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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/http/server.py | python | BaseHTTPRequestHandler.send_error | (self, code, message=None, explain=None) | Send and log an error reply.
Arguments are
* code: an HTTP error code
3 digits
* message: a simple optional 1 line reason phrase.
*( HTAB / SP / VCHAR / %x80-FF )
defaults to short entry matching the response code
* explain: a detailed message defaults to the long entry
matching the response code.
This sends an error response (so it must be called before any
output has been generated), logs the error, and finally sends
a piece of HTML explaining the error to the user. | Send and log an error reply. | [
"Send",
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"log",
"an",
"error",
"reply",
"."
] | def send_error(self, code, message=None, explain=None):
"""Send and log an error reply.
Arguments are
* code: an HTTP error code
3 digits
* message: a simple optional 1 line reason phrase.
*( HTAB / SP / VCHAR / %x80-FF )
defaults to short entry matching the response code
* explain: a detailed message defaults to the long entry
matching the response code.
This sends an error response (so it must be called before any
output has been generated), logs the error, and finally sends
a piece of HTML explaining the error to the user.
"""
try:
shortmsg, longmsg = self.responses[code]
except KeyError:
shortmsg, longmsg = '???', '???'
if message is None:
message = shortmsg
if explain is None:
explain = longmsg
self.log_error("code %d, message %s", code, message)
self.send_response(code, message)
self.send_header('Connection', 'close')
# Message body is omitted for cases described in:
# - RFC7230: 3.3. 1xx, 204(No Content), 304(Not Modified)
# - RFC7231: 6.3.6. 205(Reset Content)
body = None
if (code >= 200 and
code not in (HTTPStatus.NO_CONTENT,
HTTPStatus.RESET_CONTENT,
HTTPStatus.NOT_MODIFIED)):
# HTML encode to prevent Cross Site Scripting attacks
# (see bug #1100201)
content = (self.error_message_format % {
'code': code,
'message': html.escape(message, quote=False),
'explain': html.escape(explain, quote=False)
})
body = content.encode('UTF-8', 'replace')
self.send_header("Content-Type", self.error_content_type)
self.send_header('Content-Length', str(len(body)))
self.end_headers()
if self.command != 'HEAD' and body:
self.wfile.write(body) | [
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||
RobotLocomotion/drake | 0e18a34604c45ed65bc9018a54f7610f91cdad5b | doc/pydrake/build.py | python | _write_module | (name, f_name) | Writes an rst file for module `name` into `f_name`. | Writes an rst file for module `name` into `f_name`. | [
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"f_name",
"."
] | def _write_module(name, f_name):
"""Writes an rst file for module `name` into `f_name`.
"""
if verbose():
print("Write: {}".format(name))
subs = _get_submodules(name)
with open(f_name, 'w') as f:
f.write("\n")
rst_name = name.replace("_", "\\_")
f.write("{}\n".format(rst_name))
f.write("=" * len(rst_name) + "\n")
f.write("\n")
if len(subs) > 0:
f.write(".. toctree::\n")
f.write(" :maxdepth: 1\n")
f.write("\n")
for sub in subs:
f.write(" {}\n".format(sub))
f.write("\n\n")
f.write(".. automodule:: {}\n".format(name))
f.write(" :members:\n")
# See if there's a corresponding private CcPybind library.
if _has_cc_imported_symbols(name):
f.write(" :imported-members:\n")
f.write(" :undoc-members:\n")
f.write(" :show-inheritance:\n") | [
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||
htcondor/htcondor | 4829724575176d1d6c936e4693dfd78a728569b0 | bindings/python/htcondor/htchirp/htchirp.py | python | HTChirp.rmdir | (self, remote_path, recursive=False) | Delete a directory on the remote machine.
The directory must be empty unless recursive is set to True.
:param remote_path: Path to directory
:param recursive: If set to True, recursively delete remote_path | Delete a directory on the remote machine. | [
"Delete",
"a",
"directory",
"on",
"the",
"remote",
"machine",
"."
] | def rmdir(self, remote_path, recursive=False):
"""Delete a directory on the remote machine.
The directory must be empty unless recursive is set to True.
:param remote_path: Path to directory
:param recursive: If set to True, recursively delete remote_path
"""
if recursive:
self.rmall(remote_path)
else:
self._simple_command("rmdir {0}\n".format(quote(remote_path))) | [
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||
RamadhanAmizudin/malware | 2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1 | Fuzzbunch/fuzzbunch/command.py | python | FbCmd.cmdloop | (self) | Repeatedly issue a prompt, accept input, parse an initial prefix
off the received input, and dispatch to action methods, passing them
the remainder of the line as argument. | Repeatedly issue a prompt, accept input, parse an initial prefix
off the received input, and dispatch to action methods, passing them
the remainder of the line as argument. | [
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] | def cmdloop(self):
"""Repeatedly issue a prompt, accept input, parse an initial prefix
off the received input, and dispatch to action methods, passing them
the remainder of the line as argument.
"""
self.preloop()
self.io.pre_input(self.complete)
try:
stop = None
while not stop:
if self.cmdqueue:
# First, clear out anything we have in the command queue
line = self.cmdqueue.pop(0)
else:
# Then, accept input
line = self.io.get_input(self.prompt)
stop = self.runcmd(line)
self.postloop()
finally:
self.io.post_input() | [
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||
google/ion | ef47f3b824050499ce5c6f774b366f6c4dbce0af | ion/build.py | python | BuildState.GetAdditionalGypGeneratorFlags | (self) | return self.GetCommandLineOptions().G | Returns list of additional gyp variables.
These are directly passed on the command line as -G=foo=bar.
Returns:
A list of extra flags to pass through to the gyp as generator flags. | Returns list of additional gyp variables. | [
"Returns",
"list",
"of",
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] | def GetAdditionalGypGeneratorFlags(self):
"""Returns list of additional gyp variables.
These are directly passed on the command line as -G=foo=bar.
Returns:
A list of extra flags to pass through to the gyp as generator flags.
"""
return self.GetCommandLineOptions().G | [
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|
oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/win_tool.py | python | WinTool.ExecClCompile | (self, project_dir, selected_files) | return subprocess.call(cmd, shell=True, cwd=BASE_DIR) | Executed by msvs-ninja projects when the 'ClCompile' target is used to
build selected C/C++ files. | Executed by msvs-ninja projects when the 'ClCompile' target is used to
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] | def ExecClCompile(self, project_dir, selected_files):
"""Executed by msvs-ninja projects when the 'ClCompile' target is used to
build selected C/C++ files."""
project_dir = os.path.relpath(project_dir, BASE_DIR)
selected_files = selected_files.split(";")
ninja_targets = [
os.path.join(project_dir, filename) + "^^" for filename in selected_files
]
cmd = ["ninja.exe"]
cmd.extend(ninja_targets)
return subprocess.call(cmd, shell=True, cwd=BASE_DIR) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/ec2/autoscale/__init__.py | python | AutoScaleConnection.get_all_scaling_process_types | (self) | return self.get_list('DescribeScalingProcessTypes', {},
[('member', ProcessType)]) | Returns scaling process types for use in the ResumeProcesses and
SuspendProcesses actions. | Returns scaling process types for use in the ResumeProcesses and
SuspendProcesses actions. | [
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] | def get_all_scaling_process_types(self):
"""
Returns scaling process types for use in the ResumeProcesses and
SuspendProcesses actions.
"""
return self.get_list('DescribeScalingProcessTypes', {},
[('member', ProcessType)]) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/gslib/commands/defacl.py | python | DefAclCommand._ChDefAcl | (self) | Parses options and changes default object ACLs on specified buckets. | Parses options and changes default object ACLs on specified buckets. | [
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] | def _ChDefAcl(self):
"""Parses options and changes default object ACLs on specified buckets."""
self.parse_versions = True
self.changes = []
if self.sub_opts:
for o, a in self.sub_opts:
if o == '-g':
self.changes.append(
aclhelpers.AclChange(a, scope_type=aclhelpers.ChangeType.GROUP))
if o == '-u':
self.changes.append(
aclhelpers.AclChange(a, scope_type=aclhelpers.ChangeType.USER))
if o == '-p':
self.changes.append(
aclhelpers.AclChange(a, scope_type=aclhelpers.ChangeType.PROJECT))
if o == '-d':
self.changes.append(aclhelpers.AclDel(a))
if not self.changes:
raise CommandException(
'Please specify at least one access change '
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if (not UrlsAreForSingleProvider(self.args) or
StorageUrlFromString(self.args[0]).scheme != 'gs'):
raise CommandException(
'The "{0}" command can only be used with gs:// URLs'.format(
self.command_name))
bucket_urls = set()
for url_arg in self.args:
for result in self.WildcardIterator(url_arg):
if not result.storage_url.IsBucket():
raise CommandException(
'The defacl ch command can only be applied to buckets.')
bucket_urls.add(result.storage_url)
for storage_url in bucket_urls:
self.ApplyAclChanges(storage_url) | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Jinja2/py3/jinja2/compiler.py | python | CodeGenerator.return_buffer_contents | (
self, frame: Frame, force_unescaped: bool = False
) | Return the buffer contents of the frame. | Return the buffer contents of the frame. | [
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] | def return_buffer_contents(
self, frame: Frame, force_unescaped: bool = False
) -> None:
"""Return the buffer contents of the frame."""
if not force_unescaped:
if frame.eval_ctx.volatile:
self.writeline("if context.eval_ctx.autoescape:")
self.indent()
self.writeline(f"return Markup(concat({frame.buffer}))")
self.outdent()
self.writeline("else:")
self.indent()
self.writeline(f"return concat({frame.buffer})")
self.outdent()
return
elif frame.eval_ctx.autoescape:
self.writeline(f"return Markup(concat({frame.buffer}))")
return
self.writeline(f"return concat({frame.buffer})") | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_gdi.py | python | AlphaPixelData_Accessor.MoveTo | (*args, **kwargs) | return _gdi_.AlphaPixelData_Accessor_MoveTo(*args, **kwargs) | MoveTo(self, AlphaPixelData data, int x, int y) | MoveTo(self, AlphaPixelData data, int x, int y) | [
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] | def MoveTo(*args, **kwargs):
"""MoveTo(self, AlphaPixelData data, int x, int y)"""
return _gdi_.AlphaPixelData_Accessor_MoveTo(*args, **kwargs) | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/_extends/remote/kernel_build_server.py | python | AkgBuilder.create | (self, process_num, waitime) | Create akg processor | Create akg processor | [
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""" Create akg processor"""
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0ad/0ad | f58db82e0e925016d83f4e3fa7ca599e3866e2af | source/tools/lobbybots/xpartamupp/echelon.py | python | EcheLOn._muc_online | (self, presence) | Add joining players to the list of players.
Arguments:
presence (sleekxmpp.stanza.presence.Presence): Received
presence stanza. | Add joining players to the list of players. | [
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"""Add joining players to the list of players.
Arguments:
presence (sleekxmpp.stanza.presence.Presence): Received
presence stanza.
"""
nick = str(presence['muc']['nick'])
jid = sleekxmpp.jid.JID(presence['muc']['jid'])
if nick == self.nick:
return
if jid.resource != '0ad':
return
self.leaderboard.get_or_create_player(jid)
self._broadcast_rating_list()
logging.debug("Client '%s' connected with a nick of '%s'.", jid, nick) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/Blast/Editor/Scripts/external/pyassimp/helper.py | python | hasattr_silent | (object, name) | Calls hasttr() with the given parameters and preserves the legacy (pre-Python 3.2)
functionality of silently catching exceptions.
Returns the result of hasatter() or False if an exception was raised. | Calls hasttr() with the given parameters and preserves the legacy (pre-Python 3.2)
functionality of silently catching exceptions. | [
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] | def hasattr_silent(object, name):
"""
Calls hasttr() with the given parameters and preserves the legacy (pre-Python 3.2)
functionality of silently catching exceptions.
Returns the result of hasatter() or False if an exception was raised.
"""
try:
if not object:
return False
return hasattr(object, name)
except AttributeError:
return False | [
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||
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/libdeps/libdeps/analyzer.py | python | CommonDependents.run | (self) | return sorted(list(set.intersection(*neighbor_sets))) | For a given set of nodes, report what nodes depend on all nodes from that set. | For a given set of nodes, report what nodes depend on all nodes from that set. | [
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] | def run(self):
"""For a given set of nodes, report what nodes depend on all nodes from that set."""
neighbor_sets = [set(self._dependents_graph[node]) for node in self._nodes]
return sorted(list(set.intersection(*neighbor_sets))) | [
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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/_internal/utils/misc.py | python | is_svn_page | (html) | return (re.search(r'<title>[^<]*Revision \d+:', html) and
re.search(r'Powered by (?:<a[^>]*?>)?Subversion', html, re.I)) | Returns true if the page appears to be the index page of an svn repository | Returns true if the page appears to be the index page of an svn repository | [
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# type: (Union[str, Text]) -> Optional[Match[Union[str, Text]]]
"""
Returns true if the page appears to be the index page of an svn repository
"""
return (re.search(r'<title>[^<]*Revision \d+:', html) and
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/idlelib/configdialog.py | python | HighPage.on_new_color_set | (self) | Display sample of new color selection on the dialog. | Display sample of new color selection on the dialog. | [
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] | def on_new_color_set(self):
"Display sample of new color selection on the dialog."
new_color = self.color.get()
self.style.configure('frame_color_set.TFrame', background=new_color)
plane = 'foreground' if self.fg_bg_toggle.get() else 'background'
sample_element = self.theme_elements[self.highlight_target.get()][0]
self.highlight_sample.tag_config(sample_element, **{plane: new_color})
theme = self.custom_name.get()
theme_element = sample_element + '-' + plane
changes.add_option('highlight', theme, theme_element, new_color) | [
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idaholab/moose | 9eeebc65e098b4c30f8205fb41591fd5b61eb6ff | python/peacock/ExodusViewer/plugins/CameraPlugin.py | python | CameraPlugin._callbackResetButton | (self) | Recomputes the original view. | Recomputes the original view. | [
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"."
] | def _callbackResetButton(self):
"""
Recomputes the original view.
"""
if self._result:
renderer = self._result.getVTKRenderer()
renderer.ResetCamera()
camera = renderer.GetActiveCamera()
fp = camera.GetFocalPoint()
p = camera.GetPosition()
dist = math.sqrt( (p[0]-fp[0])**2 + (p[1]-fp[1])**2 + (p[2]-fp[2])**2 )
camera.SetPosition(fp[0], fp[1], fp[2]+dist)
camera.SetViewUp(0.0, 1.0, 0.0)
self._result.setNeedsUpdate(True)
self.windowRequiresUpdate.emit() | [
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||
hakuna-m/wubiuefi | caec1af0a09c78fd5a345180ada1fe45e0c63493 | src/wubi/backends/common/tasklist.py | python | Task._get_weight | (self) | return float(self.size*self.weight) + sum(subtasks_weight) | get total weight for this task and all the subtasks | get total weight for this task and all the subtasks | [
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] | def _get_weight(self):
'''
get total weight for this task and all the subtasks
'''
subtasks_weight = [s._get_weight() for s in self.subtasks]
return float(self.size*self.weight) + sum(subtasks_weight) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/plat-mac/findertools.py | python | emptytrash | () | empty the trash | empty the trash | [
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] | def emptytrash():
"""empty the trash"""
finder = _getfinder()
args = {}
attrs = {}
args['----'] = aetypes.ObjectSpecifier(want=aetypes.Type('prop'), form="prop", seld=aetypes.Type('trsh'), fr=None)
_reply, args, attrs = finder.send("fndr", "empt", args, attrs)
if 'errn' in args:
raise aetools.Error, aetools.decodeerror(args) | [
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||
weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/pep8.py | python | filename_match | (filename, patterns, default=True) | return any(fnmatch(filename, pattern) for pattern in patterns) | Check if patterns contains a pattern that matches filename.
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"""
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/learn/python/learn/monitors.py | python | BaseMonitor.step_begin | (self, step) | return [] | Callback before training step begins.
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Args:
step: `int`, the current value of the global step.
Returns:
List of `Tensor` objects or string tensor names to be run.
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step: `int`, the current value of the global step.
Returns:
List of `Tensor` objects or string tensor names to be run.
Raises:
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"""
if (step < 0) or (
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/traci/_trafficlight.py | python | TrafficLightDomain.setProgram | (self, tlsID, programID) | setProgram(string, string) -> None
Switches to the program with the given programID. The program must have
been loaded earlier. The special value 'off' can always be used to
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"""setProgram(string, string) -> None
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||
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | toolkit/crashreporter/tools/symbolstore.py | python | Dumper_Mac.ShouldSkipDir | (self, dir) | return False | We create .dSYM bundles on the fly, but if someone runs
buildsymbols twice, we should skip any bundles we created
previously, otherwise we'll recurse into them and try to
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/masked/textctrl.py | python | BaseMaskedTextCtrl._CalcSize | (self, size=None) | return self._calcSize(size) | Calculate automatic size if allowed; use base mixin function. | Calculate automatic size if allowed; use base mixin function. | [
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|
microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPM2_RSA_Decrypt_REQUEST.__init__ | (self, keyHandle = TPM_HANDLE(), cipherText = None, inScheme = None, label = None) | This command performs RSA decryption using the indicated padding
scheme according to IETF RFC 8017 ((PKCS#1).
Attributes:
keyHandle (TPM_HANDLE): RSA key to use for decryption
Auth Index: 1
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cipherText (bytes): Cipher text to be decrypted
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TPMS_NULL_ASYM_SCHEME.
label (bytes): Label whose association with the message is to be verified | This command performs RSA decryption using the indicated padding
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keyHandle (TPM_HANDLE): RSA key to use for decryption
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bigartm/bigartm | 47e37f982de87aa67bfd475ff1f39da696b181b3 | 3rdparty/protobuf-3.0.0/python/mox.py | python | MoxMetaTestBase.CleanUpTest | (cls, func) | return new_method | Adds Mox cleanup code to any MoxTestBase method.
Always unsets stubs after a test. Will verify all mocks for tests that
otherwise pass.
Args:
cls: MoxTestBase or subclass; the class whose test method we are altering.
func: method; the method of the MoxTestBase test class we wish to alter.
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Always unsets stubs after a test. Will verify all mocks for tests that
otherwise pass.
Args:
cls: MoxTestBase or subclass; the class whose test method we are altering.
func: method; the method of the MoxTestBase test class we wish to alter.
Returns:
The modified method.
"""
def new_method(self, *args, **kwargs):
mox_obj = getattr(self, 'mox', None)
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try:
func(self, *args, **kwargs)
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if cleanup_mox:
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new_method.__name__ = func.__name__
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llvm/llvm-project | ffa6262cb4e2a335d26416fad39a581b4f98c5f4 | clang/bindings/python/clang/cindex.py | python | Cursor.walk_preorder | (self) | Depth-first preorder walk over the cursor and its descendants.
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"""Depth-first preorder walk over the cursor and its descendants.
Yields cursors.
"""
yield self
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rapidsai/cudf | d5b2448fc69f17509304d594f029d0df56984962 | python/cudf/cudf/core/column/column.py | python | nullmask | (self) | return self.mask_array_view | The gpu buffer for the null-mask | The gpu buffer for the null-mask | [
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|
rodeofx/OpenWalter | 6116fbe3f04f1146c854afbfbdbe944feaee647e | walter/maya/scripts/walterPanel/walterMayaTraverser.py | python | WalterMayaImplementation.expressionGroups | (self, origin) | return sorted(groupSet) | Get all available expression groups. | Get all available expression groups. | [
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groupSet = set(alembicGroups)
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groupSet.add(grp)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/cgutils.py | python | raw_memcpy | (builder, dst, src, count, itemsize, align=1) | return _raw_memcpy(builder, 'llvm.memcpy', dst, src, count, itemsize, align) | Emit a raw memcpy() call for `count` items of size `itemsize`
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apple/swift | 469f72fdae2ea828b3b6c0d7d62d7e4cf98c4893 | utils/build_swift/build_swift/shell.py | python | _flatmap | (func, *iterables) | return itertools.chain.from_iterable(map(func, *iterables)) | Helper function that maps the given func over the iterables and then
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/eclipse.py | python | CalculateGeneratorInputInfo | (params) | Calculate the generator specific info that gets fed to input (called by
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generator_flags = params.get('generator_flags', {})
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||
lukasmonk/lucaschess | 13e2e5cb13b38a720ccf897af649054a64bcb914 | Code/QT/Columnas.py | python | Columna.QTcolorTexto | (self, rgb) | Convierte un parametro de color del texto para que sea usable por QT | Convierte un parametro de color del texto para que sea usable por QT | [
"Convierte",
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"parametro",
"de",
"color",
"del",
"texto",
"para",
"que",
"sea",
"usable",
"por",
"QT"
] | def QTcolorTexto(self, rgb):
"""
Convierte un parametro de color del texto para que sea usable por QT
"""
if rgb == -1:
return None
else:
return QtGui.QColor(rgb) | [
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||
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/session_bundle/gc.py | python | negation | (f) | return keep | Negate a filter.
Args:
f: filter function to invert
Returns:
A filter function that returns the negation of f. | Negate a filter. | [
"Negate",
"a",
"filter",
"."
] | def negation(f):
"""Negate a filter.
Args:
f: filter function to invert
Returns:
A filter function that returns the negation of f.
"""
def keep(paths):
l = set(paths)
r = set(f(paths))
return sorted(list(l-r))
return keep | [
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|
SoarGroup/Soar | a1c5e249499137a27da60533c72969eef3b8ab6b | scons/scons-local-4.1.0/SCons/Node/Python.py | python | ValueWithMemo | (value, built_value=None, name=None) | Memoized Value() node factory. | Memoized Value() node factory. | [
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"node",
"factory",
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] | def ValueWithMemo(value, built_value=None, name=None):
"""
Memoized Value() node factory.
"""
global _memo_lookup_map
# No current support for memoizing a value that needs to be built.
if built_value:
return Value(value, built_value, name=name)
try:
memo_lookup_key = hash((value, name))
except TypeError:
# Non-primitive types will hit this codepath.
return Value(value, name=name)
try:
return _memo_lookup_map[memo_lookup_key]
except KeyError:
v = Value(value, built_value, name)
_memo_lookup_map[memo_lookup_key] = v
return v | [
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||
alibaba/weex_js_engine | 2bdf4b6f020c1fc99c63f649718f6faf7e27fdde | jni/v8core/v8/build/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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|
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model.py | python | StateSpaceModel._imputation_step | (self, current_times, state) | return (estimated_state, estimated_state_var,
previous_times + catchup_times) | Add state transition noise to catch `state` up to `current_times`.
State space models are inherently sequential, so we need to "predict
through" any missing time steps to catch up each element of the batch to its
next observation/prediction time.
Args:
current_times: A [batch size] Tensor of times to impute up to, not
inclusive.
state: A tuple of (mean, covariance, previous_times) having shapes
mean; [batch size x state dimension]
covariance; [batch size x state dimension x state dimension]
previous_times; [batch size]
Returns:
Imputed model state corresponding to the `state` argument. | Add state transition noise to catch `state` up to `current_times`. | [
"Add",
"state",
"transition",
"noise",
"to",
"catch",
"state",
"up",
"to",
"current_times",
"."
] | def _imputation_step(self, current_times, state):
"""Add state transition noise to catch `state` up to `current_times`.
State space models are inherently sequential, so we need to "predict
through" any missing time steps to catch up each element of the batch to its
next observation/prediction time.
Args:
current_times: A [batch size] Tensor of times to impute up to, not
inclusive.
state: A tuple of (mean, covariance, previous_times) having shapes
mean; [batch size x state dimension]
covariance; [batch size x state dimension x state dimension]
previous_times; [batch size]
Returns:
Imputed model state corresponding to the `state` argument.
"""
estimated_state, estimated_state_var, previous_times = state
catchup_times = current_times - previous_times
non_negative_assertion = control_flow_ops.Assert(
math_ops.reduce_all(catchup_times >= 0), [
"Negative imputation interval", catchup_times, current_times,
previous_times
],
summarize=100)
with ops.control_dependencies([non_negative_assertion]):
transition_matrices, transition_noise_sums = ( # pylint: disable=unbalanced-tuple-unpacking
self._cached_transition_powers_and_sums(catchup_times))
estimated_state = self._kalman_filter.predict_state_mean(
estimated_state, transition_matrices)
estimated_state_var = self._kalman_filter.predict_state_var(
estimated_state_var, transition_matrices, transition_noise_sums)
return (estimated_state, estimated_state_var,
previous_times + catchup_times) | [
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|
miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/contrib/copy_graph/python/util/copy_elements.py | python | copy_op_to_graph | (org_instance, to_graph, variables,
scope="") | Given an `Operation` 'org_instance` from one `Graph`,
initializes and returns a copy of it from another `Graph`,
under the specified scope (default `""`).
The copying is done recursively, so any `Operation` whose output
is required to evaluate the `org_instance`, is also copied (unless
already done).
Since `Variable` instances are copied separately, those required
to evaluate `org_instance` must be provided as input.
Args:
org_instance: An `Operation` from some `Graph`. Could be a
`Placeholder` as well.
to_graph: The `Graph` to copy `org_instance` to.
variables: An iterable of `Variable` instances to copy `org_instance` to.
scope: A scope for the new `Variable` (default `""`).
Returns:
The copied `Operation` from `to_graph`.
Raises:
TypeError: If `org_instance` is not an `Operation` or `Tensor`. | Given an `Operation` 'org_instance` from one `Graph`,
initializes and returns a copy of it from another `Graph`,
under the specified scope (default `""`). | [
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] | def copy_op_to_graph(org_instance, to_graph, variables,
scope=""):
"""Given an `Operation` 'org_instance` from one `Graph`,
initializes and returns a copy of it from another `Graph`,
under the specified scope (default `""`).
The copying is done recursively, so any `Operation` whose output
is required to evaluate the `org_instance`, is also copied (unless
already done).
Since `Variable` instances are copied separately, those required
to evaluate `org_instance` must be provided as input.
Args:
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to_graph: The `Graph` to copy `org_instance` to.
variables: An iterable of `Variable` instances to copy `org_instance` to.
scope: A scope for the new `Variable` (default `""`).
Returns:
The copied `Operation` from `to_graph`.
Raises:
TypeError: If `org_instance` is not an `Operation` or `Tensor`.
"""
#The name of the new instance
if scope != '':
new_name = scope + '/' + org_instance.name
else:
new_name = org_instance.name
#Extract names of variables
copied_variables = dict((x.name, x) for x in variables)
#If a variable by the new name already exists, return the
#correspondng tensor that will act as an input
if new_name in copied_variables:
return to_graph.get_tensor_by_name(
copied_variables[new_name].name)
#If an instance of the same name exists, return appropriately
try:
already_present = to_graph.as_graph_element(new_name,
allow_tensor=True,
allow_operation=True)
return already_present
except:
pass
#Get the collections that the new instance needs to be added to.
#The new collections will also be a part of the given scope.
collections = []
for name, collection in org_instance.graph._collections.items():
if org_instance in collection:
if scope == '':
collections.append(name)
else:
collections.append(scope + '/' + name)
#Take action based on the class of the instance
if isinstance(org_instance, ops.Tensor):
#If its a Tensor, it is one of the outputs of the underlying
#op. Therefore, copy the op itself and return the appropriate
#output.
op = org_instance.op
new_op = copy_op_to_graph(op, to_graph, variables, scope)
output_index = op.outputs.index(org_instance)
new_tensor = new_op.outputs[output_index]
#Add to collections if any
for collection in collections:
to_graph.add_to_collection(collection, new_tensor)
return new_tensor
elif isinstance(org_instance, ops.Operation):
op = org_instance
#If it has an original_op parameter, copy it
if op._original_op is not None:
new_original_op = copy_op_to_graph(op._original_op, to_graph,
variables, scope)
else:
new_original_op = None
#If it has control inputs, call this function recursively on each.
new_control_inputs = [copy_op_to_graph(x, to_graph, variables,
scope)
for x in op.control_inputs]
#If it has inputs, call this function recursively on each.
new_inputs = [copy_op_to_graph(x, to_graph, variables,
scope)
for x in op.inputs]
#Make a new node_def based on that of the original.
#An instance of tensorflow.core.framework.graph_pb2.NodeDef, it
#stores String-based info such as name, device and type of the op.
#Unique to every Operation instance.
new_node_def = deepcopy(op._node_def)
#Change the name
new_node_def.name = new_name
#Copy the other inputs needed for initialization
output_types = op._output_types[:]
input_types = op._input_types[:]
#Make a copy of the op_def too.
#Its unique to every _type_ of Operation.
op_def = deepcopy(op._op_def)
#Initialize a new Operation instance
new_op = ops.Operation(new_node_def,
to_graph,
new_inputs,
output_types,
new_control_inputs,
input_types,
new_original_op,
op_def)
#Use Graph's hidden methods to add the op
to_graph._add_op(new_op)
to_graph._record_op_seen_by_control_dependencies(new_op)
for device_function in reversed(to_graph._device_function_stack):
new_op._set_device(device_function(new_op))
return new_op
else:
raise TypeError("Could not copy instance: " + str(org_instance)) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/arrays/datetimes.py | python | DatetimeArray.month_name | (self, locale=None) | return result | Return the month names of the DateTimeIndex with specified locale.
.. versionadded:: 0.23.0
Parameters
----------
locale : str, optional
Locale determining the language in which to return the month name.
Default is English locale.
Returns
-------
Index
Index of month names.
Examples
--------
>>> idx = pd.date_range(start='2018-01', freq='M', periods=3)
>>> idx
DatetimeIndex(['2018-01-31', '2018-02-28', '2018-03-31'],
dtype='datetime64[ns]', freq='M')
>>> idx.month_name()
Index(['January', 'February', 'March'], dtype='object') | Return the month names of the DateTimeIndex with specified locale. | [
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"""
Return the month names of the DateTimeIndex with specified locale.
.. versionadded:: 0.23.0
Parameters
----------
locale : str, optional
Locale determining the language in which to return the month name.
Default is English locale.
Returns
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Examples
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>>> idx = pd.date_range(start='2018-01', freq='M', periods=3)
>>> idx
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>>> idx.month_name()
Index(['January', 'February', 'March'], dtype='object')
"""
if self.tz is not None and not timezones.is_utc(self.tz):
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/lite/tools/dataset/cropper/cropper_configure.py | python | extract_classname_source_node | (header_content) | return re.findall(r"(?<=class )[\w\d_]+(?=Node : )", header_content) | Use regex to find class names in header files of source nodes
:param header_content: string containing header of a source node IR file
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"""
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:param header_content: string containing header of a source node IR file
:return: list of source node classes found
"""
return re.findall(r"(?<=class )[\w\d_]+(?=Node : )", header_content) | [
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|
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_x86_64/python2.7/dist-packages/rosdep2/installers.py | python | InstallerContext.get_os_installer_keys | (self, os_key) | Get list of installer keys registered for the specified OS.
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:param os_key: Key for OS
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microsoft/onnxruntime | f92e47e95b13a240e37caf7b36577983544f98fc | onnxruntime/python/tools/quantization/calibrate.py | python | CalibraterBase.select_tensors_to_calibrate | (self, model) | return tensors_to_calibrate, value_infos | select all quantization_candidates op type nodes' input/output tensors.
returns:
tensors (set): set of tensor name.
value_infos (dict): tensor name to value info. | select all quantization_candidates op type nodes' input/output tensors.
returns:
tensors (set): set of tensor name.
value_infos (dict): tensor name to value info. | [
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'''
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returns:
tensors (set): set of tensor name.
value_infos (dict): tensor name to value info.
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value_infos = {vi.name: vi for vi in model.graph.value_info}
value_infos.update({ot.name: ot for ot in model.graph.output})
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initializer = set(init.name for init in model.graph.initializer)
tensors_to_calibrate = set()
tensor_type_to_calibrate = set([TensorProto.FLOAT, TensorProto.FLOAT16])
for node in model.graph.node:
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for tensor_name in itertools.chain(node.input, node.output):
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if vi.type.HasField('tensor_type') and (
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tensors_to_calibrate.add(tensor_name)
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/_pydecimal.py | python | Decimal.__divmod__ | (self, other, context=None) | return quotient, remainder | Return (self // other, self % other) | Return (self // other, self % other) | [
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"""
Return (self // other, self % other)
"""
other = _convert_other(other)
if other is NotImplemented:
return other
if context is None:
context = getcontext()
ans = self._check_nans(other, context)
if ans:
return (ans, ans)
sign = self._sign ^ other._sign
if self._isinfinity():
if other._isinfinity():
ans = context._raise_error(InvalidOperation, 'divmod(INF, INF)')
return ans, ans
else:
return (_SignedInfinity[sign],
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if not other:
if not self:
ans = context._raise_error(DivisionUndefined, 'divmod(0, 0)')
return ans, ans
else:
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quotient, remainder = self._divide(other, context)
remainder = remainder._fix(context)
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py | python | NeuralNetworkBuilder.add_max_broadcastable | (self, name, input_names, output_name) | return spec_layer | Add a max_broadcastable layer to the model that performs element-wise
maximum operation with broadcast support.
Refer to the **MaxBroadcastableLayerParams** message in specification (NeuralNetwork.proto) for more details.
Parameters
----------
name: str
The name of this layer.
input_names: list of str
The input blob names of this layer.
output_name: str
The output blob name of this layer. | Add a max_broadcastable layer to the model that performs element-wise
maximum operation with broadcast support.
Refer to the **MaxBroadcastableLayerParams** message in specification (NeuralNetwork.proto) for more details. | [
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"""
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spec_layer.maxBroadcastable.MergeFromString(b"")
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/fsspec/spec.py | python | AbstractFileSystem.ls | (self, path, detail=True, **kwargs) | List objects at path.
This should include subdirectories and files at that location. The
difference between a file and a directory must be clear when details
are requested.
The specific keys, or perhaps a FileInfo class, or similar, is TBD,
but must be consistent across implementations.
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path: str
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(str).
kwargs: may have additional backend-specific options, such as version
information
Returns
-------
List of strings if detail is False, or list of directory information
dicts if detail is True. | List objects at path. | [
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"""List objects at path.
This should include subdirectories and files at that location. The
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are requested.
The specific keys, or perhaps a FileInfo class, or similar, is TBD,
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PixarAnimationStudios/USD | faed18ce62c8736b02413635b584a2f637156bad | build_scripts/build_usd.py | python | GetXcodeDeveloperDirectory | () | return GetCommandOutput("xcode-select -p") | Returns the active developer directory as reported by 'xcode-select -p'.
Returns None if none is set. | Returns the active developer directory as reported by 'xcode-select -p'.
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return GetCommandOutput("xcode-select -p") | [
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|
dogecoin/dogecoin | 31afd133119dd2e15862d46530cb99424cf564b0 | contrib/seeds/makeseeds.py | python | filtermultiport | (ips) | return [value[0] for (key,value) in list(hist.items()) if len(value)==1] | Filter out hosts with more nodes per IP | Filter out hosts with more nodes per IP | [
"Filter",
"out",
"hosts",
"with",
"more",
"nodes",
"per",
"IP"
] | def filtermultiport(ips):
'''Filter out hosts with more nodes per IP'''
hist = collections.defaultdict(list)
for ip in ips:
hist[ip['sortkey']].append(ip)
return [value[0] for (key,value) in list(hist.items()) if len(value)==1] | [
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|
eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/traci/_gui.py | python | GuiDomain.track | (self, objID, viewID=DEFAULT_VIEW) | track(string, string) -> None
Start visually tracking the given vehicle or person on the given view. | track(string, string) -> None
Start visually tracking the given vehicle or person on the given view. | [
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"""track(string, string) -> None
Start visually tracking the given vehicle or person on the given view.
"""
self._setCmd(tc.VAR_TRACK_VEHICLE, viewID, "s", objID) | [
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||
rdiankov/openrave | d1a23023fd4b58f077d2ca949ceaf1b91f3f13d7 | python/databases/grasping.py | python | GraspingModel.setPreshape | (self,grasp) | sets the preshape on the robot, assumes environment is locked | sets the preshape on the robot, assumes environment is locked | [
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"assumes",
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] | def setPreshape(self,grasp):
"""sets the preshape on the robot, assumes environment is locked"""
self.robot.SetDOFValues(grasp[self.graspindices['igrasppreshape']],self.manip.GetGripperIndices()) | [
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||
hakuna-m/wubiuefi | caec1af0a09c78fd5a345180ada1fe45e0c63493 | src/wubi/backends/common/tasklist.py | python | Task._get_completed | (self) | return float(self.completed*self.weight) + sum(completed_subtasks) | get weighted sum of percent completed for this task and all the subtasks | get weighted sum of percent completed for this task and all the subtasks | [
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] | def _get_completed(self):
'''
get weighted sum of percent completed for this task and all the subtasks
'''
completed_subtasks = [s._get_completed() for s in self.subtasks]
return float(self.completed*self.weight) + sum(completed_subtasks) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/_osx_support.py | python | _find_appropriate_compiler | (_config_vars) | return _config_vars | Find appropriate C compiler for extension module builds | Find appropriate C compiler for extension module builds | [
"Find",
"appropriate",
"C",
"compiler",
"for",
"extension",
"module",
"builds"
] | def _find_appropriate_compiler(_config_vars):
"""Find appropriate C compiler for extension module builds"""
# Issue #13590:
# The OSX location for the compiler varies between OSX
# (or rather Xcode) releases. With older releases (up-to 10.5)
# the compiler is in /usr/bin, with newer releases the compiler
# can only be found inside Xcode.app if the "Command Line Tools"
# are not installed.
#
# Furthermore, the compiler that can be used varies between
# Xcode releases. Up to Xcode 4 it was possible to use 'gcc-4.2'
# as the compiler, after that 'clang' should be used because
# gcc-4.2 is either not present, or a copy of 'llvm-gcc' that
# miscompiles Python.
# skip checks if the compiler was overridden with a CC env variable
if 'CC' in os.environ:
return _config_vars
# The CC config var might contain additional arguments.
# Ignore them while searching.
cc = oldcc = _config_vars['CC'].split()[0]
if not _find_executable(cc):
# Compiler is not found on the shell search PATH.
# Now search for clang, first on PATH (if the Command LIne
# Tools have been installed in / or if the user has provided
# another location via CC). If not found, try using xcrun
# to find an uninstalled clang (within a selected Xcode).
# NOTE: Cannot use subprocess here because of bootstrap
# issues when building Python itself (and os.popen is
# implemented on top of subprocess and is therefore not
# usable as well)
cc = _find_build_tool('clang')
elif os.path.basename(cc).startswith('gcc'):
# Compiler is GCC, check if it is LLVM-GCC
data = _read_output("'%s' --version"
% (cc.replace("'", "'\"'\"'"),))
if data and 'llvm-gcc' in data:
# Found LLVM-GCC, fall back to clang
cc = _find_build_tool('clang')
if not cc:
raise SystemError(
"Cannot locate working compiler")
if cc != oldcc:
# Found a replacement compiler.
# Modify config vars using new compiler, if not already explicitly
# overridden by an env variable, preserving additional arguments.
for cv in _COMPILER_CONFIG_VARS:
if cv in _config_vars and cv not in os.environ:
cv_split = _config_vars[cv].split()
cv_split[0] = cc if cv != 'CXX' else cc + '++'
_save_modified_value(_config_vars, cv, ' '.join(cv_split))
return _config_vars | [
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|
Kitware/ParaView | f760af9124ff4634b23ebbeab95a4f56e0261955 | Wrapping/Python/paraview/servermanager.py | python | FieldDataInformation.iteritems | (self) | return FieldDataInformationIterator(self, True) | Implementation of the PY2 dictionary API | Implementation of the PY2 dictionary API | [
"Implementation",
"of",
"the",
"PY2",
"dictionary",
"API"
] | def iteritems(self):
"""Implementation of the PY2 dictionary API"""
return FieldDataInformationIterator(self, True) | [
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|
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/client/session.py | python | _DictFetchMapper.__init__ | (self, fetches) | Creates a _DictFetchMapper.
Args:
fetches: Dict of fetches. | Creates a _DictFetchMapper. | [
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"."
] | def __init__(self, fetches):
"""Creates a _DictFetchMapper.
Args:
fetches: Dict of fetches.
"""
self._fetch_type = type(fetches)
if isinstance(fetches, collections.defaultdict):
self._type_ctor = functools.partial(collections.defaultdict,
fetches.default_factory)
else:
self._type_ctor = self._fetch_type
self._keys = fetches.keys()
self._mappers = [
_FetchMapper.for_fetch(fetch) for fetch in fetches.values()
]
self._unique_fetches, self._value_indices = _uniquify_fetches(self._mappers) | [
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||
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/SANS/isis_reduction_steps.py | python | ConvertToQISIS.execute | (self, reducer, workspace) | Calculate the normalization workspaces and then call the chosen Q conversion algorithm. | Calculate the normalization workspaces and then call the chosen Q conversion algorithm. | [
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] | def execute(self, reducer, workspace):
"""
Calculate the normalization workspaces and then call the chosen Q conversion algorithm.
"""
wavepixeladj = ""
if reducer.wide_angle_correction and reducer.transmission_calculator.output_wksp:
# calculate the transmission wide angle correction
_issueWarning("sans solid angle correction execution")
SANSWideAngleCorrection(SampleData=workspace,
TransmissionData=reducer.transmission_calculator.output_wksp,
OutputWorkspace='transmissionWorkspace')
wavepixeladj = 'transmissionWorkspace'
# create normalization workspaces
if self._norms:
# the empty list at the end appears to be needed (the system test SANS2DWaveloops) is this a bug in Python?
wave_adj, pixel_adj = self._norms.calculate(reducer, [])
else:
raise RuntimeError('Normalization workspaces must be created by CalculateNorm() and passed to this step')
# Create the QResolution workspace, but only if it A) is requested by the user and does not exist
# B) is requested by the user, exists, but does not
# have the correct binning --> This is currently not implemented,
# but should be addressed in an optimization step
qResolution = self._get_q_resolution_workspace(det_bank_workspace=workspace)
# Debug output
if DEBUG:
sanslog.warning("###############################################")
sanslog.warning("File : %s" % str(self._q_resolution_moderator_file_name))
sanslog.warning("A1 : %s" % str(self._q_resolution_a1))
sanslog.warning("A2 : %s" % str(self._q_resolution_a2))
sanslog.warning("H1 : %s" % str(self._q_resolution_h1))
sanslog.warning("H2 : %s" % str(self._q_resolution_h1))
sanslog.warning("W1 : %s" % str(self._q_resolution_w1))
sanslog.warning("W2 : %s" % str(self._q_resolution_w2))
sanslog.warning("LCol: %s" % str(self._q_resolution_collimation_length))
sanslog.warning("DR : %s" % str(self._q_resolution_delta_r))
sanslog.warning("Exists: %s" % str(qResolution is not None))
try:
if self._Q_alg == 'Q1D':
Q1D(DetBankWorkspace=workspace,
OutputWorkspace=workspace,
OutputBinning=self.binning,
WavelengthAdj=wave_adj,
PixelAdj=pixel_adj,
AccountForGravity=self._use_gravity,
RadiusCut=self.r_cut * 1000.0,
WaveCut=self.w_cut,
OutputParts=self.outputParts,
WavePixelAdj=wavepixeladj,
ExtraLength=self._grav_extra_length,
QResolution=qResolution)
elif self._Q_alg == 'Qxy':
Qxy(InputWorkspace=workspace,
OutputWorkspace=workspace,
MaxQxy=reducer.QXY2,
DeltaQ=reducer.DQXY,
WavelengthAdj=wave_adj,
PixelAdj=pixel_adj,
AccountForGravity=self._use_gravity,
RadiusCut=self.r_cut * 1000.0,
WaveCut=self.w_cut,
OutputParts=self.outputParts,
ExtraLength=self._grav_extra_length)
ReplaceSpecialValues(InputWorkspace=workspace,
OutputWorkspace=workspace,
NaNValue="0", InfinityValue="0")
# We need to correct for special values in the partial outputs. The
# counts seem to have NANS.
if self.outputParts:
sum_of_counts = workspace + "_sumOfCounts"
sum_of_norm = workspace + "_sumOfNormFactors"
ReplaceSpecialValues(InputWorkspace=sum_of_counts,
OutputWorkspace=sum_of_counts,
NaNValue="0", InfinityValue="0")
ReplaceSpecialValues(InputWorkspace=sum_of_norm,
OutputWorkspace=sum_of_norm,
NaNValue="0", InfinityValue="0")
else:
raise NotImplementedError('The type of Q reduction has not been set, e.g. 1D or 2D')
except:
# when we are all up to Python 2.5 replace the duplicated code below with one finally:
reducer.deleteWorkspaces([wave_adj, pixel_adj, wavepixeladj])
raise
reducer.deleteWorkspaces([wave_adj, pixel_adj, wavepixeladj]) | [
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||
smartdevicelink/sdl_core | 68f082169e0a40fccd9eb0db3c83911c28870f07 | tools/InterfaceGenerator/generator/generators/SmartFactoryBase.py | python | CodeGenerator._gen_struct_impl | (self, struct, namespace, class_name) | return self._struct_impl_template.substitute(
namespace=namespace,
class_name=class_name,
struct_name=struct.name,
code=self._indent_code(
self._struct_impl_code_tempate.substitute(
struct_name=struct.name,
schema_loc_decl=self._gen_schema_loc_decls(
struct.members.values(), processed_enums),
schema_items_decl=self._gen_schema_items_decls(
struct.members.values()),
schema_item_fill=self._gen_schema_items_fill(
struct.members.values(), struct.since, struct.until, struct.deprecated, struct.removed)),
1)) | Generate struct implementation for source file.
Generates implementation code of method that provide schema item for
struct. This code should be used in the source file.
Keyword arguments:
struct -- struct to generate method for.
namespace -- name of destination namespace.
class_name -- name of the parent class.
Returns:
String with structs implementation source code. | Generate struct implementation for source file. | [
"Generate",
"struct",
"implementation",
"for",
"source",
"file",
"."
] | def _gen_struct_impl(self, struct, namespace, class_name):
"""Generate struct implementation for source file.
Generates implementation code of method that provide schema item for
struct. This code should be used in the source file.
Keyword arguments:
struct -- struct to generate method for.
namespace -- name of destination namespace.
class_name -- name of the parent class.
Returns:
String with structs implementation source code.
"""
processed_enums = []
return self._struct_impl_template.substitute(
namespace=namespace,
class_name=class_name,
struct_name=struct.name,
code=self._indent_code(
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schema_loc_decl=self._gen_schema_loc_decls(
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schema_items_decl=self._gen_schema_items_decls(
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schema_item_fill=self._gen_schema_items_fill(
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|
ZintrulCre/LeetCode_Archiver | de23e16ead29336b5ee7aa1898a392a5d6463d27 | LeetCode/python3/775.py | python | Solution.isIdealPermutation | (self, A) | return True | :type A: List[int]
:rtype: bool | :type A: List[int]
:rtype: bool | [
":",
"type",
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] | def isIdealPermutation(self, A):
"""
:type A: List[int]
:rtype: bool
"""
size, m = len(A), 0
for i in range(size - 2):
m = max(m, A[i])
if m > A[i + 2]:
return False
return True | [
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|
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/Inelastic/vesuvio/profiles.py | python | GaussianMassProfile.create_fit_function_str | (self, param_vals=None, param_prefix="") | return fitting_str + ";" | Creates a string used by the Fit algorithm for this profile
:param param_vals: A table of values for the parameters that override those set
on the object already. Default=None
:param param_prefix: A string prefix for the parameter as seen by the Mantid Fit algorithm | Creates a string used by the Fit algorithm for this profile | [
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"used",
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"the",
"Fit",
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"for",
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] | def create_fit_function_str(self, param_vals=None, param_prefix=""):
"""Creates a string used by the Fit algorithm for this profile
:param param_vals: A table of values for the parameters that override those set
on the object already. Default=None
:param param_prefix: A string prefix for the parameter as seen by the Mantid Fit algorithm
"""
vals_provided = (param_vals is not None)
if vals_provided:
def_width = param_vals[param_prefix + "Width"]
else:
def_width = self.width
if isinstance(def_width, list):
def_width = def_width[1]
fitting_str = "name={0},Mass={1:f},Width={2:f}".format(self.cfunction, self.mass, def_width)
if vals_provided:
param_name = "Intensity"
intensity_str = "{0}={1:f}".format(param_name, param_vals[param_prefix + param_name])
fitting_str += "," + intensity_str
elif self.intensity is not None:
fitting_str += ",Intensity={0:f}".format(self.intensity)
logger.debug("Gaussian profile fit function string: {0}".format(fitting_str))
return fitting_str + ";" | [
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|
tkn-tub/ns3-gym | 19bfe0a583e641142609939a090a09dfc63a095f | src/visualizer/visualizer/hud.py | python | Axes.__init__ | (self, viz) | !
Initializer function
@param self: this object
@param viz: visualization object
@return none | !
Initializer function | [
"!",
"Initializer",
"function"
] | def __init__(self, viz):
"""!
Initializer function
@param self: this object
@param viz: visualization object
@return none
"""
self.viz = viz
self.color = 0x8080C0FF
self.hlines = GooCanvas.CanvasPath(parent=viz.canvas.get_root_item(), stroke_color_rgba=self.color)
self.hlines.lower(None)
self.vlines = GooCanvas.CanvasPath(parent=viz.canvas.get_root_item(), stroke_color_rgba=self.color)
self.vlines.lower(None)
self.labels = []
hadj = self.viz.get_hadjustment()
vadj = self.viz.get_vadjustment()
def update(adj):
if self.visible:
self.update_view()
hadj.connect("value-changed", update)
vadj.connect("value-changed", update)
hadj.connect("changed", update)
vadj.connect("changed", update)
self.visible = True
self.update_view() | [
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||
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/framework/errors_impl.py | python | UnimplementedError.__init__ | (self, node_def, op, message) | Creates an `UnimplementedError`. | Creates an `UnimplementedError`. | [
"Creates",
"an",
"UnimplementedError",
"."
] | def __init__(self, node_def, op, message):
"""Creates an `UnimplementedError`."""
super(UnimplementedError, self).__init__(node_def, op, message,
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/html.py | python | HtmlCell.GetWidth | (*args, **kwargs) | return _html.HtmlCell_GetWidth(*args, **kwargs) | GetWidth(self) -> int | GetWidth(self) -> int | [
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"""GetWidth(self) -> int"""
return _html.HtmlCell_GetWidth(*args, **kwargs) | [
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|
zhaoweicai/cascade-rcnn | 2252f46158ea6555868ca6fa5c221ea71d9b5e6c | tools/extra/parse_log.py | python | fix_initial_nan_learning_rate | (dict_list) | Correct initial value of learning rate
Learning rate is normally not printed until after the initial test and
training step, which means the initial testing and training rows have
LearningRate = NaN. Fix this by copying over the LearningRate from the
second row, if it exists. | Correct initial value of learning rate | [
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"value",
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"learning",
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] | def fix_initial_nan_learning_rate(dict_list):
"""Correct initial value of learning rate
Learning rate is normally not printed until after the initial test and
training step, which means the initial testing and training rows have
LearningRate = NaN. Fix this by copying over the LearningRate from the
second row, if it exists.
"""
if len(dict_list) > 1:
dict_list[0]['LearningRate'] = dict_list[1]['LearningRate'] | [
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||
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/eager/function_cache.py | python | FunctionCache.lookup | (self, key: FunctionCacheKey, use_function_subtyping: bool) | return None | Looks up a concrete function based on the key. | Looks up a concrete function based on the key. | [
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] | def lookup(self, key: FunctionCacheKey, use_function_subtyping: bool):
"""Looks up a concrete function based on the key."""
if not use_function_subtyping:
return self._primary.get(key, None)
dispatch_key = self._dispatch_table.dispatch(key)
if dispatch_key is not None:
return self._primary[dispatch_key]
return None | [
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|
nasa/fprime | 595cf3682d8365943d86c1a6fe7c78f0a116acf0 | Autocoders/Python/src/fprime_ac/generators/writers/AbstractWriter.py | python | AbstractWriter.includes1Write | (self, obj) | Defined to generate includes within a file.
Usually used for the base classes but also for Port types
@param args: the instance of the concrete element to operation on. | Defined to generate includes within a file.
Usually used for the base classes but also for Port types | [
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".",
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"used",
"for",
"the",
"base",
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"but",
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] | def includes1Write(self, obj):
"""
Defined to generate includes within a file.
Usually used for the base classes but also for Port types
@param args: the instance of the concrete element to operation on.
"""
raise Exception(
"# AbstractWriter.includesWrite1() - Implementation Error: you must supply your own concrete implementation."
) | [
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||
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/gslib/copy_helper.py | python | FixWindowsNaming | (src_url, dst_url) | return dst_url | Translates Windows pathnames to cloud pathnames.
Rewrites the destination URL built by ConstructDstUrl().
Args:
src_url: Source StorageUrl to be copied.
dst_url: The destination StorageUrl built by ConstructDstUrl().
Returns:
StorageUrl to use for copy. | Translates Windows pathnames to cloud pathnames. | [
"Translates",
"Windows",
"pathnames",
"to",
"cloud",
"pathnames",
"."
] | def FixWindowsNaming(src_url, dst_url):
"""Translates Windows pathnames to cloud pathnames.
Rewrites the destination URL built by ConstructDstUrl().
Args:
src_url: Source StorageUrl to be copied.
dst_url: The destination StorageUrl built by ConstructDstUrl().
Returns:
StorageUrl to use for copy.
"""
if (src_url.IsFileUrl() and src_url.delim == '\\'
and dst_url.IsCloudUrl()):
trans_url_str = re.sub(r'\\', '/', dst_url.url_string)
dst_url = StorageUrlFromString(trans_url_str)
return dst_url | [
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|
zhaoweicai/cascade-rcnn | 2252f46158ea6555868ca6fa5c221ea71d9b5e6c | scripts/cpp_lint.py | python | ReplaceAll | (pattern, rep, s) | return _regexp_compile_cache[pattern].sub(rep, s) | Replaces instances of pattern in a string with a replacement.
The compiled regex is kept in a cache shared by Match and Search.
Args:
pattern: regex pattern
rep: replacement text
s: search string
Returns:
string with replacements made (or original string if no replacements) | Replaces instances of pattern in a string with a replacement. | [
"Replaces",
"instances",
"of",
"pattern",
"in",
"a",
"string",
"with",
"a",
"replacement",
"."
] | def ReplaceAll(pattern, rep, s):
"""Replaces instances of pattern in a string with a replacement.
The compiled regex is kept in a cache shared by Match and Search.
Args:
pattern: regex pattern
rep: replacement text
s: search string
Returns:
string with replacements made (or original string if no replacements)
"""
if pattern not in _regexp_compile_cache:
_regexp_compile_cache[pattern] = sre_compile.compile(pattern)
return _regexp_compile_cache[pattern].sub(rep, s) | [
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|
p4lang/p4c | 3272e79369f20813cc1a555a5eb26f44432f84a4 | tools/cpplint.py | python | _NamespaceInfo.CheckEnd | (self, filename, clean_lines, linenum, error) | Check end of namespace comments. | Check end of namespace comments. | [
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"namespace",
"comments",
"."
] | def CheckEnd(self, filename, clean_lines, linenum, error):
"""Check end of namespace comments."""
line = clean_lines.raw_lines[linenum]
# Check how many lines is enclosed in this namespace. Don't issue
# warning for missing namespace comments if there aren't enough
# lines. However, do apply checks if there is already an end of
# namespace comment and it's incorrect.
#
# TODO(unknown): We always want to check end of namespace comments
# if a namespace is large, but sometimes we also want to apply the
# check if a short namespace contained nontrivial things (something
# other than forward declarations). There is currently no logic on
# deciding what these nontrivial things are, so this check is
# triggered by namespace size only, which works most of the time.
if (linenum - self.starting_linenum < 10
and not Match(r'^\s*};*\s*(//|/\*).*\bnamespace\b', line)):
return
# Look for matching comment at end of namespace.
#
# Note that we accept C style "/* */" comments for terminating
# namespaces, so that code that terminate namespaces inside
# preprocessor macros can be cpplint clean.
#
# We also accept stuff like "// end of namespace <name>." with the
# period at the end.
#
# Besides these, we don't accept anything else, otherwise we might
# get false negatives when existing comment is a substring of the
# expected namespace.
if self.name:
# Named namespace
if not Match((r'^\s*};*\s*(//|/\*).*\bnamespace\s+' +
re.escape(self.name) + r'[\*/\.\\\s]*$'),
line):
error(filename, linenum, 'readability/namespace', 5,
'Namespace should be terminated with "// namespace %s"' %
self.name)
else:
# Anonymous namespace
if not Match(r'^\s*};*\s*(//|/\*).*\bnamespace[\*/\.\\\s]*$', line):
# If "// namespace anonymous" or "// anonymous namespace (more text)",
# mention "// anonymous namespace" as an acceptable form
if Match(r'^\s*}.*\b(namespace anonymous|anonymous namespace)\b', line):
error(filename, linenum, 'readability/namespace', 5,
'Anonymous namespace should be terminated with "// namespace"'
' or "// anonymous namespace"')
else:
error(filename, linenum, 'readability/namespace', 5,
'Anonymous namespace should be terminated with "// namespace"') | [
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||
yun-liu/RCF | 91bfb054ad04187dbbe21e539e165ad9bd3ff00b | scripts/cpp_lint.py | python | CheckForMultilineCommentsAndStrings | (filename, clean_lines, linenum, error) | Logs an error if we see /* ... */ or "..." that extend past one line.
/* ... */ comments are legit inside macros, for one line.
Otherwise, we prefer // comments, so it's ok to warn about the
other. Likewise, it's ok for strings to extend across multiple
lines, as long as a line continuation character (backslash)
terminates each line. Although not currently prohibited by the C++
style guide, it's ugly and unnecessary. We don't do well with either
in this lint program, so we warn about both.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found. | Logs an error if we see /* ... */ or "..." that extend past one line. | [
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"...",
"*",
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"or",
"...",
"that",
"extend",
"past",
"one",
"line",
"."
] | def CheckForMultilineCommentsAndStrings(filename, clean_lines, linenum, error):
"""Logs an error if we see /* ... */ or "..." that extend past one line.
/* ... */ comments are legit inside macros, for one line.
Otherwise, we prefer // comments, so it's ok to warn about the
other. Likewise, it's ok for strings to extend across multiple
lines, as long as a line continuation character (backslash)
terminates each line. Although not currently prohibited by the C++
style guide, it's ugly and unnecessary. We don't do well with either
in this lint program, so we warn about both.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum]
# Remove all \\ (escaped backslashes) from the line. They are OK, and the
# second (escaped) slash may trigger later \" detection erroneously.
line = line.replace('\\\\', '')
if line.count('/*') > line.count('*/'):
error(filename, linenum, 'readability/multiline_comment', 5,
'Complex multi-line /*...*/-style comment found. '
'Lint may give bogus warnings. '
'Consider replacing these with //-style comments, '
'with #if 0...#endif, '
'or with more clearly structured multi-line comments.')
if (line.count('"') - line.count('\\"')) % 2:
error(filename, linenum, 'readability/multiline_string', 5,
'Multi-line string ("...") found. This lint script doesn\'t '
'do well with such strings, and may give bogus warnings. '
'Use C++11 raw strings or concatenation instead.') | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/shutil.py | python | copytree | (src, dst, symlinks=False, ignore=None, copy_function=copy2,
ignore_dangling_symlinks=False) | return dst | Recursively copy a directory tree.
The destination directory must not already exist.
If exception(s) occur, an Error is raised with a list of reasons.
If the optional symlinks flag is true, symbolic links in the
source tree result in symbolic links in the destination tree; if
it is false, the contents of the files pointed to by symbolic
links are copied. If the file pointed by the symlink doesn't
exist, an exception will be added in the list of errors raised in
an Error exception at the end of the copy process.
You can set the optional ignore_dangling_symlinks flag to true if you
want to silence this exception. Notice that this has no effect on
platforms that don't support os.symlink.
The optional ignore argument is a callable. If given, it
is called with the `src` parameter, which is the directory
being visited by copytree(), and `names` which is the list of
`src` contents, as returned by os.listdir():
callable(src, names) -> ignored_names
Since copytree() is called recursively, the callable will be
called once for each directory that is copied. It returns a
list of names relative to the `src` directory that should
not be copied.
The optional copy_function argument is a callable that will be used
to copy each file. It will be called with the source path and the
destination path as arguments. By default, copy2() is used, but any
function that supports the same signature (like copy()) can be used. | Recursively copy a directory tree. | [
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"copy",
"a",
"directory",
"tree",
"."
] | def copytree(src, dst, symlinks=False, ignore=None, copy_function=copy2,
ignore_dangling_symlinks=False):
"""Recursively copy a directory tree.
The destination directory must not already exist.
If exception(s) occur, an Error is raised with a list of reasons.
If the optional symlinks flag is true, symbolic links in the
source tree result in symbolic links in the destination tree; if
it is false, the contents of the files pointed to by symbolic
links are copied. If the file pointed by the symlink doesn't
exist, an exception will be added in the list of errors raised in
an Error exception at the end of the copy process.
You can set the optional ignore_dangling_symlinks flag to true if you
want to silence this exception. Notice that this has no effect on
platforms that don't support os.symlink.
The optional ignore argument is a callable. If given, it
is called with the `src` parameter, which is the directory
being visited by copytree(), and `names` which is the list of
`src` contents, as returned by os.listdir():
callable(src, names) -> ignored_names
Since copytree() is called recursively, the callable will be
called once for each directory that is copied. It returns a
list of names relative to the `src` directory that should
not be copied.
The optional copy_function argument is a callable that will be used
to copy each file. It will be called with the source path and the
destination path as arguments. By default, copy2() is used, but any
function that supports the same signature (like copy()) can be used.
"""
names = os.listdir(src)
if ignore is not None:
ignored_names = ignore(src, names)
else:
ignored_names = set()
os.makedirs(dst)
errors = []
for name in names:
if name in ignored_names:
continue
srcname = os.path.join(src, name)
dstname = os.path.join(dst, name)
try:
if os.path.islink(srcname):
linkto = os.readlink(srcname)
if symlinks:
# We can't just leave it to `copy_function` because legacy
# code with a custom `copy_function` may rely on copytree
# doing the right thing.
os.symlink(linkto, dstname)
copystat(srcname, dstname, follow_symlinks=not symlinks)
else:
# ignore dangling symlink if the flag is on
if not os.path.exists(linkto) and ignore_dangling_symlinks:
continue
# otherwise let the copy occurs. copy2 will raise an error
if os.path.isdir(srcname):
copytree(srcname, dstname, symlinks, ignore,
copy_function)
else:
copy_function(srcname, dstname)
elif os.path.isdir(srcname):
copytree(srcname, dstname, symlinks, ignore, copy_function)
else:
# Will raise a SpecialFileError for unsupported file types
copy_function(srcname, dstname)
# catch the Error from the recursive copytree so that we can
# continue with other files
except Error as err:
errors.extend(err.args[0])
except OSError as why:
errors.append((srcname, dstname, str(why)))
try:
copystat(src, dst)
except OSError as why:
# Copying file access times may fail on Windows
if getattr(why, 'winerror', None) is None:
errors.append((src, dst, str(why)))
if errors:
raise Error(errors)
return dst | [
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|
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/util/traceback_utils.py | python | is_traceback_filtering_enabled | () | return value | Check whether traceback filtering is currently enabled.
See also `tf.debugging.enable_traceback_filtering()` and
`tf.debugging.disable_traceback_filtering()`. Note that filtering out
internal frames from the tracebacks of exceptions raised by TensorFlow code
is the default behavior.
Returns:
True if traceback filtering is enabled
(e.g. if `tf.debugging.enable_traceback_filtering()` was called),
and False otherwise (e.g. if `tf.debugging.disable_traceback_filtering()`
was called). | Check whether traceback filtering is currently enabled. | [
"Check",
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"filtering",
"is",
"currently",
"enabled",
"."
] | def is_traceback_filtering_enabled():
"""Check whether traceback filtering is currently enabled.
See also `tf.debugging.enable_traceback_filtering()` and
`tf.debugging.disable_traceback_filtering()`. Note that filtering out
internal frames from the tracebacks of exceptions raised by TensorFlow code
is the default behavior.
Returns:
True if traceback filtering is enabled
(e.g. if `tf.debugging.enable_traceback_filtering()` was called),
and False otherwise (e.g. if `tf.debugging.disable_traceback_filtering()`
was called).
"""
value = getattr(_ENABLE_TRACEBACK_FILTERING, 'value', True)
return value | [
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|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/telemetry/core/platform/proc_supporting_platform_backend.py | python | ProcSupportingPlatformBackend._GetProcJiffies | (self, timer_list) | Parse '/proc/timer_list' output and returns the first jiffies attribute.
Multi-CPU machines will have multiple 'jiffies:' lines, all of which will be
essentially the same. Return the first one. | Parse '/proc/timer_list' output and returns the first jiffies attribute. | [
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] | def _GetProcJiffies(self, timer_list):
"""Parse '/proc/timer_list' output and returns the first jiffies attribute.
Multi-CPU machines will have multiple 'jiffies:' lines, all of which will be
essentially the same. Return the first one."""
if isinstance(timer_list, str):
timer_list = timer_list.splitlines()
for line in timer_list:
if line.startswith('jiffies:'):
_, value = line.split(':')
return value
raise Exception('Unable to find jiffies from /proc/timer_list') | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/fsspec/spec.py | python | AbstractFileSystem.start_transaction | (self) | return self.transaction | Begin write transaction for deferring files, non-context version | Begin write transaction for deferring files, non-context version | [
"Begin",
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] | def start_transaction(self):
"""Begin write transaction for deferring files, non-context version"""
self._intrans = True
self._transaction = Transaction(self)
return self.transaction | [
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|
GJDuck/LowFat | ecf6a0f0fa1b73a27a626cf493cc39e477b6faea | llvm-4.0.0.src/examples/Kaleidoscope/MCJIT/lazy/genk-timing.py | python | KScriptGenerator.updateCalledFunctionList | (self, callee) | Maintains a list of functions that will actually be called | Maintains a list of functions that will actually be called | [
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"""Maintains a list of functions that will actually be called"""
# Update the total call count
self.updateTotalCallCount(callee)
# If this function is already in the list, don't do anything else
if callee in self.calledFunctions:
return
# Add this function to the list of those that will be called.
self.calledFunctions.append(callee)
# If this function calls other functions, add them too
if callee in self.calledFunctionTable:
for subCallee in self.calledFunctionTable[callee]:
self.updateCalledFunctionList(subCallee) | [
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||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/mhlib.py | python | Folder.parsesequence | (self, seq) | Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
conditions cause which error messages. | Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
conditions cause which error messages. | [
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"""Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
conditions cause which error messages."""
# XXX Still not complete (see mh-format(5)).
# Missing are:
# - 'prev', 'next' as count
# - Sequence-Negation option
all = self.listmessages()
# Observed behavior: test for empty folder is done first
if not all:
raise Error, "no messages in %s" % self.name
# Common case first: all is frequently the default
if seq == 'all':
return all
# Test for X:Y before X-Y because 'seq:-n' matches both
i = seq.find(':')
if i >= 0:
head, dir, tail = seq[:i], '', seq[i+1:]
if tail[:1] in '-+':
dir, tail = tail[:1], tail[1:]
if not isnumeric(tail):
raise Error, "bad message list %s" % seq
try:
count = int(tail)
except (ValueError, OverflowError):
# Can't use sys.maxint because of i+count below
count = len(all)
try:
anchor = self._parseindex(head, all)
except Error, msg:
seqs = self.getsequences()
if not head in seqs:
if not msg:
msg = "bad message list %s" % seq
raise Error, msg, sys.exc_info()[2]
msgs = seqs[head]
if not msgs:
raise Error, "sequence %s empty" % head
if dir == '-':
return msgs[-count:]
else:
return msgs[:count]
else:
if not dir:
if head in ('prev', 'last'):
dir = '-'
if dir == '-':
i = bisect(all, anchor)
return all[max(0, i-count):i]
else:
i = bisect(all, anchor-1)
return all[i:i+count]
# Test for X-Y next
i = seq.find('-')
if i >= 0:
begin = self._parseindex(seq[:i], all)
end = self._parseindex(seq[i+1:], all)
i = bisect(all, begin-1)
j = bisect(all, end)
r = all[i:j]
if not r:
raise Error, "bad message list %s" % seq
return r
# Neither X:Y nor X-Y; must be a number or a (pseudo-)sequence
try:
n = self._parseindex(seq, all)
except Error, msg:
seqs = self.getsequences()
if not seq in seqs:
if not msg:
msg = "bad message list %s" % seq
raise Error, msg
return seqs[seq]
else:
if n not in all:
if isnumeric(seq):
raise Error, "message %d doesn't exist" % n
else:
raise Error, "no %s message" % seq
else:
return [n] | [
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||
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/keras/_impl/keras/applications/mobilenet.py | python | _depthwise_conv_block | (inputs,
pointwise_conv_filters,
alpha,
depth_multiplier=1,
strides=(1, 1),
block_id=1) | return Activation(relu6, name='conv_pw_%d_relu' % block_id)(x) | Adds a depthwise convolution block.
A depthwise convolution block consists of a depthwise conv,
batch normalization, relu6, pointwise convolution,
batch normalization and relu6 activation.
Arguments:
inputs: Input tensor of shape `(rows, cols, channels)`
(with `channels_last` data format) or
(channels, rows, cols) (with `channels_first` data format).
pointwise_conv_filters: Integer, the dimensionality of the output space
(i.e. the number output of filters in the pointwise convolution).
alpha: controls the width of the network.
- If `alpha` < 1.0, proportionally decreases the number
of filters in each layer.
- If `alpha` > 1.0, proportionally increases the number
of filters in each layer.
- If `alpha` = 1, default number of filters from the paper
are used at each layer.
depth_multiplier: The number of depthwise convolution output channels
for each input channel.
The total number of depthwise convolution output
channels will be equal to `filters_in * depth_multiplier`.
strides: An integer or tuple/list of 2 integers,
specifying the strides of the convolution along the width and height.
Can be a single integer to specify the same value for
all spatial dimensions.
Specifying any stride value != 1 is incompatible with specifying
any `dilation_rate` value != 1.
block_id: Integer, a unique identification designating the block number.
Input shape:
4D tensor with shape:
`(batch, channels, rows, cols)` if data_format='channels_first'
or 4D tensor with shape:
`(batch, rows, cols, channels)` if data_format='channels_last'.
Output shape:
4D tensor with shape:
`(batch, filters, new_rows, new_cols)` if data_format='channels_first'
or 4D tensor with shape:
`(batch, new_rows, new_cols, filters)` if data_format='channels_last'.
`rows` and `cols` values might have changed due to stride.
Returns:
Output tensor of block. | Adds a depthwise convolution block. | [
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"convolution",
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"."
] | def _depthwise_conv_block(inputs,
pointwise_conv_filters,
alpha,
depth_multiplier=1,
strides=(1, 1),
block_id=1):
"""Adds a depthwise convolution block.
A depthwise convolution block consists of a depthwise conv,
batch normalization, relu6, pointwise convolution,
batch normalization and relu6 activation.
Arguments:
inputs: Input tensor of shape `(rows, cols, channels)`
(with `channels_last` data format) or
(channels, rows, cols) (with `channels_first` data format).
pointwise_conv_filters: Integer, the dimensionality of the output space
(i.e. the number output of filters in the pointwise convolution).
alpha: controls the width of the network.
- If `alpha` < 1.0, proportionally decreases the number
of filters in each layer.
- If `alpha` > 1.0, proportionally increases the number
of filters in each layer.
- If `alpha` = 1, default number of filters from the paper
are used at each layer.
depth_multiplier: The number of depthwise convolution output channels
for each input channel.
The total number of depthwise convolution output
channels will be equal to `filters_in * depth_multiplier`.
strides: An integer or tuple/list of 2 integers,
specifying the strides of the convolution along the width and height.
Can be a single integer to specify the same value for
all spatial dimensions.
Specifying any stride value != 1 is incompatible with specifying
any `dilation_rate` value != 1.
block_id: Integer, a unique identification designating the block number.
Input shape:
4D tensor with shape:
`(batch, channels, rows, cols)` if data_format='channels_first'
or 4D tensor with shape:
`(batch, rows, cols, channels)` if data_format='channels_last'.
Output shape:
4D tensor with shape:
`(batch, filters, new_rows, new_cols)` if data_format='channels_first'
or 4D tensor with shape:
`(batch, new_rows, new_cols, filters)` if data_format='channels_last'.
`rows` and `cols` values might have changed due to stride.
Returns:
Output tensor of block.
"""
channel_axis = 1 if K.image_data_format() == 'channels_first' else -1
pointwise_conv_filters = int(pointwise_conv_filters * alpha)
x = DepthwiseConv2D( # pylint: disable=not-callable
(3, 3),
padding='same',
depth_multiplier=depth_multiplier,
strides=strides,
use_bias=False,
name='conv_dw_%d' % block_id)(inputs)
x = BatchNormalization(axis=channel_axis, name='conv_dw_%d_bn' % block_id)(x)
x = Activation(relu6, name='conv_dw_%d_relu' % block_id)(x)
x = Conv2D(
pointwise_conv_filters, (1, 1),
padding='same',
use_bias=False,
strides=(1, 1),
name='conv_pw_%d' % block_id)(x)
x = BatchNormalization(axis=channel_axis, name='conv_pw_%d_bn' % block_id)(x)
return Activation(relu6, name='conv_pw_%d_relu' % block_id)(x) | [
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|
cathywu/Sentiment-Analysis | eb501fd1375c0c3f3ab430f963255f1bb858e659 | PyML-0.7.9/PyML/utils/misc.py | python | update | (x, **entries) | Update a dict or an object with according to entries.
>>> update({'a': 1}, a=10, b=20)
{'a': 10, 'b': 20}
>>> update(Struct(a=1), a=10, b=20)
Struct(a=10, b=20) | Update a dict or an object with according to entries.
>>> update({'a': 1}, a=10, b=20)
{'a': 10, 'b': 20}
>>> update(Struct(a=1), a=10, b=20)
Struct(a=10, b=20) | [
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{'a': 10, 'b': 20}
>>> update(Struct(a=1), a=10, b=20)
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x.update(entries)
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facebook/proxygen | a9ca025af207787815cb01eee1971cd572c7a81e | build/fbcode_builder/getdeps/manifest.py | python | ManifestParser.is_first_party_project | (self) | return self.shipit_project is not None | returns true if this is an FB first-party project | returns true if this is an FB first-party project | [
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"""returns true if this is an FB first-party project"""
return self.shipit_project is not None | [
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|
bulletphysics/bullet3 | f0f2a952e146f016096db6f85cf0c44ed75b0b9a | examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur.py | python | Minitaur._ResetPoseForLeg | (self, leg_id, add_constraint) | Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet. | Reset the initial pose for the leg. | [
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] | def _ResetPoseForLeg(self, leg_id, add_constraint):
"""Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet.
"""
knee_friction_force = 0
half_pi = math.pi / 2.0
knee_angle = -2.1834
leg_position = LEG_POSITION[leg_id]
self._pybullet_client.resetJointState(self.quadruped,
self._joint_name_to_id["motor_" + leg_position +
"L_joint"],
self._motor_direction[2 * leg_id] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(self.quadruped,
self._joint_name_to_id["knee_" + leg_position +
"L_link"],
self._motor_direction[2 * leg_id] * knee_angle,
targetVelocity=0)
self._pybullet_client.resetJointState(self.quadruped,
self._joint_name_to_id["motor_" + leg_position +
"R_joint"],
self._motor_direction[2 * leg_id + 1] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(self.quadruped,
self._joint_name_to_id["knee_" + leg_position +
"R_link"],
self._motor_direction[2 * leg_id + 1] * knee_angle,
targetVelocity=0)
if add_constraint:
self._pybullet_client.createConstraint(
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "R_link"],
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "L_link"],
self._pybullet_client.JOINT_POINT2POINT, [0, 0, 0], KNEE_CONSTRAINT_POINT_RIGHT,
KNEE_CONSTRAINT_POINT_LEFT)
if self._accurate_motor_model_enabled or self._pd_control_enabled:
# Disable the default motor in pybullet.
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position + "L_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position + "R_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
else:
self._SetDesiredMotorAngleByName("motor_" + leg_position + "L_joint",
self._motor_direction[2 * leg_id] * half_pi)
self._SetDesiredMotorAngleByName("motor_" + leg_position + "R_joint",
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self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "L_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "R_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
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||
miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/python/ops/math_ops.py | python | imag | (input, name=None) | Returns the imaginary part of a complex number.
Given a tensor `input` of complex numbers, this operation returns a tensor of
type `float32` or `float64` that is the imaginary part of each element in
`input`. All elements in `input` must be complex numbers of the form \\(a +
bj\\), where *a* is the real part and *b* is the imaginary part returned by
this operation.
For example:
```
# tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j]
tf.imag(input) ==> [4.75, 5.75]
```
Args:
input: A `Tensor`. Must be one of the following types: `complex64`, `complex128`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `float32` or `float64`. | Returns the imaginary part of a complex number. | [
"Returns",
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"imaginary",
"part",
"of",
"a",
"complex",
"number",
"."
] | def imag(input, name=None):
"""Returns the imaginary part of a complex number.
Given a tensor `input` of complex numbers, this operation returns a tensor of
type `float32` or `float64` that is the imaginary part of each element in
`input`. All elements in `input` must be complex numbers of the form \\(a +
bj\\), where *a* is the real part and *b* is the imaginary part returned by
this operation.
For example:
```
# tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j]
tf.imag(input) ==> [4.75, 5.75]
```
Args:
input: A `Tensor`. Must be one of the following types: `complex64`, `complex128`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `float32` or `float64`.
"""
with ops.op_scope([input], name, "Imag") as name:
return gen_math_ops.imag(input, Tout=input.dtype.real_dtype, name=name) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/aui/auibar.py | python | AuiToolBar.OnIdle | (self, event) | Handles the ``wx.EVT_IDLE`` event for :class:`AuiToolBar`.
:param `event`: a :class:`IdleEvent` event to be processed. | Handles the ``wx.EVT_IDLE`` event for :class:`AuiToolBar`. | [
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] | def OnIdle(self, event):
"""
Handles the ``wx.EVT_IDLE`` event for :class:`AuiToolBar`.
:param `event`: a :class:`IdleEvent` event to be processed.
"""
self.DoIdleUpdate()
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||
gimli-org/gimli | 17aa2160de9b15ababd9ef99e89b1bc3277bbb23 | pygimli/frameworks/methodManager.py | python | MethodManager.checkData | (self, data) | return data | Overwrite for special checks to return data values | Overwrite for special checks to return data values | [
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"checks",
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"return",
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] | def checkData(self, data):
"""Overwrite for special checks to return data values"""
# if self._dataToken == 'nan':
# pg.critical('self._dataToken nan, should be set in class', self)
# return data(self._dataToken)
return data | [
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|
FEniCS/dolfinx | 3dfdf038cccdb70962865b58a63bf29c2e55ec6e | python/dolfinx/io.py | python | extract_gmsh_geometry | (gmsh_model, model_name=None) | return points[perm_sort] | For a given gmsh model, extract the mesh geometry as a numpy
(N,3) array where the i-th row corresponds to the i-th node in the
mesh. | For a given gmsh model, extract the mesh geometry as a numpy
(N,3) array where the i-th row corresponds to the i-th node in the
mesh. | [
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] | def extract_gmsh_geometry(gmsh_model, model_name=None):
"""For a given gmsh model, extract the mesh geometry as a numpy
(N,3) array where the i-th row corresponds to the i-th node in the
mesh.
"""
if model_name is not None:
gmsh_model.setCurrent(model_name)
# Get the unique tag and coordinates for nodes
# in mesh
indices, points, _ = gmsh_model.mesh.getNodes()
points = points.reshape(-1, 3)
# GMSH indices starts at 1
indices -= 1
# Sort nodes in geometry according to the unique index
perm_sort = np.argsort(indices)
assert np.all(indices[perm_sort] == np.arange(len(indices)))
return points[perm_sort] | [
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|
y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Node/FS.py | python | sconsign_dir | (node) | return node._sconsign | Return the .sconsign file info for this directory,
creating it first if necessary. | Return the .sconsign file info for this directory,
creating it first if necessary. | [
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] | def sconsign_dir(node):
"""Return the .sconsign file info for this directory,
creating it first if necessary."""
if not node._sconsign:
import SCons.SConsign
node._sconsign = SCons.SConsign.ForDirectory(node)
return node._sconsign | [
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|
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/rosbag/src/rosbag/bag.py | python | Bag.reindex | (self) | return self._reader.reindex() | Reindexes the bag file. Yields position of each chunk for progress. | Reindexes the bag file. Yields position of each chunk for progress. | [
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"""
Reindexes the bag file. Yields position of each chunk for progress.
"""
self._clear_index()
return self._reader.reindex() | [
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|
adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | third_party/protobuf/python/google/protobuf/internal/decoder.py | python | _EndGroup | (buffer, pos, end) | return -1 | Skipping an END_GROUP tag returns -1 to tell the parent loop to break. | Skipping an END_GROUP tag returns -1 to tell the parent loop to break. | [
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"""Skipping an END_GROUP tag returns -1 to tell the parent loop to break."""
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/stats/_distn_infrastructure.py | python | _expect | (fun, lb, ub, x0, inc, maxcount=1000, tolerance=1e-10,
chunksize=32) | return tot | Helper for computing the expectation value of `fun`. | Helper for computing the expectation value of `fun`. | [
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chunksize=32):
"""Helper for computing the expectation value of `fun`."""
# short-circuit if the support size is small enough
if (ub - lb) <= chunksize:
supp = np.arange(lb, ub+1, inc)
vals = fun(supp)
return np.sum(vals)
# otherwise, iterate starting from x0
if x0 < lb:
x0 = lb
if x0 > ub:
x0 = ub
count, tot = 0, 0.
# iterate over [x0, ub] inclusive
for x in _iter_chunked(x0, ub+1, chunksize=chunksize, inc=inc):
count += x.size
delta = np.sum(fun(x))
tot += delta
if abs(delta) < tolerance * x.size:
break
if count > maxcount:
warnings.warn('expect(): sum did not converge', RuntimeWarning)
return tot
# iterate over [lb, x0)
for x in _iter_chunked(x0-1, lb-1, chunksize=chunksize, inc=-inc):
count += x.size
delta = np.sum(fun(x))
tot += delta
if abs(delta) < tolerance * x.size:
break
if count > maxcount:
warnings.warn('expect(): sum did not converge', RuntimeWarning)
break
return tot | [
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|
pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/deps/v8/third_party/jinja2/compiler.py | python | CodeGenerator.write_commons | (self) | Writes a common preamble that is used by root and block functions.
Primarily this sets up common local helpers and enforces a generator
through a dead branch. | Writes a common preamble that is used by root and block functions.
Primarily this sets up common local helpers and enforces a generator
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] | def write_commons(self):
"""Writes a common preamble that is used by root and block functions.
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self.writeline('resolve = context.resolve_or_missing')
self.writeline('undefined = environment.undefined')
self.writeline('if 0: yield None') | [
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||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | BaseWidget.destroy | (self) | Destroy this and all descendants widgets. | Destroy this and all descendants widgets. | [
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self.tk.call('destroy', self._w)
if self._name in self.master.children:
del self.master.children[self._name]
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||
livecode/livecode | 4606a10ea10b16d5071d0f9f263ccdd7ede8b31d | gyp/pylib/gyp/mac_tool.py | python | MacTool._GetCFBundleIdentifier | (self) | return info_plist_data['CFBundleIdentifier'] | Extracts CFBundleIdentifier value from Info.plist in the bundle.
Returns:
Value of CFBundleIdentifier in the Info.plist located in the bundle. | Extracts CFBundleIdentifier value from Info.plist in the bundle. | [
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] | def _GetCFBundleIdentifier(self):
"""Extracts CFBundleIdentifier value from Info.plist in the bundle.
Returns:
Value of CFBundleIdentifier in the Info.plist located in the bundle.
"""
info_plist_path = os.path.join(
os.environ['TARGET_BUILD_DIR'],
os.environ['INFOPLIST_PATH'])
info_plist_data = self._LoadPlistMaybeBinary(info_plist_path)
return info_plist_data['CFBundleIdentifier'] | [
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|
NVIDIAGameWorks/kaolin | e5148d05e9c1e2ce92a07881ce3593b1c5c3f166 | kaolin/ops/voxelgrid.py | python | extract_surface | (voxelgrids, mode="wide") | return output | r"""Removes any internal structure(s) from a voxelgrids.
Args:
voxelgrids (torch.Tensor): Binary voxelgrids of shape (N, X, Y ,Z)
from which to extract surface
mode (str): Either "wide" or "thin". Each voxel can be seen as a cube in a grid.
"wide" mode keeps each filled voxel with at least one vertex in contact
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Returns:
torch.BoolTensor: binary surface voxelgrids tensor
Example:
>>> voxelgrids = torch.ones((1, 3, 3, 3))
>>> output = extract_surface(voxelgrids)
>>> output[0]
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[ True, True, True],
[ True, True, True]]]) | r"""Removes any internal structure(s) from a voxelgrids. | [
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] | def extract_surface(voxelgrids, mode="wide"):
r"""Removes any internal structure(s) from a voxelgrids.
Args:
voxelgrids (torch.Tensor): Binary voxelgrids of shape (N, X, Y ,Z)
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voxelgrids = _force_float(voxelgrids)
if voxelgrids.ndim != 4:
voxelgrids_dim = voxelgrids.ndim
raise ValueError(f"Expected voxelgrids to have 4 dimensions "
f"but got {voxelgrids_dim} dimensions.")
if mode == "wide":
output = F.avg_pool3d(voxelgrids.unsqueeze(1), kernel_size=(3, 3, 3), padding=1, stride=1).squeeze(1)
output = (output < 1) * voxelgrids.bool()
elif mode == "thin":
output_x = F.avg_pool3d(voxelgrids.unsqueeze(1), kernel_size=(3, 1, 1), padding=(1, 0, 0), stride=1).squeeze(1)
output_y = F.avg_pool3d(voxelgrids.unsqueeze(1), kernel_size=(1, 3, 1), padding=(0, 1, 0), stride=1).squeeze(1)
output_z = F.avg_pool3d(voxelgrids.unsqueeze(1), kernel_size=(1, 1, 3), padding=(0, 0, 1), stride=1).squeeze(1)
output = ((output_x < 1) | (output_y < 1) | (output_z < 1)) * voxelgrids.bool()
else:
raise ValueError(f'mode "{mode}" is not supported.')
return output | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/protobuf/py3/google/protobuf/service.py | python | RpcController.Failed | (self) | Returns true if the call failed.
After a call has finished, returns true if the call failed. The possible
reasons for failure depend on the RPC implementation. Failed() must not
be called before a call has finished. If Failed() returns true, the
contents of the response message are undefined. | Returns true if the call failed. | [
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"""Returns true if the call failed.
After a call has finished, returns true if the call failed. The possible
reasons for failure depend on the RPC implementation. Failed() must not
be called before a call has finished. If Failed() returns true, the
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"""
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||
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/rospy/src/rospy/topics.py | python | _SubscriberImpl.set_buff_size | (self, buff_size) | Set the receive buffer size. The exact meaning of this is
transport dependent.
@param buff_size: receive buffer size
@type buff_size: int | Set the receive buffer size. The exact meaning of this is
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if type(buff_size) != int:
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amd/OpenCL-caffe | 638543108517265366c18ae5821f3096cf5cf34a | python/caffe/io.py | python | array_to_blobproto | (arr, diff=None) | return blob | Converts a 4-dimensional array to blob proto. If diff is given, also
convert the diff. You need to make sure that arr and diff have the same
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/ssl.py | python | SSLSocket.do_handshake | (self) | Perform a TLS/SSL handshake. | Perform a TLS/SSL handshake. | [
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||
FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/drafttaskpanels/task_scale.py | python | ScaleTaskPanel.setValue | (self, val=None) | Set the value of the points. | Set the value of the points. | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/analogclock/analogclock.py | python | AnalogClock.GetTickSize | (self, target=ALL) | return self.Box.GetTickSize(target) | Gets sizes of ticks. | Gets sizes of ticks. | [
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return self.Box.GetTickSize(target) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/gslib/copy_helper.py | python | _CompressFileForUpload | (src_url, src_obj_filestream, src_obj_size, logger) | return StorageUrlFromString(gzip_path), gzip_size | Compresses a to-be-uploaded local file to save bandwidth.
Args:
src_url: Source FileUrl.
src_obj_filestream: Read stream of the source file - will be consumed
and closed.
src_obj_size: Size of the source file.
logger: for outputting log messages.
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"""Compresses a to-be-uploaded local file to save bandwidth.
Args:
src_url: Source FileUrl.
src_obj_filestream: Read stream of the source file - will be consumed
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src_obj_size: Size of the source file.
logger: for outputting log messages.
Returns:
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"""
# TODO: Compress using a streaming model as opposed to all at once here.
if src_obj_size >= MIN_SIZE_COMPUTE_LOGGING:
logger.info(
'Compressing %s (to tmp)...', src_url)
(gzip_fh, gzip_path) = tempfile.mkstemp()
gzip_fp = None
try:
# Check for temp space. Assume the compressed object is at most 2x
# the size of the object (normally should compress to smaller than
# the object)
if CheckFreeSpace(gzip_path) < 2*int(src_obj_size):
raise CommandException('Inadequate temp space available to compress '
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gzip_fp = gzip.open(gzip_path, 'wb')
data = src_obj_filestream.read(GZIP_CHUNK_SIZE)
while data:
gzip_fp.write(data)
data = src_obj_filestream.read(GZIP_CHUNK_SIZE)
finally:
if gzip_fp:
gzip_fp.close()
os.close(gzip_fh)
src_obj_filestream.close()
gzip_size = os.path.getsize(gzip_path)
return StorageUrlFromString(gzip_path), gzip_size | [
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|
blackberry/Boost | fc90c3fde129c62565c023f091eddc4a7ed9902b | tools/build/v2/build/property_set.py | python | PropertySet.add | (self, ps) | return self.added_[ps] | Creates a new property set containing the properties in this one,
plus the ones of the property set passed as argument. | Creates a new property set containing the properties in this one,
plus the ones of the property set passed as argument. | [
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if not self.added_.has_key(ps):
self.added_[ps] = create(self.all_ + ps.all())
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|
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/python/turicreate/meta/asttools/visitors/graph_visitor.py | python | make_graph | (node, call_deps=False) | return gen.graph, gen.undefined | Create a dependency graph from an ast node.
:param node: ast node.
:param call_deps: if true, then the graph will create a cyclic dependence for all
function calls. (i.e for `a.b(c)` a depends on b and b depends on a)
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"""
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:param node: ast node.
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function calls. (i.e for `a.b(c)` a depends on b and b depends on a)
:returns: a tuple of (graph, undefined)
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gen = GraphGen(call_deps=call_deps)
gen.visit(node)
return gen.graph, gen.undefined | [
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/tools/gyp/pylib/gyp/generator/msvs.py | python | _GetLibraryDirs | (config) | return library_dirs | Returns the list of directories to be used for library search paths.
Arguments:
config: The dictionary that defines the special processing to be done
for this configuration.
Returns:
The list of directory paths. | Returns the list of directories to be used for library search paths. | [
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Arguments:
config: The dictionary that defines the special processing to be done
for this configuration.
Returns:
The list of directory paths.
"""
library_dirs = config.get('library_dirs', [])
library_dirs = _FixPaths(library_dirs)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/aui.py | python | AuiManager.DrawHintRect | (*args, **kwargs) | return _aui.AuiManager_DrawHintRect(*args, **kwargs) | DrawHintRect(self, Window paneWindow, Point pt, Point offset) | DrawHintRect(self, Window paneWindow, Point pt, Point offset) | [
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"""DrawHintRect(self, Window paneWindow, Point pt, Point offset)"""
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