of the output of the model. "complex" splits the real and imaginary
part of the parameters and output. It works also for non holomorphic
models. holomorphic works for any function assuming it's holomorphic
or real valued.
holomorphic: a flag to indicate that the function is holomorphic.
rescale_shift: If True rescales the diagonal shift. | Semi-lazy representation of an S Matrix where the Jacobian O_k is precomputed
and stored as a PyTree. | [
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] | def QGTJacobianPyTree(
vstate=None,
*,
mode: str = None,
holomorphic: bool = None,
rescale_shift=False,
**kwargs,
) -> "QGTJacobianPyTreeT":
"""
Semi-lazy representation of an S Matrix where the Jacobian O_k is precomputed
and stored as a PyTree.
The matrix of gradients O is computed on initialisation, but not S,
which can be computed by calling :code:`to_dense`.
The details on how the ⟨S⟩⁻¹⟨F⟩ system is solved are contaianed in
the field `sr`.
Args:
vstate: The variational state
mode: "real", "complex" or "holomorphic": specifies the implementation
used to compute the jacobian. "real" discards the imaginary part
of the output of the model. "complex" splits the real and imaginary
part of the parameters and output. It works also for non holomorphic
models. holomorphic works for any function assuming it's holomorphic
or real valued.
holomorphic: a flag to indicate that the function is holomorphic.
rescale_shift: If True rescales the diagonal shift.
"""
if vstate is None:
return partial(
QGTJacobianPyTree,
mode=mode,
holomorphic=holomorphic,
rescale_shift=rescale_shift,
**kwargs,
)
# TODO: Find a better way to handle this case
from netket.vqs import ExactState
if isinstance(vstate, ExactState):
samples = split_array_mpi(vstate._all_states)
pdf = split_array_mpi(vstate.probability_distribution())
else:
samples = vstate.samples
pdf = None
# Choose sensible default mode
if mode is None:
mode = choose_jacobian_mode(
vstate._apply_fun,
vstate.parameters,
vstate.model_state,
samples,
mode=mode,
holomorphic=holomorphic,
)
elif holomorphic is not None:
raise ValueError("Cannot specify both `mode` and `holomorphic`.")
if hasattr(vstate, "chunk_size"):
chunk_size = vstate.chunk_size
else:
chunk_size = None
O, scale = prepare_centered_oks(
vstate._apply_fun,
vstate.parameters,
samples.reshape(-1, samples.shape[-1]),
vstate.model_state,
mode,
rescale_shift,
pdf,
chunk_size,
)
return QGTJacobianPyTreeT(
O=O, scale=scale, params=vstate.parameters, mode=mode, **kwargs
) | [
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | gr-utils/blocktool/core/parseheader_generic.py | python | GenericHeaderParser.run_blocktool | (self) | Run, run, run. | Run, run, run. | [
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"run",
"run",
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] | def run_blocktool(self):
""" Run, run, run. """
pass | [
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] | https://github.com/gnuradio/gnuradio/blob/09c3c4fa4bfb1a02caac74cb5334dfe065391e3b/gr-utils/blocktool/core/parseheader_generic.py#L350-L352 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/models/wheel.py | python | Wheel.support_index_min | (self, tags) | return min(tags.index(tag) for tag in self.file_tags if tag in tags) | Return the lowest index that one of the wheel's file_tag combinations
achieves in the given list of supported tags.
For example, if there are 8 supported tags and one of the file tags
is first in the list, then return 0.
:param tags: the PEP 425 tags to check the wheel against, in order
with most preferred first.
:raises ValueError: If none of the wheel's file tags match one of
the supported tags. | Return the lowest index that one of the wheel's file_tag combinations | [
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] | def support_index_min(self, tags):
# type: (List[Tag]) -> int
"""Return the lowest index that one of the wheel's file_tag combinations
achieves in the given list of supported tags.
For example, if there are 8 supported tags and one of the file tags
is first in the list, then return 0.
:param tags: the PEP 425 tags to check the wheel against, in order
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:raises ValueError: If none of the wheel's file tags match one of
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"""
return min(tags.index(tag) for tag in self.file_tags if tag in tags) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/robotsim.py | python | SimRobotController.getControlType | (self) | return _robotsim.SimRobotController_getControlType(self) | getControlType(SimRobotController self) -> std::string
Returns the control type for the active controller.
Possible return values are:
* unknown
* off
* torque
* PID
* locked_velocity | getControlType(SimRobotController self) -> std::string | [
"getControlType",
"(",
"SimRobotController",
"self",
")",
"-",
">",
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"::",
"string"
] | def getControlType(self):
"""
getControlType(SimRobotController self) -> std::string
Returns the control type for the active controller.
Possible return values are:
* unknown
* off
* torque
* PID
* locked_velocity
"""
return _robotsim.SimRobotController_getControlType(self) | [
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cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | DataFormats/FWLite/python/__init__.py | python | Lumis._next | (self) | (Internal) Iterator internals | (Internal) Iterator internals | [
"(",
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")",
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] | def _next (self):
"""(Internal) Iterator internals"""
while True:
if self._lumi.atEnd():
if not self._createFWLiteLumi():
# there are no more files here, so we are done
break
yield self
self._lumiCounts += 1
if self._maxLumis > 0 and self._lumiCounts >= self._maxLumis:
break
self._lumi.__preinc__() | [
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wujian16/Cornell-MOE | df299d1be882d2af9796d7a68b3f9505cac7a53e | moe/optimal_learning/python/cpp_wrappers/domain.py | python | SimplexIntersectTensorProductDomain.__init__ | (self, domain_bounds) | Construct a SimplexIntersectTensorProductDomain that can be used with cpp_wrappers.* functions/classes.
:param domain_bounds: the boundaries of a dim-dimensional tensor-product domain.
:type domain_bounds: iterable of dim ClosedInterval | Construct a SimplexIntersectTensorProductDomain that can be used with cpp_wrappers.* functions/classes. | [
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"/",
"classes",
"."
] | def __init__(self, domain_bounds):
"""Construct a SimplexIntersectTensorProductDomain that can be used with cpp_wrappers.* functions/classes.
:param domain_bounds: the boundaries of a dim-dimensional tensor-product domain.
:type domain_bounds: iterable of dim ClosedInterval
"""
self._tensor_product_domain = TensorProductDomain(domain_bounds)
self._domain_type = C_GP.DomainTypes.simplex | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/six.py | python | _SixMetaPathImporter.get_code | (self, fullname) | return None | Return None
Required, if is_package is implemented | Return None | [
"Return",
"None"
] | def get_code(self, fullname):
"""Return None
Required, if is_package is implemented"""
self.__get_module(fullname) # eventually raises ImportError
return None | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/pubsub/utils/topictreeprinter.py | python | printTreeDocs | (rootTopic=None, topicMgr=None, **kwargs) | Print out the topic tree to a file (or file-like object like a
StringIO), starting at rootTopic. If root topic should be root of
whole tree, get it from pub.getDefaultTopicTreeRoot().
The treeVisitor is an instance of pub.TopicTreeTraverser.
Printing the tree docs would normally involve this::
from pubsub import pub
from pubsub.utils.topictreeprinter import TopicTreePrinter
traverser = pub.TopicTreeTraverser( TopicTreePrinter(**kwargs) )
traverser.traverse( pub.getDefaultTopicTreeRoot() )
With printTreeDocs, it looks like this::
from pubsub import pub
from pubsub.utils import printTreeDocs
printTreeDocs()
The kwargs are the same as for TopicTreePrinter constructor:
extra(None), width(70), indentStep(4), bulletTopic, bulletTopicItem,
bulletTopicArg, fileObj(stdout). If fileObj not given, stdout is used. | Print out the topic tree to a file (or file-like object like a
StringIO), starting at rootTopic. If root topic should be root of
whole tree, get it from pub.getDefaultTopicTreeRoot().
The treeVisitor is an instance of pub.TopicTreeTraverser. | [
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"""Print out the topic tree to a file (or file-like object like a
StringIO), starting at rootTopic. If root topic should be root of
whole tree, get it from pub.getDefaultTopicTreeRoot().
The treeVisitor is an instance of pub.TopicTreeTraverser.
Printing the tree docs would normally involve this::
from pubsub import pub
from pubsub.utils.topictreeprinter import TopicTreePrinter
traverser = pub.TopicTreeTraverser( TopicTreePrinter(**kwargs) )
traverser.traverse( pub.getDefaultTopicTreeRoot() )
With printTreeDocs, it looks like this::
from pubsub import pub
from pubsub.utils import printTreeDocs
printTreeDocs()
The kwargs are the same as for TopicTreePrinter constructor:
extra(None), width(70), indentStep(4), bulletTopic, bulletTopicItem,
bulletTopicArg, fileObj(stdout). If fileObj not given, stdout is used."""
if rootTopic is None:
if topicMgr is None:
from .. import pub
topicMgr = pub.getDefaultTopicMgr()
rootTopic = topicMgr.getRootAllTopics()
printer = TopicTreePrinter(**kwargs)
traverser = TopicTreeTraverser(printer)
traverser.traverse(rootTopic) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/src/motionplanning.py | python | CSpaceInterface.setFeasibility | (self, pyFeas) | return _motionplanning.CSpaceInterface_setFeasibility(self, pyFeas) | setFeasibility(CSpaceInterface self, PyObject * pyFeas) | setFeasibility(CSpaceInterface self, PyObject * pyFeas) | [
"setFeasibility",
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] | def setFeasibility(self, pyFeas):
"""
setFeasibility(CSpaceInterface self, PyObject * pyFeas)
"""
return _motionplanning.CSpaceInterface_setFeasibility(self, pyFeas) | [
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