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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib2to3/refactor.py | python | RefactoringTool.traverse_by | (self, fixers, traversal) | Traverse an AST, applying a set of fixers to each node.
This is a helper method for refactor_tree().
Args:
fixers: a list of fixer instances.
traversal: a generator that yields AST nodes.
Returns:
None | Traverse an AST, applying a set of fixers to each node. | [
"Traverse",
"an",
"AST",
"applying",
"a",
"set",
"of",
"fixers",
"to",
"each",
"node",
"."
] | def traverse_by(self, fixers, traversal):
"""Traverse an AST, applying a set of fixers to each node.
This is a helper method for refactor_tree().
Args:
fixers: a list of fixer instances.
traversal: a generator that yields AST nodes.
Returns:
None
"""
if not fixers:
return
for node in traversal:
for fixer in fixers[node.type]:
results = fixer.match(node)
if results:
new = fixer.transform(node, results)
if new is not None:
node.replace(new)
node = new | [
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||
eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/misc/shapeformat.py | python | get_shapefile | (filepath) | return sf | Returns shapefile handler and proj4 parameter string
of shape file with given path. | Returns shapefile handler and proj4 parameter string
of shape file with given path. | [
"Returns",
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"handler",
"and",
"proj4",
"parameter",
"string",
"of",
"shape",
"file",
"with",
"given",
"path",
"."
] | def get_shapefile(filepath):
"""
Returns shapefile handler and proj4 parameter string
of shape file with given path.
"""
parts = os.path.basename(filepath).split('.')
basename = ''
for part in parts[:-1]:
basename += part
dirname = os.path.dirname(filepath)
shapefilepath = os.path.join(dirname, basename)
print 'import_shapefile *%s*' % (shapefilepath), type(str(shapefilepath))
sf = shapefile.Reader(str(shapefilepath))
return sf | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | contrib/gizmos/osx_cocoa/gizmos.py | python | TreeListCtrl.GetFirstChild | (*args, **kwargs) | return _gizmos.TreeListCtrl_GetFirstChild(*args, **kwargs) | GetFirstChild(self, TreeItemId item) -> PyObject | GetFirstChild(self, TreeItemId item) -> PyObject | [
"GetFirstChild",
"(",
"self",
"TreeItemId",
"item",
")",
"-",
">",
"PyObject"
] | def GetFirstChild(*args, **kwargs):
"""GetFirstChild(self, TreeItemId item) -> PyObject"""
return _gizmos.TreeListCtrl_GetFirstChild(*args, **kwargs) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/io/formats/info.py | python | TableBuilderAbstract.display_memory_usage | (self) | return bool(self.info.memory_usage) | Whether to display memory usage. | Whether to display memory usage. | [
"Whether",
"to",
"display",
"memory",
"usage",
"."
] | def display_memory_usage(self) -> bool:
"""Whether to display memory usage."""
return bool(self.info.memory_usage) | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/difflib.py | python | SequenceMatcher.__init__ | (self, isjunk=None, a='', b='', autojunk=True) | Construct a SequenceMatcher.
Optional arg isjunk is None (the default), or a one-argument
function that takes a sequence element and returns true iff the
element is junk. None is equivalent to passing "lambda x: 0", i.e.
no elements are considered to be junk. For example, pass
lambda x: x in " \\t"
if you're comparing lines as sequences of characters, and don't
want to synch up on blanks or hard tabs.
Optional arg a is the first of two sequences to be compared. By
default, an empty string. The elements of a must be hashable. See
also .set_seqs() and .set_seq1().
Optional arg b is the second of two sequences to be compared. By
default, an empty string. The elements of b must be hashable. See
also .set_seqs() and .set_seq2().
Optional arg autojunk should be set to False to disable the
"automatic junk heuristic" that treats popular elements as junk
(see module documentation for more information). | Construct a SequenceMatcher. | [
"Construct",
"a",
"SequenceMatcher",
"."
] | def __init__(self, isjunk=None, a='', b='', autojunk=True):
"""Construct a SequenceMatcher.
Optional arg isjunk is None (the default), or a one-argument
function that takes a sequence element and returns true iff the
element is junk. None is equivalent to passing "lambda x: 0", i.e.
no elements are considered to be junk. For example, pass
lambda x: x in " \\t"
if you're comparing lines as sequences of characters, and don't
want to synch up on blanks or hard tabs.
Optional arg a is the first of two sequences to be compared. By
default, an empty string. The elements of a must be hashable. See
also .set_seqs() and .set_seq1().
Optional arg b is the second of two sequences to be compared. By
default, an empty string. The elements of b must be hashable. See
also .set_seqs() and .set_seq2().
Optional arg autojunk should be set to False to disable the
"automatic junk heuristic" that treats popular elements as junk
(see module documentation for more information).
"""
# Members:
# a
# first sequence
# b
# second sequence; differences are computed as "what do
# we need to do to 'a' to change it into 'b'?"
# b2j
# for x in b, b2j[x] is a list of the indices (into b)
# at which x appears; junk and popular elements do not appear
# fullbcount
# for x in b, fullbcount[x] == the number of times x
# appears in b; only materialized if really needed (used
# only for computing quick_ratio())
# matching_blocks
# a list of (i, j, k) triples, where a[i:i+k] == b[j:j+k];
# ascending & non-overlapping in i and in j; terminated by
# a dummy (len(a), len(b), 0) sentinel
# opcodes
# a list of (tag, i1, i2, j1, j2) tuples, where tag is
# one of
# 'replace' a[i1:i2] should be replaced by b[j1:j2]
# 'delete' a[i1:i2] should be deleted
# 'insert' b[j1:j2] should be inserted
# 'equal' a[i1:i2] == b[j1:j2]
# isjunk
# a user-supplied function taking a sequence element and
# returning true iff the element is "junk" -- this has
# subtle but helpful effects on the algorithm, which I'll
# get around to writing up someday <0.9 wink>.
# DON'T USE! Only __chain_b uses this. Use "in self.bjunk".
# bjunk
# the items in b for which isjunk is True.
# bpopular
# nonjunk items in b treated as junk by the heuristic (if used).
self.isjunk = isjunk
self.a = self.b = None
self.autojunk = autojunk
self.set_seqs(a, b) | [
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/difflib.py#L151-L213 |
||
ltcmelo/psychec | 46672204681d73b40772a7bf24137dca23175e81 | cnippet/wrapper/Python/Version.py | python | Version.git_sha | () | return out[:7] | Get git HEAD's sha. | Get git HEAD's sha. | [
"Get",
"git",
"HEAD",
"s",
"sha",
"."
] | def git_sha():
"""
Get git HEAD's sha.
"""
cmd = ['git', 'rev-parse', 'HEAD']
process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
out, err = process.communicate()
if err:
sys.exit(DiagnosticReporter.fatal(ERROR_FETCHING_GIT_SHA))
return out[:7] | [
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|
alibaba/weex_js_engine | 2bdf4b6f020c1fc99c63f649718f6faf7e27fdde | jni/v8core/v8/build/gyp/pylib/gyp/MSVSVersion.py | python | SelectVisualStudioVersion | (version='auto') | return versions[0] | Select which version of Visual Studio projects to generate.
Arguments:
version: Hook to allow caller to force a particular version (vs auto).
Returns:
An object representing a visual studio project format version. | Select which version of Visual Studio projects to generate. | [
"Select",
"which",
"version",
"of",
"Visual",
"Studio",
"projects",
"to",
"generate",
"."
] | def SelectVisualStudioVersion(version='auto'):
"""Select which version of Visual Studio projects to generate.
Arguments:
version: Hook to allow caller to force a particular version (vs auto).
Returns:
An object representing a visual studio project format version.
"""
# In auto mode, check environment variable for override.
if version == 'auto':
version = os.environ.get('GYP_MSVS_VERSION', 'auto')
version_map = {
'auto': ('10.0', '9.0', '8.0', '11.0'),
'2005': ('8.0',),
'2005e': ('8.0',),
'2008': ('9.0',),
'2008e': ('9.0',),
'2010': ('10.0',),
'2010e': ('10.0',),
'2012': ('11.0',),
'2012e': ('11.0',),
}
version = str(version)
versions = _DetectVisualStudioVersions(version_map[version], 'e' in version)
if not versions:
if version == 'auto':
# Default to 2005 if we couldn't find anything
return _CreateVersion('2005', None)
else:
return _CreateVersion(version, None)
return versions[0] | [
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|
scribusproject/scribus | 41ec7c775a060912cf251682a8b1437f753f80f4 | scribus/plugins/scriptplugin_py2x/scripts/FontSample.py | python | Application.__aboutDlgShow | (self) | Brings up a dialog with support url etc. | Brings up a dialog with support url etc. | [
"Brings",
"up",
"a",
"dialog",
"with",
"support",
"url",
"etc",
"."
] | def __aboutDlgShow(self):
"""Brings up a dialog with support url etc."""
about = AboutDialog(self) | [
"def",
"__aboutDlgShow",
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"self",
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] | https://github.com/scribusproject/scribus/blob/41ec7c775a060912cf251682a8b1437f753f80f4/scribus/plugins/scriptplugin_py2x/scripts/FontSample.py#L1505-L1507 |
||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/npdatetime.py | python | get_best_unit | (unit_a, unit_b) | return unit_a | Get the best (i.e. finer-grained) of two units. | Get the best (i.e. finer-grained) of two units. | [
"Get",
"the",
"best",
"(",
"i",
".",
"e",
".",
"finer",
"-",
"grained",
")",
"of",
"two",
"units",
"."
] | def get_best_unit(unit_a, unit_b):
"""
Get the best (i.e. finer-grained) of two units.
"""
a = DATETIME_UNITS[unit_a]
b = DATETIME_UNITS[unit_b]
if a == 14:
return unit_b
if b == 14:
return unit_a
if b > a:
return unit_b
return unit_a | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py2/IPython/core/crashhandler.py | python | CrashHandler.__call__ | (self, etype, evalue, etb) | Handle an exception, call for compatible with sys.excepthook | Handle an exception, call for compatible with sys.excepthook | [
"Handle",
"an",
"exception",
"call",
"for",
"compatible",
"with",
"sys",
".",
"excepthook"
] | def __call__(self, etype, evalue, etb):
"""Handle an exception, call for compatible with sys.excepthook"""
# do not allow the crash handler to be called twice without reinstalling it
# this prevents unlikely errors in the crash handling from entering an
# infinite loop.
sys.excepthook = sys.__excepthook__
# Report tracebacks shouldn't use color in general (safer for users)
color_scheme = 'NoColor'
# Use this ONLY for developer debugging (keep commented out for release)
#color_scheme = 'Linux' # dbg
try:
rptdir = self.app.ipython_dir
except:
rptdir = getcwd()
if rptdir is None or not os.path.isdir(rptdir):
rptdir = getcwd()
report_name = os.path.join(rptdir,self.crash_report_fname)
# write the report filename into the instance dict so it can get
# properly expanded out in the user message template
self.crash_report_fname = report_name
self.info['crash_report_fname'] = report_name
TBhandler = ultratb.VerboseTB(
color_scheme=color_scheme,
long_header=1,
call_pdb=self.call_pdb,
)
if self.call_pdb:
TBhandler(etype,evalue,etb)
return
else:
traceback = TBhandler.text(etype,evalue,etb,context=31)
# print traceback to screen
if self.show_crash_traceback:
print(traceback, file=sys.stderr)
# and generate a complete report on disk
try:
report = open(report_name,'w')
except:
print('Could not create crash report on disk.', file=sys.stderr)
return
# Inform user on stderr of what happened
print('\n'+'*'*70+'\n', file=sys.stderr)
print(self.message_template.format(**self.info), file=sys.stderr)
# Construct report on disk
report.write(self.make_report(traceback))
report.close()
input("Hit <Enter> to quit (your terminal may close):") | [
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||
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/emr/connection.py | python | EmrConnection.list_bootstrap_actions | (self, cluster_id, marker=None) | return self.get_object('ListBootstrapActions', params, BootstrapActionList) | Get a list of bootstrap actions for an Elastic MapReduce cluster
:type cluster_id: str
:param cluster_id: The cluster id of interest
:type marker: str
:param marker: Pagination marker | Get a list of bootstrap actions for an Elastic MapReduce cluster | [
"Get",
"a",
"list",
"of",
"bootstrap",
"actions",
"for",
"an",
"Elastic",
"MapReduce",
"cluster"
] | def list_bootstrap_actions(self, cluster_id, marker=None):
"""
Get a list of bootstrap actions for an Elastic MapReduce cluster
:type cluster_id: str
:param cluster_id: The cluster id of interest
:type marker: str
:param marker: Pagination marker
"""
params = {
'ClusterId': cluster_id
}
if marker:
params['Marker'] = marker
return self.get_object('ListBootstrapActions', params, BootstrapActionList) | [
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|
lhmRyan/deep-supervised-hashing-DSH | 631901f82e2ab031fbac33f914a5b08ef8e21d57 | scripts/cpp_lint.py | python | FindNextMatchingAngleBracket | (clean_lines, linenum, init_suffix) | return True | Find the corresponding > to close a template.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: Current line number.
init_suffix: Remainder of the current line after the initial <.
Returns:
True if a matching bracket exists. | Find the corresponding > to close a template. | [
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] | def FindNextMatchingAngleBracket(clean_lines, linenum, init_suffix):
"""Find the corresponding > to close a template.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: Current line number.
init_suffix: Remainder of the current line after the initial <.
Returns:
True if a matching bracket exists.
"""
line = init_suffix
nesting_stack = ['<']
while True:
# Find the next operator that can tell us whether < is used as an
# opening bracket or as a less-than operator. We only want to
# warn on the latter case.
#
# We could also check all other operators and terminate the search
# early, e.g. if we got something like this "a<b+c", the "<" is
# most likely a less-than operator, but then we will get false
# positives for default arguments and other template expressions.
match = Search(r'^[^<>(),;\[\]]*([<>(),;\[\]])(.*)$', line)
if match:
# Found an operator, update nesting stack
operator = match.group(1)
line = match.group(2)
if nesting_stack[-1] == '<':
# Expecting closing angle bracket
if operator in ('<', '(', '['):
nesting_stack.append(operator)
elif operator == '>':
nesting_stack.pop()
if not nesting_stack:
# Found matching angle bracket
return True
elif operator == ',':
# Got a comma after a bracket, this is most likely a template
# argument. We have not seen a closing angle bracket yet, but
# it's probably a few lines later if we look for it, so just
# return early here.
return True
else:
# Got some other operator.
return False
else:
# Expecting closing parenthesis or closing bracket
if operator in ('<', '(', '['):
nesting_stack.append(operator)
elif operator in (')', ']'):
# We don't bother checking for matching () or []. If we got
# something like (] or [), it would have been a syntax error.
nesting_stack.pop()
else:
# Scan the next line
linenum += 1
if linenum >= len(clean_lines.elided):
break
line = clean_lines.elided[linenum]
# Exhausted all remaining lines and still no matching angle bracket.
# Most likely the input was incomplete, otherwise we should have
# seen a semicolon and returned early.
return True | [
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] | https://github.com/lhmRyan/deep-supervised-hashing-DSH/blob/631901f82e2ab031fbac33f914a5b08ef8e21d57/scripts/cpp_lint.py#L2517-L2583 |
|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/stc.py | python | StyledTextCtrl.StyleGetEOLFilled | (*args, **kwargs) | return _stc.StyledTextCtrl_StyleGetEOLFilled(*args, **kwargs) | StyleGetEOLFilled(self, int style) -> bool
Get is a style to have its end of line filled or not. | StyleGetEOLFilled(self, int style) -> bool | [
"StyleGetEOLFilled",
"(",
"self",
"int",
"style",
")",
"-",
">",
"bool"
] | def StyleGetEOLFilled(*args, **kwargs):
"""
StyleGetEOLFilled(self, int style) -> bool
Get is a style to have its end of line filled or not.
"""
return _stc.StyledTextCtrl_StyleGetEOLFilled(*args, **kwargs) | [
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|
ros-planning/moveit2 | dd240ef6fd8b9932a7a53964140f2952786187a9 | moveit_commander/src/moveit_commander/move_group.py | python | MoveGroupCommander.detach_object | (self, name="") | return self._g.detach_object(name) | Given the name of a link, detach the object(s) from that link. If no such link exists, the name is interpreted as an object name. If there is no name specified, an attempt is made to detach all objects attached to any link in the group. | Given the name of a link, detach the object(s) from that link. If no such link exists, the name is interpreted as an object name. If there is no name specified, an attempt is made to detach all objects attached to any link in the group. | [
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] | def detach_object(self, name=""):
""" Given the name of a link, detach the object(s) from that link. If no such link exists, the name is interpreted as an object name. If there is no name specified, an attempt is made to detach all objects attached to any link in the group."""
return self._g.detach_object(name) | [
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|
macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/pylib/gyp/generator/ninja.py | python | QuoteShellArgument | (arg, flavor) | return "'" + arg.replace("'", "'" + '"\'"' + "'") + "'" | Quote a string such that it will be interpreted as a single argument
by the shell. | Quote a string such that it will be interpreted as a single argument
by the shell. | [
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] | def QuoteShellArgument(arg, flavor):
"""Quote a string such that it will be interpreted as a single argument
by the shell."""
# Rather than attempting to enumerate the bad shell characters, just
# whitelist common OK ones and quote anything else.
if re.match(r'^[a-zA-Z0-9_=.\\/-]+$', arg):
return arg # No quoting necessary.
if flavor == 'win':
return gyp.msvs_emulation.QuoteForRspFile(arg)
return "'" + arg.replace("'", "'" + '"\'"' + "'") + "'" | [
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|
triton-inference-server/server | 11a11d9cb1e9734ed9fd305e752da70f07d1992f | qa/common/sequence_util.py | python | SequenceBatcherTestUtil.check_sequence_shape_tensor_io | (self,
model_name,
input_dtype,
correlation_id,
sequence_thresholds,
values,
expected_result,
shm_region_handles,
using_dynamic_batcher=False,
sequence_name="<unknown>") | Perform sequence of inferences using async run. The 'values' holds
a list of tuples, one for each inference with format:
(flag_str, shape_value, value, pre_delay_ms) | Perform sequence of inferences using async run. The 'values' holds
a list of tuples, one for each inference with format: | [
"Perform",
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":"
] | def check_sequence_shape_tensor_io(self,
model_name,
input_dtype,
correlation_id,
sequence_thresholds,
values,
expected_result,
shm_region_handles,
using_dynamic_batcher=False,
sequence_name="<unknown>"):
"""Perform sequence of inferences using async run. The 'values' holds
a list of tuples, one for each inference with format:
(flag_str, shape_value, value, pre_delay_ms)
"""
tensor_shape = (1, 1)
# shape tensor is 1-D tensor that doesn't contain batch size as first value
shape_tensor_shape = (1,)
self.assertFalse(_test_cuda_shared_memory,
"Shape tensors does not support CUDA shared memory")
client_utils = grpcclient
triton_client = client_utils.InferenceServerClient("localhost:8001",
verbose=True)
user_data = UserData()
triton_client.start_stream(partial(completion_callback, user_data))
# Execute the sequence of inference...
try:
seq_start_ms = int(round(time.time() * 1000))
sent_count = 0
shape_values = list()
for flag_str, shape_value, value, pre_delay_ms in values:
seq_start = False
seq_end = False
if flag_str is not None:
seq_start = ("start" in flag_str)
seq_end = ("end" in flag_str)
# Construct request IOs
inputs = []
outputs = []
# input order: input, shape(, dummy)
inputs.append(
client_utils.InferInput(
"INPUT", tensor_shape,
np_to_triton_dtype(np.int32 if using_dynamic_batcher
else input_dtype)))
inputs.append(
client_utils.InferInput("SHAPE_INPUT", shape_tensor_shape,
np_to_triton_dtype(np.int32)))
if using_dynamic_batcher:
inputs.append(
client_utils.InferInput(
"DUMMY_INPUT", tensor_shape,
np_to_triton_dtype(input_dtype)))
# output order: shape, output, resized
outputs.append(
client_utils.InferRequestedOutput("SHAPE_OUTPUT"))
outputs.append(client_utils.InferRequestedOutput("OUTPUT"))
outputs.append(
client_utils.InferRequestedOutput("RESIZED_OUTPUT"))
# Set IO values
shape_values.append(
np.full(shape_tensor_shape, shape_value, dtype=np.int32))
if not _test_system_shared_memory:
if using_dynamic_batcher:
if input_dtype == np.object_:
dummy_in0 = np.full(tensor_shape,
value,
dtype=np.int32)
dummy_in0n = np.array(
[str(x) for x in in0.reshape(dummy_in0.size)],
dtype=object)
dummy_in0 = dummy_in0n.reshape(tensor_shape)
else:
dummy_in0 = np.full(tensor_shape,
value,
dtype=input_dtype)
in0 = np.full(tensor_shape, value, dtype=np.int32)
else:
if input_dtype == np.object_:
in0 = np.full(tensor_shape, value, dtype=np.int32)
in0n = np.array(
[str(x) for x in in0.reshape(in0.size)],
dtype=object)
in0 = in0n.reshape(tensor_shape)
else:
in0 = np.full(tensor_shape,
value,
dtype=input_dtype)
inputs[0].set_data_from_numpy(in0)
inputs[1].set_data_from_numpy(shape_values[-1])
if using_dynamic_batcher:
inputs[2].set_data_from_numpy(dummy_in0)
else:
if using_dynamic_batcher:
input_offset = 6 * sent_count
output_offset = 6 * sent_count + 3
else:
input_offset = 5 * sent_count
output_offset = 5 * sent_count + 2
for i in range(len(inputs)):
inputs[i].set_shared_memory(
shm_region_handles[input_offset + i][0],
shm_region_handles[input_offset + i][1])
for i in range(len(outputs)):
outputs[i].set_shared_memory(
shm_region_handles[output_offset + i][0],
shm_region_handles[output_offset + i][1])
if pre_delay_ms is not None:
time.sleep(pre_delay_ms / 1000.0)
triton_client.async_stream_infer(model_name,
inputs,
outputs=outputs,
sequence_id=correlation_id,
sequence_start=seq_start,
sequence_end=seq_end)
sent_count += 1
# Wait for the results in the order sent
result = None
processed_count = 0
while processed_count < sent_count:
(results, error) = user_data._completed_requests.get()
if error is not None:
raise error
# Get value of "OUTPUT", for shared memory, need to get it via
# shared memory utils
if (not _test_system_shared_memory):
out = results.as_numpy("OUTPUT")
else:
output = results.get_output("OUTPUT")
output_offset = 6 * processed_count + 4 if using_dynamic_batcher else 5 * processed_count + 3
output_shape = output.shape
output_type = np.int32 if using_dynamic_batcher else np.float32
out = shm.get_contents_as_numpy(
shm_region_handles[output_offset][2], output_type,
output_shape)
result = out[0][0]
# Validate the (debatched) shape of the resized output matches
# with the shape input values
resized_shape = results.get_output("RESIZED_OUTPUT").shape[1:]
self.assertTrue(
np.array_equal(resized_shape,
shape_values[processed_count]),
"{}, {}, slot {}, expected: {}, got {}".format(
model_name, "RESIZED_OUTPUT", processed_count,
shape_values[processed_count], resized_shape))
print("{}: {}".format(sequence_name, result))
processed_count += 1
seq_end_ms = int(round(time.time() * 1000))
if input_dtype == np.object_:
self.assertEqual(int(result), expected_result)
else:
self.assertEqual(result, expected_result)
if sequence_thresholds is not None:
lt_ms = sequence_thresholds[0]
gt_ms = sequence_thresholds[1]
if lt_ms is not None:
if _test_jetson:
lt_ms *= _jetson_slowdown_factor
self.assertTrue((seq_end_ms - seq_start_ms) < lt_ms,
"sequence expected less than " +
str(lt_ms) + "ms response time, got " +
str(seq_end_ms - seq_start_ms) + " ms")
if gt_ms is not None:
self.assertTrue((seq_end_ms - seq_start_ms) > gt_ms,
"sequence expected greater than " +
str(gt_ms) + "ms response time, got " +
str(seq_end_ms - seq_start_ms) + " ms")
except Exception as ex:
self.add_deferred_exception(ex)
triton_client.stop_stream() | [
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | current/deps/v8/third_party/jinja2/environment.py | python | Environment.lex | (self, source, name=None, filename=None) | Lex the given sourcecode and return a generator that yields
tokens as tuples in the form ``(lineno, token_type, value)``.
This can be useful for :ref:`extension development <writing-extensions>`
and debugging templates.
This does not perform preprocessing. If you want the preprocessing
of the extensions to be applied you have to filter source through
the :meth:`preprocess` method. | Lex the given sourcecode and return a generator that yields
tokens as tuples in the form ``(lineno, token_type, value)``.
This can be useful for :ref:`extension development <writing-extensions>`
and debugging templates. | [
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"""Lex the given sourcecode and return a generator that yields
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This can be useful for :ref:`extension development <writing-extensions>`
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/core/arrayprint.py | python | set_printoptions | (precision=None, threshold=None, edgeitems=None,
linewidth=None, suppress=None, nanstr=None, infstr=None,
formatter=None, sign=None, floatmode=None, **kwarg) | Set printing options.
These options determine the way floating point numbers, arrays and
other NumPy objects are displayed.
Parameters
----------
precision : int or None, optional
Number of digits of precision for floating point output (default 8).
May be None if `floatmode` is not `fixed`, to print as many digits as
necessary to uniquely specify the value.
threshold : int, optional
Total number of array elements which trigger summarization
rather than full repr (default 1000).
To always use the full repr without summarization, pass `sys.maxsize`.
edgeitems : int, optional
Number of array items in summary at beginning and end of
each dimension (default 3).
linewidth : int, optional
The number of characters per line for the purpose of inserting
line breaks (default 75).
suppress : bool, optional
If True, always print floating point numbers using fixed point
notation, in which case numbers equal to zero in the current precision
will print as zero. If False, then scientific notation is used when
absolute value of the smallest number is < 1e-4 or the ratio of the
maximum absolute value to the minimum is > 1e3. The default is False.
nanstr : str, optional
String representation of floating point not-a-number (default nan).
infstr : str, optional
String representation of floating point infinity (default inf).
sign : string, either '-', '+', or ' ', optional
Controls printing of the sign of floating-point types. If '+', always
print the sign of positive values. If ' ', always prints a space
(whitespace character) in the sign position of positive values. If
'-', omit the sign character of positive values. (default '-')
formatter : dict of callables, optional
If not None, the keys should indicate the type(s) that the respective
formatting function applies to. Callables should return a string.
Types that are not specified (by their corresponding keys) are handled
by the default formatters. Individual types for which a formatter
can be set are:
- 'bool'
- 'int'
- 'timedelta' : a `numpy.timedelta64`
- 'datetime' : a `numpy.datetime64`
- 'float'
- 'longfloat' : 128-bit floats
- 'complexfloat'
- 'longcomplexfloat' : composed of two 128-bit floats
- 'numpystr' : types `numpy.string_` and `numpy.unicode_`
- 'object' : `np.object_` arrays
- 'str' : all other strings
Other keys that can be used to set a group of types at once are:
- 'all' : sets all types
- 'int_kind' : sets 'int'
- 'float_kind' : sets 'float' and 'longfloat'
- 'complex_kind' : sets 'complexfloat' and 'longcomplexfloat'
- 'str_kind' : sets 'str' and 'numpystr'
floatmode : str, optional
Controls the interpretation of the `precision` option for
floating-point types. Can take the following values
(default maxprec_equal):
* 'fixed': Always print exactly `precision` fractional digits,
even if this would print more or fewer digits than
necessary to specify the value uniquely.
* 'unique': Print the minimum number of fractional digits necessary
to represent each value uniquely. Different elements may
have a different number of digits. The value of the
`precision` option is ignored.
* 'maxprec': Print at most `precision` fractional digits, but if
an element can be uniquely represented with fewer digits
only print it with that many.
* 'maxprec_equal': Print at most `precision` fractional digits,
but if every element in the array can be uniquely
represented with an equal number of fewer digits, use that
many digits for all elements.
legacy : string or `False`, optional
If set to the string `'1.13'` enables 1.13 legacy printing mode. This
approximates numpy 1.13 print output by including a space in the sign
position of floats and different behavior for 0d arrays. If set to
`False`, disables legacy mode. Unrecognized strings will be ignored
with a warning for forward compatibility.
.. versionadded:: 1.14.0
See Also
--------
get_printoptions, printoptions, set_string_function, array2string
Notes
-----
`formatter` is always reset with a call to `set_printoptions`.
Use `printoptions` as a context manager to set the values temporarily.
Examples
--------
Floating point precision can be set:
>>> np.set_printoptions(precision=4)
>>> np.array([1.123456789])
[1.1235]
Long arrays can be summarised:
>>> np.set_printoptions(threshold=5)
>>> np.arange(10)
array([0, 1, 2, ..., 7, 8, 9])
Small results can be suppressed:
>>> eps = np.finfo(float).eps
>>> x = np.arange(4.)
>>> x**2 - (x + eps)**2
array([-4.9304e-32, -4.4409e-16, 0.0000e+00, 0.0000e+00])
>>> np.set_printoptions(suppress=True)
>>> x**2 - (x + eps)**2
array([-0., -0., 0., 0.])
A custom formatter can be used to display array elements as desired:
>>> np.set_printoptions(formatter={'all':lambda x: 'int: '+str(-x)})
>>> x = np.arange(3)
>>> x
array([int: 0, int: -1, int: -2])
>>> np.set_printoptions() # formatter gets reset
>>> x
array([0, 1, 2])
To put back the default options, you can use:
>>> np.set_printoptions(edgeitems=3, infstr='inf',
... linewidth=75, nanstr='nan', precision=8,
... suppress=False, threshold=1000, formatter=None)
Also to temporarily override options, use `printoptions` as a context manager:
>>> with np.printoptions(precision=2, suppress=True, threshold=5):
... np.linspace(0, 10, 10)
array([ 0. , 1.11, 2.22, ..., 7.78, 8.89, 10. ]) | Set printing options. | [
"Set",
"printing",
"options",
"."
] | def set_printoptions(precision=None, threshold=None, edgeitems=None,
linewidth=None, suppress=None, nanstr=None, infstr=None,
formatter=None, sign=None, floatmode=None, **kwarg):
"""
Set printing options.
These options determine the way floating point numbers, arrays and
other NumPy objects are displayed.
Parameters
----------
precision : int or None, optional
Number of digits of precision for floating point output (default 8).
May be None if `floatmode` is not `fixed`, to print as many digits as
necessary to uniquely specify the value.
threshold : int, optional
Total number of array elements which trigger summarization
rather than full repr (default 1000).
To always use the full repr without summarization, pass `sys.maxsize`.
edgeitems : int, optional
Number of array items in summary at beginning and end of
each dimension (default 3).
linewidth : int, optional
The number of characters per line for the purpose of inserting
line breaks (default 75).
suppress : bool, optional
If True, always print floating point numbers using fixed point
notation, in which case numbers equal to zero in the current precision
will print as zero. If False, then scientific notation is used when
absolute value of the smallest number is < 1e-4 or the ratio of the
maximum absolute value to the minimum is > 1e3. The default is False.
nanstr : str, optional
String representation of floating point not-a-number (default nan).
infstr : str, optional
String representation of floating point infinity (default inf).
sign : string, either '-', '+', or ' ', optional
Controls printing of the sign of floating-point types. If '+', always
print the sign of positive values. If ' ', always prints a space
(whitespace character) in the sign position of positive values. If
'-', omit the sign character of positive values. (default '-')
formatter : dict of callables, optional
If not None, the keys should indicate the type(s) that the respective
formatting function applies to. Callables should return a string.
Types that are not specified (by their corresponding keys) are handled
by the default formatters. Individual types for which a formatter
can be set are:
- 'bool'
- 'int'
- 'timedelta' : a `numpy.timedelta64`
- 'datetime' : a `numpy.datetime64`
- 'float'
- 'longfloat' : 128-bit floats
- 'complexfloat'
- 'longcomplexfloat' : composed of two 128-bit floats
- 'numpystr' : types `numpy.string_` and `numpy.unicode_`
- 'object' : `np.object_` arrays
- 'str' : all other strings
Other keys that can be used to set a group of types at once are:
- 'all' : sets all types
- 'int_kind' : sets 'int'
- 'float_kind' : sets 'float' and 'longfloat'
- 'complex_kind' : sets 'complexfloat' and 'longcomplexfloat'
- 'str_kind' : sets 'str' and 'numpystr'
floatmode : str, optional
Controls the interpretation of the `precision` option for
floating-point types. Can take the following values
(default maxprec_equal):
* 'fixed': Always print exactly `precision` fractional digits,
even if this would print more or fewer digits than
necessary to specify the value uniquely.
* 'unique': Print the minimum number of fractional digits necessary
to represent each value uniquely. Different elements may
have a different number of digits. The value of the
`precision` option is ignored.
* 'maxprec': Print at most `precision` fractional digits, but if
an element can be uniquely represented with fewer digits
only print it with that many.
* 'maxprec_equal': Print at most `precision` fractional digits,
but if every element in the array can be uniquely
represented with an equal number of fewer digits, use that
many digits for all elements.
legacy : string or `False`, optional
If set to the string `'1.13'` enables 1.13 legacy printing mode. This
approximates numpy 1.13 print output by including a space in the sign
position of floats and different behavior for 0d arrays. If set to
`False`, disables legacy mode. Unrecognized strings will be ignored
with a warning for forward compatibility.
.. versionadded:: 1.14.0
See Also
--------
get_printoptions, printoptions, set_string_function, array2string
Notes
-----
`formatter` is always reset with a call to `set_printoptions`.
Use `printoptions` as a context manager to set the values temporarily.
Examples
--------
Floating point precision can be set:
>>> np.set_printoptions(precision=4)
>>> np.array([1.123456789])
[1.1235]
Long arrays can be summarised:
>>> np.set_printoptions(threshold=5)
>>> np.arange(10)
array([0, 1, 2, ..., 7, 8, 9])
Small results can be suppressed:
>>> eps = np.finfo(float).eps
>>> x = np.arange(4.)
>>> x**2 - (x + eps)**2
array([-4.9304e-32, -4.4409e-16, 0.0000e+00, 0.0000e+00])
>>> np.set_printoptions(suppress=True)
>>> x**2 - (x + eps)**2
array([-0., -0., 0., 0.])
A custom formatter can be used to display array elements as desired:
>>> np.set_printoptions(formatter={'all':lambda x: 'int: '+str(-x)})
>>> x = np.arange(3)
>>> x
array([int: 0, int: -1, int: -2])
>>> np.set_printoptions() # formatter gets reset
>>> x
array([0, 1, 2])
To put back the default options, you can use:
>>> np.set_printoptions(edgeitems=3, infstr='inf',
... linewidth=75, nanstr='nan', precision=8,
... suppress=False, threshold=1000, formatter=None)
Also to temporarily override options, use `printoptions` as a context manager:
>>> with np.printoptions(precision=2, suppress=True, threshold=5):
... np.linspace(0, 10, 10)
array([ 0. , 1.11, 2.22, ..., 7.78, 8.89, 10. ])
"""
legacy = kwarg.pop('legacy', None)
if kwarg:
msg = "set_printoptions() got unexpected keyword argument '{}'"
raise TypeError(msg.format(kwarg.popitem()[0]))
opt = _make_options_dict(precision, threshold, edgeitems, linewidth,
suppress, nanstr, infstr, sign, formatter,
floatmode, legacy)
# formatter is always reset
opt['formatter'] = formatter
_format_options.update(opt)
# set the C variable for legacy mode
if _format_options['legacy'] == '1.13':
set_legacy_print_mode(113)
# reset the sign option in legacy mode to avoid confusion
_format_options['sign'] = '-'
elif _format_options['legacy'] is False:
set_legacy_print_mode(0) | [
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||
tomahawk-player/tomahawk-resolvers | 7f827bbe410ccfdb0446f7d6a91acc2199c9cc8d | archive/spotify/breakpad/third_party/protobuf/protobuf/python/mox.py | python | MockMethod.__init__ | (self, method_name, call_queue, replay_mode) | Construct a new mock method.
Args:
# method_name: the name of the method
# call_queue: deque of calls, verify this call against the head, or add
# this call to the queue.
# replay_mode: False if we are recording, True if we are verifying calls
# against the call queue.
method_name: str
call_queue: list or deque
replay_mode: bool | Construct a new mock method. | [
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] | def __init__(self, method_name, call_queue, replay_mode):
"""Construct a new mock method.
Args:
# method_name: the name of the method
# call_queue: deque of calls, verify this call against the head, or add
# this call to the queue.
# replay_mode: False if we are recording, True if we are verifying calls
# against the call queue.
method_name: str
call_queue: list or deque
replay_mode: bool
"""
self._name = method_name
self._call_queue = call_queue
if not isinstance(call_queue, deque):
self._call_queue = deque(self._call_queue)
self._replay_mode = replay_mode
self._params = None
self._named_params = None
self._return_value = None
self._exception = None
self._side_effects = None | [
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tensorflow/deepmath | b5b721f54de1d5d6a02d78f5da5995237f9995f9 | deepmath/premises/model_definition_hybrid_pool2.py | python | Model.axiom_embedding | (self, axioms) | Compute the embedding for each of the axioms. | Compute the embedding for each of the axioms. | [
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] | def axiom_embedding(self, axioms):
"""Compute the embedding for each of the axioms."""
with tf.variable_scope('axiom'):
return self.make_embedding(axioms) | [
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||
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/session_bundle/bundle_shim.py | python | _convert_signatures_to_signature_defs | (metagraph_def) | return default_signature_def, named_signature_def | Produce default and named upconverted SignatureDef objects from Signatures.
Args:
metagraph_def: object of type meta_graph_pb2.MetaGraphDef containing legacy
format Session Bundle signatures
Returns:
default_signature_def: object of type SignatureDef which contains an
upconverted version of default signatures in metagraph_def
named_signature_def: object of type SignatureDef which contains an
upconverted version of named signatures in metagraph_def | Produce default and named upconverted SignatureDef objects from Signatures. | [
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"SignatureDef",
"objects",
"from",
"Signatures",
"."
] | def _convert_signatures_to_signature_defs(metagraph_def):
"""Produce default and named upconverted SignatureDef objects from Signatures.
Args:
metagraph_def: object of type meta_graph_pb2.MetaGraphDef containing legacy
format Session Bundle signatures
Returns:
default_signature_def: object of type SignatureDef which contains an
upconverted version of default signatures in metagraph_def
named_signature_def: object of type SignatureDef which contains an
upconverted version of named signatures in metagraph_def
"""
collection_def = metagraph_def.collection_def
signatures_proto = manifest_pb2.Signatures()
signatures = collection_def[legacy_constants.SIGNATURES_KEY].any_list.value[0]
signatures.Unpack(signatures_proto)
default_signature_def = None
named_signature_def = None
if signatures_proto.HasField("default_signature"):
default_signature_def = _convert_default_signature_to_signature_def(
signatures_proto)
if len(signatures_proto.named_signatures) > 1:
named_signature_def = _convert_named_signatures_to_signature_def(
signatures_proto)
return default_signature_def, named_signature_def | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/richtext.py | python | RichTextFileHandler.SaveStream | (*args, **kwargs) | return _richtext.RichTextFileHandler_SaveStream(*args, **kwargs) | SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool | SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool | [
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"""SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool"""
return _richtext.RichTextFileHandler_SaveStream(*args, **kwargs) | [
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openvinotoolkit/openvino | dedcbeafa8b84cccdc55ca64b8da516682b381c7 | tools/mo/openvino/tools/mo/utils/graph.py | python | bfs_search | (graph: Graph, start_nodes: list = list()) | return result | Performs breadth-first search over a graph and returns a list of nodes in the BFS order.
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:param start_nodes: list of start nodes of the graph. If the list is empty then start from all nodes that do not
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d = deque(start_nodes)
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/distutils/sysconfig.py | python | expand_makefile_vars | (s, vars) | return s | Expand Makefile-style variables -- "${foo}" or "$(foo)" -- in
'string' according to 'vars' (a dictionary mapping variable names to
values). Variables not present in 'vars' are silently expanded to the
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variable expansions; if 'vars' is the output of 'parse_makefile()',
you're fine. Returns a variable-expanded version of 's'. | Expand Makefile-style variables -- "${foo}" or "$(foo)" -- in
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values). Variables not present in 'vars' are silently expanded to the
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] | def expand_makefile_vars(s, vars):
"""Expand Makefile-style variables -- "${foo}" or "$(foo)" -- in
'string' according to 'vars' (a dictionary mapping variable names to
values). Variables not present in 'vars' are silently expanded to the
empty string. The variable values in 'vars' should not contain further
variable expansions; if 'vars' is the output of 'parse_makefile()',
you're fine. Returns a variable-expanded version of 's'.
"""
# This algorithm does multiple expansion, so if vars['foo'] contains
# "${bar}", it will expand ${foo} to ${bar}, and then expand
# ${bar}... and so forth. This is fine as long as 'vars' comes from
# 'parse_makefile()', which takes care of such expansions eagerly,
# according to make's variable expansion semantics.
while True:
m = _findvar1_rx.search(s) or _findvar2_rx.search(s)
if m:
(beg, end) = m.span()
s = s[0:beg] + vars.get(m.group(1)) + s[end:]
else:
break
return s | [
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|
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/validate_mongocryptd.py | python | can_validation_be_skipped | (evg_config, variant) | return False | Determine if the given build variant needs to be validated.
A build variant does not need to be validated if it does not run the 'push' task or
if it does not exist in the configuration (it is dynamically created).
:param evg_config: Evergreen configuration.
:param variant: Build variant to check.
:return: True if validation can be skipped. | Determine if the given build variant needs to be validated. | [
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] | def can_validation_be_skipped(evg_config, variant):
"""
Determine if the given build variant needs to be validated.
A build variant does not need to be validated if it does not run the 'push' task or
if it does not exist in the configuration (it is dynamically created).
:param evg_config: Evergreen configuration.
:param variant: Build variant to check.
:return: True if validation can be skipped.
"""
variant_config = evg_config.get_variant(variant)
if not variant_config:
return True
if PUSH_TASK_NAME not in variant_config.task_names:
return True
return False | [
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|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/tlslite/tlslite/utils/Python_RSAKey.py | python | Python_RSAKey.parsePEM | (s, passwordCallback=None) | Parse a string containing a <privateKey> or <publicKey>, or
PEM-encoded key. | Parse a string containing a <privateKey> or <publicKey>, or
PEM-encoded key. | [
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] | def parsePEM(s, passwordCallback=None):
"""Parse a string containing a <privateKey> or <publicKey>, or
PEM-encoded key."""
start = s.find("-----BEGIN PRIVATE KEY-----")
if start != -1:
end = s.find("-----END PRIVATE KEY-----")
if end == -1:
raise SyntaxError("Missing PEM Postfix")
s = s[start+len("-----BEGIN PRIVATE KEY -----") : end]
bytes = base64ToBytes(s)
return Python_RSAKey._parsePKCS8(bytes)
else:
start = s.find("-----BEGIN RSA PRIVATE KEY-----")
if start != -1:
end = s.find("-----END RSA PRIVATE KEY-----")
if end == -1:
raise SyntaxError("Missing PEM Postfix")
s = s[start+len("-----BEGIN RSA PRIVATE KEY -----") : end]
bytes = base64ToBytes(s)
return Python_RSAKey._parseSSLeay(bytes)
raise SyntaxError("Missing PEM Prefix") | [
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||
bristolcrypto/SPDZ-2 | 721abfae849625a02ea49aabc534f9cf41ca643f | Compiler/comparison.py | python | PRandM | (r_dprime, r_prime, b, k, m, kappa) | r_dprime = random secret integer in range [0, 2^(k + kappa - m) - 1]
r_prime = random secret integer in range [0, 2^m - 1]
b = array containing bits of r_prime | r_dprime = random secret integer in range [0, 2^(k + kappa - m) - 1]
r_prime = random secret integer in range [0, 2^m - 1]
b = array containing bits of r_prime | [
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"""
r_dprime = random secret integer in range [0, 2^(k + kappa - m) - 1]
r_prime = random secret integer in range [0, 2^m - 1]
b = array containing bits of r_prime
"""
t = [[program.curr_block.new_reg('s') for j in range(2)] for i in range(m)]
t[0][1] = b[-1]
PRandInt(r_dprime, k + kappa - m)
# r_dprime is always multiplied by 2^m
program.curr_tape.require_bit_length(k + kappa)
bit(b[-1])
for i in range(1,m):
adds(t[i][0], t[i-1][1], t[i-1][1])
bit(b[-i-1])
adds(t[i][1], t[i][0], b[-i-1])
movs(r_prime, t[m-1][1]) | [
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] | https://github.com/bristolcrypto/SPDZ-2/blob/721abfae849625a02ea49aabc534f9cf41ca643f/Compiler/comparison.py#L188-L204 |
||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/ssl.py | python | SSLObject.pending | (self) | return self._sslobj.pending() | Return the number of bytes that can be read immediately. | Return the number of bytes that can be read immediately. | [
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"that",
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"be",
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] | def pending(self):
"""Return the number of bytes that can be read immediately."""
return self._sslobj.pending() | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/graphy/graphy/common.py | python | BaseChart._GetAxes | (self) | Return a generator of (position_code, Axis) tuples for this chart's axes.
The axes will be sorted by position using the canonical ordering sequence,
_POSITION_CODES. | Return a generator of (position_code, Axis) tuples for this chart's axes. | [
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] | def _GetAxes(self):
"""Return a generator of (position_code, Axis) tuples for this chart's axes.
The axes will be sorted by position using the canonical ordering sequence,
_POSITION_CODES.
"""
for code in self._POSITION_CODES:
for axis in self._axes.get(code, []):
yield (code, axis) | [
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||
google/llvm-propeller | 45c226984fe8377ebfb2ad7713c680d652ba678d | lldb/third_party/Python/module/six/six.py | python | add_metaclass | (metaclass) | return wrapper | Class decorator for creating a class with a metaclass. | Class decorator for creating a class with a metaclass. | [
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"class",
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"metaclass",
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] | def add_metaclass(metaclass):
"""Class decorator for creating a class with a metaclass."""
def wrapper(cls):
orig_vars = cls.__dict__.copy()
slots = orig_vars.get('__slots__')
if slots is not None:
if isinstance(slots, str):
slots = [slots]
for slots_var in slots:
orig_vars.pop(slots_var)
orig_vars.pop('__dict__', None)
orig_vars.pop('__weakref__', None)
return metaclass(cls.__name__, cls.__bases__, orig_vars)
return wrapper | [
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|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/imputil.py | python | _compile | (pathname, timestamp) | return code | Compile (and cache) a Python source file.
The file specified by <pathname> is compiled to a code object and
returned.
Presuming the appropriate privileges exist, the bytecodes will be
saved back to the filesystem for future imports. The source file's
modification timestamp must be provided as a Long value. | Compile (and cache) a Python source file. | [
"Compile",
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"a",
"Python",
"source",
"file",
"."
] | def _compile(pathname, timestamp):
"""Compile (and cache) a Python source file.
The file specified by <pathname> is compiled to a code object and
returned.
Presuming the appropriate privileges exist, the bytecodes will be
saved back to the filesystem for future imports. The source file's
modification timestamp must be provided as a Long value.
"""
codestring = open(pathname, 'rU').read()
if codestring and codestring[-1] != '\n':
codestring = codestring + '\n'
code = __builtin__.compile(codestring, pathname, 'exec')
# try to cache the compiled code
try:
f = open(pathname + _suffix_char, 'wb')
except IOError:
pass
else:
f.write('\0\0\0\0')
f.write(struct.pack('<I', timestamp))
marshal.dump(code, f)
f.flush()
f.seek(0, 0)
f.write(imp.get_magic())
f.close()
return code | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/oauthlib/oauth1/rfc5849/request_validator.py | python | RequestValidator.validate_client_key | (self, client_key, request) | Validates that supplied client key is a registered and valid client.
:param client_key: The client/consumer key.
:param request: An oauthlib.common.Request object.
:returns: True or False
Note that if the dummy client is supplied it should validate in same
or nearly the same amount of time as a valid one.
Ensure latency inducing tasks are mimiced even for dummy clients.
For example, use::
from your_datastore import Client
try:
return Client.exists(client_key, access_token)
except DoesNotExist:
return False
Rather than::
from your_datastore import Client
if access_token == self.dummy_access_token:
return False
else:
return Client.exists(client_key, access_token)
This method is used by
* AccessTokenEndpoint
* RequestTokenEndpoint
* ResourceEndpoint
* SignatureOnlyEndpoint | Validates that supplied client key is a registered and valid client. | [
"Validates",
"that",
"supplied",
"client",
"key",
"is",
"a",
"registered",
"and",
"valid",
"client",
"."
] | def validate_client_key(self, client_key, request):
"""Validates that supplied client key is a registered and valid client.
:param client_key: The client/consumer key.
:param request: An oauthlib.common.Request object.
:returns: True or False
Note that if the dummy client is supplied it should validate in same
or nearly the same amount of time as a valid one.
Ensure latency inducing tasks are mimiced even for dummy clients.
For example, use::
from your_datastore import Client
try:
return Client.exists(client_key, access_token)
except DoesNotExist:
return False
Rather than::
from your_datastore import Client
if access_token == self.dummy_access_token:
return False
else:
return Client.exists(client_key, access_token)
This method is used by
* AccessTokenEndpoint
* RequestTokenEndpoint
* ResourceEndpoint
* SignatureOnlyEndpoint
"""
raise self._subclass_must_implement("validate_client_key") | [
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/oauthlib/oauth1/rfc5849/request_validator.py#L461-L495 |
||
y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/PathList.py | python | _PathList.__init__ | (self, pathlist) | Initializes a PathList object, canonicalizing the input and
pre-processing it for quicker substitution later.
The stored representation of the PathList is a list of tuples
containing (type, value), where the "type" is one of the TYPE_*
variables defined above. We distinguish between:
strings that contain no '$' and therefore need no
delayed-evaluation string substitution (we expect that there
will be many of these and that we therefore get a pretty
big win from avoiding string substitution)
strings that contain '$' and therefore need substitution
(the hard case is things like '${TARGET.dir}/include',
which require re-evaluation for every target + source)
other objects (which may be something like an EntryProxy
that needs a method called to return a Node)
Pre-identifying the type of each element in the PathList up-front
and storing the type in the list of tuples is intended to reduce
the amount of calculation when we actually do the substitution
over and over for each target. | Initializes a PathList object, canonicalizing the input and
pre-processing it for quicker substitution later. | [
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] | def __init__(self, pathlist):
"""
Initializes a PathList object, canonicalizing the input and
pre-processing it for quicker substitution later.
The stored representation of the PathList is a list of tuples
containing (type, value), where the "type" is one of the TYPE_*
variables defined above. We distinguish between:
strings that contain no '$' and therefore need no
delayed-evaluation string substitution (we expect that there
will be many of these and that we therefore get a pretty
big win from avoiding string substitution)
strings that contain '$' and therefore need substitution
(the hard case is things like '${TARGET.dir}/include',
which require re-evaluation for every target + source)
other objects (which may be something like an EntryProxy
that needs a method called to return a Node)
Pre-identifying the type of each element in the PathList up-front
and storing the type in the list of tuples is intended to reduce
the amount of calculation when we actually do the substitution
over and over for each target.
"""
if SCons.Util.is_String(pathlist):
pathlist = pathlist.split(os.pathsep)
elif not SCons.Util.is_Sequence(pathlist):
pathlist = [pathlist]
pl = []
for p in pathlist:
try:
index = p.find('$')
except (AttributeError, TypeError):
type = TYPE_OBJECT
else:
if index == -1:
type = TYPE_STRING_NO_SUBST
else:
type = TYPE_STRING_SUBST
pl.append((type, p))
self.pathlist = tuple(pl) | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/ndimage/filters.py | python | generic_filter1d | (input, function, filter_size, axis=-1,
output=None, mode="reflect", cval=0.0, origin=0,
extra_arguments=(), extra_keywords = None) | return return_value | Calculate a one-dimensional filter along the given axis.
`generic_filter1d` iterates over the lines of the array, calling the
given function at each line. The arguments of the line are the
input line, and the output line. The input and output lines are 1D
double arrays. The input line is extended appropriately according
to the filter size and origin. The output line must be modified
in-place with the result.
Parameters
----------
%(input)s
function : callable
Function to apply along given axis.
filter_size : scalar
Length of the filter.
%(axis)s
%(output)s
%(mode)s
%(cval)s
%(origin)s
%(extra_arguments)s
%(extra_keywords)s | Calculate a one-dimensional filter along the given axis. | [
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] | def generic_filter1d(input, function, filter_size, axis=-1,
output=None, mode="reflect", cval=0.0, origin=0,
extra_arguments=(), extra_keywords = None):
"""Calculate a one-dimensional filter along the given axis.
`generic_filter1d` iterates over the lines of the array, calling the
given function at each line. The arguments of the line are the
input line, and the output line. The input and output lines are 1D
double arrays. The input line is extended appropriately according
to the filter size and origin. The output line must be modified
in-place with the result.
Parameters
----------
%(input)s
function : callable
Function to apply along given axis.
filter_size : scalar
Length of the filter.
%(axis)s
%(output)s
%(mode)s
%(cval)s
%(origin)s
%(extra_arguments)s
%(extra_keywords)s
"""
if extra_keywords is None:
extra_keywords = {}
input = numpy.asarray(input)
if numpy.iscomplexobj(input):
raise TypeError('Complex type not supported')
output, return_value = _ni_support._get_output(output, input)
if filter_size < 1:
raise RuntimeError('invalid filter size')
axis = _ni_support._check_axis(axis, input.ndim)
if (filter_size // 2 + origin < 0) or (filter_size // 2 + origin >=
filter_size):
raise ValueError('invalid origin')
mode = _ni_support._extend_mode_to_code(mode)
_nd_image.generic_filter1d(input, function, filter_size, axis, output,
mode, cval, origin, extra_arguments, extra_keywords)
return return_value | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/mailbox.py | python | Maildir.__len__ | (self) | return len(self._toc) | Return a count of messages in the mailbox. | Return a count of messages in the mailbox. | [
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] | def __len__(self):
"""Return a count of messages in the mailbox."""
self._refresh()
return len(self._toc) | [
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|
klzgrad/naiveproxy | ed2c513637c77b18721fe428d7ed395b4d284c83 | src/build/android/gyp/util/resource_utils.py | python | RJavaBuildOptions._MaybeRewriteRTxtPackageIds | (self, r_txt_path) | Rewrites package IDs in the R.txt file if necessary.
If SetFinalPackageId() was called, some of the resource IDs may have had
their package ID changed. This function rewrites the R.txt file to match
those changes. | Rewrites package IDs in the R.txt file if necessary. | [
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] | def _MaybeRewriteRTxtPackageIds(self, r_txt_path):
"""Rewrites package IDs in the R.txt file if necessary.
If SetFinalPackageId() was called, some of the resource IDs may have had
their package ID changed. This function rewrites the R.txt file to match
those changes.
"""
if self.final_package_id is None:
return
entries = _ParseTextSymbolsFile(r_txt_path)
with open(r_txt_path, 'w') as f:
for entry in entries:
value = entry.value
if self._IsResourceFinal(entry):
value = re.sub(r'0x(?:00|7f)',
'0x{:02x}'.format(self.final_package_id), value)
f.write('{} {} {} {}\n'.format(entry.java_type, entry.resource_type,
entry.name, value)) | [
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||
OSGeo/gdal | 3748fc4ba4fba727492774b2b908a2130c864a83 | swig/python/osgeo/gdal.py | python | Dataset.WriteRaster | (self, *args, **kwargs) | return _gdal.Dataset_WriteRaster(self, *args, **kwargs) | r"""WriteRaster(Dataset self, int xoff, int yoff, int xsize, int ysize, GIntBig buf_len, int * buf_xsize=None, int * buf_ysize=None, GDALDataType * buf_type=None, int band_list=0, GIntBig * buf_pixel_space=None, GIntBig * buf_line_space=None, GIntBig * buf_band_space=None) -> CPLErr | r"""WriteRaster(Dataset self, int xoff, int yoff, int xsize, int ysize, GIntBig buf_len, int * buf_xsize=None, int * buf_ysize=None, GDALDataType * buf_type=None, int band_list=0, GIntBig * buf_pixel_space=None, GIntBig * buf_line_space=None, GIntBig * buf_band_space=None) -> CPLErr | [
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return _gdal.Dataset_WriteRaster(self, *args, **kwargs) | [
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snap-stanford/snap-python | d53c51b0a26aa7e3e7400b014cdf728948fde80a | setup/snap.py | python | TStr_AddToFMid | (*args) | return _snap.TStr_AddToFMid(*args) | TStr_AddToFMid(TStr FNm, TStr ExtFMid) -> TStr
Parameters:
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ExtFMid: TStr const & | TStr_AddToFMid(TStr FNm, TStr ExtFMid) -> TStr | [
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"""
TStr_AddToFMid(TStr FNm, TStr ExtFMid) -> TStr
Parameters:
FNm: TStr const &
ExtFMid: TStr const &
"""
return _snap.TStr_AddToFMid(*args) | [
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root-project/root | fcd3583bb14852bf2e8cd2415717cbaac0e75896 | interpreter/llvm/src/tools/clang/tools/scan-build-py/libscanbuild/arguments.py | python | normalize_args_for_analyze | (args, from_build_command) | Normalize parsed arguments for analyze-build and scan-build.
:param args: Parsed argument object. (Will be mutated.)
:param from_build_command: Boolean value tells is the command suppose
to run the analyzer against a build command or a compilation db. | Normalize parsed arguments for analyze-build and scan-build. | [
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] | def normalize_args_for_analyze(args, from_build_command):
""" Normalize parsed arguments for analyze-build and scan-build.
:param args: Parsed argument object. (Will be mutated.)
:param from_build_command: Boolean value tells is the command suppose
to run the analyzer against a build command or a compilation db. """
# make plugins always a list. (it might be None when not specified.)
if args.plugins is None:
args.plugins = []
# make exclude directory list unique and absolute.
uniq_excludes = set(os.path.abspath(entry) for entry in args.excludes)
args.excludes = list(uniq_excludes)
# because shared codes for all tools, some common used methods are
# expecting some argument to be present. so, instead of query the args
# object about the presence of the flag, we fake it here. to make those
# methods more readable. (it's an arguable choice, took it only for those
# which have good default value.)
if from_build_command:
# add cdb parameter invisibly to make report module working.
args.cdb = 'compile_commands.json'
# Make ctu_dir an abspath as it is needed inside clang
if not from_build_command and hasattr(args, 'ctu_phases') \
and hasattr(args.ctu_phases, 'dir'):
args.ctu_dir = os.path.abspath(args.ctu_dir) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/setuptools/py3/setuptools/_distutils/fancy_getopt.py | python | FancyGetopt.get_attr_name | (self, long_option) | return long_option.translate(longopt_xlate) | Translate long option name 'long_option' to the form it
has as an attribute of some object: ie., translate hyphens
to underscores. | Translate long option name 'long_option' to the form it
has as an attribute of some object: ie., translate hyphens
to underscores. | [
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"""Translate long option name 'long_option' to the form it
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to underscores."""
return long_option.translate(longopt_xlate) | [
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|
cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | Alignment/MuonAlignment/python/svgfig.py | python | Ticks.regular_miniticks | (self, N) | return output | Return exactly N linear ticks.
Normally only used internally. | Return exactly N linear ticks. | [
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] | def regular_miniticks(self, N):
"""Return exactly N linear ticks.
Normally only used internally.
"""
output = []
x = self.low
for i in range(N):
output.append(x)
x += (self.high - self.low)/(N-1.)
return output | [
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|
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_grad.py | python | _AcoshGrad | (op, grad) | Returns grad * 1/sinh(y). | Returns grad * 1/sinh(y). | [
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"""Returns grad * 1/sinh(y)."""
y = op.outputs[0]
with ops.control_dependencies([grad]):
y = math_ops.conj(y)
if compat.forward_compatible(2019, 9, 14):
return math_ops.xdivy(grad, math_ops.sinh(y))
else:
return grad / math_ops.sinh(y) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_windows.py | python | Printout._setCallbackInfo | (*args, **kwargs) | return _windows_.Printout__setCallbackInfo(*args, **kwargs) | _setCallbackInfo(self, PyObject self, PyObject _class) | _setCallbackInfo(self, PyObject self, PyObject _class) | [
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return _windows_.Printout__setCallbackInfo(*args, **kwargs) | [
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|
s9xie/hed | 94fb22f10cbfec8d84fbc0642b224022014b6bd6 | scripts/cpp_lint.py | python | _FunctionState.Check | (self, error, filename, linenum) | Report if too many lines in function body.
Args:
error: The function to call with any errors found.
filename: The name of the current file.
linenum: The number of the line to check. | Report if too many lines in function body. | [
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Args:
error: The function to call with any errors found.
filename: The name of the current file.
linenum: The number of the line to check.
"""
if Match(r'T(EST|est)', self.current_function):
base_trigger = self._TEST_TRIGGER
else:
base_trigger = self._NORMAL_TRIGGER
trigger = base_trigger * 2**_VerboseLevel()
if self.lines_in_function > trigger:
error_level = int(math.log(self.lines_in_function / base_trigger, 2))
# 50 => 0, 100 => 1, 200 => 2, 400 => 3, 800 => 4, 1600 => 5, ...
if error_level > 5:
error_level = 5
error(filename, linenum, 'readability/fn_size', error_level,
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self.current_function, self.lines_in_function, trigger)) | [
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||
google/usd_from_gltf | 6d288cce8b68744494a226574ae1d7ba6a9c46eb | tools/ufgbatch/ufgcommon/diff.py | python | handle_crc_difference | (golden_zip, golden_info, test_zip, test_info) | Returns results of more relaxed comparisons for the files. | Returns results of more relaxed comparisons for the files. | [
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"relaxed",
"comparisons",
"for",
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"files",
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] | def handle_crc_difference(golden_zip, golden_info, test_zip, test_info):
"""Returns results of more relaxed comparisons for the files."""
try:
with golden_zip.open(golden_info) as golden, test_zip.open(
test_info) as test:
return compare_images(golden, test)
except IOError:
# Non-images always return false.
return False | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/tools/gyp/pylib/gyp/xcode_emulation.py | python | XcodeSettings.GetWrapperName | (self) | return self.GetProductName() + self.GetWrapperExtension() | Returns the directory name of the bundle represented by this target.
Only valid for bundles. | Returns the directory name of the bundle represented by this target.
Only valid for bundles. | [
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"""Returns the directory name of the bundle represented by this target.
Only valid for bundles."""
assert self._IsBundle()
return self.GetProductName() + self.GetWrapperExtension() | [
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|
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/tensor_array_ops.py | python | _GraphTensorArrayV2.split | (self, value, lengths, name=None) | See TensorArray. | See TensorArray. | [
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] | def split(self, value, lengths, name=None):
"""See TensorArray."""
with ops.name_scope(name, "TensorArraySplit", [self._flow, value, lengths]):
# TODO(b/129870929): Fix after all callers provide proper init dtype.
value = ops.convert_to_tensor(
value, preferred_dtype=self._dtype, name="value")
_check_dtypes(value, self._dtype)
lengths_64 = math_ops.cast(lengths, dtypes.int64)
if not context.executing_eagerly():
clengths = tensor_util.constant_value(lengths_64)
if value.shape.dims is not None and clengths is not None:
if clengths.shape and clengths.max() == clengths.min():
self._check_element_shape(
tensor_shape.TensorShape([clengths[0]
]).concatenate(value.shape[1:]))
flow_out = list_ops.tensor_list_split(
tensor=value,
lengths=lengths_64,
element_shape=self.element_shape,
name=name)
return build_ta_with_new_flow(self, flow_out) | [
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||
LiXizhi/NPLRuntime | a42720e5fe9a6960e0a9ce40bbbcd809192906be | Server/trunk/flann-1.8.4-src/src/python/pyflann/index.py | python | FLANN.save_index | (self, filename) | This saves the index to a disk file. | This saves the index to a disk file. | [
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"the",
"index",
"to",
"a",
"disk",
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] | def save_index(self, filename):
"""
This saves the index to a disk file.
"""
if self.__curindex != None:
flann.save_index[self.__curindex_type](self.__curindex, c_char_p(to_bytes(filename))) | [
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||
snap-stanford/snap-python | d53c51b0a26aa7e3e7400b014cdf728948fde80a | setup/snap.py | python | TUCh.__lt__ | (self, *args) | return _snap.TUCh___lt__(self, *args) | __lt__(TUCh self, TUCh UCh) -> bool
Parameters:
UCh: TUCh const & | __lt__(TUCh self, TUCh UCh) -> bool | [
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"""
__lt__(TUCh self, TUCh UCh) -> bool
Parameters:
UCh: TUCh const &
"""
return _snap.TUCh___lt__(self, *args) | [
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|
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/win32comext/axdebug/gateways.py | python | DebugDocumentContext.GetDocument | (self) | Return value must be a PyIDebugDocument object | Return value must be a PyIDebugDocument object | [
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"""Return value must be a PyIDebugDocument object
"""
RaiseNotImpl("GetDocument") | [
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||
pyne/pyne | 0c2714d7c0d1b5e20be6ae6527da2c660dd6b1b3 | pyne/mcnp.py | python | Xsdir.find_table | (self, name) | return tables | Find all tables for a given ZIAD.
Parameters
----------
name : str
The ZIAD name.
Returns
-------
tables : list
All XsdirTable objects for a given ZIAD. | Find all tables for a given ZIAD. | [
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] | def find_table(self, name):
"""Find all tables for a given ZIAD.
Parameters
----------
name : str
The ZIAD name.
Returns
-------
tables : list
All XsdirTable objects for a given ZIAD.
"""
tables = []
for table in self:
if name in table.name:
tables.append(table)
return tables | [
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|
metashell/metashell | f4177e4854ea00c8dbc722cadab26ef413d798ea | 3rd/templight/clang/tools/scan-build-py/libscanbuild/report.py | python | reindent | (text, indent) | return result | Utility function to format html output and keep indentation. | Utility function to format html output and keep indentation. | [
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""" Utility function to format html output and keep indentation. """
result = ''
for line in text.splitlines():
if len(line.strip()):
result += ' ' * indent + line.split('|')[1] + os.linesep
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/build/waf-1.7.13/waflib/Runner.py | python | TaskConsumer.loop | (self) | Obtain tasks from :py:attr:`waflib.Runner.TaskConsumer.ready` and call
:py:meth:`waflib.Task.TaskBase.process`. If the object is a function, execute it. | Obtain tasks from :py:attr:`waflib.Runner.TaskConsumer.ready` and call
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"""
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"""
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if not isinstance(tsk, Task.TaskBase):
tsk(self)
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||
apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/numpy/multiarray.py | python | atleast_1d | (*arys) | return _mx_nd_np.atleast_1d(*res) | Convert inputs to arrays with at least one dimension.
Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved.
Parameters
----------
arys1, arys2, ... : ndarray
One or more input arrays.
Returns
-------
ret : ndarray
An array, or list of arrays, each with a.ndim >= 1. Copies are made only if necessary.
See also
--------
atleast_2d, atleast_3d
Examples
--------
>>> np.atleast_1d(1.0)
array([1.])
>>> x = np.arange(9.0).reshape(3,3)
>>> np.atleast_1d(x)
array([[0., 1., 2.],
[3., 4., 5.],
[6., 7., 8.]])
>>> np.atleast_1d(np.array(1), np.array([3, 4]))
[array([1.]), array([3., 4.])] | Convert inputs to arrays with at least one dimension. | [
"Convert",
"inputs",
"to",
"arrays",
"with",
"at",
"least",
"one",
"dimension",
"."
] | def atleast_1d(*arys):
"""
Convert inputs to arrays with at least one dimension.
Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved.
Parameters
----------
arys1, arys2, ... : ndarray
One or more input arrays.
Returns
-------
ret : ndarray
An array, or list of arrays, each with a.ndim >= 1. Copies are made only if necessary.
See also
--------
atleast_2d, atleast_3d
Examples
--------
>>> np.atleast_1d(1.0)
array([1.])
>>> x = np.arange(9.0).reshape(3,3)
>>> np.atleast_1d(x)
array([[0., 1., 2.],
[3., 4., 5.],
[6., 7., 8.]])
>>> np.atleast_1d(np.array(1), np.array([3, 4]))
[array([1.]), array([3., 4.])]
"""
res = []
for ary in arys:
if not isinstance(ary, NDArray):
ary = array(ary)
res.append(ary)
return _mx_nd_np.atleast_1d(*res) | [
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0ad/0ad | f58db82e0e925016d83f4e3fa7ca599e3866e2af | source/tools/i18n/extractors/jslexer.py | python | indicates_division | (token) | return token.type in ('name', 'number', 'string', 'regexp') | A helper function that helps the tokenizer to decide if the current
token may be followed by a division operator. | A helper function that helps the tokenizer to decide if the current
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] | def indicates_division(token):
"""A helper function that helps the tokenizer to decide if the current
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"""
if token.type == 'operator':
return token.value in (')', ']', '}', '++', '--')
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|
SIPp/sipp | f44d0cf5dec0013eff8fd7b4da885d455aa82e0e | cpplint.py | python | CheckEmptyLoopBody | (filename, clean_lines, linenum, error) | Loop for empty loop body with only a single semicolon.
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. | Loop for empty loop body with only a single semicolon. | [
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] | def CheckEmptyLoopBody(filename, clean_lines, linenum, error):
"""Loop for empty loop body with only a single semicolon.
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.
"""
# Search for loop keywords at the beginning of the line. Because only
# whitespaces are allowed before the keywords, this will also ignore most
# do-while-loops, since those lines should start with closing brace.
line = clean_lines.elided[linenum]
if Match(r'\s*(for|while)\s*\(', line):
# Find the end of the conditional expression
(end_line, end_linenum, end_pos) = CloseExpression(
clean_lines, linenum, line.find('('))
# Output warning if what follows the condition expression is a semicolon.
# No warning for all other cases, including whitespace or newline, since we
# have a separate check for semicolons preceded by whitespace.
if end_pos >= 0 and Match(r';', end_line[end_pos:]):
error(filename, end_linenum, 'whitespace/empty_loop_body', 5,
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||
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/debug/lib/debug_graphs.py | python | DebugGraph._prune_nodes_from_input_and_recipient_maps | (self, nodes_to_prune) | Prune nodes out of input and recipient maps.
Args:
nodes_to_prune: (`list` of `str`) Names of the nodes to be pruned. | Prune nodes out of input and recipient maps. | [
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"input",
"and",
"recipient",
"maps",
"."
] | def _prune_nodes_from_input_and_recipient_maps(self, nodes_to_prune):
"""Prune nodes out of input and recipient maps.
Args:
nodes_to_prune: (`list` of `str`) Names of the nodes to be pruned.
"""
for node in nodes_to_prune:
del self._node_inputs[node]
del self._node_ctrl_inputs[node]
del self._node_recipients[node]
del self._node_ctrl_recipients[node] | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/stc.py | python | StyledTextCtrl.StyleSetFaceName | (*args, **kwargs) | return _stc.StyledTextCtrl_StyleSetFaceName(*args, **kwargs) | StyleSetFaceName(self, int style, String fontName)
Set the font of a style. | StyleSetFaceName(self, int style, String fontName) | [
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] | def StyleSetFaceName(*args, **kwargs):
"""
StyleSetFaceName(self, int style, String fontName)
Set the font of a style.
"""
return _stc.StyledTextCtrl_StyleSetFaceName(*args, **kwargs) | [
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | parserCtxt.parseVersionNum | (self) | return ret | parse the XML version value. [26] VersionNum ::= '1.'
[0-9]+ In practice allow [0-9].[0-9]+ at that level | parse the XML version value. [26] VersionNum ::= '1.'
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] | def parseVersionNum(self):
"""parse the XML version value. [26] VersionNum ::= '1.'
[0-9]+ In practice allow [0-9].[0-9]+ at that level """
ret = libxml2mod.xmlParseVersionNum(self._o)
return ret | [
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|
GJDuck/LowFat | ecf6a0f0fa1b73a27a626cf493cc39e477b6faea | llvm-4.0.0.src/utils/llvm-build/llvmbuild/configutil.py | python | configure_file | (input_path, output_path, substitutions) | return True | configure_file(input_path, output_path, substitutions) -> bool
Given an input and output path, "configure" the file at the given input path
by replacing variables in the file with those given in the substitutions
list. Returns true if the output file was written.
The substitutions list should be given as a list of tuples (regex string,
replacement), where the regex and replacement will be used as in 're.sub' to
execute the variable replacement.
The output path's parent directory need not exist (it will be created).
If the output path does exist and the configured data is not different than
it's current contents, the output file will not be modified. This is
designed to limit the impact of configured files on build dependencies. | configure_file(input_path, output_path, substitutions) -> bool | [
"configure_file",
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"-",
">",
"bool"
] | def configure_file(input_path, output_path, substitutions):
"""configure_file(input_path, output_path, substitutions) -> bool
Given an input and output path, "configure" the file at the given input path
by replacing variables in the file with those given in the substitutions
list. Returns true if the output file was written.
The substitutions list should be given as a list of tuples (regex string,
replacement), where the regex and replacement will be used as in 're.sub' to
execute the variable replacement.
The output path's parent directory need not exist (it will be created).
If the output path does exist and the configured data is not different than
it's current contents, the output file will not be modified. This is
designed to limit the impact of configured files on build dependencies.
"""
# Read in the input data.
f = open(input_path, "rb")
try:
data = f.read()
finally:
f.close()
# Perform the substitutions.
for regex_string,replacement in substitutions:
regex = re.compile(regex_string)
data = regex.sub(replacement, data)
# Ensure the output parent directory exists.
output_parent_path = os.path.dirname(os.path.abspath(output_path))
if not os.path.exists(output_parent_path):
os.makedirs(output_parent_path)
# If the output path exists, load it and compare to the configured contents.
if os.path.exists(output_path):
current_data = None
try:
f = open(output_path, "rb")
try:
current_data = f.read()
except:
current_data = None
f.close()
except:
current_data = None
if current_data is not None and current_data == data:
return False
# Write the output contents.
f = open(output_path, "wb")
try:
f.write(data)
finally:
f.close()
return True | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemPlayerAccount/AWS/resource-manager-code/pa_service_api.py | python | command_reset_player_password | (context, args) | Reset a player's password | Reset a player's password | [
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"a",
"player",
"s",
"password"
] | def command_reset_player_password(context, args) -> None:
"""
Reset a player's password
"""
client = __get_service_api_client(context, args)
try:
response = client.navigate('admin', 'identityProviders', 'Cognito',
'users', __encode_query_parameter(args.username), 'resetUserPassword').POST(body=None)
pprint.pprint(response.DATA)
except cgf_service_client.error.NotFoundError as nfe:
print(f"[Error] {args.username} not found. {str(nfe)}") | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/slim/python/slim/data/data_provider.py | python | DataProvider._validate_items | (self, items) | Verifies that each given item is a member of the list from ListItems().
Args:
items: a list or tuple of strings.
Raises:
ValueError: if `items` is not a tuple or list or if any of the elements of
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Args:
items: a list or tuple of strings.
Raises:
ValueError: if `items` is not a tuple or list or if any of the elements of
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"""
if not isinstance(items, (list, tuple)):
raise ValueError('items must be a list or tuple')
valid_items = self.list_items()
for item in items:
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tkn-tub/ns3-gym | 19bfe0a583e641142609939a090a09dfc63a095f | utils/check-style.py | python | PatchChunkLine.set_src | (self,line) | ! Set source
@param self The current class
@param line source line
@return none | ! Set source | [
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] | def set_src(self,line):
"""! Set source
@param self The current class
@param line source line
@return none
"""
self.__type = self.SRC
self.__line = line | [
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||
ROCmSoftwarePlatform/hipCaffe | 4ec5d482515cce532348553b6db6d00d015675d5 | scripts/cpp_lint.py | python | _SetOutputFormat | (output_format) | Sets the module's output format. | Sets the module's output format. | [
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||
eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/config/configobj.py | python | Section.popitem | (self) | return key, val | Pops the first (key,val) | Pops the first (key,val) | [
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"""Pops the first (key,val)"""
sequence = (self.scalars + self.sections)
if not sequence:
raise KeyError, ": 'popitem(): dictionary is empty'"
key = sequence[0]
val = self[key]
del self[key]
return key, val | [
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|
mhammond/pywin32 | 44afd86ba8485194df93234639243252deeb40d5 | Pythonwin/pywin/mfc/dialog.py | python | PropertySheet.DoAddSinglePage | (self, page) | Page may be page, or int ID. Assumes DLL setup | Page may be page, or int ID. Assumes DLL setup | [
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if type(page) == type(0):
self.sheet.AddPage(win32ui.CreatePropertyPage(page))
else:
self.sheet.AddPage(page) | [
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||
ArduPilot/ardupilot | 6e684b3496122b8158ac412b609d00004b7ac306 | libraries/AP_MSP/Tools/msposd.py | python | display_text | (item, message, x_offset=0) | display a string message for an item | display a string message for an item | [
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'''display a string message for an item'''
XY = item_to_pos(item)
if XY is None:
return
(X,Y) = XY
text = font.render(message, True, white, black)
textRect = text.get_rect()
slen = len(message)
px = X * FontWidth + x_offset
py = Y * FontHeight
textRect.center = (px+textRect.width//2, py+textRect.height//2)
display_surface.blit(text, textRect) | [
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||
Kitware/ParaView | f760af9124ff4634b23ebbeab95a4f56e0261955 | Plugins/pvblot/blotish.py | python | rotate | (*rotations) | Rotates the 3D mesh. Each (axis, ndeg) parameter pair specifies an
axis of rotation (x, y, or z) or (elevation, azimuth, or roll) and the
number of degrees to rotate. The axes have the following meanings:
* x or elevation: rotate the camera around the focal point in the
horizontal direction.
* y or azimuth: rotate the camera around the focal point in the vertical
direction.
* z or roll: roll the camera about the view direction.
The identifiers elevation, azimuth, and roll can be abbreviated with any
unique prefix. | Rotates the 3D mesh. Each (axis, ndeg) parameter pair specifies an
axis of rotation (x, y, or z) or (elevation, azimuth, or roll) and the
number of degrees to rotate. The axes have the following meanings: | [
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"""
Rotates the 3D mesh. Each (axis, ndeg) parameter pair specifies an
axis of rotation (x, y, or z) or (elevation, azimuth, or roll) and the
number of degrees to rotate. The axes have the following meanings:
* x or elevation: rotate the camera around the focal point in the
horizontal direction.
* y or azimuth: rotate the camera around the focal point in the vertical
direction.
* z or roll: roll the camera about the view direction.
The identifiers elevation, azimuth, and roll can be abbreviated with any
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"""
camera = paraview.simple.GetActiveCamera()
# Some manging to rotation into list of pairs.
rpairs = zip(rotations[::2], rotations[1::2])
for axis, degrees in rpairs:
axis = axis.lower()
degrees = float(degrees)
if axis == x or elevation.startswith(axis):
sign = degrees/abs(degrees)
degrees = abs(degrees)
while degrees > 0:
d = min(45, degrees)
degrees = degrees - d
camera.Elevation(sign*d)
camera.OrthogonalizeViewUp()
elif axis == y or azimuth.startswith(axis):
camera.Azimuth(-degrees)
elif axis == z or roll.startswith(axis):
camera.Roll(degrees)
else:
print "Unknown axis: ", axis
_finish_plot_change() | [
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||
apiaryio/snowcrash | b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3 | tools/gyp/pylib/gyp/xcodeproj_file.py | python | XCConfigurationList.HasBuildSetting | (self, key) | return 1 | Determines the state of a build setting in all XCBuildConfiguration
child objects.
If all child objects have key in their build settings, and the value is the
same in all child objects, returns 1.
If no child objects have the key in their build settings, returns 0.
If some, but not all, child objects have the key in their build settings,
or if any children have different values for the key, returns -1. | Determines the state of a build setting in all XCBuildConfiguration
child objects. | [
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] | def HasBuildSetting(self, key):
"""Determines the state of a build setting in all XCBuildConfiguration
child objects.
If all child objects have key in their build settings, and the value is the
same in all child objects, returns 1.
If no child objects have the key in their build settings, returns 0.
If some, but not all, child objects have the key in their build settings,
or if any children have different values for the key, returns -1.
"""
has = None
value = None
for configuration in self._properties['buildConfigurations']:
configuration_has = configuration.HasBuildSetting(key)
if has is None:
has = configuration_has
elif has != configuration_has:
return -1
if configuration_has:
configuration_value = configuration.GetBuildSetting(key)
if value is None:
value = configuration_value
elif value != configuration_value:
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return 1 | [
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|
google/clif | cab24d6a105609a65c95a36a1712ae3c20c7b5df | clif/python/pyext.py | python | Module.GenerateBase | (self, ast, more_headers) | Extension module generation. | Extension module generation. | [
"Extension",
"module",
"generation",
"."
] | def GenerateBase(self, ast, more_headers):
"""Extension module generation."""
ast_manipulations.MoveExtendsBackIntoClassesInPlace(ast)
self.init += ast.extra_init
for s in gen.Headlines(
ast.source,
[
'PYTHON', 'absl/memory/memory.h',
'absl/types/optional.h'
] + more_headers +
# Container templates calling PyObj* go last.
[
'clif/python/stltypes.h',
'clif/python/slots.h'
],
open_ns=self.wrap_namespace):
yield s
yield ''
yield 'using namespace clif;'
yield ''
yield 'static const char* ThisModuleName = "%s";' % self.path
for s in postconv.GenPostConvTable(self.typemap):
yield s
if astutils.HaveEnum(ast.decls):
yield ''
yield 'static PyObject *_Enum{}, *_IntEnum{}; // set below in Init()'
self.catch_cpp_exceptions = ast.catch_exceptions
for d in ast.decls:
for s in self.WrapDecl(d):
yield s
assert not self.nested, 'decl stack not exhausted (in GenBase)'
yield ''
yield '// Initialize module'
if self.methods:
for s in gen.MethodDef(self.methods):
yield s
for s in self.GenTypesReady(): # extends self.init
yield s
for s in self.GenInitFunction(ast.source): # consumes self.init
yield s
yield ''
yield '} // namespace %s' % self.wrap_namespace
if self.types:
# Assumed we always want a deterministic output. Since dict/set order
# is not, do sorted() order traversal.
#
# Save sorted types for GenerateHeader.
self.types = sorted(self.types, key=types.Order)
for ns, ts in itertools.groupby(self.types, types.Namespace):
for s in gen.TypeConverters(ns, ts, self.wrap_namespace):
yield s
if self.static_init:
for s in gen.PyModInitFunction(
init_name=self.static_init,
ns=self.wrap_namespace):
yield s | [
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||
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/re2/lib/codereview/codereview.py | python | AbstractRpcServer._CreateRequest | (self, url, data=None) | return req | Creates a new urllib request. | Creates a new urllib request. | [
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"a",
"new",
"urllib",
"request",
"."
] | def _CreateRequest(self, url, data=None):
"""Creates a new urllib request."""
logging.debug("Creating request for: '%s' with payload:\n%s", url, data)
req = urllib2.Request(url, data=data)
if self.host_override:
req.add_header("Host", self.host_override)
for key, value in self.extra_headers.iteritems():
req.add_header(key, value)
return req | [
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|
okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_vendor/distlib/locators.py | python | Locator.prefer_url | (self, url1, url2) | return result | Choose one of two URLs where both are candidates for distribution
archives for the same version of a distribution (for example,
.tar.gz vs. zip).
The current implementation favours https:// URLs over http://, archives
from PyPI over those from other locations, wheel compatibility (if a
wheel) and then the archive name. | Choose one of two URLs where both are candidates for distribution
archives for the same version of a distribution (for example,
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"""
Choose one of two URLs where both are candidates for distribution
archives for the same version of a distribution (for example,
.tar.gz vs. zip).
The current implementation favours https:// URLs over http://, archives
from PyPI over those from other locations, wheel compatibility (if a
wheel) and then the archive name.
"""
result = url2
if url1:
s1 = self.score_url(url1)
s2 = self.score_url(url2)
if s1 > s2:
result = url1
if result != url2:
logger.debug('Not replacing %r with %r', url1, url2)
else:
logger.debug('Replacing %r with %r', url1, url2)
return result | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/grid.py | python | Grid.EnableDragCell | (*args, **kwargs) | return _grid.Grid_EnableDragCell(*args, **kwargs) | EnableDragCell(self, bool enable=True) | EnableDragCell(self, bool enable=True) | [
"EnableDragCell",
"(",
"self",
"bool",
"enable",
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] | def EnableDragCell(*args, **kwargs):
"""EnableDragCell(self, bool enable=True)"""
return _grid.Grid_EnableDragCell(*args, **kwargs) | [
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|
htcondor/htcondor | 4829724575176d1d6c936e4693dfd78a728569b0 | src/condor_scripts/gdrive_plugin.py | python | parse_args | () | return {'infile': infile, 'outfile': outfile, 'upload': is_upload} | The optparse library can't handle the types of arguments that the file
transfer plugin sends, the argparse library can't be expected to be
found on machines running EL 6 (Python 2.6), and a plugin should not
reach outside the standard library, so the plugin must roll its own argument
parser. The expected input is very rigid, so this isn't too awful. | The optparse library can't handle the types of arguments that the file
transfer plugin sends, the argparse library can't be expected to be
found on machines running EL 6 (Python 2.6), and a plugin should not
reach outside the standard library, so the plugin must roll its own argument
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'''The optparse library can't handle the types of arguments that the file
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found on machines running EL 6 (Python 2.6), and a plugin should not
reach outside the standard library, so the plugin must roll its own argument
parser. The expected input is very rigid, so this isn't too awful.'''
# The only argument lists that are acceptable are
# <this> -classad
# <this> -infile <input-filename> -outfile <output-filename>
# <this> -outfile <output-filename> -infile <input-filename>
if not len(sys.argv) in [2, 5, 6]:
print_help()
sys.exit(1)
# If -classad, print the capabilities of the plugin and exit early
elif (len(sys.argv) == 2) and (sys.argv[1] == '-classad'):
print_capabilities()
sys.exit(0)
# If -upload, set is_upload to True and remove it from the args list
is_upload = False
if '-upload' in sys.argv[1:]:
is_upload = True
sys.argv.remove('-upload')
# -infile and -outfile must be in the first and third position
if not (
('-infile' in sys.argv[1:]) and
('-outfile' in sys.argv[1:]) and
(sys.argv[1] in ['-infile', '-outfile']) and
(sys.argv[3] in ['-infile', '-outfile']) and
(len(sys.argv) == 5)):
print_help()
sys.exit(1)
infile = None
outfile = None
try:
for i, arg in enumerate(sys.argv):
if i == 0:
continue
elif arg == '-infile':
infile = sys.argv[i+1]
elif arg == '-outfile':
outfile = sys.argv[i+1]
except IndexError:
print_help()
sys.exit(1)
return {'infile': infile, 'outfile': outfile, 'upload': is_upload} | [
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|
ceph/ceph | 959663007321a369c83218414a29bd9dbc8bda3a | qa/tasks/ceph_manager.py | python | CephManager.get_osd_df | (self, osdid) | return j['nodes'][0] | Get the osd df stats | Get the osd df stats | [
"Get",
"the",
"osd",
"df",
"stats"
] | def get_osd_df(self, osdid):
"""
Get the osd df stats
"""
out = self.raw_cluster_cmd('osd', 'df', 'name', 'osd.{}'.format(osdid),
'--format=json')
j = json.loads('\n'.join(out.split('\n')[1:]))
return j['nodes'][0] | [
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|
OpenChemistry/tomviz | 0a903679318f191cb7dd3eb5ff5bc3a7d3320d9a | tomviz/python/tomviz/operators.py | python | Progress.value | (self, value) | Updates the progress of the the operator.
:param value The current progress value.
:type value: int | Updates the progress of the the operator. | [
"Updates",
"the",
"progress",
"of",
"the",
"the",
"operator",
"."
] | def value(self, value):
"""
Updates the progress of the the operator.
:param value The current progress value.
:type value: int
"""
self._operator._operator_wrapper.progress_value = value | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/xml/etree/ElementTree.py | python | Comment | (text=None) | return element | Comment element factory.
This function creates a special element which the standard serializer
serializes as an XML comment.
*text* is a string containing the comment string. | Comment element factory. | [
"Comment",
"element",
"factory",
"."
] | def Comment(text=None):
"""Comment element factory.
This function creates a special element which the standard serializer
serializes as an XML comment.
*text* is a string containing the comment string.
"""
element = Element(Comment)
element.text = text
return element | [
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|
facebook/redex | fac189a289bca2647061f9e364016afc1096500d | tools/python/dex.py | python | Progard.lookup_class | (self, new_class) | return None | Translate a new class name to the old class name. | Translate a new class name to the old class name. | [
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"a",
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"class",
"name",
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] | def lookup_class(self, new_class):
"""Translate a new class name to the old class name."""
if new_class in self.classes_dict:
(old_class, class_dict) = self.classes_dict[new_class]
if old_class is not None:
return old_class
return None | [
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|
bundy-dns/bundy | 3d41934996b82b0cd2fe22dd74d2abc1daba835d | src/bin/bundyctl/moduleinfo.py | python | CommandInfo.command_help | (self) | Prints the help info for this command to stdout | Prints the help info for this command to stdout | [
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] | def command_help(self):
"""Prints the help info for this command to stdout"""
print("Command ", self)
print("\t\thelp (Get help for command)")
params = self.params.copy()
del params["help"]
if len(params) == 0:
print("This command has no parameters")
return
print("Parameters:")
for info in params.values():
print(" %s" % info.get_basic_info())
description = info.get_desc()
if description != "":
print(textwrap.fill(description,
initial_indent=" ",
subsequent_indent=" ",
width=70)) | [
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||
GarageGames/Torque2D | 72c8891f192b44d58a8bd5ec2b293a3b48a818f4 | engine/lib/freetype/android/freetype-2.4.12/src/tools/glnames.py | python | adobe_glyph_values | () | return glyphs, values | return the list of glyph names and their unicode values | return the list of glyph names and their unicode values | [
"return",
"the",
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"of",
"glyph",
"names",
"and",
"their",
"unicode",
"values"
] | def adobe_glyph_values():
"""return the list of glyph names and their unicode values"""
lines = string.split( adobe_glyph_list, '\n' )
glyphs = []
values = []
for line in lines:
if line:
fields = string.split( line, ';' )
# print fields[1] + ' - ' + fields[0]
subfields = string.split( fields[1], ' ' )
if len( subfields ) == 1:
glyphs.append( fields[0] )
values.append( fields[1] )
return glyphs, values | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/setuptools/command/easy_install.py | python | WindowsScriptWriter.best | (cls) | return writer_lookup[launcher] | Select the best ScriptWriter suitable for Windows | Select the best ScriptWriter suitable for Windows | [
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] | def best(cls):
"""
Select the best ScriptWriter suitable for Windows
"""
writer_lookup = dict(
executable=WindowsExecutableLauncherWriter,
natural=cls,
)
# for compatibility, use the executable launcher by default
launcher = os.environ.get('SETUPTOOLS_LAUNCHER', 'executable')
return writer_lookup[launcher] | [
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|
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Builder.py | python | BuilderBase.subst_src_suffixes | (self, env) | return suffixes | The suffix list may contain construction variable expansions,
so we have to evaluate the individual strings. To avoid doing
this over and over, we memoize the results for each construction
environment. | The suffix list may contain construction variable expansions,
so we have to evaluate the individual strings. To avoid doing
this over and over, we memoize the results for each construction
environment. | [
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"""
The suffix list may contain construction variable expansions,
so we have to evaluate the individual strings. To avoid doing
this over and over, we memoize the results for each construction
environment.
"""
memo_key = id(env)
try:
memo_dict = self._memo['subst_src_suffixes']
except KeyError:
memo_dict = {}
self._memo['subst_src_suffixes'] = memo_dict
else:
try:
return memo_dict[memo_key]
except KeyError:
pass
suffixes = [env.subst(x) for x in self.src_suffix]
memo_dict[memo_key] = suffixes
return suffixes | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/metrics/metric.py | python | Metric.set_indexes | (self, indexes) | return self | This interface is to rearrange the inputs of `update`.
Given (label0, label1, logits), set the `indexes` to [2, 1] then the (logits, label1) will be the actually
inputs of `update`.
Note:
When customize a metric, decorate the `update` function with the decorator
:func:`mindspore.nn.rearrange_inputs` for the `indexes` to take effect.
Args:
indexes (List(int)): The order of logits and labels to be rearranged.
Outputs:
:class:`Metric`, its original Class instance.
Examples:
>>> import numpy as np
>>> from mindspore import nn, Tensor
>>>
>>> x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]]))
>>> y = Tensor(np.array([1, 0, 1]))
>>> y2 = Tensor(np.array([0, 0, 1]))
>>> metric = nn.Accuracy('classification').set_indexes([0, 2])
>>> metric.clear()
>>> # indexes is [0, 2], using x as logits, y2 as label.
>>> metric.update(x, y, y2)
>>> accuracy = metric.eval()
>>> print(accuracy)
0.3333333333333333 | This interface is to rearrange the inputs of `update`. | [
"This",
"interface",
"is",
"to",
"rearrange",
"the",
"inputs",
"of",
"update",
"."
] | def set_indexes(self, indexes):
"""
This interface is to rearrange the inputs of `update`.
Given (label0, label1, logits), set the `indexes` to [2, 1] then the (logits, label1) will be the actually
inputs of `update`.
Note:
When customize a metric, decorate the `update` function with the decorator
:func:`mindspore.nn.rearrange_inputs` for the `indexes` to take effect.
Args:
indexes (List(int)): The order of logits and labels to be rearranged.
Outputs:
:class:`Metric`, its original Class instance.
Examples:
>>> import numpy as np
>>> from mindspore import nn, Tensor
>>>
>>> x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]]))
>>> y = Tensor(np.array([1, 0, 1]))
>>> y2 = Tensor(np.array([0, 0, 1]))
>>> metric = nn.Accuracy('classification').set_indexes([0, 2])
>>> metric.clear()
>>> # indexes is [0, 2], using x as logits, y2 as label.
>>> metric.update(x, y, y2)
>>> accuracy = metric.eval()
>>> print(accuracy)
0.3333333333333333
"""
if not isinstance(indexes, list) or not all(isinstance(i, int) for i in indexes):
raise ValueError("For 'set_indexes', the argument 'indexes' should be a list and all its elements should "
"be int, please check whether it is correct.")
self._indexes = indexes
return self | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/polynomial/polyutils.py | python | getdomain | (x) | Return a domain suitable for given abscissae.
Find a domain suitable for a polynomial or Chebyshev series
defined at the values supplied.
Parameters
----------
x : array_like
1-d array of abscissae whose domain will be determined.
Returns
-------
domain : ndarray
1-d array containing two values. If the inputs are complex, then
the two returned points are the lower left and upper right corners
of the smallest rectangle (aligned with the axes) in the complex
plane containing the points `x`. If the inputs are real, then the
two points are the ends of the smallest interval containing the
points `x`.
See Also
--------
mapparms, mapdomain
Examples
--------
>>> from numpy.polynomial import polyutils as pu
>>> points = np.arange(4)**2 - 5; points
array([-5, -4, -1, 4])
>>> pu.getdomain(points)
array([-5., 4.])
>>> c = np.exp(complex(0,1)*np.pi*np.arange(12)/6) # unit circle
>>> pu.getdomain(c)
array([-1.-1.j, 1.+1.j]) | Return a domain suitable for given abscissae. | [
"Return",
"a",
"domain",
"suitable",
"for",
"given",
"abscissae",
"."
] | def getdomain(x):
"""
Return a domain suitable for given abscissae.
Find a domain suitable for a polynomial or Chebyshev series
defined at the values supplied.
Parameters
----------
x : array_like
1-d array of abscissae whose domain will be determined.
Returns
-------
domain : ndarray
1-d array containing two values. If the inputs are complex, then
the two returned points are the lower left and upper right corners
of the smallest rectangle (aligned with the axes) in the complex
plane containing the points `x`. If the inputs are real, then the
two points are the ends of the smallest interval containing the
points `x`.
See Also
--------
mapparms, mapdomain
Examples
--------
>>> from numpy.polynomial import polyutils as pu
>>> points = np.arange(4)**2 - 5; points
array([-5, -4, -1, 4])
>>> pu.getdomain(points)
array([-5., 4.])
>>> c = np.exp(complex(0,1)*np.pi*np.arange(12)/6) # unit circle
>>> pu.getdomain(c)
array([-1.-1.j, 1.+1.j])
"""
[x] = as_series([x], trim=False)
if x.dtype.char in np.typecodes['Complex']:
rmin, rmax = x.real.min(), x.real.max()
imin, imax = x.imag.min(), x.imag.max()
return np.array((complex(rmin, imin), complex(rmax, imax)))
else:
return np.array((x.min(), x.max())) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | InfoBar.SetShowHideEffects | (*args, **kwargs) | return _controls_.InfoBar_SetShowHideEffects(*args, **kwargs) | SetShowHideEffects(self, int showEffect, int hideEffect) | SetShowHideEffects(self, int showEffect, int hideEffect) | [
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] | def SetShowHideEffects(*args, **kwargs):
"""SetShowHideEffects(self, int showEffect, int hideEffect)"""
return _controls_.InfoBar_SetShowHideEffects(*args, **kwargs) | [
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microsoft/clang | 86d4513d3e0daa4d5a29b0b1de7c854ca15f9fe5 | bindings/python/clang/cindex.py | python | Cursor.linkage | (self) | return LinkageKind.from_id(self._linkage) | Return the linkage of this cursor. | Return the linkage of this cursor. | [
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] | def linkage(self):
"""Return the linkage of this cursor."""
if not hasattr(self, '_linkage'):
self._linkage = conf.lib.clang_getCursorLinkage(self)
return LinkageKind.from_id(self._linkage) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/importlib/_bootstrap.py | python | _exec | (spec, module) | return module | Execute the spec's specified module in an existing module's namespace. | Execute the spec's specified module in an existing module's namespace. | [
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] | def _exec(spec, module):
"""Execute the spec's specified module in an existing module's namespace."""
name = spec.name
with _ModuleLockManager(name):
if sys.modules.get(name) is not module:
msg = 'module {!r} not in sys.modules'.format(name)
raise ImportError(msg, name=name)
try:
if spec.loader is None:
if spec.submodule_search_locations is None:
raise ImportError('missing loader', name=spec.name)
# Namespace package.
_init_module_attrs(spec, module, override=True)
else:
_init_module_attrs(spec, module, override=True)
if not hasattr(spec.loader, 'exec_module'):
# (issue19713) Once BuiltinImporter and ExtensionFileLoader
# have exec_module() implemented, we can add a deprecation
# warning here.
spec.loader.load_module(name)
else:
spec.loader.exec_module(module)
finally:
# Update the order of insertion into sys.modules for module
# clean-up at shutdown.
module = sys.modules.pop(spec.name)
sys.modules[spec.name] = module
return module | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py3/scipy/spatial/transform/rotation.py | python | Rotation.as_euler | (self, seq, degrees=False) | return angles[0] if self._single else angles | Represent as Euler angles.
Any orientation can be expressed as a composition of 3 elementary
rotations. Once the axis sequence has been chosen, Euler angles define
the angle of rotation around each respective axis [1]_.
The algorithm from [2]_ has been used to calculate Euler angles for the
rotation about a given sequence of axes.
Euler angles suffer from the problem of gimbal lock [3]_, where the
representation loses a degree of freedom and it is not possible to
determine the first and third angles uniquely. In this case,
a warning is raised, and the third angle is set to zero. Note however
that the returned angles still represent the correct rotation.
Parameters
----------
seq : string, length 3
3 characters belonging to the set {'X', 'Y', 'Z'} for intrinsic
rotations, or {'x', 'y', 'z'} for extrinsic rotations [1]_.
Adjacent axes cannot be the same.
Extrinsic and intrinsic rotations cannot be mixed in one function
call.
degrees : boolean, optional
Returned angles are in degrees if this flag is True, else they are
in radians. Default is False.
Returns
-------
angles : `numpy.ndarray`, shape (3,) or (N, 3)
Shape depends on shape of inputs used to initialize object.
The returned angles are in the range:
- First angle belongs to [-180, 180] degrees (both inclusive)
- Third angle belongs to [-180, 180] degrees (both inclusive)
- Second angle belongs to:
- [-90, 90] degrees if all axes are different (like xyz)
- [0, 180] degrees if first and third axes are the same
(like zxz)
References
----------
.. [1] `Euler angle definitions
<https://en.wikipedia.org/wiki/Euler_angles#Definition_by_intrinsic_rotations>`_
.. [2] Malcolm D. Shuster, F. Landis Markley
`General Formula for Euler Angles
<https://arc.aiaa.org/doi/abs/10.2514/1.16622>`_
.. [3] `Gimbal lock
<https://en.wikipedia.org/wiki/Gimbal_lock#In_applied_mathematics>`_
Examples
--------
>>> from scipy.spatial.transform import Rotation as R
Represent a single rotation:
>>> r = R.from_rotvec([0, 0, np.pi/2])
>>> r.as_euler('zxy', degrees=True)
array([90., 0., 0.])
>>> r.as_euler('zxy', degrees=True).shape
(3,)
Represent a stack of single rotation:
>>> r = R.from_rotvec([[0, 0, np.pi/2]])
>>> r.as_euler('zxy', degrees=True)
array([[90., 0., 0.]])
>>> r.as_euler('zxy', degrees=True).shape
(1, 3)
Represent multiple rotations in a single object:
>>> r = R.from_rotvec([
... [0, 0, np.pi/2],
... [0, -np.pi/3, 0],
... [np.pi/4, 0, 0]])
>>> r.as_euler('zxy', degrees=True)
array([[ 90., 0., 0.],
[ 0., 0., -60.],
[ 0., 45., 0.]])
>>> r.as_euler('zxy', degrees=True).shape
(3, 3) | Represent as Euler angles. | [
"Represent",
"as",
"Euler",
"angles",
"."
] | def as_euler(self, seq, degrees=False):
"""Represent as Euler angles.
Any orientation can be expressed as a composition of 3 elementary
rotations. Once the axis sequence has been chosen, Euler angles define
the angle of rotation around each respective axis [1]_.
The algorithm from [2]_ has been used to calculate Euler angles for the
rotation about a given sequence of axes.
Euler angles suffer from the problem of gimbal lock [3]_, where the
representation loses a degree of freedom and it is not possible to
determine the first and third angles uniquely. In this case,
a warning is raised, and the third angle is set to zero. Note however
that the returned angles still represent the correct rotation.
Parameters
----------
seq : string, length 3
3 characters belonging to the set {'X', 'Y', 'Z'} for intrinsic
rotations, or {'x', 'y', 'z'} for extrinsic rotations [1]_.
Adjacent axes cannot be the same.
Extrinsic and intrinsic rotations cannot be mixed in one function
call.
degrees : boolean, optional
Returned angles are in degrees if this flag is True, else they are
in radians. Default is False.
Returns
-------
angles : `numpy.ndarray`, shape (3,) or (N, 3)
Shape depends on shape of inputs used to initialize object.
The returned angles are in the range:
- First angle belongs to [-180, 180] degrees (both inclusive)
- Third angle belongs to [-180, 180] degrees (both inclusive)
- Second angle belongs to:
- [-90, 90] degrees if all axes are different (like xyz)
- [0, 180] degrees if first and third axes are the same
(like zxz)
References
----------
.. [1] `Euler angle definitions
<https://en.wikipedia.org/wiki/Euler_angles#Definition_by_intrinsic_rotations>`_
.. [2] Malcolm D. Shuster, F. Landis Markley
`General Formula for Euler Angles
<https://arc.aiaa.org/doi/abs/10.2514/1.16622>`_
.. [3] `Gimbal lock
<https://en.wikipedia.org/wiki/Gimbal_lock#In_applied_mathematics>`_
Examples
--------
>>> from scipy.spatial.transform import Rotation as R
Represent a single rotation:
>>> r = R.from_rotvec([0, 0, np.pi/2])
>>> r.as_euler('zxy', degrees=True)
array([90., 0., 0.])
>>> r.as_euler('zxy', degrees=True).shape
(3,)
Represent a stack of single rotation:
>>> r = R.from_rotvec([[0, 0, np.pi/2]])
>>> r.as_euler('zxy', degrees=True)
array([[90., 0., 0.]])
>>> r.as_euler('zxy', degrees=True).shape
(1, 3)
Represent multiple rotations in a single object:
>>> r = R.from_rotvec([
... [0, 0, np.pi/2],
... [0, -np.pi/3, 0],
... [np.pi/4, 0, 0]])
>>> r.as_euler('zxy', degrees=True)
array([[ 90., 0., 0.],
[ 0., 0., -60.],
[ 0., 45., 0.]])
>>> r.as_euler('zxy', degrees=True).shape
(3, 3)
"""
if len(seq) != 3:
raise ValueError("Expected 3 axes, got {}.".format(seq))
intrinsic = (re.match(r'^[XYZ]{1,3}$', seq) is not None)
extrinsic = (re.match(r'^[xyz]{1,3}$', seq) is not None)
if not (intrinsic or extrinsic):
raise ValueError("Expected axes from `seq` to be from "
"['x', 'y', 'z'] or ['X', 'Y', 'Z'], "
"got {}".format(seq))
if any(seq[i] == seq[i+1] for i in range(2)):
raise ValueError("Expected consecutive axes to be different, "
"got {}".format(seq))
seq = seq.lower()
angles = _compute_euler_from_dcm(self.as_dcm(), seq, extrinsic)
if degrees:
angles = np.rad2deg(angles)
return angles[0] if self._single else angles | [
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|
root-project/root | fcd3583bb14852bf2e8cd2415717cbaac0e75896 | bindings/pyroot/pythonizations/python/ROOT/_pythonization/_roofit/_rooabspdf.py | python | RooAbsPdf.plotOn | (self, *args, **kwargs) | return self._plotOn(*args, **kwargs) | r"""The RooAbsPdf::plotOn() function is pythonized with the command argument pythonization.
The keywords must correspond to the CmdArgs of the function. | r"""The RooAbsPdf::plotOn() function is pythonized with the command argument pythonization.
The keywords must correspond to the CmdArgs of the function. | [
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# Redefinition of `RooAbsPdf.plotOn` for keyword arguments.
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|
ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | mp/src/thirdparty/protobuf-2.3.0/python/mox.py | python | IsAlmost.__init__ | (self, float_value, places=7) | Initialize IsAlmost.
Args:
float_value: The value for making the comparison.
places: The number of decimal places to round to. | Initialize IsAlmost. | [
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"""Initialize IsAlmost.
Args:
float_value: The value for making the comparison.
places: The number of decimal places to round to.
"""
self._float_value = float_value
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||
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/ops/math_grad.py | python | _IgammaGrad | (op, grad) | return (None,
array_ops.reshape(math_ops.reduce_sum(partial_x * grad, rx), sx)) | Returns gradient of igamma(a, x) with respect to x. | Returns gradient of igamma(a, x) with respect to x. | [
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"""Returns gradient of igamma(a, x) with respect to x."""
# TODO(ebrevdo): Perhaps add the derivative w.r.t. a
a = op.inputs[0]
x = op.inputs[1]
sa = array_ops.shape(a)
sx = array_ops.shape(x)
unused_ra, rx = gen_array_ops._broadcast_gradient_args(sa, sx)
# Perform operations in log space before summing, because Gamma(a)
# and Gamma'(a) can grow large.
partial_x = math_ops.exp(-x + (a - 1) * math_ops.log(x) - math_ops.lgamma(a))
# TODO(b/36815900): Mark None return values as NotImplemented
return (None,
array_ops.reshape(math_ops.reduce_sum(partial_x * grad, rx), sx)) | [
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|
HKUST-Aerial-Robotics/Fast-Planner | 2ddd7793eecd573dbb5b47e2c985aa06606df3cf | uav_simulator/Utils/pose_utils/build/devel/_setup_util.py | python | rollback_env_variables | (environ, env_var_subfolders) | return lines | Generate shell code to reset environment variables
by unrolling modifications based on all workspaces in CMAKE_PREFIX_PATH.
This does not cover modifications performed by environment hooks. | Generate shell code to reset environment variables
by unrolling modifications based on all workspaces in CMAKE_PREFIX_PATH.
This does not cover modifications performed by environment hooks. | [
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'''
Generate shell code to reset environment variables
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This does not cover modifications performed by environment hooks.
'''
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unmodified_environ = copy.copy(environ)
for key in sorted(env_var_subfolders.keys()):
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if not isinstance(subfolders, list):
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for subfolder in subfolders:
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environ[key] = value
lines.append(assignment(key, value))
if lines:
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return lines | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/html.py | python | HtmlCell.GetLastTerminal | (*args, **kwargs) | return _html.HtmlCell_GetLastTerminal(*args, **kwargs) | GetLastTerminal(self) -> HtmlCell | GetLastTerminal(self) -> HtmlCell | [
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"""GetLastTerminal(self) -> HtmlCell"""
return _html.HtmlCell_GetLastTerminal(*args, **kwargs) | [
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|
Z3Prover/z3 | d745d03afdfdf638d66093e2bfbacaf87187f35b | src/api/python/z3/z3.py | python | Fixedpoint.help | (self) | Display a string describing all available options. | Display a string describing all available options. | [
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||
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/clip_ops.py | python | clip_by_global_norm | (t_list, clip_norm, use_norm=None, name=None) | return list_clipped, use_norm | Clips values of multiple tensors by the ratio of the sum of their norms.
Given a tuple or list of tensors `t_list`, and a clipping ratio `clip_norm`,
this operation returns a list of clipped tensors `list_clipped`
and the global norm (`global_norm`) of all tensors in `t_list`. Optionally,
if you've already computed the global norm for `t_list`, you can specify
the global norm with `use_norm`.
To perform the clipping, the values `t_list[i]` are set to:
t_list[i] * clip_norm / max(global_norm, clip_norm)
where:
global_norm = sqrt(sum([l2norm(t)**2 for t in t_list]))
If `clip_norm > global_norm` then the entries in `t_list` remain as they are,
otherwise they're all shrunk by the global ratio.
If `global_norm == infinity` then the entries in `t_list` are all set to `NaN`
to signal that an error occurred.
Any of the entries of `t_list` that are of type `None` are ignored.
This is the correct way to perform gradient clipping (Pascanu et al., 2012).
However, it is slower than `clip_by_norm()` because all the parameters must be
ready before the clipping operation can be performed.
Args:
t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None.
clip_norm: A 0-D (scalar) `Tensor` > 0. The clipping ratio.
use_norm: A 0-D (scalar) `Tensor` of type `float` (optional). The global
norm to use. If not provided, `global_norm()` is used to compute the norm.
name: A name for the operation (optional).
Returns:
list_clipped: A list of `Tensors` of the same type as `list_t`.
global_norm: A 0-D (scalar) `Tensor` representing the global norm.
Raises:
TypeError: If `t_list` is not a sequence.
References:
On the difficulty of training Recurrent Neural Networks:
[Pascanu et al., 2012](http://proceedings.mlr.press/v28/pascanu13.html)
([pdf](http://proceedings.mlr.press/v28/pascanu13.pdf)) | Clips values of multiple tensors by the ratio of the sum of their norms. | [
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"""Clips values of multiple tensors by the ratio of the sum of their norms.
Given a tuple or list of tensors `t_list`, and a clipping ratio `clip_norm`,
this operation returns a list of clipped tensors `list_clipped`
and the global norm (`global_norm`) of all tensors in `t_list`. Optionally,
if you've already computed the global norm for `t_list`, you can specify
the global norm with `use_norm`.
To perform the clipping, the values `t_list[i]` are set to:
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where:
global_norm = sqrt(sum([l2norm(t)**2 for t in t_list]))
If `clip_norm > global_norm` then the entries in `t_list` remain as they are,
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Any of the entries of `t_list` that are of type `None` are ignored.
This is the correct way to perform gradient clipping (Pascanu et al., 2012).
However, it is slower than `clip_by_norm()` because all the parameters must be
ready before the clipping operation can be performed.
Args:
t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None.
clip_norm: A 0-D (scalar) `Tensor` > 0. The clipping ratio.
use_norm: A 0-D (scalar) `Tensor` of type `float` (optional). The global
norm to use. If not provided, `global_norm()` is used to compute the norm.
name: A name for the operation (optional).
Returns:
list_clipped: A list of `Tensors` of the same type as `list_t`.
global_norm: A 0-D (scalar) `Tensor` representing the global norm.
Raises:
TypeError: If `t_list` is not a sequence.
References:
On the difficulty of training Recurrent Neural Networks:
[Pascanu et al., 2012](http://proceedings.mlr.press/v28/pascanu13.html)
([pdf](http://proceedings.mlr.press/v28/pascanu13.pdf))
"""
if (not isinstance(t_list, collections_abc.Sequence) or
isinstance(t_list, str)):
raise TypeError("`t_list` should be a sequence of tensors. Received "
f"{type(t_list)}.")
t_list = list(t_list)
if use_norm is None:
use_norm = global_norm(t_list, name)
with ops.name_scope(name, "clip_by_global_norm",
t_list + [clip_norm]) as name:
# Calculate L2-norm, clip elements by ratio of clip_norm to L2-norm
scale_for_finite = clip_norm * math_ops.minimum(
1.0 / use_norm,
constant_op.constant(1.0, dtype=use_norm.dtype) / clip_norm)
# If use_norm is any finite number, this is a no-op. For inf/-inf/NaN,
# this will make scale NaN.
scale = scale_for_finite + (use_norm - use_norm)
values = [
ops.convert_to_tensor(
t.values if isinstance(t, indexed_slices.IndexedSlices) else t,
name="t_%d" % i) if t is not None else t
for i, t in enumerate(t_list)
]
values_clipped = []
for i, v in enumerate(values):
if v is None:
values_clipped.append(None)
else:
with ops.colocate_with(v):
values_clipped.append(
array_ops.identity(v * scale, name="%s_%d" % (name, i)))
list_clipped = [
indexed_slices.IndexedSlices(c_v, t.indices, t.dense_shape)
if isinstance(t, indexed_slices.IndexedSlices) else c_v
for (c_v, t) in zip(values_clipped, t_list)
]
return list_clipped, use_norm | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/lowering.py | python | BaseLower.init_pyapi | (self) | Init the Python API and Environment Manager for the function being
lowered. | Init the Python API and Environment Manager for the function being
lowered. | [
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"""
Init the Python API and Environment Manager for the function being
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"""
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return
self.pyapi = self.context.get_python_api(self.builder)
# Store environment argument for later use
self.env_manager = self.context.get_env_manager(self.builder)
self.env_body = self.env_manager.env_body
self.envarg = self.env_manager.env_ptr | [
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] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/lowering.py#L125-L137 |
||
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/tools/gyp/pylib/gyp/MSVSVersion.py | python | _RegistryQuery | (key, value=None) | return text | Use reg.exe to read a particular key through _RegistryQueryBase.
First tries to launch from %WinDir%\Sysnative to avoid WoW64 redirection. If
that fails, it falls back to System32. Sysnative is available on Vista and
up and available on Windows Server 2003 and XP through KB patch 942589. Note
that Sysnative will always fail if using 64-bit python due to it being a
virtual directory and System32 will work correctly in the first place.
KB 942589 - http://support.microsoft.com/kb/942589/en-us.
Arguments:
key: The registry key.
value: The particular registry value to read (optional).
Return:
stdout from reg.exe, or None for failure. | Use reg.exe to read a particular key through _RegistryQueryBase. | [
"Use",
"reg",
".",
"exe",
"to",
"read",
"a",
"particular",
"key",
"through",
"_RegistryQueryBase",
"."
] | def _RegistryQuery(key, value=None):
"""Use reg.exe to read a particular key through _RegistryQueryBase.
First tries to launch from %WinDir%\Sysnative to avoid WoW64 redirection. If
that fails, it falls back to System32. Sysnative is available on Vista and
up and available on Windows Server 2003 and XP through KB patch 942589. Note
that Sysnative will always fail if using 64-bit python due to it being a
virtual directory and System32 will work correctly in the first place.
KB 942589 - http://support.microsoft.com/kb/942589/en-us.
Arguments:
key: The registry key.
value: The particular registry value to read (optional).
Return:
stdout from reg.exe, or None for failure.
"""
text = None
try:
text = _RegistryQueryBase('Sysnative', key, value)
except OSError, e:
if e.errno == errno.ENOENT:
text = _RegistryQueryBase('System32', key, value)
else:
raise
return text | [
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|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/cookielib.py | python | CookieJar._cookie_attrs | (self, cookies) | return attrs | Return a list of cookie-attributes to be returned to server.
like ['foo="bar"; $Path="/"', ...]
The $Version attribute is also added when appropriate (currently only
once per request). | Return a list of cookie-attributes to be returned to server. | [
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"cookie",
"-",
"attributes",
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"server",
"."
] | def _cookie_attrs(self, cookies):
"""Return a list of cookie-attributes to be returned to server.
like ['foo="bar"; $Path="/"', ...]
The $Version attribute is also added when appropriate (currently only
once per request).
"""
# add cookies in order of most specific (ie. longest) path first
cookies.sort(key=lambda arg: len(arg.path), reverse=True)
version_set = False
attrs = []
for cookie in cookies:
# set version of Cookie header
# XXX
# What should it be if multiple matching Set-Cookie headers have
# different versions themselves?
# Answer: there is no answer; was supposed to be settled by
# RFC 2965 errata, but that may never appear...
version = cookie.version
if not version_set:
version_set = True
if version > 0:
attrs.append("$Version=%s" % version)
# quote cookie value if necessary
# (not for Netscape protocol, which already has any quotes
# intact, due to the poorly-specified Netscape Cookie: syntax)
if ((cookie.value is not None) and
self.non_word_re.search(cookie.value) and version > 0):
value = self.quote_re.sub(r"\\\1", cookie.value)
else:
value = cookie.value
# add cookie-attributes to be returned in Cookie header
if cookie.value is None:
attrs.append(cookie.name)
else:
attrs.append("%s=%s" % (cookie.name, value))
if version > 0:
if cookie.path_specified:
attrs.append('$Path="%s"' % cookie.path)
if cookie.domain.startswith("."):
domain = cookie.domain
if (not cookie.domain_initial_dot and
domain.startswith(".")):
domain = domain[1:]
attrs.append('$Domain="%s"' % domain)
if cookie.port is not None:
p = "$Port"
if cookie.port_specified:
p = p + ('="%s"' % cookie.port)
attrs.append(p)
return attrs | [
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] | https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/cookielib.py#L1253-L1310 |
|
apiaryio/drafter | 4634ebd07f6c6f257cc656598ccd535492fdfb55 | tools/gyp/pylib/gyp/input.py | python | PruneUnwantedTargets | (targets, flat_list, dependency_nodes, root_targets,
data) | return wanted_targets, wanted_flat_list | Return only the targets that are deep dependencies of |root_targets|. | Return only the targets that are deep dependencies of |root_targets|. | [
"Return",
"only",
"the",
"targets",
"that",
"are",
"deep",
"dependencies",
"of",
"|root_targets|",
"."
] | def PruneUnwantedTargets(targets, flat_list, dependency_nodes, root_targets,
data):
"""Return only the targets that are deep dependencies of |root_targets|."""
qualified_root_targets = []
for target in root_targets:
target = target.strip()
qualified_targets = gyp.common.FindQualifiedTargets(target, flat_list)
if not qualified_targets:
raise GypError("Could not find target %s" % target)
qualified_root_targets.extend(qualified_targets)
wanted_targets = {}
for target in qualified_root_targets:
wanted_targets[target] = targets[target]
for dependency in dependency_nodes[target].DeepDependencies():
wanted_targets[dependency] = targets[dependency]
wanted_flat_list = [t for t in flat_list if t in wanted_targets]
# Prune unwanted targets from each build_file's data dict.
for build_file in data['target_build_files']:
if not 'targets' in data[build_file]:
continue
new_targets = []
for target in data[build_file]['targets']:
qualified_name = gyp.common.QualifiedTarget(build_file,
target['target_name'],
target['toolset'])
if qualified_name in wanted_targets:
new_targets.append(target)
data[build_file]['targets'] = new_targets
return wanted_targets, wanted_flat_list | [
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] | https://github.com/apiaryio/drafter/blob/4634ebd07f6c6f257cc656598ccd535492fdfb55/tools/gyp/pylib/gyp/input.py#L2673-L2705 |
|
metashell/metashell | f4177e4854ea00c8dbc722cadab26ef413d798ea | 3rd/templight/llvm/bindings/python/llvm/object.py | python | Relocation.offset | (self) | return lib.LLVMGetRelocationOffset(self) | The offset of this relocation, in long bytes. | The offset of this relocation, in long bytes. | [
"The",
"offset",
"of",
"this",
"relocation",
"in",
"long",
"bytes",
"."
] | def offset(self):
"""The offset of this relocation, in long bytes."""
if self.expired:
raise Exception('Relocation instance has expired.')
return lib.LLVMGetRelocationOffset(self) | [
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