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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/robotsim.py | python | ContactQueryResult.__init__ | (self) | __init__(ContactQueryResult self) -> ContactQueryResult
The result from a contact query of :class:`~klampt.Geometry3D`. The number of
contacts n is variable.
Attributes:
depths (list of n floats): penetration depths for each contact point.
The depth is measured with respect to the padded geometry, and must
be nonnegative. A value of 0 indicates that depth cannot be
determined accurately.
points1, points2 (list of n lists of floats): contact points on self vs
other, The top level list has n entries, and each entry is a
3-list expressed in world coordinates. If an object is padded,
these points are on the surface of the padded geometry.
normals (list of n lists of floats): the outward-facing contact normal
from this to other at each contact point, given in world
coordinates. Each entry is a 3-list, and can be a unit vector,
or [0,0,0] if the the normal cannot be computed properly.
elems1, elems2 (list of n ints): for compound objects, these are the
element indices corresponding to each contact.
C++ includes: geometry.h | __init__(ContactQueryResult self) -> ContactQueryResult | [
"__init__",
"(",
"ContactQueryResult",
"self",
")",
"-",
">",
"ContactQueryResult"
] | def __init__(self):
"""
__init__(ContactQueryResult self) -> ContactQueryResult
The result from a contact query of :class:`~klampt.Geometry3D`. The number of
contacts n is variable.
Attributes:
depths (list of n floats): penetration depths for each contact point.
The depth is measured with respect to the padded geometry, and must
be nonnegative. A value of 0 indicates that depth cannot be
determined accurately.
points1, points2 (list of n lists of floats): contact points on self vs
other, The top level list has n entries, and each entry is a
3-list expressed in world coordinates. If an object is padded,
these points are on the surface of the padded geometry.
normals (list of n lists of floats): the outward-facing contact normal
from this to other at each contact point, given in world
coordinates. Each entry is a 3-list, and can be a unit vector,
or [0,0,0] if the the normal cannot be computed properly.
elems1, elems2 (list of n ints): for compound objects, these are the
element indices corresponding to each contact.
C++ includes: geometry.h
"""
this = _robotsim.new_ContactQueryResult()
try:
self.this.append(this)
except Exception:
self.this = this | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextBuffer.GetStyleStackSize | (*args, **kwargs) | return _richtext.RichTextBuffer_GetStyleStackSize(*args, **kwargs) | GetStyleStackSize(self) -> size_t | GetStyleStackSize(self) -> size_t | [
"GetStyleStackSize",
"(",
"self",
")",
"-",
">",
"size_t"
] | def GetStyleStackSize(*args, **kwargs):
"""GetStyleStackSize(self) -> size_t"""
return _richtext.RichTextBuffer_GetStyleStackSize(*args, **kwargs) | [
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|
naver/sling | 5671cd445a2caae0b4dd0332299e4cfede05062c | webkit/Tools/Scripts/webkitpy/common/system/filesystem.py | python | FileSystem.files_under | (self, path, dirs_to_skip=[], file_filter=None) | return files | Return the list of all files under the given path in topdown order.
Args:
dirs_to_skip: a list of directories to skip over during the
traversal (e.g., .svn, resources, etc.)
file_filter: if not None, the filter will be invoked
with the filesystem object and the dirname and basename of
each file found. The file is included in the result if the
callback returns True. | Return the list of all files under the given path in topdown order. | [
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"list",
"of",
"all",
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"under",
"the",
"given",
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"."
] | def files_under(self, path, dirs_to_skip=[], file_filter=None):
"""Return the list of all files under the given path in topdown order.
Args:
dirs_to_skip: a list of directories to skip over during the
traversal (e.g., .svn, resources, etc.)
file_filter: if not None, the filter will be invoked
with the filesystem object and the dirname and basename of
each file found. The file is included in the result if the
callback returns True.
"""
def filter_all(fs, dirpath, basename):
return True
file_filter = file_filter or filter_all
files = []
if self.isfile(path):
if file_filter(self, self.dirname(path), self.basename(path)):
files.append(path)
return files
if self.basename(path) in dirs_to_skip:
return []
for (dirpath, dirnames, filenames) in os.walk(path):
for d in dirs_to_skip:
if d in dirnames:
dirnames.remove(d)
for filename in filenames:
if file_filter(self, dirpath, filename):
files.append(self.join(dirpath, filename))
return files | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | catboost/python-package/catboost/metrics.py | python | BuiltinMetric.eval | (self,
label,
approx,
weight=None,
group_id=None,
group_weight=None,
subgroup_id=None,
pairs=None,
thread_count=-1) | return _catboost._eval_metric_util(
label, approx, str(self), weight, group_id, group_weight, subgroup_id, pairs, thread_count
) | Evaluate the metric with raw approxes and labels.
Parameters
----------
label : list or numpy.ndarrays or pandas.DataFrame or pandas.Series
Object labels.
approx : list or numpy.ndarrays or pandas.DataFrame or pandas.Series
Object approxes.
weight : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Object weights.
group_id : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Object group ids.
group_weight : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Group weights.
subgroup_id : list or numpy.ndarray, optional (default=None)
subgroup id for each instance.
If not None, giving 1 dimensional array like data.
pairs : list or numpy.ndarray or pandas.DataFrame or string or pathlib.Path
The pairs description.
If list or numpy.ndarrays or pandas.DataFrame, giving 2 dimensional.
The shape should be Nx2, where N is the pairs' count. The first element of the pair is
the index of winner object in the training set. The second element of the pair is
the index of loser object in the training set.
If string or pathlib.Path, giving the path to the file with pairs description.
thread_count : int, optional (default=-1)
Number of threads to work with.
If -1, then the number of threads is set to the number of CPU cores.
Returns
-------
metric results : list with metric values. | Evaluate the metric with raw approxes and labels. | [
"Evaluate",
"the",
"metric",
"with",
"raw",
"approxes",
"and",
"labels",
"."
] | def eval(self,
label,
approx,
weight=None,
group_id=None,
group_weight=None,
subgroup_id=None,
pairs=None,
thread_count=-1):
"""
Evaluate the metric with raw approxes and labels.
Parameters
----------
label : list or numpy.ndarrays or pandas.DataFrame or pandas.Series
Object labels.
approx : list or numpy.ndarrays or pandas.DataFrame or pandas.Series
Object approxes.
weight : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Object weights.
group_id : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Object group ids.
group_weight : list or numpy.ndarray or pandas.DataFrame or pandas.Series, optional (default=None)
Group weights.
subgroup_id : list or numpy.ndarray, optional (default=None)
subgroup id for each instance.
If not None, giving 1 dimensional array like data.
pairs : list or numpy.ndarray or pandas.DataFrame or string or pathlib.Path
The pairs description.
If list or numpy.ndarrays or pandas.DataFrame, giving 2 dimensional.
The shape should be Nx2, where N is the pairs' count. The first element of the pair is
the index of winner object in the training set. The second element of the pair is
the index of loser object in the training set.
If string or pathlib.Path, giving the path to the file with pairs description.
thread_count : int, optional (default=-1)
Number of threads to work with.
If -1, then the number of threads is set to the number of CPU cores.
Returns
-------
metric results : list with metric values.
"""
if len(label) > 0 and not isinstance(label[0], _ARRAY_TYPES):
label = [label]
if len(approx) == 0:
approx = [[]]
if not isinstance(approx[0], _ARRAY_TYPES):
approx = [approx]
return _catboost._eval_metric_util(
label, approx, str(self), weight, group_id, group_weight, subgroup_id, pairs, thread_count
) | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/io/stata.py | python | StataStrLWriter.generate_blob | (self, gso_table) | return bio.read() | Generates the binary blob of GSOs that is written to the dta file.
Parameters
----------
gso_table : dict
Ordered dictionary (str, vo)
Returns
-------
gso : bytes
Binary content of dta file to be placed between strl tags
Notes
-----
Output format depends on dta version. 117 uses two uint32s to
express v and o while 118+ uses a uint32 for v and a uint64 for o. | Generates the binary blob of GSOs that is written to the dta file. | [
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"binary",
"blob",
"of",
"GSOs",
"that",
"is",
"written",
"to",
"the",
"dta",
"file",
"."
] | def generate_blob(self, gso_table):
"""
Generates the binary blob of GSOs that is written to the dta file.
Parameters
----------
gso_table : dict
Ordered dictionary (str, vo)
Returns
-------
gso : bytes
Binary content of dta file to be placed between strl tags
Notes
-----
Output format depends on dta version. 117 uses two uint32s to
express v and o while 118+ uses a uint32 for v and a uint64 for o.
"""
# Format information
# Length includes null term
# 117
# GSOvvvvooootllllxxxxxxxxxxxxxxx...x
# 3 u4 u4 u1 u4 string + null term
#
# 118, 119
# GSOvvvvooooooootllllxxxxxxxxxxxxxxx...x
# 3 u4 u8 u1 u4 string + null term
bio = BytesIO()
gso = bytes("GSO", "ascii")
gso_type = struct.pack(self._byteorder + "B", 130)
null = struct.pack(self._byteorder + "B", 0)
v_type = self._byteorder + self._gso_v_type
o_type = self._byteorder + self._gso_o_type
len_type = self._byteorder + "I"
for strl, vo in gso_table.items():
if vo == (0, 0):
continue
v, o = vo
# GSO
bio.write(gso)
# vvvv
bio.write(struct.pack(v_type, v))
# oooo / oooooooo
bio.write(struct.pack(o_type, o))
# t
bio.write(gso_type)
# llll
utf8_string = bytes(strl, "utf-8")
bio.write(struct.pack(len_type, len(utf8_string) + 1))
# xxx...xxx
bio.write(utf8_string)
bio.write(null)
bio.seek(0)
return bio.read() | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/aquabutton.py | python | AquaButton.DoGetBestSize | (self) | return wx.Size(retWidth+constant, retHeight+constant) | Overridden base class virtual. Determines the best size of the
button based on the label and bezel size.
:return: An instance of :class:`Size`.
:note: Overridden from :class:`PyControl`. | Overridden base class virtual. Determines the best size of the
button based on the label and bezel size. | [
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] | def DoGetBestSize(self):
"""
Overridden base class virtual. Determines the best size of the
button based on the label and bezel size.
:return: An instance of :class:`Size`.
:note: Overridden from :class:`PyControl`.
"""
label = self.GetLabel()
if not label:
return wx.Size(112, 48)
dc = wx.ClientDC(self)
dc.SetFont(self.GetFont())
retWidth, retHeight = dc.GetTextExtent(label)
bmpWidth = bmpHeight = 0
constant = 24
if self._bitmap:
bmpWidth, bmpHeight = self._bitmap.GetWidth()+10, self._bitmap.GetHeight()
retWidth += bmpWidth
retHeight = max(bmpHeight, retHeight)
constant = 24
return wx.Size(retWidth+constant, retHeight+constant) | [
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|
SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/convert/tool/subtool/acquire_sourcedir.py | python | set_custom_wineprefix | () | Allow the customization of the WINEPREFIX environment variable. | Allow the customization of the WINEPREFIX environment variable. | [
"Allow",
"the",
"customization",
"of",
"the",
"WINEPREFIX",
"environment",
"variable",
"."
] | def set_custom_wineprefix():
"""
Allow the customization of the WINEPREFIX environment variable.
"""
print("The WINEPREFIX is a separate 'container' for windows "
"software installations.")
current_wineprefix = os.environ.get("WINEPREFIX")
if current_wineprefix:
print(f"Currently: WINEPREFIX='{current_wineprefix}'")
print("Enter a custom value or leave empty to keep it as-is:")
while True:
new_wineprefix = input("WINEPREFIX=")
if not new_wineprefix:
break
new_wineprefix = expand_relative_path(new_wineprefix)
# test if it probably is a wineprefix
if (Path(new_wineprefix) / "drive_c").is_dir(): # pylint: disable=no-member
break
print("This does not appear to be a valid WINEPREFIX.")
print("Enter a valid one, or leave it empty to skip.")
# store the updated env variable for the wine subprocess
if new_wineprefix:
os.environ["WINEPREFIX"] = new_wineprefix | [
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||
mavlink/mavros | a32232d57a5e91abf6737e454d4199cae29b369c | mavros/mavros/cmd/system.py | python | rate | (
ctx,
client,
all,
raw_sensors,
ext_status,
rc_channels,
raw_controller,
position,
extra1,
extra2,
extra3,
stream_id,
) | Set stream rate. | Set stream rate. | [
"Set",
"stream",
"rate",
"."
] | def rate(
ctx,
client,
all,
raw_sensors,
ext_status,
rc_channels,
raw_controller,
position,
extra1,
extra2,
extra3,
stream_id,
):
"""Set stream rate."""
_ = 1 # yapf
def set_rate(rate_arg: typing.Optional[int], id_: int):
if rate_arg is None:
return
req = StreamRate.Request(
stream_id=id_,
message_rate=rate_arg,
on_off=(rate_arg != 0),
)
client.system.cli_set_stream_rate.call(req)
set_rate(all, StreamRate.Request.STREAM_ALL)
set_rate(raw_sensors, StreamRate.Request.STREAM_RAW_SENSORS)
set_rate(ext_status, StreamRate.Request.STREAM_EXTENDED_STATUS)
set_rate(rc_channels, StreamRate.Request.STREAM_RC_CHANNELS)
set_rate(raw_controller, StreamRate.Request.STREAM_RAW_CONTROLLER)
set_rate(position, StreamRate.Request.STREAM_POSITION)
set_rate(extra1, StreamRate.Request.STREAM_EXTRA1)
set_rate(extra2, StreamRate.Request.STREAM_EXTRA2)
set_rate(extra3, StreamRate.Request.STREAM_EXTRA3)
if stream_id:
set_rate(stream_id[1], stream_id[0]) | [
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||
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/winpython/wppm.py | python | Distribution.find_package | (self, name) | Find installed package | Find installed package | [
"Find",
"installed",
"package"
] | def find_package(self, name):
"""Find installed package"""
for pack in self.get_installed_packages():
if pack.name == name:
return pack | [
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||
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/Paste/paste/auth/form.py | python | make_form | (app, global_conf, realm, authfunc, **kw) | return AuthFormHandler(app, authfunc, template) | Grant access via form authentication
Config looks like this::
[filter:grant]
use = egg:Paste#auth_form
realm=myrealm
authfunc=somepackage.somemodule:somefunction | Grant access via form authentication | [
"Grant",
"access",
"via",
"form",
"authentication"
] | def make_form(app, global_conf, realm, authfunc, **kw):
"""
Grant access via form authentication
Config looks like this::
[filter:grant]
use = egg:Paste#auth_form
realm=myrealm
authfunc=somepackage.somemodule:somefunction
"""
from paste.util.import_string import eval_import
import types
authfunc = eval_import(authfunc)
assert isinstance(authfunc, types.FunctionType), "authfunc must resolve to a function"
template = kw.get('template')
if template is not None:
template = eval_import(template)
assert isinstance(template, str), "template must resolve to a string"
return AuthFormHandler(app, authfunc, template) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/telemetry/telemetry/core/android_action_runner.py | python | AndroidActionRunner.InputTap | (self, x_coord, y_coord) | Perform a tap input at the given coordinates.
Args:
x_coord: The x coordinate of the tap event.
y_coord: The y coordinate of the tap event. | Perform a tap input at the given coordinates. | [
"Perform",
"a",
"tap",
"input",
"at",
"the",
"given",
"coordinates",
"."
] | def InputTap(self, x_coord, y_coord):
"""Perform a tap input at the given coordinates.
Args:
x_coord: The x coordinate of the tap event.
y_coord: The y coordinate of the tap event.
"""
self._platform_backend.device.RunShellCommand('input tap %s %s' % (x_coord,
y_coord)) | [
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||
pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/nn/modules/container.py | python | ModuleDict.keys | (self) | return self._modules.keys() | r"""Return an iterable of the ModuleDict keys. | r"""Return an iterable of the ModuleDict keys. | [
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] | def keys(self) -> Iterable[str]:
r"""Return an iterable of the ModuleDict keys.
"""
return self._modules.keys() | [
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|
apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | scripts/Python/static-binding/lldb.py | python | SBTypeSynthetic.GetData | (self) | return _lldb.SBTypeSynthetic_GetData(self) | GetData(SBTypeSynthetic self) -> char const * | GetData(SBTypeSynthetic self) -> char const * | [
"GetData",
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] | def GetData(self):
"""GetData(SBTypeSynthetic self) -> char const *"""
return _lldb.SBTypeSynthetic_GetData(self) | [
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|
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/labeled_tensor/python/ops/core.py | python | LabeledTensor._as_graph_element | (self) | return self.tensor | Support tf.Graph.as_graph_element on LabeledTensor objects.
This allows operations such as tf.name_scope to take labeled tensors.
Returns:
self.tensor | Support tf.Graph.as_graph_element on LabeledTensor objects. | [
"Support",
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"Graph",
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"as_graph_element",
"on",
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"objects",
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] | def _as_graph_element(self):
"""Support tf.Graph.as_graph_element on LabeledTensor objects.
This allows operations such as tf.name_scope to take labeled tensors.
Returns:
self.tensor
"""
return self.tensor | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py2/IPython/utils/_process_win32_controller.py | python | Win32ShellCommandController.__init__ | (self, cmd, mergeout = True) | Initializes the shell command controller.
The cmd is the program to execute, and mergeout is
whether to blend stdout and stderr into one output
in stdout. Merging them together in this fashion more
reliably keeps stdout and stderr in the correct order
especially for interactive shell usage. | Initializes the shell command controller. | [
"Initializes",
"the",
"shell",
"command",
"controller",
"."
] | def __init__(self, cmd, mergeout = True):
"""Initializes the shell command controller.
The cmd is the program to execute, and mergeout is
whether to blend stdout and stderr into one output
in stdout. Merging them together in this fashion more
reliably keeps stdout and stderr in the correct order
especially for interactive shell usage.
"""
self.cmd = cmd
self.mergeout = mergeout | [
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||
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | uCSIsPrivateUseArea | (code) | return ret | Check whether the character is part of PrivateUseArea UCS
Block | Check whether the character is part of PrivateUseArea UCS
Block | [
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"character",
"is",
"part",
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"PrivateUseArea",
"UCS",
"Block"
] | def uCSIsPrivateUseArea(code):
"""Check whether the character is part of PrivateUseArea UCS
Block """
ret = libxml2mod.xmlUCSIsPrivateUseArea(code)
return ret | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_misc.py | python | DataObject.IsSupported | (*args, **kwargs) | return _misc_.DataObject_IsSupported(*args, **kwargs) | IsSupported(self, DataFormat format, int dir=Get) -> bool
Returns True if this format is supported. | IsSupported(self, DataFormat format, int dir=Get) -> bool | [
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"""
IsSupported(self, DataFormat format, int dir=Get) -> bool
Returns True if this format is supported.
"""
return _misc_.DataObject_IsSupported(*args, **kwargs) | [
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|
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model.py | python | StateSpaceModel.get_prior_covariance | (self) | Constructs a variable prior covariance with data-based initialization.
Models should wrap any variables defined here in the model's variable scope.
Returns:
A two-dimensional [state dimension, state dimension] floating point Tensor
with a (positive definite) prior state covariance matrix. | Constructs a variable prior covariance with data-based initialization. | [
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"variable",
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"covariance",
"with",
"data",
"-",
"based",
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"."
] | def get_prior_covariance(self):
"""Constructs a variable prior covariance with data-based initialization.
Models should wrap any variables defined here in the model's variable scope.
Returns:
A two-dimensional [state dimension, state dimension] floating point Tensor
with a (positive definite) prior state covariance matrix.
"""
with variable_scope.variable_scope(self._variable_scope):
state_dimension = ops.convert_to_tensor(
self.get_state_transition()).get_shape()[0].value
if self._configuration.trainable_start_state:
base_covariance = math_utils.variable_covariance_matrix(
state_dimension, "prior_state_var",
dtype=self.dtype)
else:
return linalg_ops.eye(state_dimension, dtype=self.dtype)
if self._input_statistics is not None:
# Make sure initial latent value uncertainty is at least on the same
# scale as noise in the data.
covariance_multiplier = math_ops.reduce_max(
self._scale_variance(
self._input_statistics.series_start_moments.variance))
return base_covariance * gen_math_ops.maximum(
covariance_multiplier, 1.0)
else:
return base_covariance | [
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||
livecode/livecode | 4606a10ea10b16d5071d0f9f263ccdd7ede8b31d | gyp/pylib/gyp/MSVSProject.py | python | Tool._GetSpecification | (self) | return ['Tool', self._attrs] | Creates an element for the tool.
Returns:
A new xml.dom.Element for the tool. | Creates an element for the tool. | [
"Creates",
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"element",
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"the",
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"."
] | def _GetSpecification(self):
"""Creates an element for the tool.
Returns:
A new xml.dom.Element for the tool.
"""
return ['Tool', self._attrs] | [
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] | https://github.com/livecode/livecode/blob/4606a10ea10b16d5071d0f9f263ccdd7ede8b31d/gyp/pylib/gyp/MSVSProject.py#L26-L32 |
|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Pygments/py3/pygments/util.py | python | duplicates_removed | (it, already_seen=()) | return lst | Returns a list with duplicates removed from the iterable `it`.
Order is preserved. | Returns a list with duplicates removed from the iterable `it`. | [
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] | def duplicates_removed(it, already_seen=()):
"""
Returns a list with duplicates removed from the iterable `it`.
Order is preserved.
"""
lst = []
seen = set()
for i in it:
if i in seen or i in already_seen:
continue
lst.append(i)
seen.add(i)
return lst | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/composite/base.py | python | _Grad.__init__ | (self, get_by_list=False, sens_param=False, get_by_position=False) | Initialize _Grad. | Initialize _Grad. | [
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] | def __init__(self, get_by_list=False, sens_param=False, get_by_position=False):
"""Initialize _Grad."""
if not isinstance(get_by_position, bool):
raise TypeError(f"For '_Grad', the 'get_by_position' should be bool, "
f"but got {type(get_by_position).__name__}")
if not isinstance(get_by_list, bool):
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if not isinstance(sens_param, bool):
raise TypeError(f"For '_Grad', the 'sens_param' should be bool, "
f"but got {type(sens_param).__name__}")
self.get_by_position = get_by_position
self.get_by_list = get_by_list
self.sens_param = sens_param
GradOperation_.__init__(self, 'grad', False, get_by_list, sens_param, get_by_position)
self.grad_fn = None
self.fn = None
self.pynative_ = False
self.grad_position = None | [
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||
BertaBescos/DynaSLAM | 8f894a8b9d63c0a608fd871d63c10796491b9312 | src/python/model.py | python | identity_block | (input_tensor, kernel_size, filters, stage, block,
use_bias=True) | return x | The identity_block is the block that has no conv layer at shortcut
# Arguments
input_tensor: input tensor
kernel_size: defualt 3, the kernel size of middle conv layer at main path
filters: list of integers, the nb_filters of 3 conv layer at main path
stage: integer, current stage label, used for generating layer names
block: 'a','b'..., current block label, used for generating layer names | The identity_block is the block that has no conv layer at shortcut
# Arguments
input_tensor: input tensor
kernel_size: defualt 3, the kernel size of middle conv layer at main path
filters: list of integers, the nb_filters of 3 conv layer at main path
stage: integer, current stage label, used for generating layer names
block: 'a','b'..., current block label, used for generating layer names | [
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use_bias=True):
"""The identity_block is the block that has no conv layer at shortcut
# Arguments
input_tensor: input tensor
kernel_size: defualt 3, the kernel size of middle conv layer at main path
filters: list of integers, the nb_filters of 3 conv layer at main path
stage: integer, current stage label, used for generating layer names
block: 'a','b'..., current block label, used for generating layer names
"""
nb_filter1, nb_filter2, nb_filter3 = filters
conv_name_base = 'res' + str(stage) + block + '_branch'
bn_name_base = 'bn' + str(stage) + block + '_branch'
x = KL.Conv2D(nb_filter1, (1, 1), name=conv_name_base + '2a',
use_bias=use_bias)(input_tensor)
x = BatchNorm(axis=3, name=bn_name_base + '2a')(x)
x = KL.Activation('relu')(x)
x = KL.Conv2D(nb_filter2, (kernel_size, kernel_size), padding='same',
name=conv_name_base + '2b', use_bias=use_bias)(x)
x = BatchNorm(axis=3, name=bn_name_base + '2b')(x)
x = KL.Activation('relu')(x)
x = KL.Conv2D(nb_filter3, (1, 1), name=conv_name_base + '2c',
use_bias=use_bias)(x)
x = BatchNorm(axis=3, name=bn_name_base + '2c')(x)
x = KL.Add()([x, input_tensor])
x = KL.Activation('relu', name='res'+str(stage)+block+'_out')(x)
return x | [
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|
albertz/openlierox | d316c14a8eb57848ef56e9bfa7b23a56f694a51b | tools/DedicatedServerVideo/gdata/docs/service.py | python | DocsService._UploadFile | (self, media_source, title, category, folder_or_uri=None) | return entry | Uploads a file to the Document List feed.
Args:
media_source: A gdata.MediaSource object containing the file to be
uploaded.
title: string The title of the document on the server after being
uploaded.
category: An atom.Category object specifying the appropriate document
type.
folder_or_uri: DocumentListEntry or string (optional) An object with a
link to a folder or a uri to a folder to upload to.
Note: A valid uri for a folder is of the form:
/feeds/folders/private/full/folder%3Afolder_id
Returns:
A DocumentListEntry containing information about the document created on
the Google Documents service. | Uploads a file to the Document List feed. | [
"Uploads",
"a",
"file",
"to",
"the",
"Document",
"List",
"feed",
"."
] | def _UploadFile(self, media_source, title, category, folder_or_uri=None):
"""Uploads a file to the Document List feed.
Args:
media_source: A gdata.MediaSource object containing the file to be
uploaded.
title: string The title of the document on the server after being
uploaded.
category: An atom.Category object specifying the appropriate document
type.
folder_or_uri: DocumentListEntry or string (optional) An object with a
link to a folder or a uri to a folder to upload to.
Note: A valid uri for a folder is of the form:
/feeds/folders/private/full/folder%3Afolder_id
Returns:
A DocumentListEntry containing information about the document created on
the Google Documents service.
"""
if folder_or_uri:
try:
uri = folder_or_uri.content.src
except AttributeError:
uri = folder_or_uri
else:
uri = '/feeds/documents/private/full'
entry = gdata.docs.DocumentListEntry()
entry.title = atom.Title(text=title)
if category is not None:
entry.category.append(category)
entry = self.Post(entry, uri, media_source=media_source,
extra_headers={'Slug': media_source.file_name},
converter=gdata.docs.DocumentListEntryFromString)
return entry | [
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|
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/mhlib.py | python | Folder.getsequences | (self) | return sequences | Return the set of sequences for the folder. | Return the set of sequences for the folder. | [
"Return",
"the",
"set",
"of",
"sequences",
"for",
"the",
"folder",
"."
] | def getsequences(self):
"""Return the set of sequences for the folder."""
sequences = {}
fullname = self.getsequencesfilename()
try:
f = open(fullname, 'r')
except IOError:
return sequences
while 1:
line = f.readline()
if not line: break
fields = line.split(':')
if len(fields) != 2:
self.error('bad sequence in %s: %s' %
(fullname, line.strip()))
key = fields[0].strip()
value = IntSet(fields[1].strip(), ' ').tolist()
sequences[key] = value
return sequences | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/Blast/3rdParty/assimp/port/PyAssimp/scripts/transformations.py | python | vector_norm | (data, axis=None, out=None) | Return length, i.e. eucledian norm, of ndarray along axis.
>>> v = numpy.random.random(3)
>>> n = vector_norm(v)
>>> numpy.allclose(n, numpy.linalg.norm(v))
True
>>> v = numpy.random.rand(6, 5, 3)
>>> n = vector_norm(v, axis=-1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=2)))
True
>>> n = vector_norm(v, axis=1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> v = numpy.random.rand(5, 4, 3)
>>> n = numpy.empty((5, 3), dtype=numpy.float64)
>>> vector_norm(v, axis=1, out=n)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> vector_norm([])
0.0
>>> vector_norm([1.0])
1.0 | Return length, i.e. eucledian norm, of ndarray along axis. | [
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".",
"e",
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] | def vector_norm(data, axis=None, out=None):
"""Return length, i.e. eucledian norm, of ndarray along axis.
>>> v = numpy.random.random(3)
>>> n = vector_norm(v)
>>> numpy.allclose(n, numpy.linalg.norm(v))
True
>>> v = numpy.random.rand(6, 5, 3)
>>> n = vector_norm(v, axis=-1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=2)))
True
>>> n = vector_norm(v, axis=1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> v = numpy.random.rand(5, 4, 3)
>>> n = numpy.empty((5, 3), dtype=numpy.float64)
>>> vector_norm(v, axis=1, out=n)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> vector_norm([])
0.0
>>> vector_norm([1.0])
1.0
"""
data = numpy.array(data, dtype=numpy.float64, copy=True)
if out is None:
if data.ndim == 1:
return math.sqrt(numpy.dot(data, data))
data *= data
out = numpy.atleast_1d(numpy.sum(data, axis=axis))
numpy.sqrt(out, out)
return out
else:
data *= data
numpy.sum(data, axis=axis, out=out)
numpy.sqrt(out, out) | [
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/Blast/3rdParty/assimp/port/PyAssimp/scripts/transformations.py#L1535-L1571 |
||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/idlelib/configHandler.py | python | IdleConf.CurrentTheme | (self) | return self.GetOption('main','Theme','name',default='') | Returns the name of the currently active theme | Returns the name of the currently active theme | [
"Returns",
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"name",
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] | def CurrentTheme(self):
"""
Returns the name of the currently active theme
"""
return self.GetOption('main','Theme','name',default='') | [
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|
BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/SimpleHTTPServer.py | python | SimpleHTTPRequestHandler.send_head | (self) | return f | Common code for GET and HEAD commands.
This sends the response code and MIME headers.
Return value is either a file object (which has to be copied
to the outputfile by the caller unless the command was HEAD,
and must be closed by the caller under all circumstances), or
None, in which case the caller has nothing further to do. | Common code for GET and HEAD commands. | [
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"HEAD",
"commands",
"."
] | def send_head(self):
"""Common code for GET and HEAD commands.
This sends the response code and MIME headers.
Return value is either a file object (which has to be copied
to the outputfile by the caller unless the command was HEAD,
and must be closed by the caller under all circumstances), or
None, in which case the caller has nothing further to do.
"""
path = self.translate_path(self.path)
f = None
if os.path.isdir(path):
if not self.path.endswith('/'):
# redirect browser - doing basically what apache does
self.send_response(301)
self.send_header("Location", self.path + "/")
self.end_headers()
return None
for index in "index.html", "index.htm":
index = os.path.join(path, index)
if os.path.exists(index):
path = index
break
else:
return self.list_directory(path)
ctype = self.guess_type(path)
try:
# Always read in binary mode. Opening files in text mode may cause
# newline translations, making the actual size of the content
# transmitted *less* than the content-length!
f = open(path, 'rb')
except IOError:
self.send_error(404, "File not found")
return None
self.send_response(200)
self.send_header("Content-type", ctype)
fs = os.fstat(f.fileno())
self.send_header("Content-Length", str(fs[6]))
self.send_header("Last-Modified", self.date_time_string(fs.st_mtime))
self.end_headers()
return f | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/operator.py | python | ilshift | (a, b) | return a | Same as a <<= b. | Same as a <<= b. | [
"Same",
"as",
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"<<",
"=",
"b",
"."
] | def ilshift(a, b):
"Same as a <<= b."
a <<= b
return a | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/configparser.py | python | RawConfigParser._convert_to_boolean | (self, value) | return self.BOOLEAN_STATES[value.lower()] | Return a boolean value translating from other types if necessary. | Return a boolean value translating from other types if necessary. | [
"Return",
"a",
"boolean",
"value",
"translating",
"from",
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"types",
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"necessary",
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] | def _convert_to_boolean(self, value):
"""Return a boolean value translating from other types if necessary.
"""
if value.lower() not in self.BOOLEAN_STATES:
raise ValueError('Not a boolean: %s' % value)
return self.BOOLEAN_STATES[value.lower()] | [
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tensorflow/deepmath | b5b721f54de1d5d6a02d78f5da5995237f9995f9 | deepmath/deephol/prover.py | python | NoBacktrackProver.prove_one | (self, tree: proof_search_tree.ProofSearchTree,
task: proof_assistant_pb2.ProverTask) | Searches for a proof without backtracking.
Args:
tree: Search tree with a single goal node to be proved.
task: ProverTask to be performed.
Returns:
None on success and error message on failure. | Searches for a proof without backtracking. | [
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] | def prove_one(self, tree: proof_search_tree.ProofSearchTree,
task: proof_assistant_pb2.ProverTask) -> Optional[Text]:
"""Searches for a proof without backtracking.
Args:
tree: Search tree with a single goal node to be proved.
task: ProverTask to be performed.
Returns:
None on success and error message on failure.
"""
root = tree.nodes[0]
budget = NO_BACKTRACK_SEARCH_NODES
cur_index = 0
while not root.closed and not self.timed_out():
if cur_index >= len(tree.nodes):
# This situation can happen only if the tactics succeed, but end up
# reconstructing an earlier node.
return 'NoBacktrack: Loop.'
node = tree.nodes[cur_index]
cur_index += 1
prover_util.try_tactics(node, budget, 0, 1, task.premise_set,
self.action_gen,
self.prover_options.tactic_timeout_ms)
if not node.successful_attempts:
return ('NoBacktrack: No successful tactic applications within '
'limit %d' % budget)
else:
if len(node.successful_attempts) != 1:
tf.logging.info('%d successful attempts.',
len(node.successful_attempts))
for tac_app in node.successful_attempts:
tf.logging.info('attempt: %s', tac_app.tactic)
assert len(node.successful_attempts) == 1
budget -= len(node.failed_attempts) + 1
if not root.closed:
if self.timed_out():
return 'Timed out.'
else:
return 'NoBacktrack: Could not find proof.' | [
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||
NREL/EnergyPlus | fadc5973b85c70e8cc923efb69c144e808a26078 | third_party/EP-Launch-Lite/EPLaunchLite/EPLaunchLiteWindow.py | python | Window.gui_build_body | (self) | return vbox | This function builds out the specific widgets on the GUI
* Returns: A gtk.VBox suitable for adding directly onto the main gtk.Window | This function builds out the specific widgets on the GUI | [
"This",
"function",
"builds",
"out",
"the",
"specific",
"widgets",
"on",
"the",
"GUI"
] | def gui_build_body(self):
"""
This function builds out the specific widgets on the GUI
* Returns: A gtk.VBox suitable for adding directly onto the main gtk.Window
"""
# create a vbox here first
vbox = gtk.VBox(False, self.box_spacing)
# create the menu bar itself to hold the menus
mb = gtk.MenuBar()
# create the actual actionable items under the file menu
menu_item_file_about = gtk.MenuItem(_("About..."))
menu_item_file_about.connect("activate", self.about_dialog)
menu_item_file_about.show()
menu_item_file_exit = gtk.MenuItem(_("Exit"))
menu_item_file_exit.connect("activate", self.quit)
menu_item_file_exit.show()
# create the actual actionable items under the language menu
menu_item_english = gtk.MenuItem("Language: English")
menu_item_english.connect("activate", self.switch_language, Languages.English)
menu_item_english.show()
if self.settings[Keys.language] == Languages.English:
menu_item_english.set_sensitive(False)
menu_item_spanish = gtk.MenuItem("Idioma: Espanol")
menu_item_spanish.connect("activate", self.switch_language, Languages.Spanish)
menu_item_spanish.show()
if self.settings[Keys.language] == Languages.Spanish:
menu_item_spanish.set_sensitive(False)
menu_item_french = gtk.MenuItem("Langue: Francais")
menu_item_french.connect("activate", self.switch_language, Languages.French)
menu_item_french.show()
if self.settings[Keys.language] == Languages.French:
menu_item_french.set_sensitive(False)
# create the list of items that will eventually be dropped down, and append items in the right order
filemenu = gtk.Menu()
filemenu.append(menu_item_file_about)
filemenu.append(gtk.SeparatorMenuItem())
filemenu.append(menu_item_file_exit)
langmenu = gtk.Menu()
langmenu.append(menu_item_english)
langmenu.append(menu_item_spanish)
langmenu.append(menu_item_french)
# create the root drop-down-able menu items, and assign their submenus to the lists above
menu_item_file = gtk.MenuItem(_("File"))
menu_item_file.set_submenu(filemenu)
menu_item_lang = gtk.MenuItem("Language/Idioma/Langue")
menu_item_lang.set_submenu(langmenu)
# attach the root menus to the main menu bar
mb.append(menu_item_file)
mb.append(menu_item_lang)
# and finally attach the main menu bar to the window
vbox.pack_start(mb, False)
# create the input file button and textbox section
hbox1 = gtk.HBox(False, self.box_spacing)
button1 = gtk.Button(_("Choose Input File.."))
button1.connect("clicked", self.select_input_file, FileTypes.IDF)
alignment = gtk.Alignment(xalign=1.0, yalign=0.5, xscale=1.0, yscale=0.5)
alignment.add(button1)
hbox1.pack_start(alignment, True, True, self.box_spacing)
self.input_file_path = gtk.Entry()
self.input_file_path.connect("changed", self.check_file_paths)
self.input_file_path.set_text(self.settings['last_idf']) # "/tmp/RefBldgHospitalNew2004_Chicago.idf")
self.input_file_path.set_size_request(width=500, height=-1)
alignment = gtk.Alignment(xalign=1.0, yalign=0.5, xscale=1.0, yscale=0.5)
alignment.add(self.input_file_path)
hbox1.pack_start(alignment, True, True, self.box_spacing)
self.edit_idf_button = gtk.Button(_("Edit Input File.."))
self.edit_idf_button.connect("clicked", self.open_input_file)
alignment = gtk.Alignment(xalign=1.0, yalign=0.5, xscale=1.0, yscale=0.5)
alignment.add(self.edit_idf_button)
hbox1.pack_start(alignment, True, True, self.box_spacing)
vbox.pack_start(self.framed(hbox1), True, True, 0)
# create the weather file button and textbox section
hbox2 = gtk.HBox(False, self.box_spacing)
button1 = gtk.Button(_("Choose Weather File.."))
button1.connect("clicked", self.select_input_file, FileTypes.EPW)
alignment = gtk.Alignment(xalign=1.0, yalign=0.5, xscale=1.0, yscale=0.5)
alignment.add(button1)
hbox2.pack_start(alignment, True, True, self.box_spacing)
self.weather_file_path = gtk.Entry()
self.weather_file_path.connect("changed", self.check_file_paths)
self.weather_file_path.set_text(
self.settings['last_epw']) # '"/Users/elee/EnergyPlus/repos/2eplus/weather/CZ06RV2.epw")
self.weather_file_path.set_size_request(width=500, height=-1)
alignment = gtk.Alignment(xalign=1.0, yalign=0.5, xscale=1.0, yscale=0.5)
alignment.add(self.weather_file_path)
hbox2.pack_start(alignment, True, True, self.box_spacing)
vbox.pack_start(self.framed(hbox2), True, True, 0)
# separator
vbox.pack_start(self.framed(gtk.HSeparator()), False)
# create the simulate/cancel button section
hbox3 = gtk.HBox(False, self.box_spacing)
self.button_sim = gtk.Button(_("Simulate"))
self.button_sim.connect("clicked", self.run_simulation)
alignment = gtk.Alignment(xalign=0.5, yalign=0.5, xscale=0.5, yscale=0.5)
alignment.add(self.button_sim)
hbox3.pack_start(alignment, True, True, self.box_spacing)
self.button_cancel = gtk.Button(_("Cancel"))
self.button_cancel.connect("clicked", self.cancel_simulation)
alignment = gtk.Alignment(xalign=0.5, yalign=0.5, xscale=0.5, yscale=0.5)
alignment.add(self.button_cancel)
self.update_run_buttons(running=False)
hbox3.pack_start(alignment, True, True, self.box_spacing)
# self.button_language = gtk.Button(_("Switch language"))
# self.button_language.connect("clicked", self.switch_language)
# alignment = gtk.Alignment(xalign=0.5, yalign=0.5, xscale=0.5, yscale=0.5)
# alignment.add(self.button_language)
# hbox3.pack_start(alignment, True, True, self.box_spacing)
vbox.pack_start(self.framed(hbox3), True, True, 0)
# separator
vbox.pack_start(self.framed(gtk.HSeparator()), False)
# create the status bar
hbox = gtk.HBox(False, self.box_spacing)
self.ep_version_label = gtk.Label()
self.ep_version_label.set_text(_("E+ Version"))
aligner = gtk.Alignment(1, 0.5, 1, 1)
aligner.add(self.ep_version_label)
hbox.pack_start(self.framed(gtk.VSeparator()), False)
hbox.pack_start(aligner, False, True, 0)
self.status_bar = gtk.Statusbar()
self.status_bar.set_has_resize_grip(False)
self.status_bar_context_id = self.status_bar.get_context_id("Statusbar example")
self.status_bar.push(self.status_bar_context_id, _("Ready for launch"))
aligner = gtk.Alignment(1, 1, 1, 0)
aligner.add(self.status_bar)
hbox.pack_start(self.framed(gtk.VSeparator()), False)
hbox.pack_start(aligner)
vbox.pack_end(self.framed(hbox), False, True, 0)
hbox.pack_start(self.framed(gtk.VSeparator()), False)
# return the vbox
return vbox | [
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] | https://github.com/NREL/EnergyPlus/blob/fadc5973b85c70e8cc923efb69c144e808a26078/third_party/EP-Launch-Lite/EPLaunchLite/EPLaunchLiteWindow.py#L106-L251 |
|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | build/android/buildbot/bb_device_steps.py | python | UploadHTML | (options, gs_base_dir, dir_to_upload, link_text,
link_rel_path='index.html', gs_url=GS_URL) | Uploads directory at |dir_to_upload| to Google Storage and output a link.
Args:
options: Command line options.
gs_base_dir: The Google Storage base directory (e.g.
'chromium-code-coverage/java')
dir_to_upload: Absolute path to the directory to be uploaded.
link_text: Link text to be displayed on the step.
link_rel_path: Link path relative to |dir_to_upload|.
gs_url: Google storage URL. | Uploads directory at |dir_to_upload| to Google Storage and output a link. | [
"Uploads",
"directory",
"at",
"|dir_to_upload|",
"to",
"Google",
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"output",
"a",
"link",
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] | def UploadHTML(options, gs_base_dir, dir_to_upload, link_text,
link_rel_path='index.html', gs_url=GS_URL):
"""Uploads directory at |dir_to_upload| to Google Storage and output a link.
Args:
options: Command line options.
gs_base_dir: The Google Storage base directory (e.g.
'chromium-code-coverage/java')
dir_to_upload: Absolute path to the directory to be uploaded.
link_text: Link text to be displayed on the step.
link_rel_path: Link path relative to |dir_to_upload|.
gs_url: Google storage URL.
"""
revision = _GetRevision(options)
bot_id = options.build_properties.get('buildername', 'testing')
randhash = hashlib.sha1(str(random.random())).hexdigest()
gs_path = '%s/%s/%s/%s' % (gs_base_dir, bot_id, revision, randhash)
RunCmd([bb_utils.GSUTIL_PATH, 'cp', '-R', dir_to_upload, 'gs://%s' % gs_path])
bb_annotations.PrintLink(link_text,
'%s/%s/%s' % (gs_url, gs_path, link_rel_path)) | [
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] | https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/build/android/buildbot/bb_device_steps.py#L489-L508 |
||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/protobuf/py2/google/protobuf/internal/decoder.py | python | MessageSetItemDecoder | (descriptor) | return DecodeItem | Returns a decoder for a MessageSet item.
The parameter is the message Descriptor.
The message set message looks like this:
message MessageSet {
repeated group Item = 1 {
required int32 type_id = 2;
required string message = 3;
}
} | Returns a decoder for a MessageSet item. | [
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] | def MessageSetItemDecoder(descriptor):
"""Returns a decoder for a MessageSet item.
The parameter is the message Descriptor.
The message set message looks like this:
message MessageSet {
repeated group Item = 1 {
required int32 type_id = 2;
required string message = 3;
}
}
"""
type_id_tag_bytes = encoder.TagBytes(2, wire_format.WIRETYPE_VARINT)
message_tag_bytes = encoder.TagBytes(3, wire_format.WIRETYPE_LENGTH_DELIMITED)
item_end_tag_bytes = encoder.TagBytes(1, wire_format.WIRETYPE_END_GROUP)
local_ReadTag = ReadTag
local_DecodeVarint = _DecodeVarint
local_SkipField = SkipField
def DecodeItem(buffer, pos, end, message, field_dict):
"""Decode serialized message set to its value and new position.
Args:
buffer: memoryview of the serialized bytes.
pos: int, position in the memory view to start at.
end: int, end position of serialized data
message: Message object to store unknown fields in
field_dict: Map[Descriptor, Any] to store decoded values in.
Returns:
int, new position in serialized data.
"""
message_set_item_start = pos
type_id = -1
message_start = -1
message_end = -1
# Technically, type_id and message can appear in any order, so we need
# a little loop here.
while 1:
(tag_bytes, pos) = local_ReadTag(buffer, pos)
if tag_bytes == type_id_tag_bytes:
(type_id, pos) = local_DecodeVarint(buffer, pos)
elif tag_bytes == message_tag_bytes:
(size, message_start) = local_DecodeVarint(buffer, pos)
pos = message_end = message_start + size
elif tag_bytes == item_end_tag_bytes:
break
else:
pos = SkipField(buffer, pos, end, tag_bytes)
if pos == -1:
raise _DecodeError('Missing group end tag.')
if pos > end:
raise _DecodeError('Truncated message.')
if type_id == -1:
raise _DecodeError('MessageSet item missing type_id.')
if message_start == -1:
raise _DecodeError('MessageSet item missing message.')
extension = message.Extensions._FindExtensionByNumber(type_id)
# pylint: disable=protected-access
if extension is not None:
value = field_dict.get(extension)
if value is None:
message_type = extension.message_type
if not hasattr(message_type, '_concrete_class'):
# pylint: disable=protected-access
message._FACTORY.GetPrototype(message_type)
value = field_dict.setdefault(
extension, message_type._concrete_class())
if value._InternalParse(buffer, message_start,message_end) != message_end:
# The only reason _InternalParse would return early is if it encountered
# an end-group tag.
raise _DecodeError('Unexpected end-group tag.')
else:
if not message._unknown_fields:
message._unknown_fields = []
message._unknown_fields.append(
(MESSAGE_SET_ITEM_TAG, buffer[message_set_item_start:pos].tobytes()))
if message._unknown_field_set is None:
message._unknown_field_set = containers.UnknownFieldSet()
message._unknown_field_set._add(
type_id,
wire_format.WIRETYPE_LENGTH_DELIMITED,
buffer[message_start:message_end].tobytes())
# pylint: enable=protected-access
return pos
return DecodeItem | [
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|
DeepGraphLearning/graphvite | e067c59146f676e3eee3eee6106dce7ccc7cf9e4 | python/graphvite/application/application.py | python | GraphApplication.node_classification | (self, X=None, Y=None, file_name=None, portions=(0.02,), normalization=False, times=1,
patience=100) | return metrics | Evaluate node embeddings on node classification task.
Parameters:
X (list of str, optional): names of nodes
Y (list, optional): labels of nodes
file_name (str, optional): file of nodes & labels
portions (tuple of float, optional): how much data for training
normalization (bool, optional): normalize the embeddings or not
times (int, optional): number of trials
patience (int, optional): patience on loss convergence
Returns:
dict: macro-F1 & micro-F1 averaged over all trials | Evaluate node embeddings on node classification task. | [
"Evaluate",
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"task",
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] | def node_classification(self, X=None, Y=None, file_name=None, portions=(0.02,), normalization=False, times=1,
patience=100):
"""
Evaluate node embeddings on node classification task.
Parameters:
X (list of str, optional): names of nodes
Y (list, optional): labels of nodes
file_name (str, optional): file of nodes & labels
portions (tuple of float, optional): how much data for training
normalization (bool, optional): normalize the embeddings or not
times (int, optional): number of trials
patience (int, optional): patience on loss convergence
Returns:
dict: macro-F1 & micro-F1 averaged over all trials
"""
import scipy.sparse as sp
self.solver.clear()
if file_name:
if not (X is None and Y is None):
raise ValueError("Evaluation data and file should not be provided at the same time")
X = []
Y = []
with open(file_name, "r") as fin:
for line in fin:
tokens = self.tokenize(line)
if len(tokens) == 0:
continue
x, y = tokens
X.append(x)
Y.append(y)
if X is None or Y is None:
raise ValueError("Either evaluataion data (X, Y) or a file name should be provided")
name2id = self.graph.name2id
class2id = {c:i for i, c in enumerate(np.unique(Y))}
new_X, new_Y = self.name_map((name2id, class2id), (X, Y))
logger.info("effective labels: %d / %d" % (len(new_X), len(X)))
X = np.asarray(new_X)
Y = np.asarray(new_Y)
labels = sp.coo_matrix((np.ones_like(X), (X, Y)), dtype=np.int32).todense()
indexes, _ = np.where(np.sum(labels, axis=1) > 0)
# discard non-labeled nodes
labels = labels[indexes]
vertex_embeddings = SharedNDArray(self.solver.vertex_embeddings[indexes])
settings = []
for portion in portions:
settings.append((vertex_embeddings, labels, portion, normalization, times, patience))
results = self.gpu_map(linear_classification, settings)
metrics = {}
for result in results:
metrics.update(result)
return metrics | [
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|
CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | ExFileObject.readlines | (self) | return result | Return a list with all remaining lines. | Return a list with all remaining lines. | [
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] | def readlines(self):
"""Return a list with all remaining lines.
"""
result = []
while True:
line = self.readline()
if not line: break
result.append(line)
return result | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/train/summary/_summary_adapter.py | python | package_summary_event | (data_list, step, wall_time) | return summary_event | Package the summary to event protobuffer.
Args:
data_list (list): Summary data list.
step (Number): The recode step index.
wall_time (float): The wall time.
Returns:
Summary, the summary event. | Package the summary to event protobuffer. | [
"Package",
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"summary",
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"event",
"protobuffer",
"."
] | def package_summary_event(data_list, step, wall_time):
"""
Package the summary to event protobuffer.
Args:
data_list (list): Summary data list.
step (Number): The recode step index.
wall_time (float): The wall time.
Returns:
Summary, the summary event.
"""
# create the event of summary
summary_event = Event()
summary = summary_event.summary
summary_event.wall_time = wall_time
summary_event.step = int(step)
for value in data_list:
summary_type = value["_type"]
data = value["data"]
tag = value["name"]
logger.debug(f"Now process {summary_type} summary, tag = {tag}")
summary_value = summary.value.add()
summary_value.tag = tag
# get the summary type and parse the tag
if summary_type == 'Scalar':
if not _fill_scalar_summary(tag, data, summary_value):
del summary.value[-1]
elif summary_type == 'Tensor':
_fill_tensor_summary(tag, data, summary_value.tensor)
elif summary_type == 'Image':
if not _fill_image_summary(tag, data, summary_value.image, MS_IMAGE_TENSOR_FORMAT):
del summary.value[-1]
elif summary_type == 'Histogram':
_fill_histogram_summary(tag, data, summary_value.histogram)
elif summary_type == 'Landscape':
summary_value.loss_landscape.ParseFromString(data)
else:
# The data is invalid ,jump the data
logger.error(f"Summary type({summary_type}) is error, tag = {tag}")
del summary.value[-1]
return summary_event | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/distutils/ccompiler.py | python | CCompiler._fix_compile_args | (self, output_dir, macros, include_dirs) | return output_dir, macros, include_dirs | Typecheck and fix-up some of the arguments to the 'compile()'
method, and return fixed-up values. Specifically: if 'output_dir'
is None, replaces it with 'self.output_dir'; ensures that 'macros'
is a list, and augments it with 'self.macros'; ensures that
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Guarantees that the returned values are of the correct type,
i.e. for 'output_dir' either string or None, and for 'macros' and
'include_dirs' either list or None. | Typecheck and fix-up some of the arguments to the 'compile()'
method, and return fixed-up values. Specifically: if 'output_dir'
is None, replaces it with 'self.output_dir'; ensures that 'macros'
is a list, and augments it with 'self.macros'; ensures that
'include_dirs' is a list, and augments it with 'self.include_dirs'.
Guarantees that the returned values are of the correct type,
i.e. for 'output_dir' either string or None, and for 'macros' and
'include_dirs' either list or None. | [
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is None, replaces it with 'self.output_dir'; ensures that 'macros'
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output_dir = self.output_dir
elif not isinstance(output_dir, str):
raise TypeError, "'output_dir' must be a string or None"
if macros is None:
macros = self.macros
elif isinstance(macros, list):
macros = macros + (self.macros or [])
else:
raise TypeError, "'macros' (if supplied) must be a list of tuples"
if include_dirs is None:
include_dirs = self.include_dirs
elif isinstance(include_dirs, (list, tuple)):
include_dirs = list (include_dirs) + (self.include_dirs or [])
else:
raise TypeError, \
"'include_dirs' (if supplied) must be a list of strings"
return output_dir, macros, include_dirs | [
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|
etotheipi/BitcoinArmory | 2a6fc5355bb0c6fe26e387ccba30a5baafe8cd98 | armoryengine/ArmoryUtils.py | python | hex_to_int | (h, endIn=LITTLEENDIAN) | return( int(hstr, 16) ) | Convert hex-string to integer (or long). Default behavior is to interpret
hex string as little-endian | Convert hex-string to integer (or long). Default behavior is to interpret
hex string as little-endian | [
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] | def hex_to_int(h, endIn=LITTLEENDIAN):
"""
Convert hex-string to integer (or long). Default behavior is to interpret
hex string as little-endian
"""
hstr = h.replace(' ','') # copies data, no references
if endIn==LITTLEENDIAN:
hstr = hex_switchEndian(hstr)
return( int(hstr, 16) ) | [
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|
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/rnn/python/ops/core_rnn_cell.py | python | InputProjectionWrapper.call | (self, inputs, state) | return self._cell(projected, state) | Run the input projection and then the cell. | Run the input projection and then the cell. | [
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"""Run the input projection and then the cell."""
# Default scope: "InputProjectionWrapper"
projected = _linear(inputs, self._num_proj, True)
if self._activation:
projected = self._activation(projected)
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|
OAID/Caffe-HRT | aae71e498ab842c6f92bcc23fc668423615a4d65 | scripts/cpp_lint.py | python | CheckForNonConstReference | (filename, clean_lines, linenum,
nesting_state, error) | Check for non-const references.
Separate from CheckLanguage since it scans backwards from current
line, instead of scanning forward.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: The function to call with any errors found. | Check for non-const references. | [
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nesting_state, error):
"""Check for non-const references.
Separate from CheckLanguage since it scans backwards from current
line, instead of scanning forward.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: The function to call with any errors found.
"""
# Do nothing if there is no '&' on current line.
line = clean_lines.elided[linenum]
if '&' not in line:
return
# Long type names may be broken across multiple lines, usually in one
# of these forms:
# LongType
# ::LongTypeContinued &identifier
# LongType::
# LongTypeContinued &identifier
# LongType<
# ...>::LongTypeContinued &identifier
#
# If we detected a type split across two lines, join the previous
# line to current line so that we can match const references
# accordingly.
#
# Note that this only scans back one line, since scanning back
# arbitrary number of lines would be expensive. If you have a type
# that spans more than 2 lines, please use a typedef.
if linenum > 1:
previous = None
if Match(r'\s*::(?:[\w<>]|::)+\s*&\s*\S', line):
# previous_line\n + ::current_line
previous = Search(r'\b((?:const\s*)?(?:[\w<>]|::)+[\w<>])\s*$',
clean_lines.elided[linenum - 1])
elif Match(r'\s*[a-zA-Z_]([\w<>]|::)+\s*&\s*\S', line):
# previous_line::\n + current_line
previous = Search(r'\b((?:const\s*)?(?:[\w<>]|::)+::)\s*$',
clean_lines.elided[linenum - 1])
if previous:
line = previous.group(1) + line.lstrip()
else:
# Check for templated parameter that is split across multiple lines
endpos = line.rfind('>')
if endpos > -1:
(_, startline, startpos) = ReverseCloseExpression(
clean_lines, linenum, endpos)
if startpos > -1 and startline < linenum:
# Found the matching < on an earlier line, collect all
# pieces up to current line.
line = ''
for i in xrange(startline, linenum + 1):
line += clean_lines.elided[i].strip()
# Check for non-const references in function parameters. A single '&' may
# found in the following places:
# inside expression: binary & for bitwise AND
# inside expression: unary & for taking the address of something
# inside declarators: reference parameter
# We will exclude the first two cases by checking that we are not inside a
# function body, including one that was just introduced by a trailing '{'.
# TODO(unknwon): Doesn't account for preprocessor directives.
# TODO(unknown): Doesn't account for 'catch(Exception& e)' [rare].
check_params = False
if not nesting_state.stack:
check_params = True # top level
elif (isinstance(nesting_state.stack[-1], _ClassInfo) or
isinstance(nesting_state.stack[-1], _NamespaceInfo)):
check_params = True # within class or namespace
elif Match(r'.*{\s*$', line):
if (len(nesting_state.stack) == 1 or
isinstance(nesting_state.stack[-2], _ClassInfo) or
isinstance(nesting_state.stack[-2], _NamespaceInfo)):
check_params = True # just opened global/class/namespace block
# We allow non-const references in a few standard places, like functions
# called "swap()" or iostream operators like "<<" or ">>". Do not check
# those function parameters.
#
# We also accept & in static_assert, which looks like a function but
# it's actually a declaration expression.
whitelisted_functions = (r'(?:[sS]wap(?:<\w:+>)?|'
r'operator\s*[<>][<>]|'
r'static_assert|COMPILE_ASSERT'
r')\s*\(')
if Search(whitelisted_functions, line):
check_params = False
elif not Search(r'\S+\([^)]*$', line):
# Don't see a whitelisted function on this line. Actually we
# didn't see any function name on this line, so this is likely a
# multi-line parameter list. Try a bit harder to catch this case.
for i in xrange(2):
if (linenum > i and
Search(whitelisted_functions, clean_lines.elided[linenum - i - 1])):
check_params = False
break
if check_params:
decls = ReplaceAll(r'{[^}]*}', ' ', line) # exclude function body
for parameter in re.findall(_RE_PATTERN_REF_PARAM, decls):
if not Match(_RE_PATTERN_CONST_REF_PARAM, parameter):
error(filename, linenum, 'runtime/references', 2,
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/targets/externals.py | python | set_fnclex | (context, c_helpers) | return library | Install fnclex before fmod calls.
Workaround for https://support.microsoft.com/en-us/kb/982107 | Install fnclex before fmod calls.
Workaround for https://support.microsoft.com/en-us/kb/982107 | [
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"""
Install fnclex before fmod calls.
Workaround for https://support.microsoft.com/en-us/kb/982107
"""
ptr_set_fnclex = c_helpers['set_fnclex']
fn = ctypes.CFUNCTYPE(None, ctypes.c_void_p)(ptr_set_fnclex)
library = compile_fnclex(context)
fnclex_ptr = library.get_pointer_to_function('fnclex')
fn(fnclex_ptr)
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|
GJDuck/LowFat | ecf6a0f0fa1b73a27a626cf493cc39e477b6faea | llvm-4.0.0.src/tools/clang/tools/scan-build-py/libscanbuild/report.py | python | report_directory | (hint, keep) | Responsible for the report directory.
hint -- could specify the parent directory of the output directory.
keep -- a boolean value to keep or delete the empty report directory. | Responsible for the report directory. | [
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] | def report_directory(hint, keep):
""" Responsible for the report directory.
hint -- could specify the parent directory of the output directory.
keep -- a boolean value to keep or delete the empty report directory. """
stamp_format = 'scan-build-%Y-%m-%d-%H-%M-%S-%f-'
stamp = datetime.datetime.now().strftime(stamp_format)
parentdir = os.path.abspath(hint)
if not os.path.exists(parentdir):
os.makedirs(parentdir)
name = tempfile.mkdtemp(prefix=stamp, dir=parentdir)
logging.info('Report directory created: %s', name)
try:
yield name
finally:
if os.listdir(name):
msg = "Run 'scan-view %s' to examine bug reports."
keep = True
else:
if keep:
msg = "Report directory '%s' contans no report, but kept."
else:
msg = "Removing directory '%s' because it contains no report."
logging.warning(msg, name)
if not keep:
os.rmdir(name) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/stc.py | python | StyledTextCtrl.GetSearchFlags | (*args, **kwargs) | return _stc.StyledTextCtrl_GetSearchFlags(*args, **kwargs) | GetSearchFlags(self) -> int
Get the search flags used by SearchInTarget. | GetSearchFlags(self) -> int | [
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] | def GetSearchFlags(*args, **kwargs):
"""
GetSearchFlags(self) -> int
Get the search flags used by SearchInTarget.
"""
return _stc.StyledTextCtrl_GetSearchFlags(*args, **kwargs) | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_core.py | python | MenuItem.SetOwnerDrawn | (*args, **kwargs) | return _core_.MenuItem_SetOwnerDrawn(*args, **kwargs) | SetOwnerDrawn(self, bool ownerDrawn=True) | SetOwnerDrawn(self, bool ownerDrawn=True) | [
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return _core_.MenuItem_SetOwnerDrawn(*args, **kwargs) | [
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|
apiaryio/snowcrash | b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3 | tools/gyp/pylib/gyp/msvs_emulation.py | python | MsvsSettings._TargetConfig | (self, config) | return config | Returns the target-specific configuration. | Returns the target-specific configuration. | [
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# There's two levels of architecture/platform specification in VS. The
# first level is globally for the configuration (this is what we consider
# "the" config at the gyp level, which will be something like 'Debug' or
# 'Release_x64'), and a second target-specific configuration, which is an
# override for the global one. |config| is remapped here to take into
# account the local target-specific overrides to the global configuration.
arch = self.GetArch(config)
if arch == 'x64' and not config.endswith('_x64'):
config += '_x64'
if arch == 'x86' and config.endswith('_x64'):
config = config.rsplit('_', 1)[0]
return config | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/ultimatelistctrl.py | python | UltimateListMainWindow.SetGradientStyle | (self, vertical=0) | Sets the gradient style for gradient-style selections.
:param `vertical`: 0 for horizontal gradient-style selections, 1 for vertical
gradient-style selections. | Sets the gradient style for gradient-style selections. | [
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] | def SetGradientStyle(self, vertical=0):
"""
Sets the gradient style for gradient-style selections.
:param `vertical`: 0 for horizontal gradient-style selections, 1 for vertical
gradient-style selections.
"""
# 0 = Horizontal, 1 = Vertical
self._gradientstyle = vertical
if self._usegradients:
self.RefreshSelected() | [
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||
FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Path/PathScripts/PathToolLibraryEditor.py | python | EditorPanel.loadTable | (self, name) | loads the tools for the selected tool table | loads the tools for the selected tool table | [
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"""loads the tools for the selected tool table"""
tooldata = self.TLM.getTools(name)
if tooldata:
self.form.ToolsList.setModel(tooldata)
self.form.ToolsList.resizeColumnsToContents()
self.form.ToolsList.horizontalHeader().setResizeMode(
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self.setCurrentToolTableByName(name) | [
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||
microsoft/ELL | a1d6bacc37a14879cc025d9be2ba40b1a0632315 | tools/importers/CNTK/lib/cntk_layers.py | python | MaxPoolingLayer.clone_cntk_layer | (self, feature) | return MaxPooling(filterShape, strides=(stride, stride), pad=pad)(feature) | Returns a clone of the CNTK layer for per-layer forward prop validation | Returns a clone of the CNTK layer for per-layer forward prop validation | [
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"""Returns a clone of the CNTK layer for per-layer forward prop validation"""
pad, filterShape, stride = self.get_cntk_parameters()
return MaxPooling(filterShape, strides=(stride, stride), pad=pad)(feature) | [
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|
krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/model/robotinfo.py | python | RobotInfo.klamptModel | (self) | return self.robotModel | Returns the Klamp't RobotModel associated with this robot, either by
the ``robotModel`` object or loading from the given filename
``self.modelFile``.
The results are cached so this can be called many times without a
performance hit. | Returns the Klamp't RobotModel associated with this robot, either by
the ``robotModel`` object or loading from the given filename
``self.modelFile``. | [
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"""Returns the Klamp't RobotModel associated with this robot, either by
the ``robotModel`` object or loading from the given filename
``self.modelFile``.
The results are cached so this can be called many times without a
performance hit.
"""
if self.robotModel is not None:
return self.robotModel
if self.modelFile is None:
raise RuntimeError("Can't load robot model for {}, no file given".format(self.name))
self._worldTemp = WorldModel()
def doload(fn):
self.robotModel = self._worldTemp.loadRobot(fn)
return self.robotModel.index >= 0
if not self._tryload(self.modelFile,doload):
raise IOError("Unable to load robot from file {}".format(self.modelFile))
self.robotModel.setName(self.name)
#apply calibration
for (k,file) in self.calibrationFiles.items():
if k == 'kinematics':
def docalib(fn):
try:
with open(fn,'r') as f:
jsonobj = json.load(f)
except IOError:
return False
for k,items in jsonobj.items():
link = self.robotModel.link(k)
if link.index < 0:
raise ValueError("Calibration file refers to invalid link {}".format(k))
for key,value in items.items():
if key == 'axis':
link.setAxis(value)
elif key == 'Tparent':
link.setParentTransform(value)
else:
raise KeyError("Invalid calibration item {}".format(key))
return True
if not self._tryload(file,docalib):
raise IOError("Unable to load kinematics calibration from file "+file)
else:
s = self.robotModel.sensor(k)
if s.getName():
self.configureSensor(s)
else:
warnings.warn("Calibration item {} doesn't refer to a sensor or kinematics".format(k))
return self.robotModel | [
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | xpathParserContext.xpathErr | (self, error) | Handle an XPath error | Handle an XPath error | [
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"an",
"XPath",
"error"
] | def xpathErr(self, error):
"""Handle an XPath error """
libxml2mod.xmlXPathErr(self._o, error) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_controls.py | python | Button_GetClassDefaultAttributes | (*args, **kwargs) | return _controls_.Button_GetClassDefaultAttributes(*args, **kwargs) | Button_GetClassDefaultAttributes(int variant=WINDOW_VARIANT_NORMAL) -> VisualAttributes
Get the default attributes for this class. This is useful if you want
to use the same font or colour in your own control as in a standard
control -- which is a much better idea than hard coding specific
colours or fonts which might look completely out of place on the
user's system, especially if it uses themes.
The variant parameter is only relevant under Mac currently and is
ignore under other platforms. Under Mac, it will change the size of
the returned font. See `wx.Window.SetWindowVariant` for more about
this. | Button_GetClassDefaultAttributes(int variant=WINDOW_VARIANT_NORMAL) -> VisualAttributes | [
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"=",
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] | def Button_GetClassDefaultAttributes(*args, **kwargs):
"""
Button_GetClassDefaultAttributes(int variant=WINDOW_VARIANT_NORMAL) -> VisualAttributes
Get the default attributes for this class. This is useful if you want
to use the same font or colour in your own control as in a standard
control -- which is a much better idea than hard coding specific
colours or fonts which might look completely out of place on the
user's system, especially if it uses themes.
The variant parameter is only relevant under Mac currently and is
ignore under other platforms. Under Mac, it will change the size of
the returned font. See `wx.Window.SetWindowVariant` for more about
this.
"""
return _controls_.Button_GetClassDefaultAttributes(*args, **kwargs) | [
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|
Atarity/Lightpack | 4dee73a443cba4c4073291febe450e6c1941f3af | Software/apiexamples/liOSC/OSC.py | python | OSCMultiClient.hasOSCTarget | (self, address, prefix=None) | return False | Return True if the given OSCTarget exists in the Client's dict.
the 'address' argument can be a ((host, port) tuple), or a hostname.
If the 'prefix' argument is given, the return-value is only True if the address and prefix match. | Return True if the given OSCTarget exists in the Client's dict.
the 'address' argument can be a ((host, port) tuple), or a hostname.
If the 'prefix' argument is given, the return-value is only True if the address and prefix match. | [
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"""Return True if the given OSCTarget exists in the Client's dict.
the 'address' argument can be a ((host, port) tuple), or a hostname.
If the 'prefix' argument is given, the return-value is only True if the address and prefix match.
"""
if type(address) in types.StringTypes:
address = self._searchHostAddr(address)
if type(address) == types.TupleType:
(host, port) = address[:2]
try:
host = socket.gethostbyname(host)
except socket.error:
pass
address = (host, port)
if address in self.targets.keys():
if prefix == None:
return True
elif prefix == self.targets[address][0]:
return True
return False | [
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|
swift/swift | 12d031cf8177fdec0137f9aa7e2912fa23c4416b | 3rdParty/SCons/scons-3.0.1/engine/SCons/Node/FS.py | python | File.retrieve_from_cache | (self) | return self.get_build_env().get_CacheDir().retrieve(self) | Try to retrieve the node's content from a cache
This method is called from multiple threads in a parallel build,
so only do thread safe stuff here. Do thread unsafe stuff in
built().
Returns true if the node was successfully retrieved. | Try to retrieve the node's content from a cache | [
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This method is called from multiple threads in a parallel build,
so only do thread safe stuff here. Do thread unsafe stuff in
built().
Returns true if the node was successfully retrieved.
"""
if self.nocache:
return None
if not self.is_derived():
return None
return self.get_build_env().get_CacheDir().retrieve(self) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/ast.py | python | copy_location | (new_node, old_node) | return new_node | Copy source location (`lineno` and `col_offset` attributes) from
*old_node* to *new_node* if possible, and return *new_node*. | Copy source location (`lineno` and `col_offset` attributes) from
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/autograph/impl/conversion.py | python | is_unsupported | (o) | return False | Checks whether an entity is supported by AutoGraph at all. | Checks whether an entity is supported by AutoGraph at all. | [
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# TODO(b/122265385): Remove this bypass.
if (_is_known_loaded_type(o, 'wrapt', 'FunctionWrapper') or
_is_known_loaded_type(o, 'wrapt', 'BoundFunctionWrapper')):
logging.warning(
'{} appears to be decorated by wrapt, which is not yet supported'
' by AutoGraph. The function will run as-is.'
' You may still apply AutoGraph before the wrapt decorator.'.format(o))
logging.log(2, 'Permanently allowed: %s: wrapt decorated', o)
return True
if _is_known_loaded_type(o, 'functools', '_lru_cache_wrapper'):
logging.log(2, 'Permanently allowed: %s: lru_cache', o)
return True
# Constructors are permanently allowed.
# TODO(mdan): Toggle as experimental feature instead.
# TODO(b/124016764): Remove this limitation.
if inspect_utils.isconstructor(o):
logging.log(2, 'Permanently allowed: %s: constructor', o)
return True
# Other built-in modules are permanently allowed.
# TODO(mdan): Figure out how to do this consistently for all stdlib modules.
if any(
_is_of_known_loaded_module(o, m)
for m in ('collections', 'pdb', 'copy', 'inspect', 're')):
logging.log(2, 'Permanently allowed: %s: part of builtin module', o)
return True
# Custom ops and kernels are also permanently allowed.
# See tensorflow.framework.load_library.
if (hasattr(o, '__module__') and
hasattr(o.__module__, '_IS_TENSORFLOW_PLUGIN')):
logging.log(2, 'Permanently allowed: %s: TensorFlow plugin', o)
return True
return False | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_controls.py | python | ListCtrl.GetItem | (*args, **kwargs) | return val | GetItem(self, long itemId, int col=0) -> ListItem | GetItem(self, long itemId, int col=0) -> ListItem | [
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] | def GetItem(*args, **kwargs):
"""GetItem(self, long itemId, int col=0) -> ListItem"""
val = _controls_.ListCtrl_GetItem(*args, **kwargs)
if val is not None: val.thisown = 1
return val | [
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|
TimoSaemann/caffe-segnet-cudnn5 | abcf30dca449245e101bf4ced519f716177f0885 | scripts/cpp_lint.py | python | CheckForMultilineCommentsAndStrings | (filename, clean_lines, linenum, error) | Logs an error if we see /* ... */ or "..." that extend past one line.
/* ... */ comments are legit inside macros, for one line.
Otherwise, we prefer // comments, so it's ok to warn about the
other. Likewise, it's ok for strings to extend across multiple
lines, as long as a line continuation character (backslash)
terminates each line. Although not currently prohibited by the C++
style guide, it's ugly and unnecessary. We don't do well with either
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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. | Logs an error if we see /* ... */ or "..." that extend past one line. | [
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] | def CheckForMultilineCommentsAndStrings(filename, clean_lines, linenum, error):
"""Logs an error if we see /* ... */ or "..." that extend past one line.
/* ... */ comments are legit inside macros, for one line.
Otherwise, we prefer // comments, so it's ok to warn about the
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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]
# Remove all \\ (escaped backslashes) from the line. They are OK, and the
# second (escaped) slash may trigger later \" detection erroneously.
line = line.replace('\\\\', '')
if line.count('/*') > line.count('*/'):
error(filename, linenum, 'readability/multiline_comment', 5,
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'Lint may give bogus warnings. '
'Consider replacing these with //-style comments, '
'with #if 0...#endif, '
'or with more clearly structured multi-line comments.')
if (line.count('"') - line.count('\\"')) % 2:
error(filename, linenum, 'readability/multiline_string', 5,
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||
Tencent/CMONGO | c40380caa14e05509f46993aa8b8da966b09b0b5 | buildscripts/cpplint.py | python | _SetFilters | (filters) | Sets the module's error-message filters.
These filters are applied when deciding whether to emit a given
error message.
Args:
filters: A string of comma-separated filters (eg "whitespace/indent").
Each filter should start with + or -; else we die. | Sets the module's error-message filters. | [
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] | def _SetFilters(filters):
"""Sets the module's error-message filters.
These filters are applied when deciding whether to emit a given
error message.
Args:
filters: A string of comma-separated filters (eg "whitespace/indent").
Each filter should start with + or -; else we die.
"""
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/tree.py | python | TreeItem.__init__ | (self) | Constructor. Do whatever you need to do. | Constructor. Do whatever you need to do. | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_internal/network/lazy_wheel.py | python | LazyZipOverHTTP.writable | (self) | return False | Return False. | Return False. | [
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] | def writable(self):
# type: () -> bool
"""Return False."""
return False | [
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|
krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/math/symbolic.py | python | is_scalar | (v,value=None) | Returns True if v evaluates to a scalar. If value is provided, then
returns True only if v evaluates to be equal to value | Returns True if v evaluates to a scalar. If value is provided, then
returns True only if v evaluates to be equal to value | [
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"""Returns True if v evaluates to a scalar. If value is provided, then
returns True only if v evaluates to be equal to value"""
if isinstance(v,Variable):
if not v.type.is_scalar(): return False
return value is None or v.value == value
elif isinstance(v,ConstantExpression):
return is_scalar(v.value,value)
elif isinstance(v,Expression):
rt = v.returnType()
if rt is None: return False
if not rt.is_scalar(): return False
return value is None
else:
if not (isinstance(v,(bool,)+_PY_NUMERIC_TYPES) or (hasattr(v,'shape') and v.shape == ())): return False
return value is None or v == value | [
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||
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/site_compare/command_line.py | python | Command.AddArgument | (self, names, helptext, type="string", metaname=None,
required=False, default=None, positional=False) | return arg | Command-line argument to a command.
Args:
names: argument name, or list of synonyms
helptext: brief description of the argument
type: type of the argument
metaname: Name to display for value in help, inferred if not
required: True if argument must be specified
default: Default value if not specified
positional: Argument specified by location, not name
Raises:
ValueError: the argument already exists or is invalid
Returns:
The newly-created argument | Command-line argument to a command. | [
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required=False, default=None, positional=False):
"""Command-line argument to a command.
Args:
names: argument name, or list of synonyms
helptext: brief description of the argument
type: type of the argument
metaname: Name to display for value in help, inferred if not
required: True if argument must be specified
default: Default value if not specified
positional: Argument specified by location, not name
Raises:
ValueError: the argument already exists or is invalid
Returns:
The newly-created argument
"""
if IsString(names): names = [names]
names = [name.lower() for name in names]
for name in names:
if name in self.arg_dict:
raise ValueError("%s is already an argument"%name)
if (positional and required and
[arg for arg in self.args if arg.positional] and
not [arg for arg in self.args if arg.positional][-1].required):
raise ValueError(
"A required positional argument may not follow an optional one.")
arg = Command.Argument(names, helptext, type, metaname,
required, default, positional)
self.args.append(arg)
for name in names:
self.arg_dict[name] = arg
return arg | [
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|
FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftobjects/draftlink.py | python | DraftLink.canLinkProperties | (self, _obj) | return False | Link properties.
TODO: add more explanation. Overrides a C++ method? | Link properties. | [
"Link",
"properties",
"."
] | def canLinkProperties(self, _obj):
"""Link properties.
TODO: add more explanation. Overrides a C++ method?
"""
return False | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/setuptools/_vendor/ordered_set.py | python | OrderedSet.__reversed__ | (self) | return reversed(self.items) | Example:
>>> list(reversed(OrderedSet([1, 2, 3])))
[3, 2, 1] | Example:
>>> list(reversed(OrderedSet([1, 2, 3])))
[3, 2, 1] | [
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|
javafxports/openjdk-jfx | 6eabc8c84f698c04548395826a8bb738087666b5 | modules/javafx.web/src/main/native/Source/JavaScriptCore/disassembler/udis86/ud_opcode.py | python | UdOpcodeTables.walk | (self, tbl, opcodes) | return e | Walk down the opcode trie, starting at a given opcode
table, given a string of opcodes. Return None if unable
to walk, the object at the leaf otherwise. | Walk down the opcode trie, starting at a given opcode
table, given a string of opcodes. Return None if unable
to walk, the object at the leaf otherwise. | [
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"""Walk down the opcode trie, starting at a given opcode
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"""
opc = opcodes[0]
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/stc.py | python | StyledTextCtrl.AutoCompComplete | (*args, **kwargs) | return _stc.StyledTextCtrl_AutoCompComplete(*args, **kwargs) | AutoCompComplete(self)
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/pathlib.py | python | Path.touch | (self, mode=0o666, exist_ok=True) | Create this file with the given access mode, if it doesn't exist. | Create this file with the given access mode, if it doesn't exist. | [
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"""
Create this file with the given access mode, if it doesn't exist.
"""
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self._raise_closed()
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# First try to bump modification time
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self._accessor.utime(self, None)
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else:
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flags = os.O_CREAT | os.O_WRONLY
if not exist_ok:
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||
QMCPACK/qmcpack | d0948ab455e38364458740cc8e2239600a14c5cd | utils/afqmctools/afqmctools/utils/qe_driver.py | python | gen_qe_gto | (qe_info,bset,x=[],
fname='pyscf.orbitals.h5',prec=1e-12) | return nao | Writes periodic AO basis set in real space to hdf5 file.
This routine constructs a new gaussian basis set from a OptimizableBasisSet
object and an array of optimizable parameters.
With the resulting basis set, a new gto.Cell object is constructed consistent
with the QE calculation and used to generate the periodic AO basis set.
Parameters
----------
qe_info: Python Dictionary.
Dictionary with information from QE calculation, generated by qe_driver_init.
bset: Object of type OptimizableBasisSet.
Contains information about a (possibly dynamic) basis set.
x: fp array. Default: [] (no variable parameters in bset)
Array with variational parameters in the bset object.
fname: string. Default: 'pyscf.orbitals.h5'
Name of hdf5 file.
prec: floating point number. Default: 1e-12
Precision used to generate AO orbitals in real space. Controls sum over periodic images.
Returns
-------
nao: integer
Number of atomic orbitals generates. | Writes periodic AO basis set in real space to hdf5 file.
This routine constructs a new gaussian basis set from a OptimizableBasisSet
object and an array of optimizable parameters.
With the resulting basis set, a new gto.Cell object is constructed consistent
with the QE calculation and used to generate the periodic AO basis set. | [
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fname='pyscf.orbitals.h5',prec=1e-12):
""" Writes periodic AO basis set in real space to hdf5 file.
This routine constructs a new gaussian basis set from a OptimizableBasisSet
object and an array of optimizable parameters.
With the resulting basis set, a new gto.Cell object is constructed consistent
with the QE calculation and used to generate the periodic AO basis set.
Parameters
----------
qe_info: Python Dictionary.
Dictionary with information from QE calculation, generated by qe_driver_init.
bset: Object of type OptimizableBasisSet.
Contains information about a (possibly dynamic) basis set.
x: fp array. Default: [] (no variable parameters in bset)
Array with variational parameters in the bset object.
fname: string. Default: 'pyscf.orbitals.h5'
Name of hdf5 file.
prec: floating point number. Default: 1e-12
Precision used to generate AO orbitals in real space. Controls sum over periodic images.
Returns
-------
nao: integer
Number of atomic orbitals generates.
"""
assert(len(x) == bset.number_of_params)
basis = {}
for I, atm in enumerate(qe_info['species']):
basis.update({atm: molgto.parse( bset.basis_str(atm,x) )})
cell = make_cell(qe_info['latt'],
qe_info['species'],
qe_info['at_id'],
qe_info['at_pos'],
basis_=basis,
mesh=qe_info['mesh'],prec=prec)
nao = cell.nao_nr()
write_esh5_orbitals(cell, qe_info['outdir']+fname, kpts=qe_info['kpts'])
return nao | [
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|
facebookincubator/katran | 192eb988c398afc673620254097defb7035d669e | build/fbcode_builder/getdeps/copytree.py | python | copytree | (src_dir, dest_dir, ignore=None) | return shutil.copytree(src_dir, dest_dir, ignore=ignore) | Recursively copy the src_dir to the dest_dir, filtering
out entries using the ignore lambda. The behavior of the
ignore lambda must match that described by `shutil.copytree`.
This `copytree` function knows how to prefetch data when
running in an eden repo.
TODO: I'd like to either extend this or add a variant that
uses watchman to mirror src_dir into dest_dir. | Recursively copy the src_dir to the dest_dir, filtering
out entries using the ignore lambda. The behavior of the
ignore lambda must match that described by `shutil.copytree`.
This `copytree` function knows how to prefetch data when
running in an eden repo.
TODO: I'd like to either extend this or add a variant that
uses watchman to mirror src_dir into dest_dir. | [
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"""Recursively copy the src_dir to the dest_dir, filtering
out entries using the ignore lambda. The behavior of the
ignore lambda must match that described by `shutil.copytree`.
This `copytree` function knows how to prefetch data when
running in an eden repo.
TODO: I'd like to either extend this or add a variant that
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"""
prefetch_dir_if_eden(src_dir)
return shutil.copytree(src_dir, dest_dir, ignore=ignore) | [
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|
hfinkel/llvm-project-cxxjit | 91084ef018240bbb8e24235ff5cd8c355a9c1a1e | lldb/third_party/Python/module/pexpect-2.4/pxssh.py | python | pxssh.login | (
self,
server,
username,
password='',
terminal_type='ansi',
original_prompt=r"[#$]",
login_timeout=10,
port=None,
auto_prompt_reset=True) | return True | This logs the user into the given server. It uses the
'original_prompt' to try to find the prompt right after login. When it
finds the prompt it immediately tries to reset the prompt to something
more easily matched. The default 'original_prompt' is very optimistic
and is easily fooled. It's more reliable to try to match the original
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strings such as the "Message Of The Day". On many systems you can
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then this will not necessarily cause the login to fail. In the case of
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prompt was so weird that we could not match it, so we use a few tricks
to guess when we have reached the prompt. Then we hope for the best and
blindly try to reset the prompt to something more unique. If that fails
then login() raises an ExceptionPxssh exception.
In some situations it is not possible or desirable to reset the
original prompt. In this case, set 'auto_prompt_reset' to False to
inhibit setting the prompt to the UNIQUE_PROMPT. Remember that pxssh
uses a unique prompt in the prompt() method. If the original prompt is
not reset then this will disable the prompt() method unless you
manually set the PROMPT attribute. | This logs the user into the given server. It uses the
'original_prompt' to try to find the prompt right after login. When it
finds the prompt it immediately tries to reset the prompt to something
more easily matched. The default 'original_prompt' is very optimistic
and is easily fooled. It's more reliable to try to match the original
prompt as exactly as possible to prevent false matches by server
strings such as the "Message Of The Day". On many systems you can
disable the MOTD on the remote server by creating a zero-length file
called "~/.hushlogin" on the remote server. If a prompt cannot be found
then this will not necessarily cause the login to fail. In the case of
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blindly try to reset the prompt to something more unique. If that fails
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"have",
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] | def login(
self,
server,
username,
password='',
terminal_type='ansi',
original_prompt=r"[#$]",
login_timeout=10,
port=None,
auto_prompt_reset=True):
"""This logs the user into the given server. It uses the
'original_prompt' to try to find the prompt right after login. When it
finds the prompt it immediately tries to reset the prompt to something
more easily matched. The default 'original_prompt' is very optimistic
and is easily fooled. It's more reliable to try to match the original
prompt as exactly as possible to prevent false matches by server
strings such as the "Message Of The Day". On many systems you can
disable the MOTD on the remote server by creating a zero-length file
called "~/.hushlogin" on the remote server. If a prompt cannot be found
then this will not necessarily cause the login to fail. In the case of
a timeout when looking for the prompt we assume that the original
prompt was so weird that we could not match it, so we use a few tricks
to guess when we have reached the prompt. Then we hope for the best and
blindly try to reset the prompt to something more unique. If that fails
then login() raises an ExceptionPxssh exception.
In some situations it is not possible or desirable to reset the
original prompt. In this case, set 'auto_prompt_reset' to False to
inhibit setting the prompt to the UNIQUE_PROMPT. Remember that pxssh
uses a unique prompt in the prompt() method. If the original prompt is
not reset then this will disable the prompt() method unless you
manually set the PROMPT attribute. """
ssh_options = '-q'
if self.force_password:
ssh_options = ssh_options + ' ' + self.SSH_OPTS
if port is not None:
ssh_options = ssh_options + ' -p %s' % (str(port))
cmd = "ssh %s -l %s %s" % (ssh_options, username, server)
# This does not distinguish between a remote server 'password' prompt
# and a local ssh 'passphrase' prompt (for unlocking a private key).
spawn._spawn(self, cmd)
i = self.expect(
[
"(?i)are you sure you want to continue connecting",
original_prompt,
"(?i)(?:password)|(?:passphrase for key)",
"(?i)permission denied",
"(?i)terminal type",
TIMEOUT,
"(?i)connection closed by remote host"],
timeout=login_timeout)
# First phase
if i == 0:
# New certificate -- always accept it.
# This is what you get if SSH does not have the remote host's
# public key stored in the 'known_hosts' cache.
self.sendline("yes")
i = self.expect(
[
"(?i)are you sure you want to continue connecting",
original_prompt,
"(?i)(?:password)|(?:passphrase for key)",
"(?i)permission denied",
"(?i)terminal type",
TIMEOUT])
if i == 2: # password or passphrase
self.sendline(password)
i = self.expect(
[
"(?i)are you sure you want to continue connecting",
original_prompt,
"(?i)(?:password)|(?:passphrase for key)",
"(?i)permission denied",
"(?i)terminal type",
TIMEOUT])
if i == 4:
self.sendline(terminal_type)
i = self.expect(
[
"(?i)are you sure you want to continue connecting",
original_prompt,
"(?i)(?:password)|(?:passphrase for key)",
"(?i)permission denied",
"(?i)terminal type",
TIMEOUT])
# Second phase
if i == 0:
# This is weird. This should not happen twice in a row.
self.close()
raise ExceptionPxssh(
'Weird error. Got "are you sure" prompt twice.')
elif i == 1: # can occur if you have a public key pair set to authenticate.
# TODO: May NOT be OK if expect() got tricked and matched a false
# prompt.
pass
elif i == 2: # password prompt again
# For incorrect passwords, some ssh servers will
# ask for the password again, others return 'denied' right away.
# If we get the password prompt again then this means
# we didn't get the password right the first time.
self.close()
raise ExceptionPxssh('password refused')
elif i == 3: # permission denied -- password was bad.
self.close()
raise ExceptionPxssh('permission denied')
elif i == 4: # terminal type again? WTF?
self.close()
raise ExceptionPxssh(
'Weird error. Got "terminal type" prompt twice.')
elif i == 5: # Timeout
# This is tricky... I presume that we are at the command-line prompt.
# It may be that the shell prompt was so weird that we couldn't match
# it. Or it may be that we couldn't log in for some other reason. I
# can't be sure, but it's safe to guess that we did login because if
# I presume wrong and we are not logged in then this should be caught
# later when I try to set the shell prompt.
pass
elif i == 6: # Connection closed by remote host
self.close()
raise ExceptionPxssh('connection closed')
else: # Unexpected
self.close()
raise ExceptionPxssh('unexpected login response')
if not self.sync_original_prompt():
self.close()
raise ExceptionPxssh('could not synchronize with original prompt')
# We appear to be in.
# set shell prompt to something unique.
if auto_prompt_reset:
if not self.set_unique_prompt():
self.close()
raise ExceptionPxssh(
'could not set shell prompt\n' + self.before)
return True | [
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] | https://github.com/hfinkel/llvm-project-cxxjit/blob/91084ef018240bbb8e24235ff5cd8c355a9c1a1e/lldb/third_party/Python/module/pexpect-2.4/pxssh.py#L178-L315 |
|
plaidml/plaidml | f3c6681db21460e5fdc11ae651d6d7b6c27f8262 | cmake/git-clang-format.py | python | extract_lines | (patch_file) | return matches | Extract the changed lines in `patch_file`.
The return value is a dictionary mapping filename to a list of (start_line,
line_count) pairs.
The input must have been produced with ``-U0``, meaning unidiff format with
zero lines of context. The return value is a dict mapping filename to a
list of line `Range`s. | Extract the changed lines in `patch_file`. | [
"Extract",
"the",
"changed",
"lines",
"in",
"patch_file",
"."
] | def extract_lines(patch_file):
"""Extract the changed lines in `patch_file`.
The return value is a dictionary mapping filename to a list of (start_line,
line_count) pairs.
The input must have been produced with ``-U0``, meaning unidiff format with
zero lines of context. The return value is a dict mapping filename to a
list of line `Range`s."""
matches = {}
for line in patch_file:
line = convert_string(line)
match = re.search(r'^\+\+\+\ [^/]+/(.*)', line)
if match:
filename = match.group(1).rstrip('\r\n')
match = re.search(r'^@@ -[0-9,]+ \+(\d+)(,(\d+))?', line)
if match:
start_line = int(match.group(1))
line_count = 1
if match.group(3):
line_count = int(match.group(3))
if line_count > 0:
matches.setdefault(filename, []).append(Range(start_line, line_count))
return matches | [
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|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/google_appengine_cloudstorage/cloudstorage/cloudstorage_api.py | python | _Bucket._next_file_gen | (self, root) | Generator for next file element in the document.
Args:
root: root element of the XML tree.
Yields:
GCSFileStat for the next file. | Generator for next file element in the document. | [
"Generator",
"for",
"next",
"file",
"element",
"in",
"the",
"document",
"."
] | def _next_file_gen(self, root):
"""Generator for next file element in the document.
Args:
root: root element of the XML tree.
Yields:
GCSFileStat for the next file.
"""
for e in root.getiterator(common._T_CONTENTS):
st_ctime, size, etag, key = None, None, None, None
for child in e.getiterator('*'):
if child.tag == common._T_LAST_MODIFIED:
st_ctime = common.dt_str_to_posix(child.text)
elif child.tag == common._T_ETAG:
etag = child.text
elif child.tag == common._T_SIZE:
size = child.text
elif child.tag == common._T_KEY:
key = child.text
yield common.GCSFileStat(self._path + '/' + key,
size, etag, st_ctime)
e.clear()
yield None | [
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||
hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/layers/python/layers/layers.py | python | fully_connected | (inputs,
num_outputs,
activation_fn=nn.relu,
normalizer_fn=None,
normalizer_params=None,
weights_initializer=initializers.xavier_initializer(),
weights_regularizer=None,
biases_initializer=init_ops.zeros_initializer,
biases_regularizer=None,
reuse=None,
variables_collections=None,
outputs_collections=None,
trainable=True,
scope=None) | Adds a fully connected layer.
`fully_connected` creates a variable called `weights`, representing a fully
connected weight matrix, which is multiplied by the `inputs` to produce a
`Tensor` of hidden units. If a `normalizer_fn` is provided (such as
`batch_norm`), it is then applied. Otherwise, if `normalizer_fn` is
None and a `biases_initializer` is provided then a `biases` variable would be
created and added the hidden units. Finally, if `activation_fn` is not `None`,
it is applied to the hidden units as well.
Note: that if `inputs` have a rank greater than 2, then `inputs` is flattened
prior to the initial matrix multiply by `weights`.
Args:
inputs: A tensor of with at least rank 2 and value for the last dimension,
i.e. `[batch_size, depth]`, `[None, None, None, channels]`.
num_outputs: Integer or long, the number of output units in the layer.
activation_fn: activation function, set to None to skip it and maintain
a linear activation.
normalizer_fn: normalization function to use instead of `biases`. If
`normalizer_fn` is provided then `biases_initializer` and
`biases_regularizer` are ignored and `biases` are not created nor added.
default set to None for no normalizer function
normalizer_params: normalization function parameters.
weights_initializer: An initializer for the weights.
weights_regularizer: Optional regularizer for the weights.
biases_initializer: An initializer for the biases. If None skip biases.
biases_regularizer: Optional regularizer for the biases.
reuse: whether or not the layer and its variables should be reused. To be
able to reuse the layer scope must be given.
variables_collections: Optional list of collections for all the variables or
a dictionary containing a different list of collections per variable.
outputs_collections: collection to add the outputs.
trainable: If `True` also add variables to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable).
scope: Optional scope for variable_scope.
Returns:
the tensor variable representing the result of the series of operations.
Raises:
ValueError: if x has rank less than 2 or if its last dimension is not set. | Adds a fully connected layer. | [
"Adds",
"a",
"fully",
"connected",
"layer",
"."
] | def fully_connected(inputs,
num_outputs,
activation_fn=nn.relu,
normalizer_fn=None,
normalizer_params=None,
weights_initializer=initializers.xavier_initializer(),
weights_regularizer=None,
biases_initializer=init_ops.zeros_initializer,
biases_regularizer=None,
reuse=None,
variables_collections=None,
outputs_collections=None,
trainable=True,
scope=None):
"""Adds a fully connected layer.
`fully_connected` creates a variable called `weights`, representing a fully
connected weight matrix, which is multiplied by the `inputs` to produce a
`Tensor` of hidden units. If a `normalizer_fn` is provided (such as
`batch_norm`), it is then applied. Otherwise, if `normalizer_fn` is
None and a `biases_initializer` is provided then a `biases` variable would be
created and added the hidden units. Finally, if `activation_fn` is not `None`,
it is applied to the hidden units as well.
Note: that if `inputs` have a rank greater than 2, then `inputs` is flattened
prior to the initial matrix multiply by `weights`.
Args:
inputs: A tensor of with at least rank 2 and value for the last dimension,
i.e. `[batch_size, depth]`, `[None, None, None, channels]`.
num_outputs: Integer or long, the number of output units in the layer.
activation_fn: activation function, set to None to skip it and maintain
a linear activation.
normalizer_fn: normalization function to use instead of `biases`. If
`normalizer_fn` is provided then `biases_initializer` and
`biases_regularizer` are ignored and `biases` are not created nor added.
default set to None for no normalizer function
normalizer_params: normalization function parameters.
weights_initializer: An initializer for the weights.
weights_regularizer: Optional regularizer for the weights.
biases_initializer: An initializer for the biases. If None skip biases.
biases_regularizer: Optional regularizer for the biases.
reuse: whether or not the layer and its variables should be reused. To be
able to reuse the layer scope must be given.
variables_collections: Optional list of collections for all the variables or
a dictionary containing a different list of collections per variable.
outputs_collections: collection to add the outputs.
trainable: If `True` also add variables to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable).
scope: Optional scope for variable_scope.
Returns:
the tensor variable representing the result of the series of operations.
Raises:
ValueError: if x has rank less than 2 or if its last dimension is not set.
"""
if not (isinstance(num_outputs, int) or isinstance(num_outputs, long)):
raise ValueError('num_outputs should be int or long, got %s.', num_outputs)
with variable_scope.variable_scope(scope, 'fully_connected', [inputs],
reuse=reuse) as sc:
inputs = ops.convert_to_tensor(inputs)
dtype = inputs.dtype.base_dtype
inputs_shape = inputs.get_shape()
num_input_units = utils.last_dimension(inputs_shape, min_rank=2)
static_shape = inputs_shape.as_list()
static_shape[-1] = num_outputs
out_shape = array_ops.unpack(array_ops.shape(inputs))
out_shape[-1] = num_outputs
weights_shape = [num_input_units, num_outputs]
weights_collections = utils.get_variable_collections(
variables_collections, 'weights')
weights = variables.model_variable('weights',
shape=weights_shape,
dtype=dtype,
initializer=weights_initializer,
regularizer=weights_regularizer,
collections=weights_collections,
trainable=trainable)
if len(static_shape) > 2:
# Reshape inputs
inputs = array_ops.reshape(inputs, [-1, num_input_units])
outputs = standard_ops.matmul(inputs, weights)
if normalizer_fn is not None:
normalizer_params = normalizer_params or {}
outputs = normalizer_fn(outputs, **normalizer_params)
else:
if biases_initializer is not None:
biases_collections = utils.get_variable_collections(
variables_collections, 'biases')
biases = variables.model_variable('biases',
shape=[num_outputs,],
dtype=dtype,
initializer=biases_initializer,
regularizer=biases_regularizer,
collections=biases_collections,
trainable=trainable)
outputs = nn.bias_add(outputs, biases)
if activation_fn is not None:
outputs = activation_fn(outputs)
if len(static_shape) > 2:
# Reshape back outputs
outputs = array_ops.reshape(outputs, array_ops.pack(out_shape))
outputs.set_shape(static_shape)
return utils.collect_named_outputs(outputs_collections,
sc.original_name_scope, outputs) | [
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||
y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/buildscripts/linter/git.py | python | get_files_to_check_from_patch | (patches, filter_function) | return valid_files | Take a patch file generated by git diff, and scan the patch for a list of files to check. | Take a patch file generated by git diff, and scan the patch for a list of files to check. | [
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] | def get_files_to_check_from_patch(patches, filter_function):
# type: (List[str], Callable[[str], bool]) -> List[str]
"""Take a patch file generated by git diff, and scan the patch for a list of files to check."""
candidates = [] # type: List[str]
# Get a list of candidate_files
check = re.compile(r"^diff --git a\/([\w\/\.\-]+) b\/[\w\/\.\-]+")
lines = [] # type: List[str]
for patch in patches:
with open(patch, "rb") as infile:
lines += infile.readlines()
candidates = [check.match(line).group(1) for line in lines if check.match(line)]
repos = get_repos()
valid_files = list(
itertools.chain.from_iterable(
[r.get_candidates(candidates, filter_function) for r in repos]))
return valid_files | [
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|
nasa/astrobee | 9241e67e6692810d6e275abb3165b6d02f4ca5ef | scripts/git/cpplint.py | python | _FunctionState.End | (self) | Stop analyzing function body. | Stop analyzing function body. | [
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] | def End(self):
"""Stop analyzing function body."""
self.in_a_function = False | [
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||
google-ar/WebARonTango | e86965d2cbc652156b480e0fcf77c716745578cd | chromium/src/gpu/command_buffer/build_gles2_cmd_buffer.py | python | Function.WriteGLES2ImplementationHeader | (self, f) | Writes the GLES2 Implemention declaration. | Writes the GLES2 Implemention declaration. | [
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] | def WriteGLES2ImplementationHeader(self, f):
"""Writes the GLES2 Implemention declaration."""
self.type_handler.WriteGLES2ImplementationHeader(self, f) | [
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||
KhronosGroup/SPIR | f33c27876d9f3d5810162b60fa89cc13d2b55725 | bindings/python/clang/cindex.py | python | SourceLocation.offset | (self) | return self._get_instantiation()[3] | Get the file offset represented by this source location. | Get the file offset represented by this source location. | [
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|
google/syzygy | 8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5 | third_party/numpy/files/numpy/numarray/session.py | python | _callers_modules | () | return mods | returns a list containing the names of all the modules in the caller's
global namespace. | returns a list containing the names of all the modules in the caller's
global namespace. | [
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] | def _callers_modules():
"""returns a list containing the names of all the modules in the caller's
global namespace."""
g = _callers_globals()
mods = []
for k,v in g.items():
if type(v) == type(sys):
mods.append(getattr(v,"__name__"))
return mods | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/reduce4circleGUI.py | python | MainWindow.do_sync_ub | (self) | Purpose: synchronize UB matrix in use with UB matrix calculated.
Requirements: One of these must be given
1. a valid UB matrix from tableWidget_ubMatrix
2. an ascii file that contains 9 float
3. from text edit
:return: | Purpose: synchronize UB matrix in use with UB matrix calculated.
Requirements: One of these must be given
1. a valid UB matrix from tableWidget_ubMatrix
2. an ascii file that contains 9 float
3. from text edit
:return: | [
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""" Purpose: synchronize UB matrix in use with UB matrix calculated.
Requirements: One of these must be given
1. a valid UB matrix from tableWidget_ubMatrix
2. an ascii file that contains 9 float
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"""
# get the radio button that is checked
if self.ui.radioButton_ubFromTab1.isChecked():
# get ub matrix from tab 'Calculate UB Matrix'
ub_matrix = self.ui.tableWidget_ubMatrix.get_matrix()
# elif self.ui.radioButton_loadUBmatrix.isChecked():
# # load ub matrix from a file
# ISSUE 001 VZ-FUTURE: Implement this next!
# raise NotImplementedError('This tab is not implemented, because the file format has not been decided.')
elif self.ui.radioButton_ubFromList.isChecked():
# load ub matrix from text editor
ub_matrix = self.get_ub_from_text()
else:
raise RuntimeError('None radio button is selected for UB')
# set to in-use UB matrix and control
self.ui.tableWidget_ubInUse.set_from_matrix(ub_matrix)
exp_no = int(str(self.ui.lineEdit_exp.text()))
self._myControl.set_ub_matrix(exp_number=exp_no, ub_matrix=ub_matrix) | [
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nnrg/opennero | 43e12a1bcba6e228639db3886fec1dc47ddc24cb | mods/NERO/agent.py | python | NEATAgent.__init__ | (self, team_type, *args) | Create an agent brain | Create an agent brain | [
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] | def __init__(self, team_type, *args):
"""
Create an agent brain
"""
# this line is crucial, otherwise the class is not recognized as an
# AgentBrainPtr by C++
OpenNero.AgentBrain.__init__(self)
NeroAgent.__init__(self, team_type)
self.omit_friend_sensors = False
if len(args) > 0:
stream = io.BytesIO(string.join(args, '\n').encode('utf-8'))
self.org = OpenNero.Organism(stream)
else:
NEATAgent.count += 1
genome = self.base_genome.clone(NEATAgent.count, 1)
self.org = OpenNero.Organism(0, genome, 1) | [
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||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib2to3/pytree.py | python | WildcardPattern.generate_matches | (self, nodes) | Generator yielding matches for a sequence of nodes.
Args:
nodes: sequence of nodes
Yields:
(count, results) tuples where:
count: the match comprises nodes[:count];
results: dict containing named submatches. | Generator yielding matches for a sequence of nodes. | [
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] | def generate_matches(self, nodes):
"""
Generator yielding matches for a sequence of nodes.
Args:
nodes: sequence of nodes
Yields:
(count, results) tuples where:
count: the match comprises nodes[:count];
results: dict containing named submatches.
"""
if self.content is None:
# Shortcut for special case (see __init__.__doc__)
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apache/kudu | 90895ce76590f10730ad7aac3613b69d89ff5422 | src/kudu/scripts/parse_metrics_log.py | python | cache_hit_ratio | (aggregated_prev, aggregated_cur) | return cache_ratio | Calculate the cache hit ratio between the two samples.
If there were no cache hits or misses, this returns NaN. | Calculate the cache hit ratio between the two samples.
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delta_hits = delta(aggregated_prev, aggregated_cur, 'server.block_cache_hits_caching')
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_internal/network/download.py | python | sanitize_content_filename | (filename) | return os.path.basename(filename) | Sanitize the "filename" value from a Content-Disposition header. | Sanitize the "filename" value from a Content-Disposition header. | [
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# type: (str) -> str
"""
Sanitize the "filename" value from a Content-Disposition header.
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextPrintout.GetRichTextBuffer | (*args, **kwargs) | return _richtext.RichTextPrintout_GetRichTextBuffer(*args, **kwargs) | GetRichTextBuffer(self) -> RichTextBuffer | GetRichTextBuffer(self) -> RichTextBuffer | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/variables.py | python | RefVariable.scatter_max | (self, sparse_delta, use_locking=False, name=None) | return gen_state_ops.scatter_max(
self._variable,
sparse_delta.indices,
sparse_delta.values,
use_locking=use_locking,
name=name) | Updates this variable with the max of `tf.IndexedSlices` and itself.
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use_locking: If `True`, use locking during the operation.
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A `Tensor` that will hold the new value of this variable after
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Raises:
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"""Updates this variable with the max of `tf.IndexedSlices` and itself.
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"""
if not isinstance(sparse_delta, indexed_slices.IndexedSlices):
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return gen_state_ops.scatter_max(
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/dataset/engine/validators.py | python | check_celebadataset | (method) | return new_method | A wrapper that wraps a parameter checker around the original Dataset(CelebADataset). | A wrapper that wraps a parameter checker around the original Dataset(CelebADataset). | [
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"""A wrapper that wraps a parameter checker around the original Dataset(CelebADataset)."""
@wraps(method)
def new_method(self, *args, **kwargs):
_, param_dict = parse_user_args(method, *args, **kwargs)
nreq_param_int = ['num_samples', 'num_parallel_workers', 'num_shards', 'shard_id']
nreq_param_bool = ['shuffle', 'decode']
nreq_param_list = ['extensions']
nreq_param_str = ['dataset_type']
dataset_dir = param_dict.get('dataset_dir')
check_dir(dataset_dir)
validate_dataset_param_value(nreq_param_int, param_dict, int)
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usage = param_dict.get('usage')
if usage is not None and usage not in ('all', 'train', 'valid', 'test'):
raise ValueError("usage should be 'all', 'train', 'valid' or 'test'.")
check_sampler_shuffle_shard_options(param_dict)
sampler = param_dict.get('sampler')
if sampler is not None and isinstance(sampler, samplers.PKSampler):
raise ValueError("CelebADataset doesn't support PKSampler.")
cache = param_dict.get('cache')
check_cache_option(cache)
return method(self, *args, **kwargs)
return new_method | [
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|
telefonicaid/fiware-orion | 27c3202b9ddcfb9e3635a0af8d373f76e89b1d24 | scripts/cpplint.py | python | GetPreviousNonBlankLine | (clean_lines, linenum) | return ('', -1) | Return the most recent non-blank line and its line number.
Args:
clean_lines: A CleansedLines instance containing the file contents.
linenum: The number of the line to check.
Returns:
A tuple with two elements. The first element is the contents of the last
non-blank line before the current line, or the empty string if this is the
first non-blank line. The second is the line number of that line, or -1
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"""Return the most recent non-blank line and its line number.
Args:
clean_lines: A CleansedLines instance containing the file contents.
linenum: The number of the line to check.
Returns:
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bundy-dns/bundy | 3d41934996b82b0cd2fe22dd74d2abc1daba835d | src/lib/python/bundy/bundy/component.py | python | BaseComponent.set_restart_time | (self) | Calculates and sets the time this component should be restarted.
Currently, it uses a very basic algorithm; start time +
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Currently, it uses a very basic algorithm; start time +
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self._restart_at = self.__start_time + COMPONENT_RESTART_DELAY | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/distutils/text_file.py | python | TextFile.unreadline | (self, line) | Push 'line' (a string) onto an internal buffer that will be
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/interpolate/interpolate.py | python | _do_extrapolate | (fill_value) | return (isinstance(fill_value, string_types) and
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|
shedskin/shedskin | ae88dbca7b1d9671cd8be448cb0b497122758936 | examples/block.py | python | findprobs | (f=0.01,N=6) | return answer | Find probabilities of all the events
000000
000001
...
111111
<-N ->
>>> print findprobs(0.1,3) # doctest:+ELLIPSIS
[('000', 0.7...),..., ('111', 0.001...)] | Find probabilities of all the events
000000
000001
...
111111
<-N ->
>>> print findprobs(0.1,3) # doctest:+ELLIPSIS
[('000', 0.7...),..., ('111', 0.001...)] | [
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""" Find probabilities of all the events
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...
111111
<-N ->
>>> print findprobs(0.1,3) # doctest:+ELLIPSIS
[('000', 0.7...),..., ('111', 0.001...)]
"""
answer = []
for n in range(2**N):
s = dec_to_bin(n,N)
(w0,w1) = weight(s)
if verbose and 0 :
print s,w0,w1
answer.append( (s, f**w1 * (1-f)**w0 ) )
pass
assert ( len(answer) == 2**N )
return answer | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/_vendor/ordered_set.py | python | OrderedSet.union | (self, *sets) | return cls(items) | Combines all unique items.
Each items order is defined by its first appearance.
Example:
>>> oset = OrderedSet.union(OrderedSet([3, 1, 4, 1, 5]), [1, 3], [2, 0])
>>> print(oset)
OrderedSet([3, 1, 4, 5, 2, 0])
>>> oset.union([8, 9])
OrderedSet([3, 1, 4, 5, 2, 0, 8, 9])
>>> oset | {10}
OrderedSet([3, 1, 4, 5, 2, 0, 10]) | Combines all unique items.
Each items order is defined by its first appearance. | [
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>>> print(oset)
OrderedSet([3, 1, 4, 5, 2, 0])
>>> oset.union([8, 9])
OrderedSet([3, 1, 4, 5, 2, 0, 8, 9])
>>> oset | {10}
OrderedSet([3, 1, 4, 5, 2, 0, 10])
"""
cls = self.__class__ if isinstance(self, OrderedSet) else OrderedSet
containers = map(list, it.chain([self], sets))
items = it.chain.from_iterable(containers)
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|
trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/seacas/scripts/exomerge2.py | python | ExodusModel.get_side_set_ids | (self) | return sorted(self.side_sets.keys()) | Return a list of all side set ids.
Example:
>>> model.get_side_set_ids() | Return a list of all side set ids. | [
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Return a list of all side set ids.
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"""
return sorted(self.side_sets.keys()) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/http/server.py | python | BaseHTTPRequestHandler.handle_one_request | (self) | Handle a single HTTP request.
You normally don't need to override this method; see the class
__doc__ string for information on how to handle specific HTTP
commands such as GET and POST. | Handle a single HTTP request. | [
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] | def handle_one_request(self):
"""Handle a single HTTP request.
You normally don't need to override this method; see the class
__doc__ string for information on how to handle specific HTTP
commands such as GET and POST.
"""
try:
self.raw_requestline = self.rfile.readline(65537)
if len(self.raw_requestline) > 65536:
self.requestline = ''
self.request_version = ''
self.command = ''
self.send_error(HTTPStatus.REQUEST_URI_TOO_LONG)
return
if not self.raw_requestline:
self.close_connection = True
return
if not self.parse_request():
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return
mname = 'do_' + self.command
if not hasattr(self, mname):
self.send_error(
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return
method = getattr(self, mname)
method()
self.wfile.flush() #actually send the response if not already done.
except socket.timeout as e:
#a read or a write timed out. Discard this connection
self.log_error("Request timed out: %r", e)
self.close_connection = True
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||
psi4/psi4 | be533f7f426b6ccc263904e55122899b16663395 | psi4/driver/qcdb/dbwrap.py | python | Database.compute_statistics | (self, modelchem, benchmark='default', sset='default',
failoninc=True, verbose=False, returnindiv=False) | Computes summary statistics and, if *returnindiv* True,
individual errors for single model chemistry *modelchem* versus
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Particularly, imposes cross-database definitions for sset and
modelchem.
#Returns error if model chemistries are missing
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Particularly, imposes cross-database definitions for sset and
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#Returns error if model chemistries are missing
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#whereupon returns partial statistics. Returns dictionary of
#statistics labels and values. | [
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failoninc=True, verbose=False, returnindiv=False):
"""Computes summary statistics and, if *returnindiv* True,
individual errors for single model chemistry *modelchem* versus
*benchmark* over subset *sset* over all component databases.
Particularly, imposes cross-database definitions for sset and
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#Returns error if model chemistries are missing
#for any reaction in subset unless *failoninc* set to False,
#whereupon returns partial statistics. Returns dictionary of
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"""
errors = OrderedDict()
indiv = OrderedDict()
actvdb = []
for db, odb in self.dbdict.items():
dbix = self.dbdict.keys().index(db)
if self.sset[sset][dbix] is None:
errors[db], indiv[db] = (None, None)
else:
errors[db], indiv[db] = odb.compute_statistics(self.mcs[modelchem][dbix],
sset=self.sset[sset][dbix],
benchmark='ZEROS' if benchmark == 'ZEROS' else self.mcs[benchmark][dbix],
failoninc=failoninc, verbose=verbose, returnindiv=True)
actvdb.append(errors[db])
errors[self.dbse] = average_errors(*actvdb)
if returnindiv:
return errors, indiv
else:
return errors | [
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||
Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBStream.write | (self, *args) | return _lldb.SBStream_write(self, *args) | write(self, str str) | write(self, str str) | [
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] | def write(self, *args):
"""write(self, str str)"""
return _lldb.SBStream_write(self, *args) | [
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|
hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/contrib/onnx/mx2onnx/_op_translations.py | python | convert_concat | (node, **kwargs) | return [concat_node] | Map MXNet's Concat operator attributes to onnx's Concat operator
and return the created node. | Map MXNet's Concat operator attributes to onnx's Concat operator
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] | def convert_concat(node, **kwargs):
"""Map MXNet's Concat operator attributes to onnx's Concat operator
and return the created node.
"""
name, input_nodes, attrs = get_inputs(node, kwargs)
axis = int(attrs.get("dim", 1))
concat_node = onnx.helper.make_node(
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return [concat_node] | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/platform.py | python | version | () | return uname().version | Returns the system's release version, e.g. '#3 on degas'
An empty string is returned if the value cannot be determined. | Returns the system's release version, e.g. '#3 on degas' | [
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""" Returns the system's release version, e.g. '#3 on degas'
An empty string is returned if the value cannot be determined.
"""
return uname().version | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/logging/__init__.py | python | _StderrHandler.__init__ | (self, level=NOTSET) | Initialize the handler. | Initialize the handler. | [
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] | def __init__(self, level=NOTSET):
"""
Initialize the handler.
"""
Handler.__init__(self, level) | [
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||
modm-io/modm | 845840ec08566a3aa9c04167b1a18a56255afa4f | tools/xpcc_generator/builder/generate_include_graph.py | python | IncludePathBuilder.find_includes | (self, file, include_path) | return files | Find include directives in an XML file | Find include directives in an XML file | [
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] | def find_includes(self, file, include_path):
""" Find include directives in an XML file """
includeExpression = re.compile(r'<include>(\S+)</include>', re.M)
files = []
line_count = 0
for line in open(file).readlines():
line_count = line_count + 1
match = includeExpression.search(line)
if match:
try:
filename = Parser.find_include_file(
match.group(1),
os.path.abspath(file),
self.include_paths,
str(line_count))
except ParserException as e:
raise builder_base.BuilderException(e.message)
files.append(filename)
return files | [
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] | https://github.com/modm-io/modm/blob/845840ec08566a3aa9c04167b1a18a56255afa4f/tools/xpcc_generator/builder/generate_include_graph.py#L89-L108 |
Subsets and Splits