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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_gdi.py | python | DC.DrawBitmap | (*args, **kwargs) | return _gdi_.DC_DrawBitmap(*args, **kwargs) | DrawBitmap(self, Bitmap bmp, int x, int y, bool useMask=False)
Draw a bitmap on the device context at the specified point. If
*transparent* is true and the bitmap has a transparency mask, (or
alpha channel on the platforms that support it) then the bitmap will
be drawn transparently. | DrawBitmap(self, Bitmap bmp, int x, int y, bool useMask=False) | [
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fatih/subvim | 241b6d170597857105da219c9b7d36059e9f11fb | vim/base/YouCompleteMe/third_party/pythonfutures/concurrent/futures/_base.py | python | Executor.submit | (self, fn, *args, **kwargs) | Submits a callable to be executed with the given arguments.
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/grid.py | python | GridCellBoolEditor.UseStringValues | (*args, **kwargs) | return _grid.GridCellBoolEditor_UseStringValues(*args, **kwargs) | UseStringValues(String valueTrue=OneString, String valueFalse=EmptyString) | UseStringValues(String valueTrue=OneString, String valueFalse=EmptyString) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Jinja2/py2/jinja2/runtime.py | python | make_logging_undefined | (logger=None, base=None) | return LoggingUndefined | Given a logger object this returns a new undefined class that will
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:param logger: the logger to use. If not provided, a default logger
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/dataclasses.py | python | fields | (class_or_instance) | return tuple(f for f in fields.values() if f._field_type is _FIELD) | Return a tuple describing the fields of this dataclass.
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"""
# Might it be worth caching this, per class?
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/distutils/dist.py | python | Distribution.__init__ | (self, attrs=None) | Construct a new Distribution instance: initialize all the
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# we need to create a new command object, and 2) have a way
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self.cmdclass = {}
# 'command_packages' is a list of packages in which commands
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# to be named 'foo' in the module 'foo' in one of the packages
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self.script_name = None
self.script_args = None
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# they are actually needed -- ie. when the command in question is
# instantiated. It is a dictionary of dictionaries of 2-tuples:
# command_options = { command_name : { option : (source, value) } }
self.command_options = {}
# 'dist_files' is the list of (command, pyversion, file) that
# have been created by any dist commands run so far. This is
# filled regardless of whether the run is dry or not. pyversion
# gives sysconfig.get_python_version() if the dist file is
# specific to a Python version, 'any' if it is good for all
# Python versions on the target platform, and '' for a source
# file. pyversion should not be used to specify minimum or
# maximum required Python versions; use the metainfo for that
# instead.
self.dist_files = []
# These options are really the business of various commands, rather
# than of the Distribution itself. We provide aliases for them in
# Distribution as a convenience to the developer.
self.packages = None
self.package_data = {}
self.package_dir = None
self.py_modules = None
self.libraries = None
self.headers = None
self.ext_modules = None
self.ext_package = None
self.include_dirs = None
self.extra_path = None
self.scripts = None
self.data_files = None
self.password = ''
# And now initialize bookkeeping stuff that can't be supplied by
# the caller at all. 'command_obj' maps command names to
# Command instances -- that's how we enforce that every command
# class is a singleton.
self.command_obj = {}
# 'have_run' maps command names to boolean values; it keeps track
# of whether we have actually run a particular command, to make it
# cheap to "run" a command whenever we think we might need to -- if
# it's already been done, no need for expensive filesystem
# operations, we just check the 'have_run' dictionary and carry on.
# It's only safe to query 'have_run' for a command class that has
# been instantiated -- a false value will be inserted when the
# command object is created, and replaced with a true value when
# the command is successfully run. Thus it's probably best to use
# '.get()' rather than a straight lookup.
self.have_run = {}
# Now we'll use the attrs dictionary (ultimately, keyword args from
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# distribution options.
if attrs:
# Pull out the set of command options and work on them
# specifically. Note that this order guarantees that aliased
# command options will override any supplied redundantly
# through the general options dictionary.
options = attrs.get('options')
if options is not None:
del attrs['options']
for (command, cmd_options) in options.items():
opt_dict = self.get_option_dict(command)
for (opt, val) in cmd_options.items():
opt_dict[opt] = ("setup script", val)
if 'licence' in attrs:
attrs['license'] = attrs['licence']
del attrs['licence']
msg = "'licence' distribution option is deprecated; use 'license'"
if warnings is not None:
warnings.warn(msg)
else:
sys.stderr.write(msg + "\n")
# Now work on the rest of the attributes. Any attribute that's
# not already defined is invalid!
for (key, val) in attrs.items():
if hasattr(self.metadata, "set_" + key):
getattr(self.metadata, "set_" + key)(val)
elif hasattr(self.metadata, key):
setattr(self.metadata, key, val)
elif hasattr(self, key):
setattr(self, key, val)
else:
msg = "Unknown distribution option: %s" % repr(key)
warnings.warn(msg)
# no-user-cfg is handled before other command line args
# because other args override the config files, and this
# one is needed before we can load the config files.
# If attrs['script_args'] wasn't passed, assume false.
#
# This also make sure we just look at the global options
self.want_user_cfg = True
if self.script_args is not None:
for arg in self.script_args:
if not arg.startswith('-'):
break
if arg == '--no-user-cfg':
self.want_user_cfg = False
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/layers/python/layers/feature_column.py | python | _LazyBuilderByColumnsToTensor.get | (self, key) | return self._columns_to_tensors[key] | Gets the transformed feature column. | Gets the transformed feature column. | [
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emscripten-core/emscripten | 0d413d3c5af8b28349682496edc14656f5700c2f | third_party/ply/example/GardenSnake/GardenSnake.py | python | p_comparison | (p) | comparison : comparison PLUS comparison
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| comparison MULT comparison
| comparison DIV comparison
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| comparison EQ comparison
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metashell/metashell | f4177e4854ea00c8dbc722cadab26ef413d798ea | 3rd/templight/compiler-rt/lib/sanitizer_common/scripts/cpplint.py | python | IsDecltype | (clean_lines, linenum, column) | return False | Check if the token ending on (linenum, column) is decltype().
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/balloontip.py | python | BalloonTip.SetTitleColour | (self, colour=None) | Sets the colour for the top title.
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InsightSoftwareConsortium/ITK | 87acfce9a93d928311c38bc371b666b515b9f19d | Modules/ThirdParty/pygccxml/src/pygccxml/declarations/class_declaration.py | python | hierarchy_info_t.related_class | (self) | return self._related_class | reference to base or derived :class:`class <class_t>` | reference to base or derived :class:`class <class_t>` | [
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"""reference to base or derived :class:`class <class_t>`"""
return self._related_class | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/s3transfer/processpool.py | python | TransferMonitor.notify_done | (self, transfer_id) | Notify a particular transfer is complete
:param transfer_id: Unique identifier for the transfer | Notify a particular transfer is complete | [
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] | def notify_done(self, transfer_id):
"""Notify a particular transfer is complete
:param transfer_id: Unique identifier for the transfer
"""
self._transfer_states[transfer_id].set_done() | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/server/wsgi/serve/push/search/core/search_manager.py | python | SearchManager.HandlePingRequest | (self, request, response) | Handles ping database request.
Args:
request: request object.
response: response object
Raises:
psycopg2.Error/Warning. | Handles ping database request. | [
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] | def HandlePingRequest(self, request, response):
"""Handles ping database request.
Args:
request: request object.
response: response object
Raises:
psycopg2.Error/Warning.
"""
cmd = request.GetParameter(constants.CMD)
assert cmd == "Ping"
# Fire off a pinq query to make sure we have a valid db connection.
query_string = "SELECT 'ping'"
results = self._DbQuery(query_string)
if results and results[0] == "ping":
http_io.ResponseWriter.AddBodyElement(
response, constants.HDR_STATUS_CODE, constants.STATUS_SUCCESS)
else:
http_io.ResponseWriter.AddBodyElement(
response, constants.HDR_STATUS_MESSAGE,
"Cannot ping gesearch database.")
http_io.ResponseWriter.AddBodyElement(
response, constants.HDR_STATUS_CODE, constants.STATUS_FAILURE) | [
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/landuse/landuse.py | python | Facilities.get_ids_building | (self, ids=None) | return ids[self.get_landusetypes().are_area[self.ids_landusetype[ids]] == False] | Returns all building type of facilities | Returns all building type of facilities | [
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"""Returns all building type of facilities"""
# print 'get_ids_building'
if ids is None:
ids = self.get_ids()
# debug
#landusetypes = self.get_landusetypes()
# for id_fac in ids[self.get_landusetypes().are_area[self.ids_landusetype[ids]] == False]:
# id_landusetype = self.ids_landusetype[id_fac]
# print ' id_fac',id_fac,id_landusetype,'is_area',landusetypes.are_area[id_landusetype]
return ids[self.get_landusetypes().are_area[self.ids_landusetype[ids]] == False] | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBHostOS_GetLLDBPath | (*args) | return _lldb.SBHostOS_GetLLDBPath(*args) | SBHostOS_GetLLDBPath(PathType path_type) -> SBFileSpec | SBHostOS_GetLLDBPath(PathType path_type) -> SBFileSpec | [
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"""SBHostOS_GetLLDBPath(PathType path_type) -> SBFileSpec"""
return _lldb.SBHostOS_GetLLDBPath(*args) | [
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YannickJadoul/Parselmouth | 355c4746531c948faaaf9b13b828e5afea621efd | pybind11/pybind11/setup_helpers.py | python | ParallelCompile.function | (self) | return compile_function | Builds a function object usable as distutils.ccompiler.CCompiler.compile. | Builds a function object usable as distutils.ccompiler.CCompiler.compile. | [
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"""
Builds a function object usable as distutils.ccompiler.CCompiler.compile.
"""
def compile_function(
compiler,
sources,
output_dir=None,
macros=None,
include_dirs=None,
debug=0,
extra_preargs=None,
extra_postargs=None,
depends=None,
):
# These lines are directly from distutils.ccompiler.CCompiler
macros, objects, extra_postargs, pp_opts, build = compiler._setup_compile(
output_dir, macros, include_dirs, sources, depends, extra_postargs
)
cc_args = compiler._get_cc_args(pp_opts, debug, extra_preargs)
# The number of threads; start with default.
threads = self.default
# Determine the number of compilation threads, unless set by an environment variable.
if self.envvar is not None:
threads = int(os.environ.get(self.envvar, self.default))
def _single_compile(obj):
try:
src, ext = build[obj]
except KeyError:
return
if not os.path.exists(obj) or self.needs_recompile(obj, src):
compiler._compile(obj, src, ext, cc_args, extra_postargs, pp_opts)
try:
import multiprocessing
from multiprocessing.pool import ThreadPool
except ImportError:
threads = 1
if threads == 0:
try:
threads = multiprocessing.cpu_count()
threads = self.max if self.max and self.max < threads else threads
except NotImplementedError:
threads = 1
if threads > 1:
for _ in ThreadPool(threads).imap_unordered(_single_compile, objects):
pass
else:
for ob in objects:
_single_compile(ob)
return objects
return compile_function | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/idl/idl/ast.py | python | ServerParameterClass.__init__ | (self, file_name, line, column) | Construct a ServerParameterClass. | Construct a ServerParameterClass. | [
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# type: (str, int, int) -> None
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self.name = None # type: str
self.data = None # type: str
self.override_ctor = False # type: bool
self.override_set = False # type: bool
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limbo018/DREAMPlace | 146c3b9fd003d1acd52c96d9fd02e3f0a05154e4 | dreamplace/PlaceObj.py | python | PlaceObj.build_weighted_average_wl | (self, params, placedb, data_collections,
pin_pos_op) | return build_wirelength_op, build_update_gamma_op | @brief build the op to compute weighted average wirelength
@param params parameters
@param placedb placement database
@param data_collections a collection of data and variables required for constructing ops
@param pin_pos_op the op to compute pin locations according to cell locations | [] | def build_weighted_average_wl(self, params, placedb, data_collections,
pin_pos_op):
"""
@brief build the op to compute weighted average wirelength
@param params parameters
@param placedb placement database
@param data_collections a collection of data and variables required for constructing ops
@param pin_pos_op the op to compute pin locations according to cell locations
"""
# use WeightedAverageWirelength atomic
wirelength_for_pin_op = weighted_average_wirelength.WeightedAverageWirelength(
flat_netpin=data_collections.flat_net2pin_map,
netpin_start=data_collections.flat_net2pin_start_map,
pin2net_map=data_collections.pin2net_map,
net_weights=data_collections.net_weights,
net_mask=data_collections.net_mask_ignore_large_degrees,
pin_mask=data_collections.pin_mask_ignore_fixed_macros,
gamma=self.gamma,
algorithm='merged')
# wirelength for position
def build_wirelength_op(pos):
return wirelength_for_pin_op(pin_pos_op(pos))
# update gamma
base_gamma = self.base_gamma(params, placedb)
def build_update_gamma_op(iteration, overflow):
self.update_gamma(iteration, overflow, base_gamma)
#logging.debug("update gamma to %g" % (wirelength_for_pin_op.gamma.data))
return build_wirelength_op, build_update_gamma_op | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/distutils/_shell_utils.py | python | CommandLineParser.split | (cmd) | Split a command line string into a list of arguments | Split a command line string into a list of arguments | [
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | gr-utils/modtool/templates/gr-newmod/docs/doxygen/other/doxypy.py | python | Doxypy.resetCommentSearch | (self, match) | Restarts a new comment search for a different triggering line.
Closes the current commentblock and starts a new comment search. | Restarts a new comment search for a different triggering line. | [
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] | def resetCommentSearch(self, match):
"""Restarts a new comment search for a different triggering line.
Closes the current commentblock and starts a new comment search.
"""
if args.debug:
print("# CALLBACK: resetCommentSearch", file=sys.stderr)
self.__closeComment()
self.startCommentSearch(match) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/grid.py | python | Grid.GetGridColLabelWindow | (*args, **kwargs) | return _grid.Grid_GetGridColLabelWindow(*args, **kwargs) | GetGridColLabelWindow(self) -> Window | GetGridColLabelWindow(self) -> Window | [
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"""GetGridColLabelWindow(self) -> Window"""
return _grid.Grid_GetGridColLabelWindow(*args, **kwargs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_misc.py | python | Log.SetComponentLevel | (*args, **kwargs) | return _misc_.Log_SetComponentLevel(*args, **kwargs) | SetComponentLevel(String component, LogLevel level) | SetComponentLevel(String component, LogLevel level) | [
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return _misc_.Log_SetComponentLevel(*args, **kwargs) | [
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | samples/networking/01-simple-connection/client.py | python | GameClientRepository.connectSuccess | (self) | Successfully connected. But we still can't really do
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anything until we've got the doID range. """
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# it's just to display how it works for this small example.
self.setInterestZones([1, 2, 3])
# This method checks whether we actually have a valid doID range
# to create distributed objects yet
if self.haveCreateAuthority():
# we already have one
self.gotCreateReady()
else:
# Not yet, keep waiting a bit longer.
self.accept(self.uniqueName('createReady'), self.gotCreateReady) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pkg_resources/__init__.py | python | EntryPoint.parse_map | (cls, data, dist=None) | return maps | Parse a map of entry point groups | Parse a map of entry point groups | [
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data = data.items()
else:
data = split_sections(data)
maps = {}
for group, lines in data:
if group is None:
if not lines:
continue
raise ValueError("Entry points must be listed in groups")
group = group.strip()
if group in maps:
raise ValueError("Duplicate group name", group)
maps[group] = cls.parse_group(group, lines, dist)
return maps | [
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPMS_AUTH_COMMAND.fromBytes | (buffer) | return TpmBuffer(buffer).createObj(TPMS_AUTH_COMMAND) | Returns new TPMS_AUTH_COMMAND object constructed from its marshaled
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/protorpc/gen_protorpc.py | python | registry_command | (options,
host,
service_name=None,
registry_path='/protorpc') | Generate source directory structure from remote registry service.
Args:
options: Parsed command line options.
host: Web service host where registry service is located. May include
port.
service_name: Name of specific service to read. Will generate only Python
files that service is dependent on. If None, will generate source code
for all services known by the registry.
registry_path: Path to find registry if not the default 'protorpc'. | Generate source directory structure from remote registry service. | [
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] | def registry_command(options,
host,
service_name=None,
registry_path='/protorpc'):
"""Generate source directory structure from remote registry service.
Args:
options: Parsed command line options.
host: Web service host where registry service is located. May include
port.
service_name: Name of specific service to read. Will generate only Python
files that service is dependent on. If None, will generate source code
for all services known by the registry.
registry_path: Path to find registry if not the default 'protorpc'.
"""
dest_dir = os.path.expanduser(options.dest_dir)
url = 'http://%s%s' % (host, registry_path)
reg = registry.RegistryService.Stub(transport.HttpTransport(url))
if service_name is None:
service_names = [service.name for service in reg.services().services]
else:
service_names = [service_name]
file_set = reg.get_file_set(names=service_names).file_set
for file_descriptor in file_set.files:
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/kfac/examples/convnet.py | python | _num_gradient_tasks | (num_tasks) | return int(np.ceil(0.6 * num_tasks)) | Number of tasks that will update weights. | Number of tasks that will update weights. | [
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"""Number of tasks that will update weights."""
if num_tasks < 3:
return num_tasks
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/graph_editor/util.py | python | check_graphs | (*args) | Check that all the element in args belong to the same graph.
Args:
*args: a list of object with a obj.graph property.
Raises:
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Args:
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Raises:
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"""
graph = None
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graph = sgv.graph
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/tkinter/__init__.py | python | Menu.index | (self, index) | return self.tk.getint(i) | Return the index of a menu item identified by INDEX. | Return the index of a menu item identified by INDEX. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/combo.py | python | ComboPopup.Create | (*args, **kwargs) | return _combo.ComboPopup_Create(*args, **kwargs) | Create(self, Window parent) -> bool
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than that there is much flexibility in what the widget can be, its
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/utils/git-svn/convert.py | python | do_convert | (file) | Skip all preceding mail message headers until 'From: ' is encountered.
Then for each line ('From: ' header included), replace the dos style CRLF
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"""Skip all preceding mail message headers until 'From: ' is encountered.
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"""
print "converting %s ..." % file
with open(file, 'r') as f_in:
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# Boolean flag controls whether to start printing lines.
from_header_seen = False
# By default, splitlines() don't include line breaks. CRLF should be gone.
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with open(file, 'w') as f_out:
f_out.write(new_content.getvalue())
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adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | tools/json_schema_compiler/cpp_type_generator.py | python | CppTypeGenerator.GetEnumNoneValue | (self, prop) | return '%s_NONE' % prop.unix_name.upper() | Gets the enum value in the given model.Property indicating no value has
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"""
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/pyrsistent/_field_common.py | python | field | (type=PFIELD_NO_TYPE, invariant=PFIELD_NO_INVARIANT, initial=PFIELD_NO_INITIAL,
mandatory=False, factory=PFIELD_NO_FACTORY, serializer=PFIELD_NO_SERIALIZER) | return field | Field specification factory for :py:class:`PRecord`.
:param type: a type or iterable with types that are allowed for this field
:param invariant: a function specifying an invariant that must hold for the field
:param initial: value of field if not specified when instantiating the record
:param mandatory: boolean specifying if the field is mandatory or not
:param factory: function called when field is set.
:param serializer: function that returns a serialized version of the field | Field specification factory for :py:class:`PRecord`. | [
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mandatory=False, factory=PFIELD_NO_FACTORY, serializer=PFIELD_NO_SERIALIZER):
"""
Field specification factory for :py:class:`PRecord`.
:param type: a type or iterable with types that are allowed for this field
:param invariant: a function specifying an invariant that must hold for the field
:param initial: value of field if not specified when instantiating the record
:param mandatory: boolean specifying if the field is mandatory or not
:param factory: function called when field is set.
:param serializer: function that returns a serialized version of the field
"""
# NB: We have to check this predicate separately from the predicates in
# `maybe_parse_user_type` et al. because this one is related to supporting
# the argspec for `field`, while those are related to supporting the valid
# ways to specify types.
# Multiple types must be passed in one of the following containers. Note
# that a type that is a subclass of one of these containers, like a
# `collections.namedtuple`, will work as expected, since we check
# `isinstance` and not `issubclass`.
if isinstance(type, (list, set, tuple)):
types = set(maybe_parse_many_user_types(type))
else:
types = set(maybe_parse_user_type(type))
invariant_function = wrap_invariant(invariant) if invariant != PFIELD_NO_INVARIANT and callable(invariant) else invariant
field = _PField(type=types, invariant=invariant_function, initial=initial,
mandatory=mandatory, factory=factory, serializer=serializer)
_check_field_parameters(field)
return field | [
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | grc/core/base.py | python | Element.validate | (self) | Validate this element and call validate on all children.
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"""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | Window.GetScreenPosition | (*args, **kwargs) | return _core_.Window_GetScreenPosition(*args, **kwargs) | GetScreenPosition(self) -> Point
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"""
GetScreenPosition(self) -> Point
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"""
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intel/llvm | e6d0547e9d99b5a56430c4749f6c7e328bf221ab | mlir/utils/spirv/gen_spirv_dialect.py | python | update_td_opcodes | (path, instructions, filter_list) | Updates SPIRBase.td with new generated opcode cases.
Arguments:
- path: the path to SPIRBase.td
- instructions: a list containing all SPIR-V instructions' grammar
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] | def update_td_opcodes(path, instructions, filter_list):
"""Updates SPIRBase.td with new generated opcode cases.
Arguments:
- path: the path to SPIRBase.td
- instructions: a list containing all SPIR-V instructions' grammar
- filter_list: a list containing new opnames to add
"""
with open(path, 'r') as f:
content = f.read()
content = content.split(AUTOGEN_OPCODE_SECTION_MARKER)
assert len(content) == 3
# Extend opcode list with existing list
existing_opcodes = [k[11:] for k in re.findall('def SPV_OC_\w+', content[1])]
filter_list.extend(existing_opcodes)
filter_list = list(set(filter_list))
# Generate the opcode for all instructions in SPIR-V
filter_instrs = list(
filter(lambda inst: (inst['opname'] in filter_list), instructions))
# Sort instruction based on opcode
filter_instrs.sort(key=lambda inst: inst['opcode'])
opcode = gen_opcode(filter_instrs)
# Substitute the opcode
content = content[0] + AUTOGEN_OPCODE_SECTION_MARKER + '\n\n' + \
opcode + '\n\n// End ' + AUTOGEN_OPCODE_SECTION_MARKER \
+ content[2]
with open(path, 'w') as f:
f.write(content) | [
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thalium/icebox | 99d147d5b9269222225443ce171b4fd46d8985d4 | third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py | python | parserCtxt.parsePubidLiteral | (self) | return ret | parse an XML public literal [12] PubidLiteral ::= '"'
PubidChar* '"' | "'" (PubidChar - "'")* "'" | parse an XML public literal [12] PubidLiteral ::= '"'
PubidChar* '"' | "'" (PubidChar - "'")* "'" | [
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"""parse an XML public literal [12] PubidLiteral ::= '"'
PubidChar* '"' | "'" (PubidChar - "'")* "'" """
ret = libxml2mod.xmlParsePubidLiteral(self._o)
return ret | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/tensor_forest/data/data_ops.py | python | ParseLabelTensorOrDict | (labels) | Return a tensor to use for input labels to tensor_forest.
The incoming targets can be a dict where keys are the string names of the
columns, which we turn into a single 1-D tensor for classification or
2-D tensor for regression.
Converts sparse tensors to dense ones.
Args:
labels: `Tensor` or `dict` of `Tensor` objects.
Returns:
A 2-D tensor for labels/outputs. | Return a tensor to use for input labels to tensor_forest. | [
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] | def ParseLabelTensorOrDict(labels):
"""Return a tensor to use for input labels to tensor_forest.
The incoming targets can be a dict where keys are the string names of the
columns, which we turn into a single 1-D tensor for classification or
2-D tensor for regression.
Converts sparse tensors to dense ones.
Args:
labels: `Tensor` or `dict` of `Tensor` objects.
Returns:
A 2-D tensor for labels/outputs.
"""
if isinstance(labels, dict):
return math_ops.to_float(array_ops.concat(
1, [sparse_ops.sparse_tensor_to_dense(labels[
k], default_value=-1) if isinstance(labels, ops.SparseTensor) else
labels[k] for k in sorted(labels.keys())]))
else:
if isinstance(labels, ops.SparseTensor):
return math_ops.to_float(sparse_ops.sparse_tensor_to_dense(
labels, default_value=-1))
else:
return math_ops.to_float(labels) | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/distributions/python/ops/bijector.py | python | _Bijector.name | (self) | return self._name | Returns the string name of this `Bijector`. | Returns the string name of this `Bijector`. | [
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/tools/gyp/pylib/gyp/generator/make.py | python | MakefileWriter.WriteList | (self, value_list, variable=None, prefix='',
quoter=QuoteIfNecessary) | Write a variable definition that is a list of values.
E.g. WriteList(['a','b'], 'foo', prefix='blah') writes out
foo = blaha blahb
but in a pretty-printed style. | Write a variable definition that is a list of values. | [
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quoter=QuoteIfNecessary):
"""Write a variable definition that is a list of values.
E.g. WriteList(['a','b'], 'foo', prefix='blah') writes out
foo = blaha blahb
but in a pretty-printed style.
"""
values = ''
if value_list:
value_list = [quoter(prefix + l) for l in value_list]
values = ' \\\n\t' + ' \\\n\t'.join(value_list)
self.fp.write('%s :=%s\n\n' % (variable, values)) | [
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xhzdeng/crpn | a5aef0f80dbe486103123f740c634fb01e6cc9a1 | caffe-fast-rcnn/python/caffe/classifier.py | python | Classifier.predict | (self, inputs, oversample=True) | return predictions | Predict classification probabilities of inputs.
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input_[ix] = caffe.io.resize_image(in_, self.image_dims)
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caffe_in = np.zeros(np.array(input_.shape)[[0, 3, 1, 2]],
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SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/util/fslike/path.py | python | Path._resolve_w | (self) | return self.fsobj.resolve_w(self.parts) | Flatten the path recursively for write access.
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arangodb/arangodb | 0d658689c7d1b721b314fa3ca27d38303e1570c8 | 3rdParty/V8/v7.9.317/third_party/jinja2/sandbox.py | python | modifies_known_mutable | (obj, attr) | return False | This function checks if an attribute on a builtin mutable object
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/gs/key.py | python | Key.set_contents_from_stream | (self, *args, **kwargs) | Store an object using the name of the Key object as the key in
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snap-stanford/snap-python | d53c51b0a26aa7e3e7400b014cdf728948fde80a | setup/snap.py | python | TNEANet.GetEdgeAttrValue | (self, *args) | return _snap.TNEANet_GetEdgeAttrValue(self, *args) | GetEdgeAttrValue(TNEANet self, int const & EId, TStrIntPrH::TIter const & EdgeHI) -> TStr
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | build/android/pylib/utils/reraiser_thread.py | python | ReraiserThreadGroup.Add | (self, thread) | Add a thread to the group.
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zhaoweicai/cascade-rcnn | 2252f46158ea6555868ca6fa5c221ea71d9b5e6c | scripts/cpp_lint.py | python | FileInfo.IsSource | (self) | return self.Extension()[1:] in ('c', 'cc', 'cpp', 'cxx') | File has a source file extension. | File has a source file extension. | [
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p4lang/p4c | 3272e79369f20813cc1a555a5eb26f44432f84a4 | tools/stf/stf_parser.py | python | STFParser.p_priority | (self, p) | priority : INT_CONST_DEC | priority : INT_CONST_DEC | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/setuptools/wheel.py | python | Wheel.tags | (self) | return itertools.product(
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/distributions/bernoulli.py | python | Bernoulli._mode | (self) | return math_ops.cast(self.probs > 0.5, self.dtype) | Returns `1` if `prob > 0.5` and `0` otherwise. | Returns `1` if `prob > 0.5` and `0` otherwise. | [
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alexgkendall/caffe-posenet | 62aafbd7c45df91acdba14f5d1406d8295c2bc6f | scripts/cpp_lint.py | python | PrintUsage | (message) | Prints a brief usage string and exits, optionally with an error message.
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zufuliu/notepad2 | 680bb88661147936c7ae062da1dae4231486d3c1 | scintilla/scripts/FileGenerator.py | python | UpdateFileFromLines | (path, lines, lineEndToUse) | Join the lines with the lineEndToUse then update file if the result is different. | Join the lines with the lineEndToUse then update file if the result is different. | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/python/turicreate/data_structures/sarray.py | python | SArray.__deepcopy__ | (self, memo) | return SArray(_proxy=self.__proxy__) | Returns a deep copy of the sarray. As the data in an SArray is
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/timeseries/python/timeseries/model_utils.py | python | _check_predict_features | (features) | Raises errors if features are not suitable for prediction. | Raises errors if features are not suitable for prediction. | [
"Raises",
"errors",
"if",
"features",
"are",
"not",
"suitable",
"for",
"prediction",
"."
] | def _check_predict_features(features):
"""Raises errors if features are not suitable for prediction."""
if feature_keys.PredictionFeatures.TIMES not in features:
raise ValueError("Expected a '{}' feature for prediction.".format(
feature_keys.PredictionFeatures.TIMES))
if feature_keys.PredictionFeatures.STATE_TUPLE not in features:
raise ValueError("Expected a '{}' feature for prediction.".format(
feature_keys.PredictionFeatures.STATE_TUPLE))
times_feature = features[feature_keys.PredictionFeatures.TIMES]
if not times_feature.get_shape().is_compatible_with([None, None]):
raise ValueError(
("Expected shape (batch dimension, window size) for feature '{}' "
"(got shape {})").format(feature_keys.PredictionFeatures.TIMES,
times_feature.get_shape()))
_check_feature_shapes_compatible_with(
features=features,
compatible_with_name=feature_keys.PredictionFeatures.TIMES,
compatible_with_value=times_feature,
ignore=set([
feature_keys.PredictionFeatures.STATE_TUPLE # Model-dependent shapes
])) | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/engine/base_layer_utils.py | python | is_in_keras_graph | () | return call_context().in_keras_graph | Returns if currently executing inside of a Keras graph. | Returns if currently executing inside of a Keras graph. | [
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] | def is_in_keras_graph():
"""Returns if currently executing inside of a Keras graph."""
return call_context().in_keras_graph | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBUnixSignals.SetShouldNotify | (self, *args) | return _lldb.SBUnixSignals_SetShouldNotify(self, *args) | SetShouldNotify(self, int32_t signo, bool value) -> bool | SetShouldNotify(self, int32_t signo, bool value) -> bool | [
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"""SetShouldNotify(self, int32_t signo, bool value) -> bool"""
return _lldb.SBUnixSignals_SetShouldNotify(self, *args) | [
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flexflow/FlexFlow | 581fad8ba8d10a16a3102ee2b406b0319586df24 | python/flexflow/core/flexflow_cffi.py | python | FFModel.sigmoid | (self, input, name=None) | return Tensor(handle, owner_op_type=OpType.SIGMOID) | Sigmoid activation function, :math:`sigmoid(x) = 1 / (1 + exp(-x))`.
:param input: the input Tensor.
:type input: Tensor
:param name: the name of the layer. Default is None.
:type name: string
:returns: Tensor -- the output tensor. | Sigmoid activation function, :math:`sigmoid(x) = 1 / (1 + exp(-x))`.
:param input: the input Tensor.
:type input: Tensor
:param name: the name of the layer. Default is None.
:type name: string | [
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:param input: the input Tensor.
:type input: Tensor
:param name: the name of the layer. Default is None.
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c_name = get_c_name(name)
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christinaa/LLVM-VideoCore4 | 7773c3c9e5d22b785d4b96ed0acea37c8aa9c183 | utils/llvm-build/llvmbuild/configutil.py | python | configure_file | (input_path, output_path, substitutions) | return True | configure_file(input_path, output_path, substitutions) -> bool
Given an input and output path, "configure" the file at the given input path
by replacing variables in the file with those given in the substitutions
list. Returns true if the output file was written.
The substitutions list should be given as a list of tuples (regex string,
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The output path's parent directory need not exist (it will be created).
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"""configure_file(input_path, output_path, substitutions) -> bool
Given an input and output path, "configure" the file at the given input path
by replacing variables in the file with those given in the substitutions
list. Returns true if the output file was written.
The substitutions list should be given as a list of tuples (regex string,
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The output path's parent directory need not exist (it will be created).
If the output path does exist and the configured data is not different than
it's current contents, the output file will not be modified. This is
designed to limit the impact of configured files on build dependencies.
"""
# Read in the input data.
f = open(input_path, "rb")
try:
data = f.read()
finally:
f.close()
# Perform the substitutions.
for regex_string,replacement in substitutions:
regex = re.compile(regex_string)
data = regex.sub(replacement, data)
# Ensure the output parent directory exists.
output_parent_path = os.path.dirname(os.path.abspath(output_path))
if not os.path.exists(output_parent_path):
os.makedirs(output_parent_path)
# If the output path exists, load it and compare to the configured contents.
if os.path.exists(output_path):
current_data = None
try:
f = open(output_path, "rb")
try:
current_data = f.read()
except:
current_data = None
f.close()
except:
current_data = None
if current_data is not None and current_data == data:
return False
# Write the output contents.
f = open(output_path, "wb")
try:
f.write(data)
finally:
f.close()
return True | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/ssl.py | python | SSLObject.shared_ciphers | (self) | return self._sslobj.shared_ciphers() | Return a list of ciphers shared by the client during the handshake or
None if this is not a valid server connection. | Return a list of ciphers shared by the client during the handshake or
None if this is not a valid server connection. | [
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"""Return a list of ciphers shared by the client during the handshake or
None if this is not a valid server connection.
"""
return self._sslobj.shared_ciphers() | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/linter/runner.py | python | LintRunner.run | (self, cmd) | return True | Check the specified cmd succeeds. | Check the specified cmd succeeds. | [
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] | def run(self, cmd):
# type: (List[str]) -> bool
"""Check the specified cmd succeeds."""
logging.debug(str(cmd))
try:
subprocess.check_output(cmd).decode('utf-8')
except subprocess.CalledProcessError as cpe:
self._safe_print("CMD [%s] failed:\n%s" % (' '.join(cmd), cpe.output))
return False
return True | [
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logcabin/logcabin | ee6c55ae9744b82b451becd9707d26c7c1b6bbfb | scripts/cpplint.py | python | RemoveMultiLineComments | (filename, lines, error) | Removes multiline (c-style) comments from lines. | Removes multiline (c-style) comments from lines. | [
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"""Removes multiline (c-style) comments from lines."""
count = 0
lineix = 0
while lineix < len(lines):
lineix_begin = FindNextMultiLineCommentStart(lines, lineix)
if lineix_begin >= len(lines):
return
lineix_end = FindNextMultiLineCommentEnd(lines, lineix_begin)
if lineix_end >= len(lines):
error(filename, lineix_begin + 1, 'readability/multiline_comment', 5,
'Could not find end of multi-line comment')
return
#if count == 1:
# if r'\file' not in lines[lineix_begin + 1]:
# error(filename, lineix_begin + 1, 'readability/multiline_comment',
# 5, r'Second comment in file should be Doxygen \file comment.')
RemoveMultiLineCommentsFromRange(lines, lineix_begin, lineix_end + 1)
lineix = lineix_end + 1
count += 1 | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib2to3/fixer_util.py | python | _is_import_binding | (node, name, package=None) | return None | Will reuturn node if node will import name, or node
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See test cases for examples. | Will reuturn node if node will import name, or node
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""" Will reuturn node if node will import name, or node
will import * from package. None is returned otherwise.
See test cases for examples. """
if node.type == syms.import_name and not package:
imp = node.children[1]
if imp.type == syms.dotted_as_names:
for child in imp.children:
if child.type == syms.dotted_as_name:
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if last.type == token.NAME and last.value == name:
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return node
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# unicode(...) is used to make life easier here, because
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if package and unicode(node.children[1]).strip() != package:
return None
n = node.children[3]
if package and _find(u"as", n):
# See test_from_import_as for explanation
return None
elif n.type == syms.import_as_names and _find(name, n):
return node
elif n.type == syms.import_as_name:
child = n.children[2]
if child.type == token.NAME and child.value == name:
return node
elif n.type == token.NAME and n.value == name:
return node
elif package and n.type == token.STAR:
return node
return None | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/algorithms.py | python | diff | (arr, n, axis=0) | return out_arr | difference of n between self,
analogous to s-s.shift(n)
Parameters
----------
arr : ndarray
n : int
number of periods
axis : int
axis to shift on
Returns
-------
shifted | difference of n between self,
analogous to s-s.shift(n) | [
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"""
difference of n between self,
analogous to s-s.shift(n)
Parameters
----------
arr : ndarray
n : int
number of periods
axis : int
axis to shift on
Returns
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shifted
"""
n = int(n)
na = np.nan
dtype = arr.dtype
is_timedelta = False
if needs_i8_conversion(arr):
dtype = np.float64
arr = arr.view('i8')
na = iNaT
is_timedelta = True
elif is_bool_dtype(dtype):
dtype = np.object_
elif is_integer_dtype(dtype):
dtype = np.float64
dtype = np.dtype(dtype)
out_arr = np.empty(arr.shape, dtype=dtype)
na_indexer = [slice(None)] * arr.ndim
na_indexer[axis] = slice(None, n) if n >= 0 else slice(n, None)
out_arr[tuple(na_indexer)] = na
if arr.ndim == 2 and arr.dtype.name in _diff_special:
f = _diff_special[arr.dtype.name]
f(arr, out_arr, n, axis)
else:
res_indexer = [slice(None)] * arr.ndim
res_indexer[axis] = slice(n, None) if n >= 0 else slice(None, n)
res_indexer = tuple(res_indexer)
lag_indexer = [slice(None)] * arr.ndim
lag_indexer[axis] = slice(None, -n) if n > 0 else slice(-n, None)
lag_indexer = tuple(lag_indexer)
# need to make sure that we account for na for datelike/timedelta
# we don't actually want to subtract these i8 numbers
if is_timedelta:
res = arr[res_indexer]
lag = arr[lag_indexer]
mask = (arr[res_indexer] == na) | (arr[lag_indexer] == na)
if mask.any():
res = res.copy()
res[mask] = 0
lag = lag.copy()
lag[mask] = 0
result = res - lag
result[mask] = na
out_arr[res_indexer] = result
else:
out_arr[res_indexer] = arr[res_indexer] - arr[lag_indexer]
if is_timedelta:
from pandas import TimedeltaIndex
out_arr = TimedeltaIndex(out_arr.ravel().astype('int64')).asi8.reshape(
out_arr.shape).astype('timedelta64[ns]')
return out_arr | [
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | direct/src/directnotify/Logger.py | python | Logger.__getTimeStamp | (self) | return "%02d:%02d:%02d:%02d: " % (days, hours, minutes, seconds) | Return the offset between current time and log file startTime | Return the offset between current time and log file startTime | [
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Return the offset between current time and log file startTime
"""
t = time.time()
dt = t - self.__startTime
days, dt = divmod(dt, 86400)
hours, dt = divmod(dt, 3600)
minutes, dt = divmod(dt, 60)
seconds = int(math.ceil(dt))
return "%02d:%02d:%02d:%02d: " % (days, hours, minutes, seconds) | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/SANS/isis_instrument.py | python | ISISInstrument.on_load_sample | (self, ws_name, beamcentre, isSample) | return centre_shift | It will be called just after loading the workspace for sample and can
It configures the instrument for the specific run of the workspace for handle historical changes in the instrument.
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It centralizes the detector bank to the beamcentre (tuple of two values)
"""
ws_ref = mtd[str(ws_name)]
try:
run_num = LARMOR.get_run_number_from_workspace_reference(ws_ref)
except:
run_num = int(re.findall(r'\d+', str(ws_name))[0])
if isSample:
self.set_up_for_run(run_num)
if self._newCalibrationWS:
# We are about to transfer the Instrument Parameter File from the
# calibration to the original workspace. We want to add new parameters
# which the calibration file has not yet picked up.
# IMPORTANT NOTE: This takes the parameter settings from the original workspace
# if they are old too, then we don't pick up newly added parameters
self._add_parmeters_absent_in_calibration(ws_name, self._newCalibrationWS)
self.changeCalibration(ws_name)
# centralize the bank to the centre
dummy_centre, centre_shift = self.move_components(ws_name, beamcentre[0], beamcentre[1])
return centre_shift | [
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crosslife/OpenBird | 9e0198a1a2295f03fa1e8676e216e22c9c7d380b | cocos2d/tools/bindings-generator/clang/cindex.py | python | CompilationDatabase.getCompileCommands | (self, filename) | return conf.lib.clang_CompilationDatabase_getCompileCommands(self,
filename) | Get an iterable object providing all the CompileCommands available to
build filename. Returns None if filename is not found in the database. | Get an iterable object providing all the CompileCommands available to
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"""
Get an iterable object providing all the CompileCommands available to
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"""
return conf.lib.clang_CompilationDatabase_getCompileCommands(self,
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jts/nanopolish | 181549b682ffe99c1bbf1a410ee2806614a08445 | scripts/reestimate_polya_emissions.py | python | make_segmentation_dict | (segmentations_tsv_path) | return segments | Load a segmentations TSV file. Rows of `segmentations_tsv_path` look like this:
tag read_id: pos: L_0 A_0: P_0: P_1: RR: P(A)L: AL:
polya-segmentation fc06... 161684804 47.0 1851.0 8354.0 11424.0 73.76 75.18 35.23
Note that this function only takes the first available segmentation for each read, i.e.
if a read id appears more than once in the TSV, only the first segmentation is kept, and
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] | def make_segmentation_dict(segmentations_tsv_path):
"""
Load a segmentations TSV file. Rows of `segmentations_tsv_path` look like this:
tag read_id: pos: L_0 A_0: P_0: P_1: RR: P(A)L: AL:
polya-segmentation fc06... 161684804 47.0 1851.0 8354.0 11424.0 73.76 75.18 35.23
Note that this function only takes the first available segmentation for each read, i.e.
if a read id appears more than once in the TSV, only the first segmentation is kept, and
later occurrences of the read id in the TSV are ignored.
"""
segments = {}
# loop thru TSV and update the list of segmentations:
with open(segmentations_tsv_path, 'r') as f:
headers = ['tag', 'read_id', 'pos', 'L_start', 'A_start', 'P_start', 'P_end', 'rate', 'plen', 'alen']
rdr = csv.DictReader(f, delimiter='\t', quoting=csv.QUOTE_NONE, fieldnames=headers)
for row in rdr:
if row['read_id'] not in list(segments.keys()):
segments[row['read_id']] = { 'L_start': int(float(row['L_start'])),
'A_start': int(float(row['A_start'])),
'P_start': int(float(row['P_start'])),
'P_end': int(float(row['P_end'])) }
return segments | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/vision/ops.py | python | roi_pool | (x, boxes, boxes_num, output_size, spatial_scale=1.0, name=None) | This operator implements the roi_pooling layer.
Region of interest pooling (also known as RoI pooling) is to perform max pooling on inputs of nonuniform sizes to obtain fixed-size feature maps (e.g. 7*7).
The operator has three steps: 1. Dividing each region proposal into equal-sized sections with output_size(h, w) 2. Finding the largest value in each section 3. Copying these max values to the output buffer
For more information, please refer to https://stackoverflow.com/questions/43430056/what-is-roi-layer-in-fast-rcnn.
Args:
x (Tensor): input feature, 4D-Tensor with the shape of [N,C,H,W],
where N is the batch size, C is the input channel, H is Height, W is weight.
The data type is float32 or float64.
boxes (Tensor): boxes (Regions of Interest) to pool over.
2D-Tensor with the shape of [num_boxes,4].
Given as [[x1, y1, x2, y2], ...], (x1, y1) is the top left coordinates,
and (x2, y2) is the bottom right coordinates.
boxes_num (Tensor): the number of RoIs in each image, data type is int32. Default: None
output_size (int or tuple[int, int]): the pooled output size(h, w), data type is int32. If int, h and w are both equal to output_size.
spatial_scale (float, optional): multiplicative spatial scale factor to translate ROI coords from their input scale to the scale used when pooling. Default: 1.0
name(str, optional): for detailed information, please refer to :ref:`api_guide_Name`. Usually name is no need to set and None by default.
Returns:
pool_out (Tensor): the pooled feature, 4D-Tensor with the shape of [num_boxes, C, output_size[0], output_size[1]].
Examples:
.. code-block:: python
import paddle
from paddle.vision.ops import roi_pool
data = paddle.rand([1, 256, 32, 32])
boxes = paddle.rand([3, 4])
boxes[:, 2] += boxes[:, 0] + 3
boxes[:, 3] += boxes[:, 1] + 4
boxes_num = paddle.to_tensor([3]).astype('int32')
pool_out = roi_pool(data, boxes, boxes_num=boxes_num, output_size=3)
assert pool_out.shape == [3, 256, 3, 3], '' | This operator implements the roi_pooling layer.
Region of interest pooling (also known as RoI pooling) is to perform max pooling on inputs of nonuniform sizes to obtain fixed-size feature maps (e.g. 7*7).
The operator has three steps: 1. Dividing each region proposal into equal-sized sections with output_size(h, w) 2. Finding the largest value in each section 3. Copying these max values to the output buffer
For more information, please refer to https://stackoverflow.com/questions/43430056/what-is-roi-layer-in-fast-rcnn. | [
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"""
This operator implements the roi_pooling layer.
Region of interest pooling (also known as RoI pooling) is to perform max pooling on inputs of nonuniform sizes to obtain fixed-size feature maps (e.g. 7*7).
The operator has three steps: 1. Dividing each region proposal into equal-sized sections with output_size(h, w) 2. Finding the largest value in each section 3. Copying these max values to the output buffer
For more information, please refer to https://stackoverflow.com/questions/43430056/what-is-roi-layer-in-fast-rcnn.
Args:
x (Tensor): input feature, 4D-Tensor with the shape of [N,C,H,W],
where N is the batch size, C is the input channel, H is Height, W is weight.
The data type is float32 or float64.
boxes (Tensor): boxes (Regions of Interest) to pool over.
2D-Tensor with the shape of [num_boxes,4].
Given as [[x1, y1, x2, y2], ...], (x1, y1) is the top left coordinates,
and (x2, y2) is the bottom right coordinates.
boxes_num (Tensor): the number of RoIs in each image, data type is int32. Default: None
output_size (int or tuple[int, int]): the pooled output size(h, w), data type is int32. If int, h and w are both equal to output_size.
spatial_scale (float, optional): multiplicative spatial scale factor to translate ROI coords from their input scale to the scale used when pooling. Default: 1.0
name(str, optional): for detailed information, please refer to :ref:`api_guide_Name`. Usually name is no need to set and None by default.
Returns:
pool_out (Tensor): the pooled feature, 4D-Tensor with the shape of [num_boxes, C, output_size[0], output_size[1]].
Examples:
.. code-block:: python
import paddle
from paddle.vision.ops import roi_pool
data = paddle.rand([1, 256, 32, 32])
boxes = paddle.rand([3, 4])
boxes[:, 2] += boxes[:, 0] + 3
boxes[:, 3] += boxes[:, 1] + 4
boxes_num = paddle.to_tensor([3]).astype('int32')
pool_out = roi_pool(data, boxes, boxes_num=boxes_num, output_size=3)
assert pool_out.shape == [3, 256, 3, 3], ''
"""
check_type(output_size, 'output_size', (int, tuple), 'roi_pool')
if isinstance(output_size, int):
output_size = (output_size, output_size)
pooled_height, pooled_width = output_size
if in_dygraph_mode():
assert boxes_num is not None, "boxes_num should not be None in dygraph mode."
pool_out, argmaxes = _C_ops.roi_pool(
x, boxes, boxes_num, "pooled_height", pooled_height, "pooled_width",
pooled_width, "spatial_scale", spatial_scale)
return pool_out
else:
check_variable_and_dtype(x, 'x', ['float32'], 'roi_pool')
check_variable_and_dtype(boxes, 'boxes', ['float32'], 'roi_pool')
helper = LayerHelper('roi_pool', **locals())
dtype = helper.input_dtype()
pool_out = helper.create_variable_for_type_inference(dtype)
argmaxes = helper.create_variable_for_type_inference(dtype='int32')
inputs = {
"X": x,
"ROIs": boxes,
}
if boxes_num is not None:
inputs['RoisNum'] = boxes_num
helper.append_op(
type="roi_pool",
inputs=inputs,
outputs={"Out": pool_out,
"Argmax": argmaxes},
attrs={
"pooled_height": pooled_height,
"pooled_width": pooled_width,
"spatial_scale": spatial_scale
})
return pool_out | [
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v8mips/v8mips | f0c9cc0bbfd461c7f516799d9a58e9a7395f737e | PRESUBMIT.py | python | _CheckChangeLogFlag | (input_api, output_api) | return results | Checks usage of LOG= flag in the commit message. | Checks usage of LOG= flag in the commit message. | [
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] | def _CheckChangeLogFlag(input_api, output_api):
"""Checks usage of LOG= flag in the commit message."""
results = []
if input_api.change.BUG and not 'LOG' in input_api.change.tags:
results.append(output_api.PresubmitError(
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return results | [
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sc0ty/subsync | be5390d00ff475b6543eb0140c7e65b34317d95b | subsync/synchro/controller.py | python | SyncController.validateTask | (self, task, *, interactive=False) | Check if task is properly defined.
Parameters
----------
task: SyncTask
Task to validate.
interactive: bool, optional
For interactive synchronization `out` will not be vaildated.
Raises
------
Error
Invalid task.
KeyError or Exception
Invalid `task`.out.path pattern. | Check if task is properly defined. | [
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] | def validateTask(self, task, *, interactive=False):
"""Check if task is properly defined.
Parameters
----------
task: SyncTask
Task to validate.
interactive: bool, optional
For interactive synchronization `out` will not be vaildated.
Raises
------
Error
Invalid task.
KeyError or Exception
Invalid `task`.out.path pattern.
"""
sub, ref, out = task.sub, task.ref, task.out
if sub is None or not sub.path or sub.no is None:
raise Error('subtitles not set', task=task)
if ref is None or not ref.path or ref.no is None:
raise Error('reference file not set', task=task)
if not interactive and (out is None or not out.path):
raise Error('output path not set', task=task)
if not interactive:
out.validateOutputPattern() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/lib-tk/Tkinter.py | python | Spinbox.scan | (self, *args) | return self._getints(
self.tk.call((self._w, 'scan') + args)) or () | Internal function. | Internal function. | [
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"""Internal function."""
return self._getints(
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/deps/v8/third_party/jinja2/nodes.py | python | Node.set_environment | (self, environment) | return self | Set the environment for all nodes. | Set the environment for all nodes. | [
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] | def set_environment(self, environment):
"""Set the environment for all nodes."""
todo = deque([self])
while todo:
node = todo.popleft()
node.environment = environment
todo.extend(node.iter_child_nodes())
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/logging/__init__.py | python | FileHandler.close | (self) | Closes the stream. | Closes the stream. | [
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"""
Closes the stream.
"""
self.acquire()
try:
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if self.stream:
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self.flush()
finally:
stream = self.stream
self.stream = None
if hasattr(stream, "close"):
stream.close()
finally:
# Issue #19523: call unconditionally to
# prevent a handler leak when delay is set
StreamHandler.close(self)
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/idlelib/EditorWindow.py | python | HelpDialog.display | (self, parent, near=None) | Display the help dialog.
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parent - parent widget for the help window
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niwinz/phantompy | ae25ddb6791e13cb7c35126971c410030ee5dfda | phantompy/webelements.py | python | WebElement.append_after | (self, element) | Same as :py:meth:`~.append` but appends outside the current
dom element. | Same as :py:meth:`~.append` but appends outside the current
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"""
Same as :py:meth:`~.append` but appends outside the current
dom element.
"""
if isinstance(element, util.string_type):
lib.ph_webelement_append_html_after(self.ptr, util.force_bytes(element))
elif isinstance(element, WebElement):
lib.ph_webelement_append_element_after(self.ptr, element.ptr)
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | third_party/gpus/find_cuda_config.py | python | _get_header_version | (path, name) | return "" | Returns preprocessor defines in C header file. | Returns preprocessor defines in C header file. | [
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for line in io.open(path, "r", encoding="utf-8").readlines():
match = re.match("#define %s +(\d+)" % name, line)
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/utils/kernelized_utils.py | python | _to_matrix | (u) | return u | If input tensor is a vector (i.e., has rank 1), converts it to matrix. | If input tensor is a vector (i.e., has rank 1), converts it to matrix. | [
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raise ValueError('The input tensor should have rank 1 or 2. Given rank: {}'
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/build/waf-1.7.13/waflib/extras/codelite.py | python | codelite_generator.execute | (self) | Entry point | Entry point | [
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"""
Entry point
"""
self.restore()
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self.load_envs()
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# user initialization
self.init()
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self.collect_projects() # add project objects into "self.all_projects"
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tarfile.py | python | TarInfo.__init__ | (self, name="") | Construct a TarInfo object. name is the optional name
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bundy-dns/bundy | 3d41934996b82b0cd2fe22dd74d2abc1daba835d | src/lib/python/bundy/sysinfo/sysinfo.py | python | SysInfo.get_platform_machine | (self) | return self._platform_machine | Returns the platform machine architecture. | Returns the platform machine architecture. | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/xml/sax/_exceptions.py | python | SAXParseException.__str__ | (self) | return "%s:%s:%s: %s" % (sysid, linenum, colnum, self._msg) | Create a string representation of the exception. | Create a string representation of the exception. | [
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if sysid is None:
sysid = "<unknown>"
linenum = self.getLineNumber()
if linenum is None:
linenum = "?"
colnum = self.getColumnNumber()
if colnum is None:
colnum = "?"
return "%s:%s:%s: %s" % (sysid, linenum, colnum, self._msg) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tarfile.py | python | TarFile.getmember | (self, name) | return tarinfo | Return a TarInfo object for member `name'. If `name' can not be
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most up-to-date version.
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/calendar.py | python | Calendar.monthdatescalendar | (self, year, month) | return [ dates[i:i+7] for i in range(0, len(dates), 7) ] | Return a matrix (list of lists) representing a month's calendar.
Each row represents a week; week entries are datetime.date values. | Return a matrix (list of lists) representing a month's calendar.
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Return a matrix (list of lists) representing a month's calendar.
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"""
dates = list(self.itermonthdates(year, month))
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Salensoft/thu-cst-cracker | f7f6b4de460aaac6da3d776ab28d9175e8b32ae2 | 大三上/软件工程/hw/2015/Homework/作业2 - 代码风格/01_code_style/my_posixpath.py | python | normcase | (s) | return s | Normalize case of pathname. Has no effect under Posix | Normalize case of pathname. Has no effect under Posix | [
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lammps/lammps | b75c3065430a75b1b5543a10e10f46d9b4c91913 | tools/i-pi/ipi/inputs/outputs.py | python | InputProperties.check | (self) | Checks for optional parameters. | Checks for optional parameters. | [
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"""Checks for optional parameters."""
super(InputProperties,self).check()
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SpaceNetChallenge/BuildingDetectors | 3def3c44b5847c744cd2f3356182892d92496579 | qinhaifang/src/caffe-mnc/python/caffe/io.py | python | Transformer.preprocess | (self, in_, data) | return caffe_in | Format input for Caffe:
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- resize to input dimensions (preserving number of channels)
- transpose dimensions to K x H x W
- reorder channels (for instance color to BGR)
- scale raw input (e.g. from [0, 1] to [0, 255] for ImageNet models)
- subtract mean
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Parameters
----------
in_ : name of input blob to preprocess for
data : (H' x W' x K) ndarray
Returns
-------
caffe_in : (K x H x W) ndarray for input to a Net | Format input for Caffe:
- convert to single
- resize to input dimensions (preserving number of channels)
- transpose dimensions to K x H x W
- reorder channels (for instance color to BGR)
- scale raw input (e.g. from [0, 1] to [0, 255] for ImageNet models)
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mean = self.mean.get(in_)
input_scale = self.input_scale.get(in_)
in_dims = self.inputs[in_][2:]
if caffe_in.shape[:2] != in_dims:
caffe_in = resize_image(caffe_in, in_dims)
if transpose is not None:
caffe_in = caffe_in.transpose(transpose)
if channel_swap is not None:
caffe_in = caffe_in[channel_swap, :, :]
if raw_scale is not None:
caffe_in *= raw_scale
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/tornado/tornado-6/tornado/websocket.py | python | WebSocketHandler.ping_interval | (self) | return self.settings.get("websocket_ping_interval", None) | The interval for websocket keep-alive pings.
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ceph/ceph | 959663007321a369c83218414a29bd9dbc8bda3a | qa/tasks/ceph_deploy.py | python | cli_test | (ctx, config) | ceph-deploy cli to exercise most commonly use cli's and ensure
all commands works and also startup the init system. | ceph-deploy cli to exercise most commonly use cli's and ensure
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"""
ceph-deploy cli to exercise most commonly use cli's and ensure
all commands works and also startup the init system.
"""
log.info('Ceph-deploy Test')
if config is None:
config = {}
test_branch = ''
conf_dir = teuthology.get_testdir(ctx) + "/cdtest"
def execute_cdeploy(admin, cmd, path):
"""Execute ceph-deploy commands """
"""Either use git path or repo path """
args = ['cd', conf_dir, run.Raw(';')]
if path:
args.append('{path}/ceph-deploy/ceph-deploy'.format(path=path))
else:
args.append('ceph-deploy')
args.append(run.Raw(cmd))
ec = admin.run(args=args, check_status=False).exitstatus
if ec != 0:
raise RuntimeError(
"failed during ceph-deploy cmd: {cmd} , ec={ec}".format(cmd=cmd, ec=ec))
if config.get('rhbuild'):
path = None
else:
path = teuthology.get_testdir(ctx)
# test on branch from config eg: wip-* , master or next etc
# packages for all distro's should exist for wip*
if ctx.config.get('branch'):
branch = ctx.config.get('branch')
test_branch = ' --dev={branch} '.format(branch=branch)
mons = ctx.cluster.only(teuthology.is_type('mon'))
for node, role in mons.remotes.items():
admin = node
admin.run(args=['mkdir', conf_dir], check_status=False)
nodename = admin.shortname
system_type = teuthology.get_system_type(admin)
if config.get('rhbuild'):
admin.run(args=['sudo', 'yum', 'install', 'ceph-deploy', '-y'])
log.info('system type is %s', system_type)
osds = ctx.cluster.only(teuthology.is_type('osd'))
for remote, roles in osds.remotes.items():
devs = teuthology.get_scratch_devices(remote)
log.info("roles %s", roles)
if (len(devs) < 3):
log.error(
'Test needs minimum of 3 devices, only found %s',
str(devs))
raise RuntimeError("Needs minimum of 3 devices ")
conf_path = '{conf_dir}/ceph.conf'.format(conf_dir=conf_dir)
new_cmd = 'new ' + nodename
execute_cdeploy(admin, new_cmd, path)
if config.get('conf') is not None:
confp = config.get('conf')
for section, keys in confp.items():
lines = '[{section}]\n'.format(section=section)
admin.sudo_write_file(conf_path, lines, append=True)
for key, value in keys.items():
log.info("[%s] %s = %s" % (section, key, value))
lines = '{key} = {value}\n'.format(key=key, value=value)
admin.sudo_write_file(conf_path, lines, append=True)
new_mon_install = 'install {branch} --mon '.format(
branch=test_branch) + nodename
new_mgr_install = 'install {branch} --mgr '.format(
branch=test_branch) + nodename
new_osd_install = 'install {branch} --osd '.format(
branch=test_branch) + nodename
new_admin = 'install {branch} --cli '.format(branch=test_branch) + nodename
create_initial = 'mon create-initial '
mgr_create = 'mgr create ' + nodename
# either use create-keys or push command
push_keys = 'admin ' + nodename
execute_cdeploy(admin, new_mon_install, path)
execute_cdeploy(admin, new_mgr_install, path)
execute_cdeploy(admin, new_osd_install, path)
execute_cdeploy(admin, new_admin, path)
execute_cdeploy(admin, create_initial, path)
execute_cdeploy(admin, mgr_create, path)
execute_cdeploy(admin, push_keys, path)
for i in range(3):
zap_disk = 'disk zap ' + "{n}:{d}".format(n=nodename, d=devs[i])
prepare = 'osd prepare ' + "{n}:{d}".format(n=nodename, d=devs[i])
execute_cdeploy(admin, zap_disk, path)
execute_cdeploy(admin, prepare, path)
log.info("list files for debugging purpose to check file permissions")
admin.run(args=['ls', run.Raw('-lt'), conf_dir])
remote.run(args=['sudo', 'ceph', '-s'], check_status=False)
out = remote.sh('sudo ceph health')
log.info('Ceph health: %s', out.rstrip('\n'))
log.info("Waiting for cluster to become healthy")
with contextutil.safe_while(sleep=10, tries=6,
action='check health') as proceed:
while proceed():
out = remote.sh('sudo ceph health')
if (out.split(None, 1)[0] == 'HEALTH_OK'):
break
rgw_install = 'install {branch} --rgw {node}'.format(
branch=test_branch,
node=nodename,
)
rgw_create = 'rgw create ' + nodename
execute_cdeploy(admin, rgw_install, path)
execute_cdeploy(admin, rgw_create, path)
log.info('All ceph-deploy cli tests passed')
try:
yield
finally:
log.info("cleaning up")
ctx.cluster.run(args=['sudo', 'systemctl', 'stop', 'ceph.target'],
check_status=False)
time.sleep(4)
for i in range(3):
umount_dev = "{d}1".format(d=devs[i])
remote.run(args=['sudo', 'umount', run.Raw(umount_dev)])
cmd = 'purge ' + nodename
execute_cdeploy(admin, cmd, path)
cmd = 'purgedata ' + nodename
execute_cdeploy(admin, cmd, path)
log.info("Removing temporary dir")
admin.run(
args=[
'rm',
run.Raw('-rf'),
run.Raw(conf_dir)],
check_status=False)
if config.get('rhbuild'):
admin.run(args=['sudo', 'yum', 'remove', 'ceph-deploy', '-y']) | [
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widelands/widelands | e9f047d46a23d81312237d52eabf7d74e8de52d6 | utils/make_spritemap.py | python | build_frame_group_regions | (frames) | return (float(cost) / len(frames), newframes) | Given a list of frame, identify variable subregions and split frames
into blits accordingly.
Return (avgcost, list of list of ((x, y), pic, pc_pic)) | Given a list of frame, identify variable subregions and split frames
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] | def build_frame_group_regions(frames):
"""Given a list of frame, identify variable subregions and split frames
into blits accordingly.
Return (avgcost, list of list of ((x, y), pic, pc_pic))
"""
pc = frames[0].pc_pic is not None
regions = []
if len(frames) > 1:
# Find the regions that are not equal over all frames
followers = np.asarray([frame.pic for frame in frames[1:]])
diff = np.any(np.any(frames[0].pic != followers, 3), 0)
if pc:
followers_pc = np.asarray([frame.pc_pic for frame in frames[1:]])
diff = diff | np.any(np.any(frames[0].pc_pic != followers_pc, 3) & followers[
:, :, :, 3] != 0, 0)
# TODO: use rectangle covering instead, once it becomes more efficient
label_img, nlabels = ndimage.label(diff)
for i in range(1, nlabels + 1):
ys, xs = np.where(label_img == i)
regions.append((ys.min(), xs.min(), ys.max() + 1, xs.max() + 1))
else:
diff = np.zeros(frames[0].pic.shape[:2], np.bool)
base_pic_mask = frames[0].pic[:, :, 3] != 0 & ~diff
for region in regions:
base_pic_mask[region[0]:region[2], region[1]:region[3]] = False
ys, xs = np.where(base_pic_mask)
cost = 0
base_pic_rect = None
if len(ys) and len(xs):
base_pic_rect = (ys.min(), xs.min(), ys.max() + 1, xs.max() + 1)
base_pic_base = frames[0].pic.copy()
base_pic_base[:, :, 3] = np.choose(
base_pic_mask, [0, base_pic_base[:, :, 3]])
base_pic = base_pic_base[base_pic_rect[0]:base_pic_rect[
2], base_pic_rect[1]:base_pic_rect[3]]
if pc:
base_pic_pc = frames[0].pc_pic[base_pic_rect[
0]:base_pic_rect[2], base_pic_rect[1]:base_pic_rect[3]]
else:
base_pic_pc = None
cost = rectangle_cost(base_pic_rect)
newframes = []
for frame in frames:
newframe = [((base_pic_rect[0], base_pic_rect[1]),
base_pic, base_pic_pc)] if base_pic_rect else []
for region in regions:
pic = frame.pic[region[0]:region[2], region[1]:region[3]]
if pc:
pc_pic = frame.pc_pic[region[0]:region[2], region[1]:region[3]]
else:
pc_pic = None
newframe.append(((region[0], region[1]), pic, pc_pic))
cost += rectangle_cost(region)
newframes.append(newframe)
return (float(cost) / len(frames), newframes) | [
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Project-OSRM/osrm-backend | f2e284623e25b5570dd2a5e6985abcb3790fd348 | third_party/flatbuffers/python/flatbuffers/table.py | python | Table.Vector | (self, off) | return x | Vector retrieves the start of data of the vector whose offset is
stored at "off" in this object. | Vector retrieves the start of data of the vector whose offset is
stored at "off" in this object. | [
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] | def Vector(self, off):
"""Vector retrieves the start of data of the vector whose offset is
stored at "off" in this object."""
N.enforce_number(off, N.UOffsetTFlags)
off += self.Pos
x = off + self.Get(N.UOffsetTFlags, off)
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llvm/llvm-project | ffa6262cb4e2a335d26416fad39a581b4f98c5f4 | clang/tools/scan-build-py/lib/libscanbuild/intercept.py | python | is_preload_disabled | (platform) | Library-based interposition will fail silently if SIP is enabled,
so this should be detected. You can detect whether SIP is enabled on
Darwin by checking whether (1) there is a binary called 'csrutil' in
the path and, if so, (2) whether the output of executing 'csrutil status'
contains 'System Integrity Protection status: enabled'.
:param platform: name of the platform (returned by sys.platform),
:return: True if library preload will fail by the dynamic linker. | Library-based interposition will fail silently if SIP is enabled,
so this should be detected. You can detect whether SIP is enabled on
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the path and, if so, (2) whether the output of executing 'csrutil status'
contains 'System Integrity Protection status: enabled'. | [
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""" Library-based interposition will fail silently if SIP is enabled,
so this should be detected. You can detect whether SIP is enabled on
Darwin by checking whether (1) there is a binary called 'csrutil' in
the path and, if so, (2) whether the output of executing 'csrutil status'
contains 'System Integrity Protection status: enabled'.
:param platform: name of the platform (returned by sys.platform),
:return: True if library preload will fail by the dynamic linker. """
if platform in WRAPPER_ONLY_PLATFORMS:
return True
elif platform == 'darwin':
command = ['csrutil', 'status']
pattern = re.compile(r'System Integrity Protection status:\s+enabled')
try:
return any(pattern.match(line) for line in run_command(command))
except:
return False
else:
return False | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/richtext.py | python | RichTextFileHandler.SaveStream | (*args, **kwargs) | return _richtext.RichTextFileHandler_SaveStream(*args, **kwargs) | SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool | SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool | [
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"""SaveStream(self, RichTextBuffer buffer, wxOutputStream stream) -> bool"""
return _richtext.RichTextFileHandler_SaveStream(*args, **kwargs) | [
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facebookincubator/katran | 192eb988c398afc673620254097defb7035d669e | 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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] | def is_first_party_project(self):
"""returns true if this is an FB first-party project"""
return self.shipit_project is not None | [
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | src/mem/qos/QoSMemSinkInterface.py | python | QoSMemSinkInterface.controller | (self) | return controller | Instantiate the memory controller and bind it to
the current interface. | Instantiate the memory controller and bind it to
the current interface. | [
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] | def controller(self):
"""
Instantiate the memory controller and bind it to
the current interface.
"""
controller = QoSMemSinkCtrl()
controller.interface = self
return controller | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/distutils/ccompiler_opt.py | python | _Parse._parse_policy_autovec | (self, has_baseline, final_targets, extra_flags) | return has_baseline, final_targets, extra_flags | skip features that has no auto-vectorized support by compiler | skip features that has no auto-vectorized support by compiler | [
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"-",
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] | def _parse_policy_autovec(self, has_baseline, final_targets, extra_flags):
"""skip features that has no auto-vectorized support by compiler"""
skipped = []
for tar in final_targets[:]:
if isinstance(tar, str):
can = self.feature_can_autovec(tar)
else: # multiple target
can = all([
self.feature_can_autovec(t)
for t in tar
])
if not can:
final_targets.remove(tar)
skipped.append(tar)
if skipped:
self.dist_log("skip non auto-vectorized features", skipped)
return has_baseline, final_targets, extra_flags | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/models.py | python | Response.links | (self) | return l | Returns the parsed header links of the response, if any. | Returns the parsed header links of the response, if any. | [
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] | def links(self):
"""Returns the parsed header links of the response, if any."""
header = self.headers.get('link')
# l = MultiDict()
l = {}
if header:
links = parse_header_links(header)
for link in links:
key = link.get('rel') or link.get('url')
l[key] = link
return l | [
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giuspen/cherrytree | 84712f206478fcf9acf30174009ad28c648c6344 | pygtk2/modules/tablez.py | python | TablesHandler.on_table_cell_key_press | (self, widget, event, path, model, col_num) | return False | Catches Table Cell key presses | Catches Table Cell key presses | [
"Catches",
"Table",
"Cell",
"key",
"presses"
] | def on_table_cell_key_press(self, widget, event, path, model, col_num):
"""Catches Table Cell key presses"""
keyname = gtk.gdk.keyval_name(event.keyval)
if event.state & gtk.gdk.SHIFT_MASK:
pass
elif event.state & gtk.gdk.MOD1_MASK:
pass
elif event.state & gtk.gdk.CONTROL_MASK:
# on Win32, emtpy Ctrl deselects selected text, so to fix it
if cons.IS_WIN_OS:
if keyname in cons.STR_KEYS_CONTROL:
return True
if keyname == "period":
self.curr_table_cell = widget
self.curr_table_cell_insert_newline()
return True
elif keyname == "comma":
return True
else:
if keyname in [cons.STR_KEY_RETURN, cons.STR_KEY_TAB, cons.STR_KEY_UP, cons.STR_KEY_DOWN]:
if model[path][col_num] != widget.get_text():
if self.dad.is_curr_node_not_read_only_or_error():
model[path][col_num] = widget.get_text()
self.dad.update_window_save_needed("nbuf", True)
if keyname == cons.STR_KEY_UP:
if col_num > 0:
next_col_num = col_num - 1
next_path = path
else:
next_iter = None
next_path = model.get_path(model.get_iter(path))
while not next_iter and next_path[0] > 0:
node_path_list = list(next_path)
node_path_list[0] -= 1
next_path = tuple(node_path_list)
next_iter = model.get_iter(next_path)
#next_iter = model.iter_next(model.get_iter(path))
if not next_iter: return False
next_path = model.get_path(next_iter)
next_col_num = self.dad.table_columns-1
else:
if col_num < self.dad.table_columns-1:
next_col_num = col_num + 1
next_path = path
else:
next_iter = model.iter_next(model.get_iter(path))
if not next_iter: return False
next_path = model.get_path(next_iter)
next_col_num = 0
#print "(path, col_num) = (%s, %s)" % (path, col_num)
#print "(next_path, next_col_num) = (%s, %s)" % (next_path, next_col_num)
next_column = self.curr_table_anchor.treeview.get_columns()[next_col_num]
self.curr_table_anchor.treeview.set_cursor_on_cell(next_path,
focus_column=next_column,
focus_cell=next_column.get_cell_renderers()[0],
start_editing=True)
return True
return False | [
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cyberbotics/webots | af7fa7d68dcf7b4550f1f2e132092b41e83698fc | resources/osm_importer/utils/vector.py | python | Vector2D.__truediv__ | (self, other) | Divide the vector to another. | Divide the vector to another. | [
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] | def __truediv__(self, other):
"""Divide the vector to another."""
if isinstance(other, Vector2D):
# Dot product
return self.x / other.x + self.y / other.y
elif isinstance(other, float):
# Scalar product
return Vector2D(self.x / other, self.y / other)
else:
raise TypeError() | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftmake/make_line.py | python | make_line | (first_param, last_param=None) | return obj | makeLine(first_param, p2)
Creates a line from 2 points or from a given object.
Parameters
----------
first_param :
Base.Vector -> First point of the line (if p2 is None)
Part.LineSegment -> Line is created from the given Linesegment
Shape -> Line is created from the give Shape
last_param : Base.Vector
Second point of the line, if not set the function evaluates
the first_param to look for a Part.LineSegment or a Shape | makeLine(first_param, p2)
Creates a line from 2 points or from a given object. | [
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"""makeLine(first_param, p2)
Creates a line from 2 points or from a given object.
Parameters
----------
first_param :
Base.Vector -> First point of the line (if p2 is None)
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last_param : Base.Vector
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if last_param:
p1 = first_param
p2 = last_param
else:
if hasattr(first_param, "StartPoint") and hasattr(first_param, "EndPoint"):
p2 = first_param.EndPoint
p1 = first_param.StartPoint
elif hasattr(p1,"Vertexes"):
p2 = first_param.Vertexes[-1].Point
p1 = first_param.Vertexes[0].Point
else:
_err = "Unable to create a line from the given parameters"
App.Console.PrintError(_err + "\n")
return
obj = make_wire.make_wire([p1,p2])
return obj | [
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QMCPACK/qmcpack | d0948ab455e38364458740cc8e2239600a14c5cd | nexus/lib/grid_functions.py | python | ParallelotopeGrid.initialize_local | (self,
axes = None,
shape = None,
cells = None,
dr = None,
corner = None,
center = None,
centered = False,
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) | (`Internal API`) Initialize the parallelotope grid points and set the
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] | def initialize_local(self,
axes = None,
shape = None,
cells = None,
dr = None,
corner = None,
center = None,
centered = False,
**kwargs
):
"""
(`Internal API`) Initialize the parallelotope grid points and set the
origin if not provided.
"""
if shape is None and cells is None and dr is None:
self.error('cannot initialize grid, either "shape", "cells", or "dr" is required')
elif shape is not None:
grid_dim = len(shape)
elif cells is not None:
grid_dim = len(cells)
elif dr is not None:
grid_dim = len(dr)
#end if
bconds = kwargs.get('bconds',None)
endpoint = self.has_endpoints(bconds=bconds,grid_dim=grid_dim)
points,shape,axes = parallelotope_grid_points(
axes = axes,
shape = shape,
cells = cells,
dr = dr,
centered = centered,
endpoint = endpoint,
return_shape = True,
return_axes = True
)
if center is not None:
center = np.array(center)
corner = center - axes.sum(axis=0)/2
#end if
kwargs['axes'] = axes
if corner is not None:
kwargs['origin'] = corner
#end if
kwargs['shape'] = shape
kwargs['centered'] = centered
kwargs['points'] = points
StructuredGridWithAxes.initialize_local(self,**kwargs) | [
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"=",
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"=",
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... | https://github.com/QMCPACK/qmcpack/blob/d0948ab455e38364458740cc8e2239600a14c5cd/nexus/lib/grid_functions.py#L2221-L2271 |
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