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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/pep8.py | python | BaseReport.start | (self) | Start the timer. | Start the timer. | [
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"""Start the timer."""
self._start_time = time.time() | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/random_forest.py | python | TensorForestEstimator.predict_proba | (
self, x=None, input_fn=None, batch_size=None, as_iterable=False) | return super(TensorForestEstimator, self).predict(
x=x, input_fn=input_fn, batch_size=batch_size, as_iterable=as_iterable) | Returns prediction probabilities for given features (classification).
Args:
x: features.
input_fn: Input function. If set, x and y must be None.
batch_size: Override default batch size.
as_iterable: If True, return an iterable which keeps yielding predictions
for each example until inputs are exhausted. Note: The inputs must
terminate if you want the iterable to terminate (e.g. be sure to pass
num_epochs=1 if you are using something like read_batch_features).
Returns:
Numpy array of predicted probabilities (or an iterable of predicted
probabilities if as_iterable is True).
Raises:
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Args:
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input_fn: Input function. If set, x and y must be None.
batch_size: Override default batch size.
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Raises:
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return super(TensorForestEstimator, self).predict(
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rsummers11/CADLab | 976ed959a0b5208bb4173127a7ef732ac73a9b6f | lesion_detector_3DCE/rcnn/fio/load_ct_img.py | python | load_prep_img | (imname, slice_idx, spacing, slice_intv, do_clip=False, num_slice=3) | return im, im_scale, c | load volume, windowing, interpolate multiple slices, clip black border, resize according to spacing | load volume, windowing, interpolate multiple slices, clip black border, resize according to spacing | [
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"""load volume, windowing, interpolate multiple slices, clip black border, resize according to spacing"""
if imname.endswith('.nii.gz') or imname.endswith('.nii'):
im, mask = load_multislice_img_nifti(imname, slice_idx, slice_intv, do_clip, num_slice)
else:
im, mask = load_multislice_img_16bit_png(imname, slice_idx, slice_intv, do_clip, num_slice)
im = windowing(im, config.WINDOWING)
if do_clip: # clip black border
c = get_range(mask, margin=0)
im = im[c[0]:c[1] + 1, c[2]:c[3] + 1, :]
# mask = mask[c[0]:c[1] + 1, c[2]:c[3] + 1]
# print im.shape
else:
c = [0, im.shape[0]-1, 0, im.shape[1]-1]
im_shape = im.shape[0:2]
if spacing is not None and config.NORM_SPACING > 0: # spacing adjust, will overwrite simple scaling
im_scale = float(spacing) / config.NORM_SPACING
else:
im_scale = float(config.SCALE) / float(np.min(im_shape)) # simple scaling
max_shape = np.max(im_shape)*im_scale
if max_shape > config.MAX_SIZE:
im_scale1 = float(config.MAX_SIZE) / max_shape
im_scale *= im_scale1
if im_scale != 1:
im = cv2.resize(im, None, None, fx=im_scale, fy=im_scale, interpolation=cv2.INTER_LINEAR)
# mask = cv2.resize(mask, None, None, fx=im_scale, fy=im_scale, interpolation=cv2.INTER_LINEAR)
return im, im_scale, c | [
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|
OAID/Tengine | 66b2c22ad129d25e2fc6de3b22a608bb54dd90db | pytengine/tengine/node.py | python | Node.getOutputTensorByIdx | (self, idx) | return Tensor(tensor=tensor) | Get the output tensor handle of a node.
:param idx: <int> The index of the output tensor.
:return: The tensor handle or None on error. | Get the output tensor handle of a node.
:param idx: <int> The index of the output tensor.
:return: The tensor handle or None on error. | [
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"""
_LIB.get_node_output_tensor.restype = tensor_t
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/tornado/tornado-6/tornado/gen.py | python | is_coroutine_function | (func: Any) | return getattr(func, "__tornado_coroutine__", False) | Return whether *func* is a coroutine function, i.e. a function
wrapped with `~.gen.coroutine`.
.. versionadded:: 4.5 | Return whether *func* is a coroutine function, i.e. a function
wrapped with `~.gen.coroutine`. | [
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"""Return whether *func* is a coroutine function, i.e. a function
wrapped with `~.gen.coroutine`.
.. versionadded:: 4.5
"""
return getattr(func, "__tornado_coroutine__", False) | [
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|
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/backend.py | python | backend | () | return 'tensorflow' | Publicly accessible method for determining the current backend.
Only exists for API compatibility with multi-backend Keras.
Returns:
The string "tensorflow". | Publicly accessible method for determining the current backend. | [
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"""Publicly accessible method for determining the current backend.
Only exists for API compatibility with multi-backend Keras.
Returns:
The string "tensorflow".
"""
return 'tensorflow' | [
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|
google/mysql-protobuf | 467cda676afaa49e762c5c9164a43f6ad31a1fbf | libevent/event_rpcgen.py | python | Struct.PrintIdented | (self, file, ident, code) | Takes an array, add indentation to each entry and prints it. | Takes an array, add indentation to each entry and prints it. | [
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"""Takes an array, add indentation to each entry and prints it."""
for entry in code:
print >>file, '%s%s' % (ident, entry) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | contrib/gizmos/osx_cocoa/gizmos.py | python | TreeListCtrl.EditLabel | (*args, **kwargs) | return _gizmos.TreeListCtrl_EditLabel(*args, **kwargs) | EditLabel(self, TreeItemId item, int column=-1) | EditLabel(self, TreeItemId item, int column=-1) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/extern/aui/auibar.py | python | AuiToolBar.OnLeftUp | (self, event) | Handles the ``wx.EVT_LEFT_UP`` event for :class:`AuiToolBar`.
:param `event`: a :class:`MouseEvent` event to be processed. | Handles the ``wx.EVT_LEFT_UP`` event for :class:`AuiToolBar`. | [
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"""
Handles the ``wx.EVT_LEFT_UP`` event for :class:`AuiToolBar`.
:param `event`: a :class:`MouseEvent` event to be processed.
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self.SetPressedItem(None)
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if not manager:
return
if self._action_item.target:
pane = manager.GetPane(self._action_item.target)
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pane = manager.GetPane(self)
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e.SetManager(manager)
e.SetPane(pane)
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e = wx.CommandEvent(wx.wxEVT_COMMAND_MENU_SELECTED, self._action_item.id)
e.SetEventObject(self)
self.ProcessEvent(e)
self.DoIdleUpdate()
# reset drag and drop member variables
self._dragging = False
self._action_pos = wx.Point(-1, -1)
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||
root-project/root | fcd3583bb14852bf2e8cd2415717cbaac0e75896 | interpreter/llvm/src/tools/clang/tools/scan-build-py/libscanbuild/clang.py | python | get_checkers | (clang, plugins) | return checkers | Get all the available checkers from default and from the plugins.
:param clang: the compiler we are using
:param plugins: list of plugins which was requested by the user
:return: a dictionary of all available checkers and its status
{<checker name>: (<checker description>, <is active by default>)} | Get all the available checkers from default and from the plugins. | [
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] | def get_checkers(clang, plugins):
""" Get all the available checkers from default and from the plugins.
:param clang: the compiler we are using
:param plugins: list of plugins which was requested by the user
:return: a dictionary of all available checkers and its status
{<checker name>: (<checker description>, <is active by default>)} """
load = [elem for plugin in plugins for elem in ['-load', plugin]]
cmd = [clang, '-cc1'] + load + ['-analyzer-checker-help']
lines = run_command(cmd)
is_active_checker = is_active(get_active_checkers(clang, plugins))
checkers = {
name: (description, is_active_checker(name))
for name, description in parse_checkers(lines)
}
if not checkers:
raise Exception('Could not query Clang for available checkers.')
return checkers | [
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bareos/bareos | 56a10bb368b0a81e977bb51304033fe49d59efb0 | restapi/bareos_restapi/__init__.py | python | read_all_filesets | (
*,
response: Response,
current_user: User = Depends(get_current_user),
verbose: Optional[bareosBool] = Query("yes", title="Verbose output"),
) | return show_configuration_items(
response=response,
current_user=current_user,
itemType="filesets",
verbose=verbose,
) | Read all jobdef resources. Built on console command _show filesets_.
Needs at least Bareos Version >= 20.0.0 | Read all jobdef resources. Built on console command _show filesets_. | [
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*,
response: Response,
current_user: User = Depends(get_current_user),
verbose: Optional[bareosBool] = Query("yes", title="Verbose output"),
):
"""
Read all jobdef resources. Built on console command _show filesets_.
Needs at least Bareos Version >= 20.0.0
"""
return show_configuration_items(
response=response,
current_user=current_user,
itemType="filesets",
verbose=verbose,
) | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/roc/compiler.py | python | _unpack_argument | (ty, val, kernelargs, retr) | Convert arguments to ctypes and append to kernelargs | Convert arguments to ctypes and append to kernelargs | [
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"""
Convert arguments to ctypes and append to kernelargs
"""
if isinstance(ty, types.Array):
c_intp = ctypes.c_ssize_t
# if a dgpu is present, move the data to the device.
if dgpu_present:
devary, conv = devicearray.auto_device(val, devices.get_context())
if conv:
retr.append(lambda: devary.copy_to_host(val))
data = devary.device_ctypes_pointer
else:
data = ctypes.c_void_p(val.ctypes.data)
meminfo = parent = ctypes.c_void_p(0)
nitems = c_intp(val.size)
itemsize = c_intp(val.dtype.itemsize)
kernelargs.append(meminfo)
kernelargs.append(parent)
kernelargs.append(nitems)
kernelargs.append(itemsize)
kernelargs.append(data)
for ax in range(val.ndim):
kernelargs.append(c_intp(val.shape[ax]))
for ax in range(val.ndim):
kernelargs.append(c_intp(val.strides[ax]))
elif isinstance(ty, types.Integer):
cval = getattr(ctypes, "c_%s" % ty)(val)
kernelargs.append(cval)
elif ty == types.float64:
cval = ctypes.c_double(val)
kernelargs.append(cval)
elif ty == types.float32:
cval = ctypes.c_float(val)
kernelargs.append(cval)
elif ty == types.boolean:
cval = ctypes.c_uint8(int(val))
kernelargs.append(cval)
elif ty == types.complex64:
kernelargs.append(ctypes.c_float(val.real))
kernelargs.append(ctypes.c_float(val.imag))
elif ty == types.complex128:
kernelargs.append(ctypes.c_double(val.real))
kernelargs.append(ctypes.c_double(val.imag))
else:
raise NotImplementedError(ty, val) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_core.py | python | BookCtrlEvent.SetSelection | (*args, **kwargs) | return _core_.BookCtrlEvent_SetSelection(*args, **kwargs) | SetSelection(self, int nSel) | SetSelection(self, int nSel) | [
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] | def SetSelection(*args, **kwargs):
"""SetSelection(self, int nSel)"""
return _core_.BookCtrlEvent_SetSelection(*args, **kwargs) | [
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|
cvxpy/cvxpy | 5165b4fb750dfd237de8659383ef24b4b2e33aaf | cvxpy/atoms/affine/trace.py | python | trace.shape_from_args | (self) | return tuple() | Always scalar. | Always scalar. | [
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"""Always scalar.
"""
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|
krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/robotsim.py | python | Appearance.setTexgen | (self, np_array2: Vector, worldcoordinates: bool=False) | return _robotsim.Appearance_setTexgen(self, np_array2, worldcoordinates) | r"""
Sets the texture generation. The array must be size m x 4, with m in the range
0,...,4. If worldcoordinates=true, the texture generation is performed in world
coordinates rather than object coordinates.
Args:
np_array2 (:obj:`2D Numpy array of floats`)
worldcoordinates (bool, optional): default value False | r"""
Sets the texture generation. The array must be size m x 4, with m in the range
0,...,4. If worldcoordinates=true, the texture generation is performed in world
coordinates rather than object coordinates. | [
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r"""
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0,...,4. If worldcoordinates=true, the texture generation is performed in world
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Args:
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|
macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/pylib/gyp/generator/dump_dependency_json.py | python | CalculateGeneratorInputInfo | (params) | Calculate the generator specific info that gets fed to input (called by
gyp). | Calculate the generator specific info that gets fed to input (called by
gyp). | [
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] | def CalculateGeneratorInputInfo(params):
"""Calculate the generator specific info that gets fed to input (called by
gyp)."""
generator_flags = params.get('generator_flags', {})
if generator_flags.get('adjust_static_libraries', False):
global generator_wants_static_library_dependencies_adjusted
generator_wants_static_library_dependencies_adjusted = True
toplevel = params['options'].toplevel_dir
generator_dir = os.path.relpath(params['options'].generator_output or '.')
# output_dir: relative path from generator_dir to the build directory.
output_dir = generator_flags.get('output_dir', 'out')
qualified_out_dir = os.path.normpath(os.path.join(
toplevel, generator_dir, output_dir, 'gypfiles'))
global generator_filelist_paths
generator_filelist_paths = {
'toplevel': toplevel,
'qualified_out_dir': qualified_out_dir,
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||
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/fft/fftpack.py | python | irfft2 | (a, s=None, axes=(-2, -1)) | return irfftn(a, s, axes) | Compute the 2-dimensional inverse FFT of a real array.
Parameters
----------
a : array_like
The input array
s : sequence of ints, optional
Shape of the inverse FFT.
axes : sequence of ints, optional
The axes over which to compute the inverse fft.
Default is the last two axes.
Returns
-------
out : ndarray
The result of the inverse real 2-D FFT.
See Also
--------
irfftn : Compute the inverse of the N-dimensional FFT of real input.
Notes
-----
This is really `irfftn` with different defaults.
For more details see `irfftn`. | Compute the 2-dimensional inverse FFT of a real array. | [
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] | def irfft2(a, s=None, axes=(-2, -1)):
"""
Compute the 2-dimensional inverse FFT of a real array.
Parameters
----------
a : array_like
The input array
s : sequence of ints, optional
Shape of the inverse FFT.
axes : sequence of ints, optional
The axes over which to compute the inverse fft.
Default is the last two axes.
Returns
-------
out : ndarray
The result of the inverse real 2-D FFT.
See Also
--------
irfftn : Compute the inverse of the N-dimensional FFT of real input.
Notes
-----
This is really `irfftn` with different defaults.
For more details see `irfftn`.
"""
return irfftn(a, s, axes) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/ntpath.py | python | relpath | (path, start=None) | Return a relative version of a path | Return a relative version of a path | [
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"""Return a relative version of a path"""
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if isinstance(path, bytes):
sep = b'\\'
curdir = b'.'
pardir = b'..'
else:
sep = '\\'
curdir = '.'
pardir = '..'
if start is None:
start = curdir
if not path:
raise ValueError("no path specified")
start = os.fspath(start)
try:
start_abs = abspath(normpath(start))
path_abs = abspath(normpath(path))
start_drive, start_rest = splitdrive(start_abs)
path_drive, path_rest = splitdrive(path_abs)
if normcase(start_drive) != normcase(path_drive):
raise ValueError("path is on mount %r, start on mount %r" % (
path_drive, start_drive))
start_list = [x for x in start_rest.split(sep) if x]
path_list = [x for x in path_rest.split(sep) if x]
# Work out how much of the filepath is shared by start and path.
i = 0
for e1, e2 in zip(start_list, path_list):
if normcase(e1) != normcase(e2):
break
i += 1
rel_list = [pardir] * (len(start_list)-i) + path_list[i:]
if not rel_list:
return curdir
return join(*rel_list)
except (TypeError, ValueError, AttributeError, BytesWarning, DeprecationWarning):
genericpath._check_arg_types('relpath', path, start)
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||
DGA-MI-SSI/YaCo | 9b85e6ca1809114c4df1382c11255f7e38408912 | deps/flatbuffers-1.8.0/python/flatbuffers/builder.py | python | Builder.PlaceSOffsetT | (self, x) | PlaceSOffsetT prepends a SOffsetT to the Builder, without checking
for space. | PlaceSOffsetT prepends a SOffsetT to the Builder, without checking
for space. | [
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] | def PlaceSOffsetT(self, x):
"""PlaceSOffsetT prepends a SOffsetT to the Builder, without checking
for space.
"""
N.enforce_number(x, N.SOffsetTFlags)
self.head = self.head - N.SOffsetTFlags.bytewidth
encode.Write(packer.soffset, self.Bytes, self.Head(), x) | [
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||
PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/fluid/dygraph/dygraph_to_static/partial_program.py | python | PartialProgramLayer._infer_program | (self) | return self._clone_for_test(self._origin_main_program) | Lazy initialized property of infer_program. | Lazy initialized property of infer_program. | [
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] | def _infer_program(self):
"""
Lazy initialized property of infer_program.
"""
return self._clone_for_test(self._origin_main_program) | [
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|
hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/contrib/onnx/mx2onnx/_op_translations.py | python | convert_flatten | (node, **kwargs) | return create_basic_op_node('Flatten', node, kwargs) | Map MXNet's Flatten operator attributes to onnx's Flatten operator
and return the created node. | Map MXNet's Flatten operator attributes to onnx's Flatten operator
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] | def convert_flatten(node, **kwargs):
"""Map MXNet's Flatten operator attributes to onnx's Flatten operator
and return the created node.
"""
return create_basic_op_node('Flatten', node, kwargs) | [
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|
LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/boost_1_66_0/libs/metaparse/tools/benchmark/generate.py | python | random_chars | (number) | return (
format_character(nth_char(char_map, random.randint(0, char_num - 1)))
for _ in xrange(0, number)
) | Generate random characters | Generate random characters | [
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"random",
"characters"
] | def random_chars(number):
"""Generate random characters"""
char_map = {
k: v for k, v in chars.CHARS.iteritems()
if not format_character(k).startswith('\\x')
}
char_num = sum(char_map.values())
return (
format_character(nth_char(char_map, random.randint(0, char_num - 1)))
for _ in xrange(0, number)
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|
ArduPilot/ardupilot | 6e684b3496122b8158ac412b609d00004b7ac306 | Tools/scripts/build_binaries.py | python | build_binaries.build_antennatracker | (self, tag) | build Tracker binaries | build Tracker binaries | [
"build",
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"binaries"
] | def build_antennatracker(self, tag):
'''build Tracker binaries'''
boards = self.common_boards()[:]
self.build_vehicle(tag,
"AntennaTracker",
boards,
"AntennaTracker",
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||
tum-vision/fusenet | a1451be2971b348a01b0f525c2a3a7a0e215a591 | scripts/cpp_lint.py | python | _NestingState.CheckCompletedBlocks | (self, filename, error) | Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found. | Checks that all classes and namespaces have been completely parsed. | [
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] | def CheckCompletedBlocks(self, filename, error):
"""Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found.
"""
# Note: This test can result in false positives if #ifdef constructs
# get in the way of brace matching. See the testBuildClass test in
# cpplint_unittest.py for an example of this.
for obj in self.stack:
if isinstance(obj, _ClassInfo):
error(filename, obj.starting_linenum, 'build/class', 5,
'Failed to find complete declaration of class %s' %
obj.name)
elif isinstance(obj, _NamespaceInfo):
error(filename, obj.starting_linenum, 'build/namespaces', 5,
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||
pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/tools/inspector_protocol/jinja2/parser.py | python | Parser.free_identifier | (self, lineno=None) | return rv | Return a new free identifier as :class:`~jinja2.nodes.InternalName`. | Return a new free identifier as :class:`~jinja2.nodes.InternalName`. | [
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"""Return a new free identifier as :class:`~jinja2.nodes.InternalName`."""
self._last_identifier += 1
rv = object.__new__(nodes.InternalName)
nodes.Node.__init__(rv, 'fi%d' % self._last_identifier, lineno=lineno)
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PX4/PX4-Autopilot | 0b9f60a0370be53d683352c63fd92db3d6586e18 | Tools/mavlink_px4.py | python | MAVLink.change_operator_control_ack_send | (self, gcs_system_id, control_request, ack) | return self.send(self.change_operator_control_ack_encode(gcs_system_id, control_request, ack)) | Accept / deny control of this MAV
gcs_system_id : ID of the GCS this message (uint8_t)
control_request : 0: request control of this MAV, 1: Release control of this MAV (uint8_t)
ack : 0: ACK, 1: NACK: Wrong passkey, 2: NACK: Unsupported passkey encryption method, 3: NACK: Already under control (uint8_t) | Accept / deny control of this MAV | [
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] | def change_operator_control_ack_send(self, gcs_system_id, control_request, ack):
'''
Accept / deny control of this MAV
gcs_system_id : ID of the GCS this message (uint8_t)
control_request : 0: request control of this MAV, 1: Release control of this MAV (uint8_t)
ack : 0: ACK, 1: NACK: Wrong passkey, 2: NACK: Unsupported passkey encryption method, 3: NACK: Already under control (uint8_t)
'''
return self.send(self.change_operator_control_ack_encode(gcs_system_id, control_request, ack)) | [
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|
hfinkel/llvm-project-cxxjit | 91084ef018240bbb8e24235ff5cd8c355a9c1a1e | llvm/utils/lit/lit/util.py | python | to_string | (b) | Return the parameter as type 'str', possibly encoding it.
In Python2, the 'str' type is the same as 'bytes'. In Python3, the
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"""Return the parameter as type 'str', possibly encoding it.
In Python2, the 'str' type is the same as 'bytes'. In Python3, the
'str' type is (essentially) Python2's 'unicode' type, and 'bytes' is
distinct.
"""
if isinstance(b, str):
# In Python2, this branch is taken for types 'str' and 'bytes'.
# In Python3, this branch is taken only for 'str'.
return b
if isinstance(b, bytes):
# In Python2, this branch is never taken ('bytes' is handled as 'str').
# In Python3, this is true only for 'bytes'.
try:
return b.decode('utf-8')
except UnicodeDecodeError:
# If the value is not valid Unicode, return the default
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return str(b)
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#
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try:
return b.encode('utf-8')
except AttributeError:
raise TypeError('not sure how to convert %s to %s' % (type(b), str)) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/ed_vim.py | python | Join | (editor, repeat, cmd) | Join lines command.
@see: vim_parser | Join lines command.
@see: vim_parser | [
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"""Join lines command.
@see: vim_parser
"""
editor.PushCaret()
editor.JoinLines(repeat)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/tkinter/ttk.py | python | Spinbox.set | (self, value) | Sets the value of the Spinbox to value. | Sets the value of the Spinbox to value. | [
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||
ceph/ceph | 959663007321a369c83218414a29bd9dbc8bda3a | src/pybind/mgr/cephadm/inventory.py | python | SpecStore.all_specs | (self) | return self._specs | returns active and deleted specs. Returns read-only dict. | returns active and deleted specs. Returns read-only dict. | [
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/external/boost/boost_1_68_0/tools/build/src/build/engine.py | python | Engine.get_target_variable | (self, targets, variable) | return bjam_interface.call('get-target-variable', targets, variable) | Gets the value of `variable` on set on the first target in `targets`.
Args:
targets (str or list): one or more targets to get the variable from.
variable (str): the name of the variable
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>>> ENGINE.get_target_variable(targets, 'MY-VAR')
['Hello World']
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echo [ on $(targets) return $(MY-VAR) ] ;
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Args:
targets (str or list): one or more targets to get the variable from.
variable (str): the name of the variable
Returns:
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Example:
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>>> ENGINE.set_target_variable(targets, 'MY-VAR', 'Hello World')
>>> ENGINE.get_target_variable(targets, 'MY-VAR')
['Hello World']
Equivalent Jam code:
MY-VAR on $(targets) = "Hello World" ;
echo [ on $(targets) return $(MY-VAR) ] ;
"Hello World"
"""
if isinstance(targets, str):
targets = [targets]
assert is_iterable(targets)
assert isinstance(variable, basestring)
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftguitools/gui_annotationstyleeditor.py | python | AnnotationStyleEditor.on_delete | (self) | Execute as a callback when the delete button is pressed. | Execute as a callback when the delete button is pressed. | [
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return
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/distribute/v1/all_reduce.py | python | _build_nccl_hybrid | (input_tensors, red_op, upper_level_f) | return output_tensors | Construct a subgraph for NCCL hybrid all-reduce.
Args:
input_tensors: list of `tf.Tensor` of same-shape and type values to
be reduced.
red_op: binary elementwise reduction operator.
upper_level_f: function for reducing one value per worker, across
workers.
Returns:
list of `tf.Tensor` of reduced values.
Raises:
ValueError: inputs not well-formed. | Construct a subgraph for NCCL hybrid all-reduce. | [
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] | def _build_nccl_hybrid(input_tensors, red_op, upper_level_f):
"""Construct a subgraph for NCCL hybrid all-reduce.
Args:
input_tensors: list of `tf.Tensor` of same-shape and type values to
be reduced.
red_op: binary elementwise reduction operator.
upper_level_f: function for reducing one value per worker, across
workers.
Returns:
list of `tf.Tensor` of reduced values.
Raises:
ValueError: inputs not well-formed.
"""
input_tensors, shape = _flatten_tensors(input_tensors)
devices = [t.device for t in input_tensors]
per_worker_devices, per_worker_values = _split_by_task(devices, input_tensors)
num_workers = len(per_worker_devices)
up_values = [None for w in range(0, num_workers)]
up_devices = up_values[:]
down_values = up_values[:]
# First stage: reduce within each worker using NCCL
for w in range(0, num_workers):
worker_values = build_nccl_all_reduce(per_worker_values[w], red_op)
# NOTE: these reductions will not run to completion unless
# every output value is used. Since we only need one, we
# need to put control dependencies on the rest.
with ops.control_dependencies(worker_values):
with ops.device(worker_values[0].device):
up_values[w] = array_ops.identity(worker_values[0])
up_devices[w] = per_worker_devices[w][0]
# Second stage: Apply upper_level_f to reduce across first device at
# each worker
level_2_output = upper_level_f(up_values)
# Third stage: propagate within each worker using NCCL Broadcast
for w in range(0, num_workers):
dst_tensors = []
with ops.device(per_worker_devices[w][0]):
broadcast_src = nccl_ops.broadcast(array_ops.identity(level_2_output[w]))
for d in per_worker_devices[w]:
with ops.device(d):
dst_tensors.append(array_ops.identity(broadcast_src))
down_values[w] = dst_tensors
output_tensors = [v for sublist in down_values for v in sublist]
if len(shape) != 1:
output_tensors = _reshape_tensors(output_tensors, shape)
return output_tensors | [
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|
SoarGroup/Soar | a1c5e249499137a27da60533c72969eef3b8ab6b | scons/scons-local-4.1.0/SCons/CacheDir.py | python | CacheDir.__init__ | (self, path) | Initialize a CacheDir object.
The cache configuration is stored in the object. It
is read from the config file in the supplied path if
one exists, if not the config file is created and
the default config is written, as well as saved in the object. | Initialize a CacheDir object. | [
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] | def __init__(self, path):
"""
Initialize a CacheDir object.
The cache configuration is stored in the object. It
is read from the config file in the supplied path if
one exists, if not the config file is created and
the default config is written, as well as saved in the object.
"""
self.requests = 0
self.hits = 0
self.path = path
self.current_cache_debug = None
self.debugFP = None
self.config = dict()
if path is None:
return
self._readconfig(path) | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/cef_parser.py | python | obj_analysis.get_ptr_type | (self) | return self.ptr_type | Return the C++ class type referenced by a CefRefPtr. | Return the C++ class type referenced by a CefRefPtr. | [
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""" Return the C++ class type referenced by a CefRefPtr. """
if self.is_result_vector() and self.is_result_vector_ptr():
# return the vector RefPtr type
return self.result_value[0]['ptr_type']
# return the basic RefPtr type
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eric612/MobileNet-YOLO | 69b4441cb3ec8d553fbdef788ad033e246f901bd | python/caffe/coord_map.py | python | compose | (base_map, next_map) | return ax, a1 * a2, a1 * b2 + b1 | Compose a base coord map with scale a1, shift b1 with a further coord map
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/command/build_py.py | python | build_py.check_package | (self, package, package_dir) | return init_py | Check namespace packages' __init__ for declare_namespace | Check namespace packages' __init__ for declare_namespace | [
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] | def check_package(self, package, package_dir):
"""Check namespace packages' __init__ for declare_namespace"""
try:
return self.packages_checked[package]
except KeyError:
pass
init_py = orig.build_py.check_package(self, package, package_dir)
self.packages_checked[package] = init_py
if not init_py or not self.distribution.namespace_packages:
return init_py
for pkg in self.distribution.namespace_packages:
if pkg == package or pkg.startswith(package + '.'):
break
else:
return init_py
with io.open(init_py, 'rb') as f:
contents = f.read()
if b'declare_namespace' not in contents:
raise distutils.errors.DistutilsError(
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|
gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | ext/ply/example/ansic/cparse.py | python | p_constant | (t) | constant : ICONST
| FCONST
| CCONST | constant : ICONST
| FCONST
| CCONST | [
"constant",
":",
"ICONST",
"|",
"FCONST",
"|",
"CCONST"
] | def p_constant(t):
'''constant : ICONST
| FCONST
| CCONST'''
pass | [
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||
syoyo/tinygltf | e7f1ff5c59d3ca2489923beb239bdf93d863498f | deps/cpplint.py | python | _FunctionState.Count | (self) | Count line in current function body. | Count line in current function body. | [
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] | def Count(self):
"""Count line in current function body."""
if self.in_a_function:
self.lines_in_function += 1 | [
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||
llvm/llvm-project | ffa6262cb4e2a335d26416fad39a581b4f98c5f4 | clang/utils/check_cfc/obj_diff.py | python | compare_debug_info | (objfilea, objfileb) | return first_diff(dbga, dbgb, objfilea, objfileb) | Compare debug info of two different files.
Allowing unavoidable differences, such as filenames.
Return the first difference if the debug info differs, or None.
If there are differences in the code, there will almost certainly be differences in the debug info too. | Compare debug info of two different files.
Allowing unavoidable differences, such as filenames.
Return the first difference if the debug info differs, or None.
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dbgb = dump_debug(objfileb)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_windows.py | python | FontData.GetChosenFont | (*args, **kwargs) | return _windows_.FontData_GetChosenFont(*args, **kwargs) | GetChosenFont(self) -> Font
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"""
GetChosenFont(self) -> Font
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return _windows_.FontData_GetChosenFont(*args, **kwargs) | [
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lballabio/quantlib-old | 136336947ed4fea9ecc1da6edad188700e821739 | gensrc/gensrc/addins/enumerations.py | python | Enumerations.generateEnumeratedClasses | (self) | Generate source file for enumerated types. | Generate source file for enumerated types. | [
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"""Generate source file for enumerated types."""
if not self.enumerationList_.hasEnumeratedClasses:
return
buffer = '' # code to register the enumeration
for enumeratedClassGroup in self.enumerationList_.enumeratedClassGroups():
buffer += self.generateEnumeratedClass(enumeratedClassGroup)
self.bufferEnumClasses_.set({
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fileName = self.rootPath_ + 'register_classes.cpp'
outputfile.OutputFile(self, fileName,
self.enumerationList_.enumeratedClassCopyright(), self.bufferEnumClasses_) | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py2/sklearn/svm/base.py | python | BaseLibSVM._decision_function | (self, X) | return dec_func | Distance of the samples X to the separating hyperplane.
Parameters
----------
X : array-like, shape (n_samples, n_features)
Returns
-------
X : array-like, shape (n_samples, n_class * (n_class-1) / 2)
Returns the decision function of the sample for each class
in the model. | Distance of the samples X to the separating hyperplane. | [
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] | def _decision_function(self, X):
"""Distance of the samples X to the separating hyperplane.
Parameters
----------
X : array-like, shape (n_samples, n_features)
Returns
-------
X : array-like, shape (n_samples, n_class * (n_class-1) / 2)
Returns the decision function of the sample for each class
in the model.
"""
# NOTE: _validate_for_predict contains check for is_fitted
# hence must be placed before any other attributes are used.
X = self._validate_for_predict(X)
X = self._compute_kernel(X)
if self._sparse:
dec_func = self._sparse_decision_function(X)
else:
dec_func = self._dense_decision_function(X)
# In binary case, we need to flip the sign of coef, intercept and
# decision function.
if self._impl in ['c_svc', 'nu_svc'] and len(self.classes_) == 2:
return -dec_func.ravel()
return dec_func | [
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echronos/echronos | c996f1d2c8af6c6536205eb319c1bf1d4d84569c | external_tools/pystache/renderer.py | python | Renderer._interpolate | (self, val, formatter_key, location) | return formatter(val) | Convert a value to string. | Convert a value to string. | [
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] | def _interpolate(self, val, formatter_key, location):
"""Convert a value to string.
"""
try:
formatter = self.formatters[formatter_key]
except:
raise FormatterNotFoundError(formatter_key, location)
if isinstance(val, bytes):
val = self._bytes_to_str(val)
elif not isinstance(val, str):
val = str(val)
return formatter(val) | [
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mingchen/protobuf-ios | 0958df34558cd54cb7b6e6ca5c8855bf3d475046 | compiler/python/google/protobuf/internal/encoder.py | python | Encoder.AppendSInt64NoTag | (self, value) | Appends a 64-bit integer to our buffer, zigzag-encoded and then
varint-encoded. | Appends a 64-bit integer to our buffer, zigzag-encoded and then
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"""Appends a 64-bit integer to our buffer, zigzag-encoded and then
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zigzag_value = wire_format.ZigZagEncode(value)
self._stream.AppendVarUInt64(zigzag_value) | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/ops/math_grad.py | python | _TanhGrad | (op, grad) | Returns grad * (1 - tanh(x) * tanh(x)). | Returns grad * (1 - tanh(x) * tanh(x)). | [
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"""Returns grad * (1 - tanh(x) * tanh(x))."""
y = op.outputs[0] # y = tanh(x)
with ops.control_dependencies([grad.op]):
y = math_ops.conj(y)
# pylint: disable=protected-access
return gen_math_ops._tanh_grad(y, grad) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/idlelib/PyShell.py | python | PyShellEditorWindow.store_file_breaks | (self) | Save breakpoints when file is saved | Save breakpoints when file is saved | [
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# XXX 13 Dec 2002 KBK Currently the file must be saved before it can
# be run. The breaks are saved at that time. If we introduce
# a temporary file save feature the save breaks functionality
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# breaks stay synched with the subprocess even if one of these
# unexpected breakpoint deletions occurs.
breaks = self.breakpoints
filename = self.io.filename
try:
with open(self.breakpointPath,"r") as old_file:
lines = old_file.readlines()
except IOError:
lines = []
try:
with open(self.breakpointPath,"w") as new_file:
for line in lines:
if not line.startswith(filename + '='):
new_file.write(line)
self.update_breakpoints()
breaks = self.breakpoints
if breaks:
new_file.write(filename + '=' + str(breaks) + '\n')
except IOError as err:
if not getattr(self.root, "breakpoint_error_displayed", False):
self.root.breakpoint_error_displayed = True
tkMessageBox.showerror(title='IDLE Error',
message='Unable to update breakpoint list:\n%s'
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naver/sling | 5671cd445a2caae0b4dd0332299e4cfede05062c | webkit/Tools/Scripts/webkitpy/thirdparty/irc/irclib.py | python | ServerConnection.time | (self, server="") | Send a TIME command. | Send a TIME command. | [
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"""Send a TIME command."""
self.send_raw("TIME" + (server and (" " + server))) | [
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||
trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/seacas/scripts/exodus2.in.py | python | exodus.put_elem_blk_names | (self, names) | exo.put_elem_blk_names(elem_blk_names)
-> store a list of all element block names ordered by block *INDEX*;
(see description of get_elem_blk_ids() for explanation of the
difference between block *ID* and block *INDEX*)
input value(s):
<list<string>> elem_blk_names | exo.put_elem_blk_names(elem_blk_names) | [
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".",
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"""
exo.put_elem_blk_names(elem_blk_names)
-> store a list of all element block names ordered by block *INDEX*;
(see description of get_elem_blk_ids() for explanation of the
difference between block *ID* and block *INDEX*)
input value(s):
<list<string>> elem_blk_names
"""
objType = ex_entity_type("EX_ELEM_BLOCK")
inqType = ex_inquiry("EX_INQ_ELEM_BLK")
self.__ex_put_names(objType, inqType, names) | [
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||
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/genmsg/src/genmsg/msg_loader.py | python | MsgContext.get_registered | (self, full_msg_type) | :raises: :exc:`KeyError` If not registered | :raises: :exc:`KeyError` If not registered | [
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:raises: :exc:`KeyError` If not registered
"""
full_msg_type = bare_msg_type(full_msg_type)
if self.is_registered(full_msg_type):
package, base_type = package_resource_name(full_msg_type)
return self._registered_packages[package][base_type]
else:
raise KeyError(full_msg_type) | [
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||
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/idlelib/PyShell.py | python | ModifiedInterpreter.runcommand | (self, code) | return 1 | Run the code without invoking the debugger | Run the code without invoking the debugger | [
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"Run the code without invoking the debugger"
# The code better not raise an exception!
if self.tkconsole.executing:
self.display_executing_dialog()
return 0
if self.rpcclt:
self.rpcclt.remotequeue("exec", "runcode", (code,), {})
else:
exec code in self.locals
return 1 | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/piexif/_insert.py | python | insert | (exif, image, new_file=None) | py:function:: piexif.insert(exif_bytes, filename)
Insert exif into JPEG.
:param bytes exif_bytes: Exif as bytes
:param str filename: JPEG | py:function:: piexif.insert(exif_bytes, filename) | [
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":",
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"""
py:function:: piexif.insert(exif_bytes, filename)
Insert exif into JPEG.
:param bytes exif_bytes: Exif as bytes
:param str filename: JPEG
"""
if exif[0:6] != b"\x45\x78\x69\x66\x00\x00":
raise ValueError("Given data is not exif data")
output_file = False
# Prevents "UnicodeWarning: Unicode equal comparison failed" warnings on Python 2
maybe_image = sys.version_info >= (3,0,0) or isinstance(image, str)
if maybe_image and image[0:2] == b"\xff\xd8":
image_data = image
file_type = "jpeg"
elif maybe_image and image[0:4] == b"RIFF" and image[8:12] == b"WEBP":
image_data = image
file_type = "webp"
else:
with open(image, 'rb') as f:
image_data = f.read()
if image_data[0:2] == b"\xff\xd8":
file_type = "jpeg"
elif image_data[0:4] == b"RIFF" and image_data[8:12] == b"WEBP":
file_type = "webp"
else:
raise InvalidImageDataError
output_file = True
if file_type == "jpeg":
exif = b"\xff\xe1" + struct.pack(">H", len(exif) + 2) + exif
segments = split_into_segments(image_data)
new_data = merge_segments(segments, exif)
elif file_type == "webp":
exif = exif[6:]
new_data = _webp.insert(image_data, exif)
if isinstance(new_file, io.BytesIO):
new_file.write(new_data)
new_file.seek(0)
elif new_file:
with open(new_file, "wb+") as f:
f.write(new_data)
elif output_file:
with open(image, "wb+") as f:
f.write(new_data)
else:
raise ValueError("Give a 3rd argument to 'insert' to output file") | [
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||
OSGeo/gdal | 3748fc4ba4fba727492774b2b908a2130c864a83 | swig/python/osgeo/ogr.py | python | Geometry.GetSpatialReference | (self, *args) | return _ogr.Geometry_GetSpatialReference(self, *args) | r"""
GetSpatialReference(Geometry self) -> SpatialReference
OGRSpatialReferenceH
OGR_G_GetSpatialReference(OGRGeometryH hGeom)
Returns spatial reference system for geometry.
This function relates to the SFCOM IGeometry::get_SpatialReference()
method.
This function is the same as the CPP method
OGRGeometry::getSpatialReference().
Parameters:
-----------
hGeom: handle on the geometry to get spatial reference from.
a reference to the spatial reference geometry. | r"""
GetSpatialReference(Geometry self) -> SpatialReference
OGRSpatialReferenceH
OGR_G_GetSpatialReference(OGRGeometryH hGeom) | [
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] | def GetSpatialReference(self, *args):
r"""
GetSpatialReference(Geometry self) -> SpatialReference
OGRSpatialReferenceH
OGR_G_GetSpatialReference(OGRGeometryH hGeom)
Returns spatial reference system for geometry.
This function relates to the SFCOM IGeometry::get_SpatialReference()
method.
This function is the same as the CPP method
OGRGeometry::getSpatialReference().
Parameters:
-----------
hGeom: handle on the geometry to get spatial reference from.
a reference to the spatial reference geometry.
"""
return _ogr.Geometry_GetSpatialReference(self, *args) | [
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|
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/autograph/pyct/static_analysis/activity.py | python | Scope.merge_from | (self, other) | Adds all activity from another scope to this scope. | Adds all activity from another scope to this scope. | [
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] | def merge_from(self, other):
"""Adds all activity from another scope to this scope."""
assert not self.is_final
if self.parent is not None:
assert other.parent is not None
self.parent.merge_from(other.parent)
self.isolated_names.update(other.isolated_names)
self.read.update(other.read)
self.modified.update(other.modified)
self.bound.update(other.bound)
self.deleted.update(other.deleted)
self.annotations.update(other.annotations)
self.params.update(other.params) | [
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||
idaholab/moose | 9eeebc65e098b4c30f8205fb41591fd5b61eb6ff | python/MooseDocs/common/load_config.py | python | _yaml_load_content | (config, in_ext) | return MooseDocs.common.get_content(items, in_ext) | Load the 'Content' section. | Load the 'Content' section. | [
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"the",
"Content",
"section",
"."
] | def _yaml_load_content(config, in_ext):
"""Load the 'Content' section."""
options = config.get('Content', None)
if options is None:
msg = "The 'Content' section is required."
raise exceptions.MooseDocsException(msg)
items = MooseDocs.common.get_items(options)
return MooseDocs.common.get_content(items, in_ext) | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/cell.py | python | Cell.set_broadcast_flag | (self, mode=True) | return self | Set parameter broadcast mode for this cell.
Args:
mode (bool): Specifies whether the mode is parameter broadcast. Default: True. | Set parameter broadcast mode for this cell. | [
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] | def set_broadcast_flag(self, mode=True):
"""
Set parameter broadcast mode for this cell.
Args:
mode (bool): Specifies whether the mode is parameter broadcast. Default: True.
"""
self.add_flags_recursive(broadcast_flag=mode)
return self | [
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|
hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/framework/python/framework/deprecation.py | python | deprecated_args | (date, instructions, *deprecated_arg_names) | return deprecated_wrapper | Decorator for marking specific function arguments as deprecated.
This decorator logs a deprecation warning whenever the decorated function is
called with the deprecated argument. It has the following format:
Calling <function> (from <module>) with <arg> is deprecated and will be
removed after <date>. Instructions for updating:
<instructions>
<function> will include the class name if it is a method.
It also edits the docstring of the function: ' (deprecated arguments)' is
appended to the first line of the docstring and a deprecation notice is
prepended to the rest of the docstring.
Args:
date: String. The date the function is scheduled to be removed. Must be
ISO 8601 (YYYY-MM-DD).
instructions: String. Instructions on how to update code using the
deprecated function.
*deprecated_arg_names: String. The deprecated arguments.
Returns:
Decorated function or method.
Raises:
ValueError: If date is not in ISO 8601 format, instructions are empty, or
the deprecated arguments are not present in the function signature. | Decorator for marking specific function arguments as deprecated. | [
"Decorator",
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] | def deprecated_args(date, instructions, *deprecated_arg_names):
"""Decorator for marking specific function arguments as deprecated.
This decorator logs a deprecation warning whenever the decorated function is
called with the deprecated argument. It has the following format:
Calling <function> (from <module>) with <arg> is deprecated and will be
removed after <date>. Instructions for updating:
<instructions>
<function> will include the class name if it is a method.
It also edits the docstring of the function: ' (deprecated arguments)' is
appended to the first line of the docstring and a deprecation notice is
prepended to the rest of the docstring.
Args:
date: String. The date the function is scheduled to be removed. Must be
ISO 8601 (YYYY-MM-DD).
instructions: String. Instructions on how to update code using the
deprecated function.
*deprecated_arg_names: String. The deprecated arguments.
Returns:
Decorated function or method.
Raises:
ValueError: If date is not in ISO 8601 format, instructions are empty, or
the deprecated arguments are not present in the function signature.
"""
_validate_deprecation_args(date, instructions)
if not deprecated_arg_names:
raise ValueError('Specify which argument is deprecated.')
def deprecated_wrapper(func):
"""Deprecation decorator."""
_validate_callable(func, 'deprecated_args')
arg_spec = inspect.getargspec(func)
deprecated_positions = [
(i, arg_name) for (i, arg_name) in enumerate(arg_spec.args)
if arg_name in deprecated_arg_names]
is_varargs_deprecated = arg_spec.varargs in deprecated_arg_names
is_kwargs_deprecated = arg_spec.keywords in deprecated_arg_names
if (len(deprecated_positions) + is_varargs_deprecated + is_kwargs_deprecated
!= len(deprecated_arg_names)):
known_args = arg_spec.args + [arg_spec.varargs, arg_spec.keywords]
missing_args = [arg_name for arg_name in deprecated_arg_names
if arg_name not in known_args]
raise ValueError('The following deprecated arguments are not present '
'in the function signature: %s' % missing_args)
@functools.wraps(func)
def new_func(*args, **kwargs):
"""Deprecation wrapper."""
invalid_args = []
for (i, arg_name) in deprecated_positions:
if i < len(args):
invalid_args.append(arg_name)
if is_varargs_deprecated and len(args) > len(arg_spec.args):
invalid_args.append(arg_spec.varargs)
if is_kwargs_deprecated and kwargs:
invalid_args.append(arg_spec.keywords)
for arg_name in deprecated_arg_names:
if arg_name in kwargs:
invalid_args.append(arg_name)
for arg_name in invalid_args:
logging.warning(
'Calling %s (from %s) with %s is deprecated and will be removed '
'after %s.\nInstructions for updating:\n%s',
_get_qualified_name(func), func.__module__,
arg_name, date, instructions)
return func(*args, **kwargs)
new_func.__doc__ = _add_deprecated_arg_notice_to_docstring(
func.__doc__, date, instructions)
return new_func
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|
adobe/brackets-app | 26dc31087a30bef7754b94e09fe7e74f6da9d699 | src/mac/tools/change_mach_o_flags.py | python | WriteUInt32 | (file, uint32, endian) | Writes |uint32| as an unsinged 32-bit integer to the file-like |file|
object, treating it as having endianness specified by |endian| (per the
|struct| module). | Writes |uint32| as an unsinged 32-bit integer to the file-like |file|
object, treating it as having endianness specified by |endian| (per the
|struct| module). | [
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] | def WriteUInt32(file, uint32, endian):
"""Writes |uint32| as an unsinged 32-bit integer to the file-like |file|
object, treating it as having endianness specified by |endian| (per the
|struct| module)."""
bytes = struct.pack(endian + 'I', uint32)
assert len(bytes) == 4
file.write(bytes) | [
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||
ablab/spades | 3a754192b88540524ce6fb69eef5ea9273a38465 | assembler/ext/src/python_libs/joblib3/pool.py | python | _strided_from_memmap | (filename, dtype, mode, offset, order, shape, strides,
total_buffer_len) | Reconstruct an array view on a memmory mapped file | Reconstruct an array view on a memmory mapped file | [
"Reconstruct",
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"array",
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"on",
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] | def _strided_from_memmap(filename, dtype, mode, offset, order, shape, strides,
total_buffer_len):
"""Reconstruct an array view on a memmory mapped file"""
if mode == 'w+':
# Do not zero the original data when unpickling
mode = 'r+'
if strides is None:
# Simple, contiguous memmap
return np.memmap(filename, dtype=dtype, shape=shape, mode=mode,
offset=offset, order=order)
else:
# For non-contiguous data, memmap the total enclosing buffer and then
# extract the non-contiguous view with the stride-tricks API
base = np.memmap(filename, dtype=dtype, shape=total_buffer_len,
mode=mode, offset=offset, order=order)
return as_strided(base, shape=shape, strides=strides) | [
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||
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/abins/input/euphonicloader.py | python | EuphonicLoader.__init__ | (self, input_ab_initio_filename) | :param input_ab_initio_filename: name of file with phonon data (foo.phonon) | [] | def __init__(self, input_ab_initio_filename):
"""
:param input_ab_initio_filename: name of file with phonon data (foo.phonon)
"""
if not isinstance(input_ab_initio_filename, str):
raise TypeError('Filename must be a string')
elif not Path(input_ab_initio_filename).is_file():
raise IOError(f'Ab initio file {input_ab_initio_filename} not found.')
super().__init__(input_ab_initio_filename=input_ab_initio_filename)
self._ab_initio_program = "FORCECONSTANTS" | [
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|||
apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/numpy/multiarray.py | python | may_share_memory | (a, b, max_work=None) | return _mx_nd_np.may_share_memory(a, b, max_work) | Determine if two arrays might share memory
A return of True does not necessarily mean that the two arrays
share any element. It just means that they *might*.
Only the memory bounds of a and b are checked by default.
Parameters
----------
a, b : ndarray
Input arrays
Returns
-------
out : bool
See Also
--------
shares_memory
Examples
--------
>>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
False
>>> x = np.zeros([3, 4])
>>> np.may_share_memory(x[:,0], x[:,1])
True
.. note::
This function differs from the original `numpy.may_share_memory
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.may_share_memory.html>`_ in
the following way(s):
* Does not support `max_work`, it is a dummy argument
* Actually it is same as `shares_memory` in MXNet np | Determine if two arrays might share memory | [
"Determine",
"if",
"two",
"arrays",
"might",
"share",
"memory"
] | def may_share_memory(a, b, max_work=None):
"""
Determine if two arrays might share memory
A return of True does not necessarily mean that the two arrays
share any element. It just means that they *might*.
Only the memory bounds of a and b are checked by default.
Parameters
----------
a, b : ndarray
Input arrays
Returns
-------
out : bool
See Also
--------
shares_memory
Examples
--------
>>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
False
>>> x = np.zeros([3, 4])
>>> np.may_share_memory(x[:,0], x[:,1])
True
.. note::
This function differs from the original `numpy.may_share_memory
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.may_share_memory.html>`_ in
the following way(s):
* Does not support `max_work`, it is a dummy argument
* Actually it is same as `shares_memory` in MXNet np
"""
return _mx_nd_np.may_share_memory(a, b, max_work) | [
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|
wyrover/book-code | 7f4883d9030d553bc6bcfa3da685e34789839900 | 3rdparty/protobuf/python/google/protobuf/internal/containers.py | python | RepeatedCompositeFieldContainer.MergeFrom | (self, other) | Appends the contents of another repeated field of the same type to this
one, copying each individual message. | Appends the contents of another repeated field of the same type to this
one, copying each individual message. | [
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] | def MergeFrom(self, other):
"""Appends the contents of another repeated field of the same type to this
one, copying each individual message.
"""
self.extend(other._values) | [
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||
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/saving/save.py | python | save_model | (model,
filepath,
overwrite=True,
include_optimizer=True,
save_format=None,
signatures=None) | Saves a model as a TensorFlow SavedModel or HDF5 file.
The saved model contains:
- the model's configuration (topology)
- the model's weights
- the model's optimizer's state (if any)
Thus the saved model can be reinstantiated in
the exact same state, without any of the code
used for model definition or training.
_SavedModel serialization_ (not yet added)
The SavedModel serialization path uses `tf.saved_model.save` to save the model
and all trackable objects attached to the model (e.g. layers and variables).
`@tf.function`-decorated methods are also saved. Additional trackable objects
and functions are added to the SavedModel to allow the model to be
loaded back as a Keras Model object.
Arguments:
model: Keras model instance to be saved.
filepath: One of the following:
- String, path where to save the model
- `h5py.File` object where to save the model
overwrite: Whether we should overwrite any existing model at the target
location, or instead ask the user with a manual prompt.
include_optimizer: If True, save optimizer's state together.
save_format: Either 'tf' or 'h5', indicating whether to save the model
to Tensorflow SavedModel or HDF5. Defaults to 'tf' in TF 2.X, and 'h5'
in TF 1.X.
signatures: Signatures to save with the SavedModel. Applicable to the 'tf'
format only. Please see the `signatures` argument in
`tf.saved_model.save` for details.
Raises:
ImportError: If save format is hdf5, and h5py is not available. | Saves a model as a TensorFlow SavedModel or HDF5 file. | [
"Saves",
"a",
"model",
"as",
"a",
"TensorFlow",
"SavedModel",
"or",
"HDF5",
"file",
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] | def save_model(model,
filepath,
overwrite=True,
include_optimizer=True,
save_format=None,
signatures=None):
"""Saves a model as a TensorFlow SavedModel or HDF5 file.
The saved model contains:
- the model's configuration (topology)
- the model's weights
- the model's optimizer's state (if any)
Thus the saved model can be reinstantiated in
the exact same state, without any of the code
used for model definition or training.
_SavedModel serialization_ (not yet added)
The SavedModel serialization path uses `tf.saved_model.save` to save the model
and all trackable objects attached to the model (e.g. layers and variables).
`@tf.function`-decorated methods are also saved. Additional trackable objects
and functions are added to the SavedModel to allow the model to be
loaded back as a Keras Model object.
Arguments:
model: Keras model instance to be saved.
filepath: One of the following:
- String, path where to save the model
- `h5py.File` object where to save the model
overwrite: Whether we should overwrite any existing model at the target
location, or instead ask the user with a manual prompt.
include_optimizer: If True, save optimizer's state together.
save_format: Either 'tf' or 'h5', indicating whether to save the model
to Tensorflow SavedModel or HDF5. Defaults to 'tf' in TF 2.X, and 'h5'
in TF 1.X.
signatures: Signatures to save with the SavedModel. Applicable to the 'tf'
format only. Please see the `signatures` argument in
`tf.saved_model.save` for details.
Raises:
ImportError: If save format is hdf5, and h5py is not available.
"""
from tensorflow.python.keras.engine import sequential # pylint: disable=g-import-not-at-top
default_format = 'tf' if tf2.enabled() else 'h5'
save_format = save_format or default_format
if (save_format == 'h5' or
(h5py is not None and isinstance(filepath, h5py.File)) or
os.path.splitext(filepath)[1] in _HDF5_EXTENSIONS):
# TODO(b/130258301): add utility method for detecting model type.
if (not model._is_graph_network and # pylint:disable=protected-access
not isinstance(model, sequential.Sequential)):
raise NotImplementedError(
'Saving the model to HDF5 format requires the model to be a '
'Functional model or a Sequential model. It does not work for '
'subclassed models, because such models are defined via the body of '
'a Python method, which isn\'t safely serializable. Consider saving '
'to the Tensorflow SavedModel format (by setting save_format="tf") '
'or using `save_weights`.')
hdf5_format.save_model_to_hdf5(
model, filepath, overwrite, include_optimizer)
else:
saved_model_save.save(model, filepath, overwrite, include_optimizer,
signatures) | [
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||
ceph/ceph | 959663007321a369c83218414a29bd9dbc8bda3a | src/pybind/mgr/mirroring/fs/dir_map/policy.py | python | Policy.can_shuffle_dir | (self, dir_path) | return StateTransition.is_idle(dir_state.state) and \
(time.time() - dir_state['mapped_time']) > Policy.DIR_SHUFFLE_THROTTLE_INTERVAL | Right now, shuffle directories only based on idleness. Later, we
probably want to avoid shuffling images that were recently shuffled. | Right now, shuffle directories only based on idleness. Later, we
probably want to avoid shuffling images that were recently shuffled. | [
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"""Right now, shuffle directories only based on idleness. Later, we
probably want to avoid shuffling images that were recently shuffled.
"""
log.debug(f'can_shuffle_dir: {dir_path}')
dir_state = self.dir_states[dir_path]
return StateTransition.is_idle(dir_state.state) and \
(time.time() - dir_state['mapped_time']) > Policy.DIR_SHUFFLE_THROTTLE_INTERVAL | [
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|
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/rnn_cell_impl.py | python | _linear | (args,
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bias_initializer=None,
kernel_initializer=None) | Linear map: sum_i(args[i] * W[i]), where W[i] is a variable.
Args:
args: a 2D Tensor or a list of 2D, batch, n, Tensors.
output_size: int, second dimension of W[i].
bias: boolean, whether to add a bias term or not.
bias_initializer: starting value to initialize the bias
(default is all zeros).
kernel_initializer: starting value to initialize the weight.
Returns:
A 2D Tensor with shape `[batch, output_size]` equal to
sum_i(args[i] * W[i]), where W[i]s are newly created matrices.
Raises:
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"""Linear map: sum_i(args[i] * W[i]), where W[i] is a variable.
Args:
args: a 2D Tensor or a list of 2D, batch, n, Tensors.
output_size: int, second dimension of W[i].
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"""
if args is None or (nest.is_sequence(args) and not args):
raise ValueError("`args` must be specified")
if not nest.is_sequence(args):
args = [args]
# Calculate the total size of arguments on dimension 1.
total_arg_size = 0
shapes = [a.get_shape() for a in args]
for shape in shapes:
if shape.ndims != 2:
raise ValueError("linear is expecting 2D arguments: %s" % shapes)
if shape[1].value is None:
raise ValueError("linear expects shape[1] to be provided for shape %s, "
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else:
total_arg_size += shape[1].value
dtype = [a.dtype for a in args][0]
# Now the computation.
scope = vs.get_variable_scope()
with vs.variable_scope(scope) as outer_scope:
weights = vs.get_variable(
_WEIGHTS_VARIABLE_NAME, [total_arg_size, output_size],
dtype=dtype,
initializer=kernel_initializer)
if len(args) == 1:
res = math_ops.matmul(args[0], weights)
else:
res = math_ops.matmul(array_ops.concat(args, 1), weights)
if not bias:
return res
with vs.variable_scope(outer_scope) as inner_scope:
inner_scope.set_partitioner(None)
if bias_initializer is None:
bias_initializer = init_ops.constant_initializer(0.0, dtype=dtype)
biases = vs.get_variable(
_BIAS_VARIABLE_NAME, [output_size],
dtype=dtype,
initializer=bias_initializer)
return nn_ops.bias_add(res, biases) | [
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||
facebook/ThreatExchange | 31914a51820c73c8a0daffe62ccca29a6e3d359e | api-reference-examples/python/pytx/pytx/malware.py | python | Malware.rfh | (self) | return rfh | Return a file handle of the base64-decoded and unzipped sample. | Return a file handle of the base64-decoded and unzipped sample. | [
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"""
Return a file handle of the base64-decoded and unzipped sample.
"""
zfh = self.zfh
rfh = io.BytesIO()
with zipfile.ZipFile(zfh, 'r') as zf:
for entry in zf.infolist():
rfh.write(zf.read(entry.filename,
self.get(m.PASSWORD)))
rfh.seek(0)
return rfh | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/indexes/numeric.py | python | UInt64Index.inferred_type | (self) | return "integer" | Always 'integer' for ``UInt64Index`` | Always 'integer' for ``UInt64Index`` | [
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] | def inferred_type(self) -> str:
"""
Always 'integer' for ``UInt64Index``
"""
return "integer" | [
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|
intel/llvm | e6d0547e9d99b5a56430c4749f6c7e328bf221ab | clang/bindings/python/clang/cindex.py | python | Cursor.is_const_method | (self) | return conf.lib.clang_CXXMethod_isConst(self) | Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'. | Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'. | [
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] | def is_const_method(self):
"""Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'.
"""
return conf.lib.clang_CXXMethod_isConst(self) | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/requests/cookies.py | python | morsel_to_cookie | (morsel) | return create_cookie(
comment=morsel['comment'],
comment_url=bool(morsel['comment']),
discard=False,
domain=morsel['domain'],
expires=expires,
name=morsel.key,
path=morsel['path'],
port=None,
rest={'HttpOnly': morsel['httponly']},
rfc2109=False,
secure=bool(morsel['secure']),
value=morsel.value,
version=morsel['version'] or 0,
) | Convert a Morsel object into a Cookie containing the one k/v pair. | Convert a Morsel object into a Cookie containing the one k/v pair. | [
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] | def morsel_to_cookie(morsel):
"""Convert a Morsel object into a Cookie containing the one k/v pair."""
expires = None
if morsel['max-age']:
try:
expires = int(time.time() + int(morsel['max-age']))
except ValueError:
raise TypeError('max-age: %s must be integer' % morsel['max-age'])
elif morsel['expires']:
time_template = '%a, %d-%b-%Y %H:%M:%S GMT'
expires = calendar.timegm(
time.strptime(morsel['expires'], time_template)
)
return create_cookie(
comment=morsel['comment'],
comment_url=bool(morsel['comment']),
discard=False,
domain=morsel['domain'],
expires=expires,
name=morsel.key,
path=morsel['path'],
port=None,
rest={'HttpOnly': morsel['httponly']},
rfc2109=False,
secure=bool(morsel['secure']),
value=morsel.value,
version=morsel['version'] or 0,
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | uCSIsCatPi | (code) | return ret | Check whether the character is part of Pi UCS Category | Check whether the character is part of Pi UCS Category | [
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"whether",
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"character",
"is",
"part",
"of",
"Pi",
"UCS",
"Category"
] | def uCSIsCatPi(code):
"""Check whether the character is part of Pi UCS Category """
ret = libxml2mod.xmlUCSIsCatPi(code)
return ret | [
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|
ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | sp/src/thirdparty/protobuf-2.3.0/python/mox.py | python | Func.__init__ | (self, func) | Initialize.
Args:
func: callable that takes one parameter and returns a bool | Initialize. | [
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"""Initialize.
Args:
func: callable that takes one parameter and returns a bool
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_core.py | python | FileSystemHandler.GetRightLocation | (*args, **kwargs) | return _core_.FileSystemHandler_GetRightLocation(*args, **kwargs) | GetRightLocation(String location) -> String | GetRightLocation(String location) -> String | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/urllib/robotparser.py | python | RobotFileParser.modified | (self) | Sets the time the robots.txt file was last fetched to the
current time. | Sets the time the robots.txt file was last fetched to the
current time. | [
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"""Sets the time the robots.txt file was last fetched to the
current time.
"""
import time
self.last_checked = time.time() | [
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||
JumpingYang001/webrtc | c03d6e965e1f54aeadd670e491eabe5fdb8db968 | tools_webrtc/vim/webrtc.ycm_extra_conf.py | python | GetNinjaBuildOutputsForSourceFile | (out_dir, filename) | return [
target for target in output_lines
if target and (target.endswith('.o') or target.endswith('.obj'))
] | Returns a list of build outputs for filename.
The list is generated by invoking 'ninja -t query' tool to retrieve a list of
inputs and outputs of |filename|. This list is then filtered to only include
.o and .obj outputs.
Args:
out_dir: (String) Absolute path to ninja build output directory.
filename: (String) Absolute path to source file.
Returns:
(List of Strings) List of target names. Will return [] if |filename| doesn't
yield any .o or .obj outputs. | Returns a list of build outputs for filename. | [
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] | def GetNinjaBuildOutputsForSourceFile(out_dir, filename):
"""Returns a list of build outputs for filename.
The list is generated by invoking 'ninja -t query' tool to retrieve a list of
inputs and outputs of |filename|. This list is then filtered to only include
.o and .obj outputs.
Args:
out_dir: (String) Absolute path to ninja build output directory.
filename: (String) Absolute path to source file.
Returns:
(List of Strings) List of target names. Will return [] if |filename| doesn't
yield any .o or .obj outputs.
"""
# Ninja needs the path to the source file relative to the output build
# directory.
rel_filename = os.path.relpath(filename, out_dir)
p = subprocess.Popen(['ninja', '-C', out_dir, '-t', 'query', rel_filename],
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
universal_newlines=True)
stdout, _ = p.communicate()
if p.returncode != 0:
return []
# The output looks like:
# ../../relative/path/to/source.cc:
# outputs:
# obj/reative/path/to/target.source.o
# obj/some/other/target2.source.o
# another/target.txt
#
outputs_text = stdout.partition('\n outputs:\n')[2]
output_lines = [line.strip() for line in outputs_text.split('\n')]
return [
target for target in output_lines
if target and (target.endswith('.o') or target.endswith('.obj'))
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] | https://github.com/JumpingYang001/webrtc/blob/c03d6e965e1f54aeadd670e491eabe5fdb8db968/tools_webrtc/vim/webrtc.ycm_extra_conf.py#L123-L162 |
|
perilouswithadollarsign/cstrike15_src | f82112a2388b841d72cb62ca48ab1846dfcc11c8 | thirdparty/protobuf-2.5.0/python/google/protobuf/service_reflection.py | python | GeneratedServiceType.__init__ | (cls, name, bases, dictionary) | Creates a message service class.
Args:
name: Name of the class (ignored, but required by the metaclass
protocol).
bases: Base classes of the class being constructed.
dictionary: The class dictionary of the class being constructed.
dictionary[_DESCRIPTOR_KEY] must contain a ServiceDescriptor object
describing this protocol service type. | Creates a message service class. | [
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"."
] | def __init__(cls, name, bases, dictionary):
"""Creates a message service class.
Args:
name: Name of the class (ignored, but required by the metaclass
protocol).
bases: Base classes of the class being constructed.
dictionary: The class dictionary of the class being constructed.
dictionary[_DESCRIPTOR_KEY] must contain a ServiceDescriptor object
describing this protocol service type.
"""
# Don't do anything if this class doesn't have a descriptor. This happens
# when a service class is subclassed.
if GeneratedServiceType._DESCRIPTOR_KEY not in dictionary:
return
descriptor = dictionary[GeneratedServiceType._DESCRIPTOR_KEY]
service_builder = _ServiceBuilder(descriptor)
service_builder.BuildService(cls) | [
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||
MVIG-SJTU/RMPE | 5188c230ec800c12be7369c3619615bc9b020aa4 | scripts/cpp_lint.py | python | CheckBraces | (filename, clean_lines, linenum, error) | Looks for misplaced braces (e.g. at the end of line).
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found. | Looks for misplaced braces (e.g. at the end of line). | [
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"""Looks for misplaced braces (e.g. at the end of line).
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum] # get rid of comments and strings
if Match(r'\s*{\s*$', line):
# We allow an open brace to start a line in the case where someone is using
# braces in a block to explicitly create a new scope, which is commonly used
# to control the lifetime of stack-allocated variables. Braces are also
# used for brace initializers inside function calls. We don't detect this
# perfectly: we just don't complain if the last non-whitespace character on
# the previous non-blank line is ',', ';', ':', '(', '{', or '}', or if the
# previous line starts a preprocessor block.
prevline = GetPreviousNonBlankLine(clean_lines, linenum)[0]
if (not Search(r'[,;:}{(]\s*$', prevline) and
not Match(r'\s*#', prevline)):
error(filename, linenum, 'whitespace/braces', 4,
'{ should almost always be at the end of the previous line')
# An else clause should be on the same line as the preceding closing brace.
if Match(r'\s*else\s*', line):
prevline = GetPreviousNonBlankLine(clean_lines, linenum)[0]
if Match(r'\s*}\s*$', prevline):
error(filename, linenum, 'whitespace/newline', 4,
'An else should appear on the same line as the preceding }')
# If braces come on one side of an else, they should be on both.
# However, we have to worry about "else if" that spans multiple lines!
if Search(r'}\s*else[^{]*$', line) or Match(r'[^}]*else\s*{', line):
if Search(r'}\s*else if([^{]*)$', line): # could be multi-line if
# find the ( after the if
pos = line.find('else if')
pos = line.find('(', pos)
if pos > 0:
(endline, _, endpos) = CloseExpression(clean_lines, linenum, pos)
if endline[endpos:].find('{') == -1: # must be brace after if
error(filename, linenum, 'readability/braces', 5,
'If an else has a brace on one side, it should have it on both')
else: # common case: else not followed by a multi-line if
error(filename, linenum, 'readability/braces', 5,
'If an else has a brace on one side, it should have it on both')
# Likewise, an else should never have the else clause on the same line
if Search(r'\belse [^\s{]', line) and not Search(r'\belse if\b', line):
error(filename, linenum, 'whitespace/newline', 4,
'Else clause should never be on same line as else (use 2 lines)')
# In the same way, a do/while should never be on one line
if Match(r'\s*do [^\s{]', line):
error(filename, linenum, 'whitespace/newline', 4,
'do/while clauses should not be on a single line')
# Block bodies should not be followed by a semicolon. Due to C++11
# brace initialization, there are more places where semicolons are
# required than not, so we use a whitelist approach to check these
# rather than a blacklist. These are the places where "};" should
# be replaced by just "}":
# 1. Some flavor of block following closing parenthesis:
# for (;;) {};
# while (...) {};
# switch (...) {};
# Function(...) {};
# if (...) {};
# if (...) else if (...) {};
#
# 2. else block:
# if (...) else {};
#
# 3. const member function:
# Function(...) const {};
#
# 4. Block following some statement:
# x = 42;
# {};
#
# 5. Block at the beginning of a function:
# Function(...) {
# {};
# }
#
# Note that naively checking for the preceding "{" will also match
# braces inside multi-dimensional arrays, but this is fine since
# that expression will not contain semicolons.
#
# 6. Block following another block:
# while (true) {}
# {};
#
# 7. End of namespaces:
# namespace {};
#
# These semicolons seems far more common than other kinds of
# redundant semicolons, possibly due to people converting classes
# to namespaces. For now we do not warn for this case.
#
# Try matching case 1 first.
match = Match(r'^(.*\)\s*)\{', line)
if match:
# Matched closing parenthesis (case 1). Check the token before the
# matching opening parenthesis, and don't warn if it looks like a
# macro. This avoids these false positives:
# - macro that defines a base class
# - multi-line macro that defines a base class
# - macro that defines the whole class-head
#
# But we still issue warnings for macros that we know are safe to
# warn, specifically:
# - TEST, TEST_F, TEST_P, MATCHER, MATCHER_P
# - TYPED_TEST
# - INTERFACE_DEF
# - EXCLUSIVE_LOCKS_REQUIRED, SHARED_LOCKS_REQUIRED, LOCKS_EXCLUDED:
#
# We implement a whitelist of safe macros instead of a blacklist of
# unsafe macros, even though the latter appears less frequently in
# google code and would have been easier to implement. This is because
# the downside for getting the whitelist wrong means some extra
# semicolons, while the downside for getting the blacklist wrong
# would result in compile errors.
#
# In addition to macros, we also don't want to warn on compound
# literals.
closing_brace_pos = match.group(1).rfind(')')
opening_parenthesis = ReverseCloseExpression(
clean_lines, linenum, closing_brace_pos)
if opening_parenthesis[2] > -1:
line_prefix = opening_parenthesis[0][0:opening_parenthesis[2]]
macro = Search(r'\b([A-Z_]+)\s*$', line_prefix)
if ((macro and
macro.group(1) not in (
'TEST', 'TEST_F', 'MATCHER', 'MATCHER_P', 'TYPED_TEST',
'EXCLUSIVE_LOCKS_REQUIRED', 'SHARED_LOCKS_REQUIRED',
'LOCKS_EXCLUDED', 'INTERFACE_DEF')) or
Search(r'\s+=\s*$', line_prefix)):
match = None
else:
# Try matching cases 2-3.
match = Match(r'^(.*(?:else|\)\s*const)\s*)\{', line)
if not match:
# Try matching cases 4-6. These are always matched on separate lines.
#
# Note that we can't simply concatenate the previous line to the
# current line and do a single match, otherwise we may output
# duplicate warnings for the blank line case:
# if (cond) {
# // blank line
# }
prevline = GetPreviousNonBlankLine(clean_lines, linenum)[0]
if prevline and Search(r'[;{}]\s*$', prevline):
match = Match(r'^(\s*)\{', line)
# Check matching closing brace
if match:
(endline, endlinenum, endpos) = CloseExpression(
clean_lines, linenum, len(match.group(1)))
if endpos > -1 and Match(r'^\s*;', endline[endpos:]):
# Current {} pair is eligible for semicolon check, and we have found
# the redundant semicolon, output warning here.
#
# Note: because we are scanning forward for opening braces, and
# outputting warnings for the matching closing brace, if there are
# nested blocks with trailing semicolons, we will get the error
# messages in reversed order.
error(filename, endlinenum, 'readability/braces', 4,
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] | https://github.com/MVIG-SJTU/RMPE/blob/5188c230ec800c12be7369c3619615bc9b020aa4/scripts/cpp_lint.py#L3073-L3244 |
||
rdkit/rdkit | ede860ae316d12d8568daf5ee800921c3389c84e | rdkit/ML/Cluster/Clusters.py | python | Cluster.AddChildren | (self, children) | Adds a bunch of children to our list
**Arguments**
- children: a list of Clusters | Adds a bunch of children to our list | [
"Adds",
"a",
"bunch",
"of",
"children",
"to",
"our",
"list"
] | def AddChildren(self, children):
"""Adds a bunch of children to our list
**Arguments**
- children: a list of Clusters
"""
self.children += children
self._GenPoints()
self._UpdateLength() | [
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||
miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/python/framework/common_shapes.py | python | depthwise_conv2d_native_shape | (op) | return [tensor_shape.TensorShape([batch_size, out_rows, out_cols, depth_out])] | Shape function for a DepthwiseConv2D op.
This op has two inputs:
* input, a 4D tensor with shape = [batch_size, rows, cols, depth_in]
* filter, a 4D tensor with shape = [filter_rows, filter_cols,
depth_in, depthwise_multiplier]
The output is a 4D tensor with shape = [batch_size, out_rows,
out_cols, depth_in*depthwise_multiplier], where out_rows and out_cols depend
on the value of the op's "padding" and "strides" attrs.
Args:
op: A DepthwiseConv2dNative Operation.
Returns:
A list containing the Shape of the DepthwiseConv2DNative output.
Raises:
ValueError: If the shapes of the input or filter are incompatible. | Shape function for a DepthwiseConv2D op. | [
"Shape",
"function",
"for",
"a",
"DepthwiseConv2D",
"op",
"."
] | def depthwise_conv2d_native_shape(op):
"""Shape function for a DepthwiseConv2D op.
This op has two inputs:
* input, a 4D tensor with shape = [batch_size, rows, cols, depth_in]
* filter, a 4D tensor with shape = [filter_rows, filter_cols,
depth_in, depthwise_multiplier]
The output is a 4D tensor with shape = [batch_size, out_rows,
out_cols, depth_in*depthwise_multiplier], where out_rows and out_cols depend
on the value of the op's "padding" and "strides" attrs.
Args:
op: A DepthwiseConv2dNative Operation.
Returns:
A list containing the Shape of the DepthwiseConv2DNative output.
Raises:
ValueError: If the shapes of the input or filter are incompatible.
"""
input_shape = op.inputs[0].get_shape().with_rank(4)
filter_shape = op.inputs[1].get_shape().with_rank(4)
batch_size = input_shape[0]
in_rows = input_shape[1]
in_cols = input_shape[2]
filter_rows = filter_shape[0]
filter_cols = filter_shape[1]
depth_out = filter_shape[3] * filter_shape[2]
# Check that the input depths are compatible.
input_shape[3].assert_is_compatible_with(filter_shape[2])
stride_b, stride_r, stride_c, stride_d = op.get_attr("strides")
if stride_b != 1 or stride_d != 1:
raise ValueError("Current implementation does not yet support "
"strides in the batch and depth dimensions.")
if stride_r != stride_c:
# TODO(shlens): Add support for this.
raise ValueError("Current implementation only supports equal length "
"strides in the row and column dimensions.")
# TODO(mrry,shlens): Raise an error if the stride would cause
# information in the input to be ignored. This will require a change
# in the kernel implementation.
stride = stride_r
padding = op.get_attr("padding")
out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows,
filter_cols, stride, stride,
padding)
return [tensor_shape.TensorShape([batch_size, out_rows, out_cols, depth_out])] | [
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|
ArduPilot/ardupilot | 6e684b3496122b8158ac412b609d00004b7ac306 | Tools/scripts/build_binaries.py | python | build_binaries.touch_filepath | (self, filepath) | creates a file at filepath, or updates the timestamp on filepath | creates a file at filepath, or updates the timestamp on filepath | [
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"file",
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"updates",
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"timestamp",
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] | def touch_filepath(self, filepath):
'''creates a file at filepath, or updates the timestamp on filepath'''
if os.path.exists(filepath):
os.utime(filepath, None)
else:
with open(filepath, "a"):
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||
gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | gr-digital/python/digital/qa_header_payload_demux.py | python | qa_header_payload_demux.test_001_headerpadding_payload_offset | (self) | Like test 1, but with header padding + payload offset. | Like test 1, but with header padding + payload offset. | [
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"+",
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"offset",
"."
] | def test_001_headerpadding_payload_offset(self):
""" Like test 1, but with header padding + payload offset. """
n_zeros = 3
header = [1, 2, 3]
header_padding = 1
payload_offset = -1
payload = list(range(5, 20))
data_signal = [0, ] * n_zeros + header + payload + [0, ] * 100
trigger_signal = [0] * len(data_signal)
trigger_signal[n_zeros] = 1
# This goes on output 1, item 3 + 1 (for payload offset)
testtag4 = make_tag('tag4', 314, n_zeros + len(header) + 3)
data_src = blocks.vector_source_f(
data_signal,
False,
tags=(testtag4,)
)
trigger_src = blocks.vector_source_b(trigger_signal, False)
hpd = digital.header_payload_demux(
len(header),
1, # Items per symbol
0, # Guard interval
"frame_len", # TSB tag key
"detect", # Trigger tag key
False, # No symbols please
gr.sizeof_float, # Item size
"", # Timing tag key
1.0, # Samp rate
(), # No special tags
header_padding
)
# extra system port defined for you
self.assertEqual(pmt.length(hpd.message_ports_in()), 2)
header_sink = blocks.vector_sink_f()
payload_sink = blocks.vector_sink_f()
self.tb.connect(data_src, (hpd, 0))
self.tb.connect(trigger_src, (hpd, 1))
self.tb.connect((hpd, 0), header_sink)
self.tb.connect((hpd, 1), payload_sink)
self.tb.start()
time.sleep(.2) # Need this, otherwise, the next message is ignored
hpd.to_basic_block()._post(pmt.intern('header_data'), pmt.to_pmt(
{'frame_len': len(payload), 'payload_offset': payload_offset}))
while len(payload_sink.data()) < len(payload):
time.sleep(.2)
self.tb.stop()
self.tb.wait()
# Header is now padded:
self.assertEqual(header_sink.data(), [0, ] + header + [payload[0], ])
# Payload is now offset:
self.assertEqual(payload_sink.data(), data_signal[n_zeros + len(
header) + payload_offset:n_zeros + len(header) + payload_offset + len(payload)])
ptags_payload = {}
for tag in payload_sink.tags():
ptag = gr.tag_to_python(tag)
ptags_payload[ptag.key] = ptag.offset
expected_tags_payload = {
'frame_len': 0,
'payload_offset': 0,
'tag4': 3 - payload_offset,
}
self.assertEqual(expected_tags_payload, ptags_payload) | [
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] | https://github.com/gnuradio/gnuradio/blob/09c3c4fa4bfb1a02caac74cb5334dfe065391e3b/gr-digital/python/digital/qa_header_payload_demux.py#L316-L377 |
||
google/llvm-propeller | 45c226984fe8377ebfb2ad7713c680d652ba678d | compiler-rt/lib/sanitizer_common/scripts/cpplint.py | python | ReplaceAll | (pattern, rep, s) | return _regexp_compile_cache[pattern].sub(rep, s) | Replaces instances of pattern in a string with a replacement.
The compiled regex is kept in a cache shared by Match and Search.
Args:
pattern: regex pattern
rep: replacement text
s: search string
Returns:
string with replacements made (or original string if no replacements) | Replaces instances of pattern in a string with a replacement. | [
"Replaces",
"instances",
"of",
"pattern",
"in",
"a",
"string",
"with",
"a",
"replacement",
"."
] | def ReplaceAll(pattern, rep, s):
"""Replaces instances of pattern in a string with a replacement.
The compiled regex is kept in a cache shared by Match and Search.
Args:
pattern: regex pattern
rep: replacement text
s: search string
Returns:
string with replacements made (or original string if no replacements)
"""
if pattern not in _regexp_compile_cache:
_regexp_compile_cache[pattern] = sre_compile.compile(pattern)
return _regexp_compile_cache[pattern].sub(rep, s) | [
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|
xiaohaoChen/rrc_detection | 4f2b110cd122da7f55e8533275a9b4809a88785a | scripts/cpp_lint.py | python | _Filters | () | return _cpplint_state.filters | Returns the module's list of output filters, as a list. | Returns the module's list of output filters, as a list. | [
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] | def _Filters():
"""Returns the module's list of output filters, as a list."""
return _cpplint_state.filters | [
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] | https://github.com/xiaohaoChen/rrc_detection/blob/4f2b110cd122da7f55e8533275a9b4809a88785a/scripts/cpp_lint.py#L792-L794 |
|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/_osx_support.py | python | customize_config_vars | (_config_vars) | return _config_vars | Customize Python build configuration variables.
Called internally from sysconfig with a mutable mapping
containing name/value pairs parsed from the configured
makefile used to build this interpreter. Returns
the mapping updated as needed to reflect the environment
in which the interpreter is running; in the case of
a Python from a binary installer, the installed
environment may be very different from the build
environment, i.e. different OS levels, different
built tools, different available CPU architectures.
This customization is performed whenever
distutils.sysconfig.get_config_vars() is first
called. It may be used in environments where no
compilers are present, i.e. when installing pure
Python dists. Customization of compiler paths
and detection of unavailable archs is deferred
until the first extention module build is
requested (in distutils.sysconfig.customize_compiler).
Currently called from distutils.sysconfig | Customize Python build configuration variables. | [
"Customize",
"Python",
"build",
"configuration",
"variables",
"."
] | def customize_config_vars(_config_vars):
"""Customize Python build configuration variables.
Called internally from sysconfig with a mutable mapping
containing name/value pairs parsed from the configured
makefile used to build this interpreter. Returns
the mapping updated as needed to reflect the environment
in which the interpreter is running; in the case of
a Python from a binary installer, the installed
environment may be very different from the build
environment, i.e. different OS levels, different
built tools, different available CPU architectures.
This customization is performed whenever
distutils.sysconfig.get_config_vars() is first
called. It may be used in environments where no
compilers are present, i.e. when installing pure
Python dists. Customization of compiler paths
and detection of unavailable archs is deferred
until the first extention module build is
requested (in distutils.sysconfig.customize_compiler).
Currently called from distutils.sysconfig
"""
if not _supports_universal_builds():
# On Mac OS X before 10.4, check if -arch and -isysroot
# are in CFLAGS or LDFLAGS and remove them if they are.
# This is needed when building extensions on a 10.3 system
# using a universal build of python.
_remove_universal_flags(_config_vars)
# Allow user to override all archs with ARCHFLAGS env var
_override_all_archs(_config_vars)
# Remove references to sdks that are not found
_check_for_unavailable_sdk(_config_vars)
return _config_vars | [
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|
psi4/psi4 | be533f7f426b6ccc263904e55122899b16663395 | psi4/driver/p4util/procutil.py | python | prepare_options_for_modules | (changedOnly=False, commandsInsteadDict=False) | Function to return a string of commands to replicate the
current state of user-modified options. Used to capture C++
options information for distributed (sow/reap) input files.
.. caution:: Some features are not yet implemented. Buy a developer a coffee.
- Need some option to get either all or changed
- Need some option to either get dict or set string or psimod command list
- command return doesn't revoke has_changed setting for unchanged with changedOnly=False | Function to return a string of commands to replicate the
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"""Function to return a string of commands to replicate the
current state of user-modified options. Used to capture C++
options information for distributed (sow/reap) input files.
.. caution:: Some features are not yet implemented. Buy a developer a coffee.
- Need some option to get either all or changed
- Need some option to either get dict or set string or psimod command list
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"""
options = collections.defaultdict(dict)
commands = ''
for opt in core.get_global_option_list():
if core.has_global_option_changed(opt) or not changedOnly:
if opt in ['DFT_CUSTOM_FUNCTIONAL', 'EXTERN']: # Feb 2017 hack
continue
val = core.get_global_option(opt)
options['GLOBALS'][opt] = {'value': val, 'has_changed': core.has_global_option_changed(opt)}
if isinstance(val, str):
commands += """core.set_global_option('%s', '%s')\n""" % (opt, val)
else:
commands += """core.set_global_option('%s', %s)\n""" % (opt, val)
#if changedOnly:
# print('Appending module %s option %s value %s has_changed %s.' % \
# ('GLOBALS', opt, core.get_global_option(opt), core.has_global_option_changed(opt)))
for module in _modules:
if core.option_exists_in_module(module, opt):
hoc = core.has_option_changed(module, opt)
if hoc or not changedOnly:
val = core.get_option(module, opt)
options[module][opt] = {'value': val, 'has_changed': hoc}
if isinstance(val, str):
commands += """core.set_local_option('%s', '%s', '%s')\n""" % (module, opt, val)
else:
commands += """core.set_local_option('%s', '%s', %s)\n""" % (module, opt, val)
#if changedOnly:
# print('Appending module %s option %s value %s has_changed %s.' % \
# (module, opt, core.get_option(module, opt), hoc))
if commandsInsteadDict:
return commands
else:
return options | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/build/waf-1.7.13/waflib/extras/misc.py | python | copy_func | (tsk) | Make a file copy. This might be used to make other kinds of file processing (even calling a compiler is possible) | Make a file copy. This might be used to make other kinds of file processing (even calling a compiler is possible) | [
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"Make a file copy. This might be used to make other kinds of file processing (even calling a compiler is possible)"
env = tsk.env
infile = tsk.inputs[0].abspath()
outfile = tsk.outputs[0].abspath()
try:
shutil.copy2(infile, outfile)
except (OSError, IOError):
return 1
else:
if tsk.chmod: os.chmod(outfile, tsk.chmod)
return 0 | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_controls.py | python | CollapsiblePaneEvent.__init__ | (self, *args, **kwargs) | __init__(self, Object generator, int id, bool collapsed) -> CollapsiblePaneEvent | __init__(self, Object generator, int id, bool collapsed) -> CollapsiblePaneEvent | [
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"""__init__(self, Object generator, int id, bool collapsed) -> CollapsiblePaneEvent"""
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/richtext.py | python | RichTextFileHandler.CanSave | (*args, **kwargs) | return _richtext.RichTextFileHandler_CanSave(*args, **kwargs) | CanSave(self) -> bool | CanSave(self) -> bool | [
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return _richtext.RichTextFileHandler_CanSave(*args, **kwargs) | [
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|
pirobot/rbx2 | 2a6544799fcf062e7b6bd5cf2981b2a84c0c7d2a | rbx2_utils/src/rbx2_utils/srv/_LaunchProcess.py | python | LaunchProcessRequest.deserialize_numpy | (self, str, numpy) | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | [
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"""
unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module
"""
try:
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(length,) = _struct_I.unpack(str[start:end])
start = end
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self.command = str[start:end].decode('utf-8')
else:
self.command = str[start:end]
return self
except struct.error as e:
raise genpy.DeserializationError(e) | [
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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/generator/ninja.py | python | AddArch | (output, arch) | return '%s.%s%s' % (output, arch, extension) | Adds an arch string to an output path. | Adds an arch string to an output path. | [
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] | def AddArch(output, arch):
"""Adds an arch string to an output path."""
output, extension = os.path.splitext(output)
return '%s.%s%s' % (output, arch, extension) | [
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|
microsoft/CNTK | e9396480025b9ca457d26b6f33dd07c474c6aa04 | bindings/python/cntk/contrib/crosstalk/__init__.py | python | Crosstalk.reset | (self) | Reset all variables and passes, setter/getter functions for variable types are kept | Reset all variables and passes, setter/getter functions for variable types are kept | [
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'''
Reset all variables and passes, setter/getter functions for variable types are kept
'''
self.vars = {}
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||
jiangxiluning/FOTS.PyTorch | b1851c170b4f1ad18406766352cb5171648ce603 | FOTS/utils/detect.py | python | adjust_ratio | (boxes, ratio_w, ratio_h) | return np.around(boxes) | refine boxes
Input:
boxes : detected polys <numpy.ndarray, (n,9)>
ratio_w: ratio of width
ratio_h: ratio of height
Output:
refined boxes | refine boxes
Input:
boxes : detected polys <numpy.ndarray, (n,9)>
ratio_w: ratio of width
ratio_h: ratio of height
Output:
refined boxes | [
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'''refine boxes
Input:
boxes : detected polys <numpy.ndarray, (n,9)>
ratio_w: ratio of width
ratio_h: ratio of height
Output:
refined boxes
'''
if boxes is None or boxes.size == 0:
return None
boxes[:,[0,2,4,6]] /= ratio_w
boxes[:,[1,3,5,7]] /= ratio_h
return np.around(boxes) | [
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|
google/syzygy | 8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5 | third_party/numpy/files/numpy/ma/core.py | python | MaskedArray.__float__ | (self) | return float(self.item()) | Convert to float. | Convert to float. | [
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"Convert to float."
if self.size > 1:
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elif self._mask:
warnings.warn("Warning: converting a masked element to nan.")
return np.nan
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/parfor.py | python | push_call_vars | (blocks, saved_globals, saved_getattrs, nested=False) | return | push call variables to right before their call site.
assuming one global/getattr is created for each call site and control flow
doesn't change it. | push call variables to right before their call site.
assuming one global/getattr is created for each call site and control flow
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"""
for block in blocks.values():
new_body = []
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saved_getattrs[lhs.name] = stmt
block_defs.add(lhs.name)
if not nested and isinstance(stmt, Parfor):
for s in stmt.init_block.body:
process_assign(s)
pblocks = stmt.loop_body.copy()
push_call_vars(pblocks, saved_globals, saved_getattrs, nested=True)
new_body.append(stmt)
continue
else:
process_assign(stmt)
for v in stmt.list_vars():
new_body += _get_saved_call_nodes(v.name, saved_globals,
saved_getattrs, block_defs)
new_body.append(stmt)
block.body = new_body
return | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/core/defchararray.py | python | join | (sep, seq) | return _to_string_or_unicode_array(
_vec_string(sep, object_, 'join', (seq,))) | Return a string which is the concatenation of the strings in the
sequence `seq`.
Calls `str.join` element-wise.
Parameters
----------
sep : array_like of str or unicode
seq : array_like of str or unicode
Returns
-------
out : ndarray
Output array of str or unicode, depending on input types
See Also
--------
str.join | Return a string which is the concatenation of the strings in the
sequence `seq`. | [
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"."
] | def join(sep, seq):
"""
Return a string which is the concatenation of the strings in the
sequence `seq`.
Calls `str.join` element-wise.
Parameters
----------
sep : array_like of str or unicode
seq : array_like of str or unicode
Returns
-------
out : ndarray
Output array of str or unicode, depending on input types
See Also
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str.join
"""
return _to_string_or_unicode_array(
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|
intel/caffe | 3f494b442ee3f9d17a07b09ecbd5fa2bbda00836 | examples/faster-rcnn/lib/fast_rcnn/config.py | python | _merge_a_into_b | (a, b) | Merge config dictionary a into config dictionary b, clobbering the
options in b whenever they are also specified in a. | Merge config dictionary a into config dictionary b, clobbering the
options in b whenever they are also specified in a. | [
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] | def _merge_a_into_b(a, b):
"""Merge config dictionary a into config dictionary b, clobbering the
options in b whenever they are also specified in a.
"""
if type(a) is not edict:
return
for k, v in a.iteritems():
# a must specify keys that are in b
if not b.has_key(k):
raise KeyError('{} is not a valid config key'.format(k))
# the types must match, too
old_type = type(b[k])
if old_type is not type(v):
if isinstance(b[k], np.ndarray):
v = np.array(v, dtype=b[k].dtype)
else:
raise ValueError(('Type mismatch ({} vs. {}) '
'for config key: {}').format(type(b[k]),
type(v), k))
# recursively merge dicts
if type(v) is edict:
try:
_merge_a_into_b(a[k], b[k])
except:
print('Error under config key: {}'.format(k))
raise
else:
b[k] = v | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_windows.py | python | VarHScrollHelper.RefreshColumns | (*args, **kwargs) | return _windows_.VarHScrollHelper_RefreshColumns(*args, **kwargs) | RefreshColumns(self, size_t from, size_t to) | RefreshColumns(self, size_t from, size_t to) | [
"RefreshColumns",
"(",
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] | def RefreshColumns(*args, **kwargs):
"""RefreshColumns(self, size_t from, size_t to)"""
return _windows_.VarHScrollHelper_RefreshColumns(*args, **kwargs) | [
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|
natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/ops/nn_ops.py | python | xw_plus_b_v1 | (x, weights, biases, name=None) | Computes matmul(x, weights) + biases.
This is a deprecated version of that will soon be removed.
Args:
x: a 2D tensor. Dimensions typically: batch, in_units
weights: a 2D tensor. Dimensions typically: in_units, out_units
biases: a 1D tensor. Dimensions: out_units
name: A name for the operation (optional). If not specified
"xw_plus_b_v1" is used.
Returns:
A 2-D Tensor computing matmul(x, weights) + biases.
Dimensions typically: batch, out_units. | Computes matmul(x, weights) + biases. | [
"Computes",
"matmul",
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] | def xw_plus_b_v1(x, weights, biases, name=None): # pylint: disable=invalid-name
"""Computes matmul(x, weights) + biases.
This is a deprecated version of that will soon be removed.
Args:
x: a 2D tensor. Dimensions typically: batch, in_units
weights: a 2D tensor. Dimensions typically: in_units, out_units
biases: a 1D tensor. Dimensions: out_units
name: A name for the operation (optional). If not specified
"xw_plus_b_v1" is used.
Returns:
A 2-D Tensor computing matmul(x, weights) + biases.
Dimensions typically: batch, out_units.
"""
with ops.op_scope([x, weights, biases], name, "xw_plus_b_v1") as name:
x = ops.convert_to_tensor(x, name="x")
weights = ops.convert_to_tensor(weights, name="weights")
biases = ops.convert_to_tensor(biases, name="biases")
mm = math_ops.matmul(x, weights)
return bias_add_v1(mm, biases, name=name) | [
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||
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/image_ops_impl.py | python | _Assert3DImage | (image) | return control_flow_ops.with_dependencies(
_Check3DImage(image, require_static=False), image) | Assert that we are working with a properly shaped image.
Performs the check statically if possible (i.e. if the shape
is statically known). Otherwise adds a control dependency
to an assert op that checks the dynamic shape.
Args:
image: 3-D Tensor of shape [height, width, channels]
Raises:
ValueError: if `image.shape` is not a 3-vector.
Returns:
If the shape of `image` could be verified statically, `image` is
returned unchanged, otherwise there will be a control dependency
added that asserts the correct dynamic shape. | Assert that we are working with a properly shaped image. | [
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"that",
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] | def _Assert3DImage(image):
"""Assert that we are working with a properly shaped image.
Performs the check statically if possible (i.e. if the shape
is statically known). Otherwise adds a control dependency
to an assert op that checks the dynamic shape.
Args:
image: 3-D Tensor of shape [height, width, channels]
Raises:
ValueError: if `image.shape` is not a 3-vector.
Returns:
If the shape of `image` could be verified statically, `image` is
returned unchanged, otherwise there will be a control dependency
added that asserts the correct dynamic shape.
"""
return control_flow_ops.with_dependencies(
_Check3DImage(image, require_static=False), image) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/py/py/_path/svnurl.py | python | SvnCommandPath.mkdir | (self, *args, **kwargs) | return createpath | create & return the directory joined with args.
pass a 'msg' keyword argument to set the commit message. | create & return the directory joined with args.
pass a 'msg' keyword argument to set the commit message. | [
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] | def mkdir(self, *args, **kwargs):
""" create & return the directory joined with args.
pass a 'msg' keyword argument to set the commit message.
"""
commit_msg = kwargs.get('msg', "mkdir by py lib invocation")
createpath = self.join(*args)
createpath._svnwrite('mkdir', '-m', commit_msg)
self._norev_delentry(createpath.dirpath())
return createpath | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/ed_main.py | python | MainWindow.GetShelf | (self) | return self._shelf | Get this windows Shelf
@return: reference to L{iface.Shelf} instance
@note: returns the plugin instance not the actual notebook, if
a reference to the notebook is needed for parenting call
GetWindow on the object returned by this function. | Get this windows Shelf
@return: reference to L{iface.Shelf} instance
@note: returns the plugin instance not the actual notebook, if
a reference to the notebook is needed for parenting call
GetWindow on the object returned by this function. | [
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] | def GetShelf(self):
"""Get this windows Shelf
@return: reference to L{iface.Shelf} instance
@note: returns the plugin instance not the actual notebook, if
a reference to the notebook is needed for parenting call
GetWindow on the object returned by this function.
"""
return self._shelf | [
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