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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | makepanda/makepanda.py | python | CompileRes | (target, src, opts) | Compiles a Windows .rc file into a .res file. | Compiles a Windows .rc file into a .res file. | [
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"""Compiles a Windows .rc file into a .res file."""
ipath = GetListOption(opts, "DIR:")
if (COMPILER == "MSVC"):
cmd = "rc"
cmd += " /Fo" + BracketNameWithQuotes(target)
for x in ipath: cmd += " /I" + x
for (opt,dir) in INCDIRECTORIES:
if (opt=="ALWAYS") or (opt in opts):
cmd += " /I" + BracketNameWithQuotes(dir)
for (opt,var,val) in DEFSYMBOLS:
if (opt=="ALWAYS") or (opt in opts):
cmd += " /D" + var + "=" + val
cmd += " " + BracketNameWithQuotes(src)
else:
cmd = "windres"
for x in ipath: cmd += " -I" + x
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cmd += " -i " + BracketNameWithQuotes(src)
cmd += " -o " + BracketNameWithQuotes(target)
oscmd(cmd) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py3/IPython/core/interactiveshell.py | python | InteractiveShell.init_readline | (self) | DEPRECATED
Moved to terminal subclass, here only to simplify the init logic. | DEPRECATED | [
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] | def init_readline(self):
"""DEPRECATED
Moved to terminal subclass, here only to simplify the init logic."""
# Set a number of methods that depend on readline to be no-op
warnings.warn('`init_readline` is no-op since IPython 5.0 and is Deprecated',
DeprecationWarning, stacklevel=2)
self.set_custom_completer = no_op | [
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fatih/subvim | 241b6d170597857105da219c9b7d36059e9f11fb | vim/base/ultisnips/plugin/UltiSnips/text_objects/_python_code.py | python | SnippetUtil.__rshift__ | (self, other) | Same as shift. | Same as shift. | [
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kungfu-origin/kungfu | 90c84b2b590855654cb9a6395ed050e0f7763512 | core/deps/SQLiteCpp-2.3.0/cpplint.py | python | ReplaceAll | (pattern, rep, s) | return _regexp_compile_cache[pattern].sub(rep, s) | Replaces instances of pattern in a string with a replacement.
The compiled regex is kept in a cache shared by Match and Search.
Args:
pattern: regex pattern
rep: replacement text
s: search string
Returns:
string with replacements made (or original string if no replacements) | Replaces instances of pattern in a string with a replacement. | [
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"""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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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | uCSIsMongolian | (code) | return ret | Check whether the character is part of Mongolian UCS Block | Check whether the character is part of Mongolian UCS Block | [
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"""Check whether the character is part of Mongolian UCS Block """
ret = libxml2mod.xmlUCSIsMongolian(code)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/Blast/3rdParty/assimp/port/PyAssimp/scripts/transformations.py | python | quaternion_multiply | (quaternion1, quaternion0) | return numpy.array((
x1*w0 + y1*z0 - z1*y0 + w1*x0,
-x1*z0 + y1*w0 + z1*x0 + w1*y0,
x1*y0 - y1*x0 + z1*w0 + w1*z0,
-x1*x0 - y1*y0 - z1*z0 + w1*w0), dtype=numpy.float64) | Return multiplication of two quaternions.
>>> q = quaternion_multiply([1, -2, 3, 4], [-5, 6, 7, 8])
>>> numpy.allclose(q, [-44, -14, 48, 28])
True | Return multiplication of two quaternions. | [
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] | def quaternion_multiply(quaternion1, quaternion0):
"""Return multiplication of two quaternions.
>>> q = quaternion_multiply([1, -2, 3, 4], [-5, 6, 7, 8])
>>> numpy.allclose(q, [-44, -14, 48, 28])
True
"""
x0, y0, z0, w0 = quaternion0
x1, y1, z1, w1 = quaternion1
return numpy.array((
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x1*y0 - y1*x0 + z1*w0 + w1*z0,
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/backend.py | python | manual_variable_initialization | (value) | Sets the manual variable initialization flag.
This boolean flag determines whether
variables should be initialized
as they are instantiated (default), or if
the user should handle the initialization
(e.g. via `tf.compat.v1.initialize_all_variables()`).
Args:
value: Python boolean. | Sets the manual variable initialization flag. | [
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"""Sets the manual variable initialization flag.
This boolean flag determines whether
variables should be initialized
as they are instantiated (default), or if
the user should handle the initialization
(e.g. via `tf.compat.v1.initialize_all_variables()`).
Args:
value: Python boolean.
"""
global _MANUAL_VAR_INIT
_MANUAL_VAR_INIT = value | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Jinja2/py3/jinja2/bccache.py | python | Bucket.bytecode_to_string | (self) | return out.getvalue() | Return the bytecode as bytes. | Return the bytecode as bytes. | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/ftplib.py | python | FTP.rmd | (self, dirname) | return self.voidcmd('RMD ' + dirname) | Remove a directory. | Remove a directory. | [
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'''Remove a directory.'''
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citizenfx/fivem | 88276d40cc7baf8285d02754cc5ae42ec7a8563f | code/tools/idl/xpidl/xpidl.py | python | IDLParser.t_singlelinecomment | (self, t) | r'(?m)//.*?$ | r'(?m)//.*?$ | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/turtle.py | python | _Screen.setup | (self, width=_CFG["width"], height=_CFG["height"],
startx=_CFG["leftright"], starty=_CFG["topbottom"]) | Set the size and position of the main window.
Arguments:
width: as integer a size in pixels, as float a fraction of the screen.
Default is 50% of screen.
height: as integer the height in pixels, as float a fraction of the
screen. Default is 75% of screen.
startx: if positive, starting position in pixels from the left
edge of the screen, if negative from the right edge
Default, startx=None is to center window horizontally.
starty: if positive, starting position in pixels from the top
edge of the screen, if negative from the bottom edge
Default, starty=None is to center window vertically.
Examples (for a Screen instance named screen):
>>> screen.setup (width=200, height=200, startx=0, starty=0)
sets window to 200x200 pixels, in upper left of screen
>>> screen.setup(width=.75, height=0.5, startx=None, starty=None)
sets window to 75% of screen by 50% of screen and centers | Set the size and position of the main window. | [
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""" Set the size and position of the main window.
Arguments:
width: as integer a size in pixels, as float a fraction of the screen.
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height: as integer the height in pixels, as float a fraction of the
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starty: if positive, starting position in pixels from the top
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sets window to 75% of screen by 50% of screen and centers
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/richtext.py | python | RichTextCtrl.ApplyTextEffectToSelection | (*args, **kwargs) | return _richtext.RichTextCtrl_ApplyTextEffectToSelection(*args, **kwargs) | ApplyTextEffectToSelection(self, int flags) -> bool | ApplyTextEffectToSelection(self, int flags) -> bool | [
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AirtestProject/Poco-SDK | e7bd6c21236051092e67ae44178d45890f70d803 | sdk/python/sdk/Selector.py | python | Selector.select | (self, cond, multiple=False) | return self.selectImpl(cond, multiple, self.getRoot(), 9999, True, True) | See Also: :py:meth:`select <poco.sdk.Selector.ISelector.select>` method in ``ISelector``. | See Also: :py:meth:`select <poco.sdk.Selector.ISelector.select>` method in ``ISelector``. | [
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psnonis/FinBERT | c0c555d833a14e2316a3701e59c0b5156f804b4e | bert-gpu/run_squad.py | python | get_final_text | (pred_text, orig_text, do_lower_case) | return output_text | Project the tokenized prediction back to the original text. | Project the tokenized prediction back to the original text. | [
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"""Project the tokenized prediction back to the original text."""
# When we created the data, we kept track of the alignment between original
# (whitespace tokenized) tokens and our WordPiece tokenized tokens. So
# now `orig_text` contains the span of our original text corresponding to the
# span that we predicted.
#
# However, `orig_text` may contain extra characters that we don't want in
# our prediction.
#
# For example, let's say:
# pred_text = steve smith
# orig_text = Steve Smith's
#
# We don't want to return `orig_text` because it contains the extra "'s".
#
# We don't want to return `pred_text` because it's already been normalized
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# What we really want to return is "Steve Smith".
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# Therefore, we have to apply a semi-complicated alignment heruistic between
# `pred_text` and `orig_text` to get a character-to-charcter alignment. This
# can fail in certain cases in which case we just return `orig_text`.
def _strip_spaces(text):
ns_chars = []
ns_to_s_map = collections.OrderedDict()
for (i, c) in enumerate(text):
if c == " ":
continue
ns_to_s_map[len(ns_chars)] = i
ns_chars.append(c)
ns_text = "".join(ns_chars)
return (ns_text, ns_to_s_map)
# We first tokenize `orig_text`, strip whitespace from the result
# and `pred_text`, and check if they are the same length. If they are
# NOT the same length, the heuristic has failed. If they are the same
# length, we assume the characters are one-to-one aligned.
tokenizer = tokenization.BasicTokenizer(do_lower_case=do_lower_case)
tok_text = " ".join(tokenizer.tokenize(orig_text))
start_position = tok_text.find(pred_text)
if start_position == -1:
if FLAGS.verbose_logging:
tf.logging.info(
"Unable to find text: '%s' in '%s'" % (pred_text, orig_text))
return orig_text
end_position = start_position + len(pred_text) - 1
(orig_ns_text, orig_ns_to_s_map) = _strip_spaces(orig_text)
(tok_ns_text, tok_ns_to_s_map) = _strip_spaces(tok_text)
if len(orig_ns_text) != len(tok_ns_text):
if FLAGS.verbose_logging:
tf.logging.info("Length not equal after stripping spaces: '%s' vs '%s'",
orig_ns_text, tok_ns_text)
return orig_text
# We then project the characters in `pred_text` back to `orig_text` using
# the character-to-character alignment.
tok_s_to_ns_map = {}
for (i, tok_index) in six.iteritems(tok_ns_to_s_map):
tok_s_to_ns_map[tok_index] = i
orig_start_position = None
if start_position in tok_s_to_ns_map:
ns_start_position = tok_s_to_ns_map[start_position]
if ns_start_position in orig_ns_to_s_map:
orig_start_position = orig_ns_to_s_map[ns_start_position]
if orig_start_position is None:
if FLAGS.verbose_logging:
tf.logging.info("Couldn't map start position")
return orig_text
orig_end_position = None
if end_position in tok_s_to_ns_map:
ns_end_position = tok_s_to_ns_map[end_position]
if ns_end_position in orig_ns_to_s_map:
orig_end_position = orig_ns_to_s_map[ns_end_position]
if orig_end_position is None:
if FLAGS.verbose_logging:
tf.logging.info("Couldn't map end position")
return orig_text
output_text = orig_text[orig_start_position:(orig_end_position + 1)]
return output_text | [
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rodeofx/OpenWalter | 6116fbe3f04f1146c854afbfbdbe944feaee647e | walter/common/walterWidgets/walterLayersView.py | python | LayersItem.getActions | (self) | return [
(self.OPEN_ICON, 1.0, self.ACTION_OPEN),
(self.VIS_ICON, visibleOpacity, self.ACTION_VISIBLE),
(self.RND_ICON, renderableOpacity, self.ACTION_RENDERABLE)] | The list of actions to draw on the right side of the item in the tree
view. It should return the data in the following format:
[(icon1, opacity1, action1), (icon2, opacity2, action2), ...] | The list of actions to draw on the right side of the item in the tree
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[(icon1, opacity1, action1), (icon2, opacity2, action2), ...] | [
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"""
The list of actions to draw on the right side of the item in the tree
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[(icon1, opacity1, action1), (icon2, opacity2, action2), ...]
"""
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return [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/src/robotsim.py | python | Geometry3D.setCollisionMargin | (self, margin: "double") | return _robotsim.Geometry3D_setCollisionMargin(self, margin) | r"""
setCollisionMargin(Geometry3D self, double margin)
Sets a padding around the base geometry which affects the results of proximity
queries. | r"""
setCollisionMargin(Geometry3D self, double margin) | [
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r"""
setCollisionMargin(Geometry3D self, double margin)
Sets a padding around the base geometry which affects the results of proximity
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"""
return _robotsim.Geometry3D_setCollisionMargin(self, margin) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_gdi.py | python | Region.IntersectRect | (*args, **kwargs) | return _gdi_.Region_IntersectRect(*args, **kwargs) | IntersectRect(self, Rect rect) -> bool | IntersectRect(self, Rect rect) -> bool | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/robotsim.py | python | TerrainModel.setName | (self, name: str) | return _robotsim.TerrainModel_setName(self, name) | r"""
Args:
name (str) | r"""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | ItemContainer.SetStringSelection | (*args, **kwargs) | return _core_.ItemContainer_SetStringSelection(*args, **kwargs) | SetStringSelection(self, String s) -> bool | SetStringSelection(self, String s) -> bool | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/botocore/docs/bcdoc/restdoc.py | python | DocumentStructure.delete_section | (self, name) | Delete a section | Delete a section | [
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domino-team/openwrt-cc | 8b181297c34d14d3ca521cc9f31430d561dbc688 | package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/tools/gyp/pylib/gyp/generator/make.py | python | MakefileWriter.WriteSources | (self, configs, deps, sources,
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cflags_c = config.get('cflags_c')
cflags_cc = config.get('cflags_cc')
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self.WriteList(cflags, 'CFLAGS_%s' % configname)
self.WriteLn("# Flags passed to only C files.");
self.WriteList(cflags_c, 'CFLAGS_C_%s' % configname)
self.WriteLn("# Flags passed to only C++ files.");
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if self.flavor == 'mac':
self.WriteLn("# Flags passed to only ObjC files.");
self.WriteList(cflags_objc, 'CFLAGS_OBJC_%s' % configname)
self.WriteLn("# Flags passed to only ObjC++ files.");
self.WriteList(cflags_objcc, 'CFLAGS_OBJCC_%s' % configname)
includes = config.get('include_dirs')
if includes:
includes = map(Sourceify, map(self.Absolutify, includes))
self.WriteList(includes, 'INCS_%s' % configname, prefix='-I')
compilable = filter(Compilable, sources)
objs = map(self.Objectify, map(self.Absolutify, map(Target, compilable)))
self.WriteList(objs, 'OBJS')
for obj in objs:
assert ' ' not in obj, (
"Spaces in object filenames not supported (%s)" % obj)
self.WriteLn('# Add to the list of files we specially track '
'dependencies for.')
self.WriteLn('all_deps += $(OBJS)')
self.WriteLn()
# Make sure our dependencies are built first.
if deps:
self.WriteMakeRule(['$(OBJS)'], deps,
comment = 'Make sure our dependencies are built '
'before any of us.',
order_only = True)
# Make sure the actions and rules run first.
# If they generate any extra headers etc., the per-.o file dep tracking
# will catch the proper rebuilds, so order only is still ok here.
if extra_outputs:
self.WriteMakeRule(['$(OBJS)'], extra_outputs,
comment = 'Make sure our actions/rules run '
'before any of us.',
order_only = True)
pchdeps = precompiled_header.GetObjDependencies(compilable, objs )
if pchdeps:
self.WriteLn('# Dependencies from obj files to their precompiled headers')
for source, obj, gch in pchdeps:
self.WriteLn('%s: %s' % (obj, gch))
self.WriteLn('# End precompiled header dependencies')
if objs:
extra_link_deps.append('$(OBJS)')
self.WriteLn("""\
# CFLAGS et al overrides must be target-local.
# See "Target-specific Variable Values" in the GNU Make manual.""")
self.WriteLn("$(OBJS): TOOLSET := $(TOOLSET)")
self.WriteLn("$(OBJS): GYP_CFLAGS := "
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"$(INCS_$(BUILDTYPE)) "
"%s " % precompiled_header.GetInclude('c') +
"$(CFLAGS_$(BUILDTYPE)) "
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self.WriteLn("$(OBJS): GYP_CXXFLAGS := "
"$(DEFS_$(BUILDTYPE)) "
"$(INCS_$(BUILDTYPE)) "
"%s " % precompiled_header.GetInclude('cc') +
"$(CFLAGS_$(BUILDTYPE)) "
"$(CFLAGS_CC_$(BUILDTYPE))")
if self.flavor == 'mac':
self.WriteLn("$(OBJS): GYP_OBJCFLAGS := "
"$(DEFS_$(BUILDTYPE)) "
"$(INCS_$(BUILDTYPE)) "
"%s " % precompiled_header.GetInclude('m') +
"$(CFLAGS_$(BUILDTYPE)) "
"$(CFLAGS_C_$(BUILDTYPE)) "
"$(CFLAGS_OBJC_$(BUILDTYPE))")
self.WriteLn("$(OBJS): GYP_OBJCXXFLAGS := "
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"$(INCS_$(BUILDTYPE)) "
"%s " % precompiled_header.GetInclude('mm') +
"$(CFLAGS_$(BUILDTYPE)) "
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self.WritePchTargets(precompiled_header.GetPchBuildCommands())
# If there are any object files in our input file list, link them into our
# output.
extra_link_deps += filter(Linkable, sources)
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/Tpm.py | python | Tpm.ECC_Parameters | (self, curveID) | return res.parameters if res else None | This command returns the parameters of an ECC curve identified by
its TCG-assigned curveID.
Args:
curveID (TPM_ECC_CURVE): Parameter set selector
Returns:
parameters - ECC parameters for the selected curve | This command returns the parameters of an ECC curve identified by
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req = TPM2_ECC_Parameters_REQUEST(curveID)
respBuf = self.dispatchCommand(TPM_CC.ECC_Parameters, req)
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msftguy/ssh-rd | a5f3a79daeac5844edebf01916c9613563f1c390 | _3rd/boost_1_48_0/tools/build/v2/build/virtual_target.py | python | VirtualTargetRegistry.add_suffix | (self, specified_name, file_type, prop_set) | Appends the suffix appropriate to 'type/property_set' combination
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | src/python/m5/stats/__init__.py | python | _hdf5Factory | (fn, chunking=10, desc=True, formulas=True) | return _m5.stats.initHDF5(fn, chunking, desc, formulas) | Output stats in HDF5 format.
The HDF5 file format is a structured binary file format. It has
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* Fast lookup of stats
* Plenty of existing tooling (e.g., Python libraries and graphical
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* File format can be used to store frame buffers together with
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* Large startup cost (single stat dump larger than text equivalent)
* Stat dumps are slower than text
Known limitations:
* Distributions and histograms currently unsupported.
* No support for forking.
Parameters:
* chunking (unsigned): Number of time steps to pre-allocate (default: 10)
* desc (bool): Output stat descriptions (default: True)
* formulas (bool): Output derived stats (default: True)
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apple/swift | 469f72fdae2ea828b3b6c0d7d62d7e4cf98c4893 | utils/build_swift/build_swift/presets.py | python | _catch_duplicate_section_error | (func) | return wrapper | Decorator used to catch and rethrowing configparser's
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def wrapper(*args, **kwargs):
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | BMPHandler.__init__ | (self, *args, **kwargs) | __init__(self) -> BMPHandler
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/closure_linter/closure_linter/statetracker.py | python | StateTracker.InObjectLiteral | (self) | return self._block_depth and self._block_types[-1] == self.OBJECT_LITERAL | Returns true if the current token is within an object literal.
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"""Returns true if the current token is within an object literal.
Returns:
True if the current token is within an object literal.
"""
return self._block_depth and self._block_types[-1] == self.OBJECT_LITERAL | [
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klzgrad/naiveproxy | ed2c513637c77b18721fe428d7ed395b4d284c83 | src/build/android/pylib/utils/decorators.py | python | NoRaiseException | (default_return_value=None, exception_message='') | return decorator | Returns decorator that catches and logs uncaught Exceptions.
Args:
default_return_value: Value to return in the case of uncaught Exception.
exception_message: Message for uncaught exceptions. | Returns decorator that catches and logs uncaught Exceptions. | [
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"""Returns decorator that catches and logs uncaught Exceptions.
Args:
default_return_value: Value to return in the case of uncaught Exception.
exception_message: Message for uncaught exceptions.
"""
def decorator(f):
@functools.wraps(f)
def wrapper(*args, **kwargs):
try:
return f(*args, **kwargs)
except Exception: # pylint: disable=broad-except
logging.exception(exception_message)
return default_return_value
return wrapper
return decorator | [
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google/mediapipe | e6c19885c6d3c6f410c730952aeed2852790d306 | mediapipe/python/solutions/holistic.py | python | _download_oss_pose_landmark_model | (model_complexity) | Downloads the pose landmark lite/heavy model from the MediaPipe Github repo if it doesn't exist in the package. | Downloads the pose landmark lite/heavy model from the MediaPipe Github repo if it doesn't exist in the package. | [
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"""Downloads the pose landmark lite/heavy model from the MediaPipe Github repo if it doesn't exist in the package."""
if model_complexity == 0:
download_utils.download_oss_model(
'mediapipe/modules/pose_landmark/pose_landmark_lite.tflite')
elif model_complexity == 2:
download_utils.download_oss_model(
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nasa/fprime | 595cf3682d8365943d86c1a6fe7c78f0a116acf0 | Autocoders/Python/src/fprime_ac/generators/visitors/SerialCppVisitor.py | python | SerialCppVisitor.initFilesVisit | (self, obj) | Defined to generate files for generated code products.
@param args: the instance of the concrete element to operation on. | Defined to generate files for generated code products. | [
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] | def initFilesVisit(self, obj):
"""
Defined to generate files for generated code products.
@param args: the instance of the concrete element to operation on.
"""
# Build filename here...
if self.__config.get("serialize", "XMLDefaultFileName") == "True":
namespace = "".join(obj.get_namespace().split("::"))
filename = (
namespace
+ obj.get_name()
+ self.__config.get("serialize", "SerializableCpp")
)
PRINT.info(
"Generating code filename: %s, using XML namespace and name attributes..."
% filename
)
else:
xml_file = obj.get_xml_filename()
x = xml_file.split(".")
s = self.__config.get("serialize", "SerializableXML").split(".")
l = len(s[0])
#
if (x[0][-l:] == s[0]) & (x[1] == s[1]):
filename = x[0].split(s[0])[0] + self.__config.get(
"serialize", "SerializableCpp"
)
PRINT.info(
"Generating code filename: %s, using default XML filename prefix..."
% filename
)
else:
msg = (
"XML file naming format not allowed (must be XXXSerializableAi.xml), Filename: %s"
% xml_file
)
PRINT.info(msg)
sys.exit(-1)
# Open file for writing here...
DEBUG.info("Open file: %s" % filename)
self.__fp = open(filename, "w")
if self.__fp is None:
raise Exception("Could not open %s file.") % filename
DEBUG.info("Completed") | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | Text.tag_unbind | (self, tagName, sequence, funcid=None) | Unbind for all characters with TAGNAME for event SEQUENCE the
function identified with FUNCID. | Unbind for all characters with TAGNAME for event SEQUENCE the
function identified with FUNCID. | [
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] | def tag_unbind(self, tagName, sequence, funcid=None):
"""Unbind for all characters with TAGNAME for event SEQUENCE the
function identified with FUNCID."""
self.tk.call(self._w, 'tag', 'bind', tagName, sequence, '')
if funcid:
self.deletecommand(funcid) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/client/session.py | python | BaseSession.graph | (self) | return self._graph | The graph that was launched in this session. | The graph that was launched in this session. | [
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] | def graph(self):
"""The graph that was launched in this session."""
return self._graph | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/saved_model/signature_serialization.py | python | find_function_to_export | (saveable_view) | return None | Function to export, None if no suitable function was found. | Function to export, None if no suitable function was found. | [
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] | def find_function_to_export(saveable_view):
"""Function to export, None if no suitable function was found."""
# If the user did not specify signatures, check the root object for a function
# that can be made into a signature.
functions = saveable_view.list_functions(saveable_view.root)
signature = functions.get(DEFAULT_SIGNATURE_ATTR, None)
if signature is not None:
return signature
# TODO(andresp): Discuss removing this behaviour. It can lead to WTFs when a
# user decides to annotate more functions with tf.function and suddenly
# serving that model way later in the process stops working.
possible_signatures = []
for function in functions.values():
concrete = _get_signature(function)
if concrete is not None and _valid_signature(concrete):
possible_signatures.append(concrete)
if len(possible_signatures) == 1:
single_function = possible_signatures[0]
signature = _get_signature(single_function)
if signature and _valid_signature(signature):
return signature
return None | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/requests_aws4auth/six.py | python | _add_doc | (func, doc) | Add documentation to a function. | Add documentation to a function. | [
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] | def _add_doc(func, doc):
"""Add documentation to a function."""
func.__doc__ = doc | [
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google/or-tools | 2cb85b4eead4c38e1c54b48044f92087cf165bce | ortools/sat/samples/interval_sample_sat.py | python | IntervalSampleSat | () | Showcases how to build interval variables. | Showcases how to build interval variables. | [
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"."
] | def IntervalSampleSat():
"""Showcases how to build interval variables."""
model = cp_model.CpModel()
horizon = 100
# An interval can be created from three affine expressions.
start_var = model.NewIntVar(0, horizon, 'start')
duration = 10 # Python cp/sat code accept integer variables or constants.
end_var = model.NewIntVar(0, horizon, 'end')
interval_var = model.NewIntervalVar(start_var, duration, end_var + 2,
'interval')
print(f'interval = {repr(interval_var)}')
# If the size is fixed, a simpler version uses the start expression and the
# size.
fixed_size_interval_var = model.NewFixedSizeIntervalVar(
start_var, 10, 'fixed_size_interval_var')
print(f'fixed_size_interval_var = {repr(fixed_size_interval_var)}')
# A fixed interval can be created using the same API.
fixed_interval = model.NewFixedSizeIntervalVar(5, 10, 'fixed_interval')
print(f'fixed_interval = {repr(fixed_interval)}') | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/ftplib.py | python | FTP.dir | (self, *args) | List a directory in long form.
By default list current directory to stdout.
Optional last argument is callback function; all
non-empty arguments before it are concatenated to the
LIST command. (This *should* only be used for a pathname.) | List a directory in long form.
By default list current directory to stdout.
Optional last argument is callback function; all
non-empty arguments before it are concatenated to the
LIST command. (This *should* only be used for a pathname.) | [
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'''List a directory in long form.
By default list current directory to stdout.
Optional last argument is callback function; all
non-empty arguments before it are concatenated to the
LIST command. (This *should* only be used for a pathname.)'''
cmd = 'LIST'
func = None
if args[-1:] and type(args[-1]) != type(''):
args, func = args[:-1], args[-1]
for arg in args:
if arg:
cmd = cmd + (' ' + arg)
self.retrlines(cmd, func) | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/third_party/pyserial/serial/urlhandler/protocol_hwgrep.py | python | Serial.setPort | (self, value) | translate port name before storing it | translate port name before storing it | [
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"""translate port name before storing it"""
if isinstance(value, basestring) and value.startswith('hwgrep://'):
serial.Serial.setPort(self, self.fromURL(value))
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | configs/example/read_config.py | python | ConfigManager.parse_port_name | (self, port) | return (peer, self.objects_by_name[peer], peer_port, index) | Parse the name of a port | Parse the name of a port | [
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peer, peer_port, whole_index, index = m.groups()
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/client/session.py | python | SessionInterface.partial_run | (self, handle, fetches, feed_dict=None) | Continues the execution with additional feeds and fetches. | Continues the execution with additional feeds and fetches. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | ListEvent.GetPoint | (*args, **kwargs) | return _controls_.ListEvent_GetPoint(*args, **kwargs) | GetPoint(self) -> Point | GetPoint(self) -> Point | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/math/optimize.py | python | OptimizationProblemBuilder.getBounds | (self) | return [self.variableBounds.get(v.name,((-inf,inf) if v.type.is_scalar() else ([-inf]*v.type.size,[inf]*v.type.size))) for v in self.optimizationVariables] | Returns optimization varable bounds as a list of (xmin,xmax) pairs. None is returned if the
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inf = float('inf')
if len(self.variableBounds) == 0 or not any(v.name in self.variableBounds for v in self.optimizationVariables):
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return [self.variableBounds.get(v.name,((-inf,inf) if v.type.is_scalar() else ([-inf]*v.type.size,[inf]*v.type.size))) for v in self.optimizationVariables] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/pydoc.py | python | _adjust_cli_sys_path | () | Ensures current directory is on sys.path, and __main__ directory is not.
Exception: __main__ dir is left alone if it's also pydoc's directory. | Ensures current directory is on sys.path, and __main__ directory is not. | [
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"""Ensures current directory is on sys.path, and __main__ directory is not.
Exception: __main__ dir is left alone if it's also pydoc's directory.
"""
revised_path = _get_revised_path(sys.path, sys.argv[0])
if revised_path is not None:
sys.path[:] = revised_path | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/cuda/target.py | python | CUDATargetContext.insert_addrspace_conv | (self, builder, ptr, addrspace) | return builder.call(conv, [ptr]) | Perform addrspace conversion according to the NVVM spec | Perform addrspace conversion according to the NVVM spec | [
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"""
lmod = builder.module
base_type = ptr.type.pointee
conv = nvvmutils.insert_addrspace_conv(lmod, base_type, addrspace)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_controls.py | python | DirPickerCtrl.Create | (*args, **kwargs) | return _controls_.DirPickerCtrl_Create(*args, **kwargs) | Create(self, Window parent, int id=-1, String path=EmptyString,
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/ultimatelistctrl.py | python | UltimateListHeaderWindow.OnEnterWindow | (self, event) | Handles the ``wx.EVT_ENTER_WINDOW`` event for :class:`UltimateListHeaderWindow`.
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Handles the ``wx.EVT_ENTER_WINDOW`` event for :class:`UltimateListHeaderWindow`.
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x, y = self._owner.CalcUnscrolledPosition(*self.ScreenToClient(wx.GetMousePosition()))
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simsong/bulk_extractor | 738911df22b7066ca9e1662f4131fb44090a4196 | python/be_grapher.py | python | plot_cpu | (*, reports, filename) | Read reports and plot the CPU | Read reports and plot the CPU | [
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"""Read reports and plot the CPU"""
fig = plt.figure()
ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))
ax.set_ylabel("% of CPU utilized")
ax.set_xlabel("Seconds from start of run")
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_ylim(ymin=0,ymax=400)
ymax = 100
lines = []
legends = []
for report in reports:
r = BulkReport(report)
xyvals = r.cpu_track()
# Extract timestamps and convert to seconds from beginning of run
xvals = [xy[0] for xy in xyvals]
xmin = min(xvals)
xvals = [ (x-xmin).total_seconds() for x in xvals]
# Extract CPU% and find max val
yvals = [xy[1] for xy in xyvals]
ymax = max([ymax] + yvals)
# Plot and retain handle
line, = plt.plot( xvals, yvals, label='report')
lines.append(line)
ax.legend( handles=lines ) # draw legends
ax.set_ylim(ymin=0, ymax=math.ceil(ymax/100)*100) # set ymax
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/simulation/sumo.py | python | SumoTraci.do | (self) | Called by run after is_ready verification | Called by run after is_ready verification | [
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yushroom/FishEngine | a4b9fb9b0a6dc202f7990e75f4b7d8d5163209d9 | Script/reflect/clang/cindex.py | python | Cursor.underlying_typedef_type | (self) | return self._underlying_type | Return the underlying type of a typedef declaration.
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if not hasattr(self, '_underlying_type'):
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/training/tracking/data_structures.py | python | List.__init__ | (self, *args, **kwargs) | Construct a new sequence. Arguments are passed to `list()`. | Construct a new sequence. Arguments are passed to `list()`. | [
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"""Construct a new sequence. Arguments are passed to `list()`."""
super(List, self).__init__()
self._storage = self._make_storage(*args, **kwargs)
for index, element in enumerate(self._storage):
self._storage[index] = self._track_value(
element, name=self._name_element(index)) | [
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microsoft/clang | 86d4513d3e0daa4d5a29b0b1de7c854ca15f9fe5 | tools/scan-build-py/libear/__init__.py | python | build_libear | (compiler, dst_dir) | Returns the full path to the 'libear' library. | Returns the full path to the 'libear' library. | [
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""" Returns the full path to the 'libear' library. """
try:
src_dir = os.path.dirname(os.path.realpath(__file__))
toolset = make_toolset(src_dir)
toolset.set_compiler(compiler)
toolset.set_language_standard('c99')
toolset.add_definitions(['-D_GNU_SOURCE'])
configure = do_configure(toolset)
configure.check_function_exists('execve', 'HAVE_EXECVE')
configure.check_function_exists('execv', 'HAVE_EXECV')
configure.check_function_exists('execvpe', 'HAVE_EXECVPE')
configure.check_function_exists('execvp', 'HAVE_EXECVP')
configure.check_function_exists('execvP', 'HAVE_EXECVP2')
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configure.check_function_exists('posix_spawnp', 'HAVE_POSIX_SPAWNP')
configure.check_symbol_exists('_NSGetEnviron', 'crt_externs.h',
'HAVE_NSGETENVIRON')
configure.write_by_template(
os.path.join(src_dir, 'config.h.in'),
os.path.join(dst_dir, 'config.h'))
target = create_shared_library('ear', toolset)
target.add_include(dst_dir)
target.add_sources('ear.c')
target.link_against(toolset.dl_libraries())
target.link_against(['pthread'])
target.build_release(dst_dir)
return os.path.join(dst_dir, target.name)
except Exception:
logging.info("Could not build interception library.", exc_info=True)
return None | [
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Manu343726/siplasplas | 9fae7559f87087cf8ef34f04bd1e774b84b2ea9c | reference/cindex.py | python | Cursor.location | (self) | return self._loc | Return the source location (the starting character) of the entity
pointed at by the cursor. | Return the source location (the starting character) of the entity
pointed at by the cursor. | [
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] | def location(self):
"""
Return the source location (the starting character) of the entity
pointed at by the cursor.
"""
if not hasattr(self, '_loc'):
self._loc = conf.lib.clang_getCursorLocation(self)
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | benchmarks/distributed/rpc/parameter_server/server/server.py | python | ParameterServerBase.reset_state | () | return | r"""
A method to be implemented by child class that will reset
the server state. | r"""
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r"""
A method to be implemented by child class that will reset
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"""
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/lookup/lookup_ops.py | python | index_to_string | (tensor, mapping, default_value="UNK", name=None) | return table.lookup(tensor) | Maps `tensor` of indices into string values based on `mapping`.
This operation converts `int64` indices into string values. The mapping is
initialized from a string `mapping` tensor where each element is a value and
the corresponding index within the tensor is the key.
Any input which does not have a corresponding index in 'mapping'
(an out-of-vocabulary entry) is assigned the `default_value`
The underlying table must be initialized by calling
`session.run(tf.compat.v1.tables_initializer)` once.
For example:
```python
mapping_string = tf.constant(["emerson", "lake", "palmer"])
indices = tf.constant([1, 5], tf.int64)
values = tf.contrib.lookup.index_to_string(
indices, mapping=mapping_string, default_value="UNKNOWN")
...
tf.compat.v1.tables_initializer().run()
values.eval() ==> ["lake", "UNKNOWN"]
```
Args:
tensor: A `int64` `Tensor` with the indices to map to strings.
mapping: A 1-D string `Tensor` that specifies the strings to map from
indices.
default_value: The string value to use for out-of-vocabulary indices.
name: A name for this op (optional).
Returns:
The strings values associated to the indices. The resultant dense
feature value tensor has the same shape as the corresponding `indices`. | Maps `tensor` of indices into string values based on `mapping`. | [
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] | def index_to_string(tensor, mapping, default_value="UNK", name=None):
"""Maps `tensor` of indices into string values based on `mapping`.
This operation converts `int64` indices into string values. The mapping is
initialized from a string `mapping` tensor where each element is a value and
the corresponding index within the tensor is the key.
Any input which does not have a corresponding index in 'mapping'
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```python
mapping_string = tf.constant(["emerson", "lake", "palmer"])
indices = tf.constant([1, 5], tf.int64)
values = tf.contrib.lookup.index_to_string(
indices, mapping=mapping_string, default_value="UNKNOWN")
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tf.compat.v1.tables_initializer().run()
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default_value: The string value to use for out-of-vocabulary indices.
name: A name for this op (optional).
Returns:
The strings values associated to the indices. The resultant dense
feature value tensor has the same shape as the corresponding `indices`.
"""
table = index_to_string_table_from_tensor(
mapping=mapping, default_value=default_value, name=name)
return table.lookup(tensor) | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/distutils/misc_util.py | python | all_strings | (lst) | return True | Return True if all items in lst are string objects. | Return True if all items in lst are string objects. | [
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"""Return True if all items in lst are string objects. """
for item in lst:
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return True | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/webkit.py | python | WebKitCtrl.Stop | (*args, **kwargs) | return _webkit.WebKitCtrl_Stop(*args, **kwargs) | Stop(self) | Stop(self) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/plotting/_core.py | python | scatter_plot | (data, x, y, by=None, ax=None, figsize=None, grid=False,
**kwargs) | return fig | Make a scatter plot from two DataFrame columns
Parameters
----------
data : DataFrame
x : Column name for the x-axis values
y : Column name for the y-axis values
ax : Matplotlib axis object
figsize : A tuple (width, height) in inches
grid : Setting this to True will show the grid
kwargs : other plotting keyword arguments
To be passed to scatter function
Returns
-------
fig : matplotlib.Figure | Make a scatter plot from two DataFrame columns | [
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] | def scatter_plot(data, x, y, by=None, ax=None, figsize=None, grid=False,
**kwargs):
"""
Make a scatter plot from two DataFrame columns
Parameters
----------
data : DataFrame
x : Column name for the x-axis values
y : Column name for the y-axis values
ax : Matplotlib axis object
figsize : A tuple (width, height) in inches
grid : Setting this to True will show the grid
kwargs : other plotting keyword arguments
To be passed to scatter function
Returns
-------
fig : matplotlib.Figure
"""
import matplotlib.pyplot as plt
kwargs.setdefault('edgecolors', 'none')
def plot_group(group, ax):
xvals = group[x].values
yvals = group[y].values
ax.scatter(xvals, yvals, **kwargs)
ax.grid(grid)
if by is not None:
fig = _grouped_plot(plot_group, data, by=by, figsize=figsize, ax=ax)
else:
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
else:
fig = ax.get_figure()
plot_group(data, ax)
ax.set_ylabel(pprint_thing(y))
ax.set_xlabel(pprint_thing(x))
ax.grid(grid)
return fig | [
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GJDuck/LowFat | ecf6a0f0fa1b73a27a626cf493cc39e477b6faea | llvm-4.0.0.src/projects/compiler-rt/lib/sanitizer_common/scripts/cpplint.py | python | _CppLintState.SetVerboseLevel | (self, level) | return last_verbose_level | Sets the module's verbosity, and returns the previous setting. | Sets the module's verbosity, and returns the previous setting. | [
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"""Sets the module's verbosity, and returns the previous setting."""
last_verbose_level = self.verbose_level
self.verbose_level = level
return last_verbose_level | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/probability/distribution/poisson.py | python | Poisson._cdf | (self, value, rate=None) | return self.select(comp, zeros, cdf) | r"""
Cumulative distribution function (cdf) of Poisson distributions.
Args:
value (Tensor): The value to be evaluated.
rate (Tensor): The rate of the distribution. Default: self.rate.
Note:
`value` must be greater or equal to zero.
.. math::
cdf(x) = \Gamma(x + 1) if x >= 0 else 0 | r"""
Cumulative distribution function (cdf) of Poisson distributions. | [
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Cumulative distribution function (cdf) of Poisson distributions.
Args:
value (Tensor): The value to be evaluated.
rate (Tensor): The rate of the distribution. Default: self.rate.
Note:
`value` must be greater or equal to zero.
.. math::
cdf(x) = \Gamma(x + 1) if x >= 0 else 0
"""
value = self._check_value(value, 'value')
value = self.cast(value, self.dtype)
rate = self._check_param_type(rate)
zeros = self.fill(self.dtypeop(value), self.shape(value), 0.0)
comp = self.less(value, zeros)
safe_x = self.select(comp, zeros, value)
cdf = 1. - self.igamma(1. + safe_x, rate)
return self.select(comp, zeros, cdf) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/pdb.py | python | Pdb.do_args | (self, arg) | a(rgs)
Print the argument list of the current function. | a(rgs)
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"""a(rgs)
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dict = self.curframe_locals
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if co.co_flags & inspect.CO_VARKEYWORDS: n = n+1
for i in range(n):
name = co.co_varnames[i]
if name in dict:
self.message('%s = %r' % (name, dict[name]))
else:
self.message('%s = *** undefined ***' % (name,)) | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/configobj/configobj.py | python | Section.setdefault | (self, key, default=None) | A version of setdefault that sets sequence if appropriate. | A version of setdefault that sets sequence if appropriate. | [
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"""A version of setdefault that sets sequence if appropriate."""
try:
return self[key]
except KeyError:
self[key] = default
return self[key] | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/telnetlib.py | python | Telnet.read_lazy | (self) | return self.read_very_lazy() | Process and return data that's already in the queues (lazy).
Raise EOFError if connection closed and no data available.
Return '' if no cooked data available otherwise. Don't block
unless in the midst of an IAC sequence. | Process and return data that's already in the queues (lazy). | [
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"""Process and return data that's already in the queues (lazy).
Raise EOFError if connection closed and no data available.
Return '' if no cooked data available otherwise. Don't block
unless in the midst of an IAC sequence.
"""
self.process_rawq()
return self.read_very_lazy() | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | contrib/gizmos/osx_carbon/gizmos.py | python | TreeListCtrl.Delete | (*args, **kwargs) | return _gizmos.TreeListCtrl_Delete(*args, **kwargs) | Delete(self, TreeItemId item) | Delete(self, TreeItemId item) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_controls.py | python | RadioBox.GetString | (*args, **kwargs) | return _controls_.RadioBox_GetString(*args, **kwargs) | GetString(self, int n) -> String | GetString(self, int n) -> String | [
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apache/arrow | af33dd1157eb8d7d9bfac25ebf61445b793b7943 | python/pyarrow/types.py | python | is_int16 | (t) | return t.id == lib.Type_INT16 | Return True if value is an instance of an int16 type.
Parameters
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"""
Return True if value is an instance of an int16 type.
Parameters
----------
t : DataType
"""
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/tools/optimize_for_inference_lib.py | python | fold_batch_norms | (input_graph_def) | return result_graph_def | Removes batch normalization ops by folding them into convolutions.
Batch normalization during training has multiple dynamic parameters that are
updated, but once the graph is finalized these become constants. That means
there's an opportunity to reduce the computations down to a scale and
addition, rather than the more expensive multiple ops, and even bake the
scaling into the convolution weights. This function identifies the typical
pattern of batch normalization subgraphs, and performs the transformation to
fold the computations down into a simpler form. It currently only spots batch
normalization that's performed by the BatchNormWithGlobalNormalization op, and
will need to be extended in the future to handle the newer style.
Args:
input_graph_def: A GraphDef containing a model.
Returns:
Modified graph with BN ops removed, and modified weights.
Raises:
ValueError: If the graph is badly formed with duplicate node names. | Removes batch normalization ops by folding them into convolutions. | [
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] | def fold_batch_norms(input_graph_def):
"""Removes batch normalization ops by folding them into convolutions.
Batch normalization during training has multiple dynamic parameters that are
updated, but once the graph is finalized these become constants. That means
there's an opportunity to reduce the computations down to a scale and
addition, rather than the more expensive multiple ops, and even bake the
scaling into the convolution weights. This function identifies the typical
pattern of batch normalization subgraphs, and performs the transformation to
fold the computations down into a simpler form. It currently only spots batch
normalization that's performed by the BatchNormWithGlobalNormalization op, and
will need to be extended in the future to handle the newer style.
Args:
input_graph_def: A GraphDef containing a model.
Returns:
Modified graph with BN ops removed, and modified weights.
Raises:
ValueError: If the graph is badly formed with duplicate node names.
"""
input_node_map = {}
for node in input_graph_def.node:
if node.name not in input_node_map.keys():
input_node_map[node.name] = node
else:
raise ValueError("Duplicate node names detected for ", node.name)
nodes_to_skip = {}
new_ops = []
for node in input_graph_def.node:
if node.op not in ("BatchNormWithGlobalNormalization", "FusedBatchNorm"):
continue
conv_op = node_from_map(input_node_map,
node.input[INPUT_ORDER[node.op].index("conv_op")])
if conv_op.op != "Conv2D":
tf_logging.warning(
"Didn't find expected Conv2D input to '%s'" % node.name)
continue
weights_op = node_from_map(input_node_map, conv_op.input[1])
if weights_op.op != "Const":
tf_logging.warning("Didn't find expected conv Constant input to '%s',"
" found %s instead. Maybe because freeze_graph wasn't"
" run first?" % (conv_op.name, weights_op))
continue
weights = values_from_const(weights_op)
channel_count = weights.shape[3]
mean_op = node_from_map(input_node_map,
node.input[INPUT_ORDER[node.op].index("mean_op")])
if mean_op.op != "Const":
tf_logging.warning("Didn't find expected mean Constant input to '%s',"
" found %s instead. Maybe because freeze_graph wasn't"
" run first?" % (node.name, mean_op))
continue
mean_value = values_from_const(mean_op)
if mean_value.shape != (channel_count,):
tf_logging.warning("Incorrect shape for mean, found %s, expected %s,"
" for node %s" % (str(mean_value.shape), str(
(channel_count,)), node.name))
continue
var_op = node_from_map(input_node_map,
node.input[INPUT_ORDER[node.op].index("var_op")])
if var_op.op != "Const":
tf_logging.warning("Didn't find expected var Constant input to '%s',"
" found %s instead. Maybe because freeze_graph wasn't"
" run first?" % (node.name, var_op))
continue
var_value = values_from_const(var_op)
if var_value.shape != (channel_count,):
tf_logging.warning("Incorrect shape for var, found %s, expected %s,"
" for node %s" % (str(var_value.shape), str(
(channel_count,)), node.name))
continue
beta_op = node_from_map(input_node_map,
node.input[INPUT_ORDER[node.op].index("beta_op")])
if beta_op.op != "Const":
tf_logging.warning("Didn't find expected beta Constant input to '%s',"
" found %s instead. Maybe because freeze_graph wasn't"
" run first?" % (node.name, beta_op))
continue
beta_value = values_from_const(beta_op)
if beta_value.shape != (channel_count,):
tf_logging.warning("Incorrect shape for beta, found %s, expected %s,"
" for node %s" % (str(beta_value.shape), str(
(channel_count,)), node.name))
continue
gamma_op = node_from_map(input_node_map,
node.input[INPUT_ORDER[node.op].index("gamma_op")])
if gamma_op.op != "Const":
tf_logging.warning("Didn't find expected gamma Constant input to '%s',"
" found %s instead. Maybe because freeze_graph wasn't"
" run first?" % (node.name, gamma_op))
continue
gamma_value = values_from_const(gamma_op)
if gamma_value.shape != (channel_count,):
tf_logging.warning("Incorrect shape for gamma, found %s, expected %s,"
" for node %s" % (str(gamma_value.shape), str(
(channel_count,)), node.name))
continue
variance_epsilon_value = node.attr[EPSILON_ATTR[node.op]].f
nodes_to_skip[node.name] = True
nodes_to_skip[weights_op.name] = True
nodes_to_skip[mean_op.name] = True
nodes_to_skip[var_op.name] = True
nodes_to_skip[beta_op.name] = True
nodes_to_skip[gamma_op.name] = True
nodes_to_skip[conv_op.name] = True
if scale_after_normalization(node):
scale_value = (
(1.0 / np.vectorize(math.sqrt)(var_value + variance_epsilon_value)) *
gamma_value)
else:
scale_value = (
1.0 / np.vectorize(math.sqrt)(var_value + variance_epsilon_value))
offset_value = (-mean_value * scale_value) + beta_value
scaled_weights = np.copy(weights)
it = np.nditer(
scaled_weights, flags=["multi_index"], op_flags=["readwrite"])
while not it.finished:
current_scale = scale_value[it.multi_index[3]]
it[0] *= current_scale
it.iternext()
scaled_weights_op = node_def_pb2.NodeDef()
scaled_weights_op.op = "Const"
scaled_weights_op.name = weights_op.name
scaled_weights_op.attr["dtype"].CopyFrom(weights_op.attr["dtype"])
scaled_weights_op.attr["value"].CopyFrom(
attr_value_pb2.AttrValue(tensor=tensor_util.make_tensor_proto(
scaled_weights, weights.dtype.type, weights.shape)))
new_conv_op = node_def_pb2.NodeDef()
new_conv_op.CopyFrom(conv_op)
offset_op = node_def_pb2.NodeDef()
offset_op.op = "Const"
offset_op.name = conv_op.name + "_bn_offset"
offset_op.attr["dtype"].CopyFrom(mean_op.attr["dtype"])
offset_op.attr["value"].CopyFrom(
attr_value_pb2.AttrValue(tensor=tensor_util.make_tensor_proto(
offset_value, mean_value.dtype.type, offset_value.shape)))
bias_add_op = node_def_pb2.NodeDef()
bias_add_op.op = "BiasAdd"
bias_add_op.name = node.name
bias_add_op.attr["T"].CopyFrom(conv_op.attr["T"])
bias_add_op.input.extend([new_conv_op.name, offset_op.name])
new_ops.extend([scaled_weights_op, new_conv_op, offset_op, bias_add_op])
result_graph_def = graph_pb2.GraphDef()
for node in input_graph_def.node:
if node.name in nodes_to_skip:
continue
new_node = node_def_pb2.NodeDef()
new_node.CopyFrom(node)
result_graph_def.node.extend([new_node])
result_graph_def.node.extend(new_ops)
return result_graph_def | [
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papyrussolution/OpenPapyrus | bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91 | Src/OSF/protobuf-3.19.1/python/google/protobuf/text_format.py | python | Tokenizer._ConsumeSingleByteString | (self) | return result | Consume one token of a string literal.
String literals (whether bytes or text) can come in multiple adjacent
tokens which are automatically concatenated, like in C or Python. This
method only consumes one token.
Returns:
The token parsed.
Raises:
ParseError: When the wrong format data is found. | Consume one token of a string literal. | [
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"""Consume one token of a string literal.
String literals (whether bytes or text) can come in multiple adjacent
tokens which are automatically concatenated, like in C or Python. This
method only consumes one token.
Returns:
The token parsed.
Raises:
ParseError: When the wrong format data is found.
"""
text = self.token
if len(text) < 1 or text[0] not in _QUOTES:
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if len(text) < 2 or text[-1] != text[0]:
raise self.ParseError('String missing ending quote: %r' % (text,))
try:
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/tools/graph_transforms/__init__.py | python | TransformGraph | (input_graph_def, inputs, outputs, transforms) | return output_graph_def | Python wrapper for the Graph Transform Tool.
Gives access to all graph transforms available through the command line tool.
See documentation at https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/graph_transforms/README.md
for full details of the options available.
Args:
input_graph_def: GraphDef object containing a model to be transformed.
inputs: List of node names for the model inputs.
outputs: List of node names for the model outputs.
transforms: List of strings containing transform names and parameters.
Returns:
New GraphDef with transforms applied. | Python wrapper for the Graph Transform Tool. | [
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"""Python wrapper for the Graph Transform Tool.
Gives access to all graph transforms available through the command line tool.
See documentation at https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/graph_transforms/README.md
for full details of the options available.
Args:
input_graph_def: GraphDef object containing a model to be transformed.
inputs: List of node names for the model inputs.
outputs: List of node names for the model outputs.
transforms: List of strings containing transform names and parameters.
Returns:
New GraphDef with transforms applied.
"""
input_graph_def_string = input_graph_def.SerializeToString()
inputs_string = compat.as_bytes(",".join(inputs))
outputs_string = compat.as_bytes(",".join(outputs))
transforms_string = compat.as_bytes(" ".join(transforms))
output_graph_def_string = TransformGraphWithStringInputs(
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output_graph_def = graph_pb2.GraphDef()
output_graph_def.ParseFromString(output_graph_def_string)
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/clang/bindings/python/clang/cindex.py | python | Index.create | (excludeDecls=False) | return Index(conf.lib.clang_createIndex(excludeDecls, 0)) | Create a new Index.
Parameters:
excludeDecls -- Exclude local declarations from translation units. | Create a new Index.
Parameters:
excludeDecls -- Exclude local declarations from translation units. | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/lookup/lookup_ops.py | python | string_to_index | (tensor, mapping, default_value=-1, name=None) | Maps `tensor` of strings into `int64` indices based on `mapping`.
This operation converts `tensor` of strings into `int64` indices.
The mapping is initialized from a string `mapping` tensor where each element
is a key and corresponding index within the tensor is the value.
Any entry in the input which does not have a corresponding entry in 'mapping'
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Elements in `mapping` cannot be duplicated, otherwise the initialization
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The underlying table must be initialized by calling
`tf.initialize_all_tables.run()` once.
For example:
```python
mapping_strings = t.constant(["emerson", "lake", "palmer")
feats = tf.constant(["emerson", "lake", "and", "palmer"])
ids = tf.contrib.lookup.string_to_index(
feats, mapping=mapping_strings, default_value=-1)
...
tf.initialize_all_tables().run()
ids.eval() ==> [0, 1, -1, 2]
```
Args:
tensor: A 1-D input `Tensor` with the strings to map to indices.
mapping: A 1-D string `Tensor` that specifies the mapping of strings to
indices.
default_value: The `int64` value to use for out-of-vocabulary strings.
Defaults to -1.
name: A name for this op (optional).
Returns:
The mapped indices. It has the same shape and tensor type (dense or sparse)
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"""Maps `tensor` of strings into `int64` indices based on `mapping`.
This operation converts `tensor` of strings into `int64` indices.
The mapping is initialized from a string `mapping` tensor where each element
is a key and corresponding index within the tensor is the value.
Any entry in the input which does not have a corresponding entry in 'mapping'
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For example:
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mapping_strings = t.constant(["emerson", "lake", "palmer")
feats = tf.constant(["emerson", "lake", "and", "palmer"])
ids = tf.contrib.lookup.string_to_index(
feats, mapping=mapping_strings, default_value=-1)
...
tf.initialize_all_tables().run()
ids.eval() ==> [0, 1, -1, 2]
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mapping: A 1-D string `Tensor` that specifies the mapping of strings to
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default_value: The `int64` value to use for out-of-vocabulary strings.
Defaults to -1.
name: A name for this op (optional).
Returns:
The mapped indices. It has the same shape and tensor type (dense or sparse)
as `tensor`.
"""
with ops.op_scope([tensor], name, "string_to_index") as scope:
shared_name = ""
keys = ops.convert_to_tensor(mapping, dtypes.string)
vocab_size = array_ops.size(keys)
values = math_ops.cast(math_ops.range(vocab_size), dtypes.int64)
init = KeyValueTensorInitializer(keys,
values,
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dtypes.int64,
name="table_init")
t = HashTable(init,
default_value,
shared_name=shared_name,
name="hash_table")
return t.lookup(tensor, name=scope) | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/ttk.py | python | LabeledScale._set_value | (self, val) | Set new scale value. | Set new scale value. | [
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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/Tool/GettextCommon.py | python | _detect_msgmerge | (env) | return None | Detects *msgmerge(1)* program. | Detects *msgmerge(1)* program. | [
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stack-of-tasks/pinocchio | 593d4d43fded997bb9aa2421f4e55294dbd233c4 | bindings/python/pinocchio/robot_wrapper.py | python | RobotWrapper.play | (self, q_trajectory, dt) | Play a trajectory with given time step | Play a trajectory with given time step | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/botocore/docs/utils.py | python | py_default | (type_name) | return {
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/imaplib.py | python | IMAP4.create | (self, mailbox) | return self._simple_command('CREATE', mailbox) | Create new mailbox.
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/dtypes/cast.py | python | construct_1d_arraylike_from_scalar | (
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HKUST-Aerial-Robotics/Teach-Repeat-Replan | 98505a7f74b13c8b501176ff838a38423dbef536 | utils/quadrotor_msgs/src/quadrotor_msgs/msg/_TRPYCommand.py | python | TRPYCommand.__init__ | (self, *args, **kwds) | Constructor. Any message fields that are implicitly/explicitly
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/training/summary_io.py | python | SummaryWriter.flush | (self) | Flushes the event file to disk.
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self._event_queue.join()
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Alexhuszagh/rust-lexical | 01fcdcf8efc8850edb35d8fc65fd5f31bd0981a0 | lexical-util/etc/step.py | python | find_power | (max_value, radix) | return (power, power) | Find the power of the divisor. | Find the power of the divisor. | [
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power = int(math.floor(math.log(max_value, radix))) - 1
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power -= 1
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return (power, power + 1)
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htcondor/htcondor | 4829724575176d1d6c936e4693dfd78a728569b0 | src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/conversion.py | python | IConversion.TextToUserStatus | (self, Text) | return self._TextTo('cus', Text) | Returns user status code.
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@type Text: unicode
@return: User status.
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@return: User status.
@rtype: L{User status<enums.cusUnknown>}
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/ops/math_ops.py | python | _BroadcastShape | (op) | return [common_shapes.broadcast_shape(
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/third_party/png/png.py | python | Reader.asRGB | (self) | return width,height,iterrgb(),meta | Return image as RGB pixels. RGB colour images are passed
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An alpha channel in the source image will raise an
exception.
The return values are as for the :meth:`read` method
except that the *metadata* reflect the returned pixels, not the
source image. In particular, for this method
``metadata['greyscale']`` will be ``False``. | Return image as RGB pixels. RGB colour images are passed
through unchanged; greyscales are expanded into RGB
triplets (there is a small speed overhead for doing this). | [
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] | def asRGB(self):
"""Return image as RGB pixels. RGB colour images are passed
through unchanged; greyscales are expanded into RGB
triplets (there is a small speed overhead for doing this).
An alpha channel in the source image will raise an
exception.
The return values are as for the :meth:`read` method
except that the *metadata* reflect the returned pixels, not the
source image. In particular, for this method
``metadata['greyscale']`` will be ``False``.
"""
width,height,pixels,meta = self.asDirect()
if meta['alpha']:
raise Error("will not convert image with alpha channel to RGB")
if not meta['greyscale']:
return width,height,pixels,meta
meta['greyscale'] = False
typecode = 'BH'[meta['bitdepth'] > 8]
def iterrgb():
for row in pixels:
a = array(typecode, [0]) * 3 * width
for i in range(3):
a[i::3] = row
yield a
return width,height,iterrgb(),meta | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/python/ops/control_flow_ops.py | python | WhileContext.AddForwardCounter | (self) | return total_iterations, next_n | Adds a loop that counts the number of iterations.
This is added to the forward loop at the time when we start to
create the loop for backprop gradient computation. Called in
the outer context of this forward context.
The pseudocode is:
`n = 0; while (_pivot) { n++; }`
Returns:
The number of iterations taken by the forward loop and the loop index. | Adds a loop that counts the number of iterations. | [
"Adds",
"a",
"loop",
"that",
"counts",
"the",
"number",
"of",
"iterations",
"."
] | def AddForwardCounter(self):
"""Adds a loop that counts the number of iterations.
This is added to the forward loop at the time when we start to
create the loop for backprop gradient computation. Called in
the outer context of this forward context.
The pseudocode is:
`n = 0; while (_pivot) { n++; }`
Returns:
The number of iterations taken by the forward loop and the loop index.
"""
n = constant_op.constant(0, name="f_count")
assert n.op._get_control_flow_context() == self.outer_context
self.Enter()
self.AddName(n.name)
enter_n = _Enter(n, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
name="f_count")
merge_n = merge([enter_n, enter_n])[0]
switch_n = switch(merge_n, self._pivot)
index = math_ops.add(switch_n[1], 1)
next_n = _NextIteration(index)
merge_n.op._update_input(1, next_n)
total_iterations = exit(switch_n[0], name="f_count")
self.ExitResult([total_iterations])
self.Exit()
return total_iterations, next_n | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/roc/stubs.py | python | mem_fence | (*args, **kargs) | OpenCL mem_fence()
Example:
# local memory fence
hsa.mem_fence(hsa.CLK_LOCAL_MEM_FENCE)
# global memory fence
hsa.mem_fence(hsa.CLK_GLOBAL_MEM_FENCE) | OpenCL mem_fence() | [
"OpenCL",
"mem_fence",
"()"
] | def mem_fence(*args, **kargs):
"""
OpenCL mem_fence()
Example:
# local memory fence
hsa.mem_fence(hsa.CLK_LOCAL_MEM_FENCE)
# global memory fence
hsa.mem_fence(hsa.CLK_GLOBAL_MEM_FENCE)
"""
raise _stub_error | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/protobuf/py2/google/protobuf/internal/python_message.py | python | _ReraiseTypeErrorWithFieldName | (message_name, field_name) | Re-raise the currently-handled TypeError with the field name added. | Re-raise the currently-handled TypeError with the field name added. | [
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] | def _ReraiseTypeErrorWithFieldName(message_name, field_name):
"""Re-raise the currently-handled TypeError with the field name added."""
exc = sys.exc_info()[1]
if len(exc.args) == 1 and type(exc) is TypeError:
# simple TypeError; add field name to exception message
exc = TypeError('%s for field %s.%s' % (str(exc), message_name, field_name))
# re-raise possibly-amended exception with original traceback:
six.reraise(type(exc), exc, sys.exc_info()[2]) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/propgrid.py | python | PropertyGrid.SetupTextCtrlValue | (*args, **kwargs) | return _propgrid.PropertyGrid_SetupTextCtrlValue(*args, **kwargs) | SetupTextCtrlValue(self, String text) | SetupTextCtrlValue(self, String text) | [
"SetupTextCtrlValue",
"(",
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"String",
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")"
] | def SetupTextCtrlValue(*args, **kwargs):
"""SetupTextCtrlValue(self, String text)"""
return _propgrid.PropertyGrid_SetupTextCtrlValue(*args, **kwargs) | [
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citizenfx/fivem | 88276d40cc7baf8285d02754cc5ae42ec7a8563f | vendor/chromium/tools/diagnosis/crbug_1001171.py | python | DumpStateOnLookupError | () | Prints potentially useful state info in the event of a LookupError. | Prints potentially useful state info in the event of a LookupError. | [
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] | def DumpStateOnLookupError():
"""Prints potentially useful state info in the event of a LookupError."""
try:
yield
except LookupError:
print('LookupError diagnosis for crbug.com/1001171:')
for path_index, path_entry in enumerate(sys.path):
desc = 'unknown'
if not os.path.exists(path_entry):
desc = 'missing'
elif os.path.islink(path_entry):
desc = 'link -> %s' % os.path.realpath(path_entry)
elif os.path.isfile(path_entry):
desc = 'file'
elif os.path.isdir(path_entry):
desc = 'dir'
print(' sys.path[%d]: %s (%s)' % (path_index, path_entry, desc))
real_path_entry = os.path.realpath(path_entry)
if (path_entry.endswith(os.path.join('lib', 'python2.7'))
and os.path.isdir(real_path_entry)):
encodings_dir = os.path.realpath(
os.path.join(real_path_entry, 'encodings'))
if os.path.exists(encodings_dir):
if os.path.isdir(encodings_dir):
print(' %s contents: %s' % (encodings_dir,
str(os.listdir(encodings_dir))))
else:
print(' %s exists but is not a directory' % encodings_dir)
else:
print(' %s missing' % encodings_dir)
raise | [
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] | https://github.com/citizenfx/fivem/blob/88276d40cc7baf8285d02754cc5ae42ec7a8563f/vendor/chromium/tools/diagnosis/crbug_1001171.py#L19-L51 | ||
microsoft/checkedc-clang | a173fefde5d7877b7750e7ce96dd08cf18baebf2 | compiler-rt/lib/asan/scripts/asan_symbolize.py | python | AsanSymbolizerPlugIn.process_cmdline_args | (self, pargs) | return True | Hook for handling parsed arguments. Implementations
should not modify `pargs`.
`pargs` - Instance of `argparse.Namespace` containing
parsed command line arguments.
Return `True` if plug-in should be used, otherwise
return `False`. | Hook for handling parsed arguments. Implementations
should not modify `pargs`. | [
"Hook",
"for",
"handling",
"parsed",
"arguments",
".",
"Implementations",
"should",
"not",
"modify",
"pargs",
"."
] | def process_cmdline_args(self, pargs):
"""
Hook for handling parsed arguments. Implementations
should not modify `pargs`.
`pargs` - Instance of `argparse.Namespace` containing
parsed command line arguments.
Return `True` if plug-in should be used, otherwise
return `False`.
"""
return True | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/server/wsgi/wms/ogc/common/tilecalcs.py | python | CalcZoomLevel | (log_extent, total_log_extent, pixel_extent) | return zoom | Calculates zoom level.
We want a zoom level that has enough detail to match the user's request
(i.e., we do our best not to give stretched-out pixels). A bigger zoom ==
more pixels + detail. But, it would be wasteful to use a higher zoom
level than necessary.
Args:
log_extent: map-space width, height.
total_log_extent: total defined map-space extent (size of projection
bounds, in its output coordinates).
pixel_extent: desired width, height of the final pixel image.
Returns:
zoom level with at least as much detail as required. | Calculates zoom level. | [
"Calculates",
"zoom",
"level",
"."
] | def CalcZoomLevel(log_extent, total_log_extent, pixel_extent):
"""Calculates zoom level.
We want a zoom level that has enough detail to match the user's request
(i.e., we do our best not to give stretched-out pixels). A bigger zoom ==
more pixels + detail. But, it would be wasteful to use a higher zoom
level than necessary.
Args:
log_extent: map-space width, height.
total_log_extent: total defined map-space extent (size of projection
bounds, in its output coordinates).
pixel_extent: desired width, height of the final pixel image.
Returns:
zoom level with at least as much detail as required.
"""
utils.Assert(isinstance(log_extent, geom.Pair))
utils.Assert(isinstance(total_log_extent, geom.Pair))
utils.Assert(isinstance(pixel_extent, geom.Pair))
# Simple, component-wise division.
fraction_of_total = log_extent / total_log_extent
total_pixel_extent_needed = pixel_extent / fraction_of_total
logger.debug("Pixel extent needed %s", str(total_pixel_extent_needed))
# We want to round the zoom level up; ie, have /at least/ 1 tile pixel
# per requested pixel.
# 256 x 2^zoom >= totalpixelextent => zoom = log_2(totalpixelextent / 256)
x_zoom = int(math.log(math.ceil(
total_pixel_extent_needed.x / float(_TILE_PIXEL_SIZE)), 2))
y_zoom = int(math.log(math.ceil(
total_pixel_extent_needed.y / float(_TILE_PIXEL_SIZE)), 2))
logger.debug("Zoom:x,y %d, %d", x_zoom, y_zoom)
zoom = max(x_zoom, y_zoom)
if _MAX_ZOOM < zoom:
logger.warning("WHOA; wild zoom (%d - should be max %d), "
"alert Google. Limiting to %d.",
zoom, _MAX_ZOOM, _MAX_ZOOM)
zoom = _MAX_ZOOM
return zoom | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/os.py | python | renames | (old, new) | renames(old, new)
Super-rename; create directories as necessary and delete any left
empty. Works like rename, except creation of any intermediate
directories needed to make the new pathname good is attempted
first. After the rename, directories corresponding to rightmost
path segments of the old name will be pruned way until either the
whole path is consumed or a nonempty directory is found.
Note: this function can fail with the new directory structure made
if you lack permissions needed to unlink the leaf directory or
file. | renames(old, new) | [
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"""renames(old, new)
Super-rename; create directories as necessary and delete any left
empty. Works like rename, except creation of any intermediate
directories needed to make the new pathname good is attempted
first. After the rename, directories corresponding to rightmost
path segments of the old name will be pruned way until either the
whole path is consumed or a nonempty directory is found.
Note: this function can fail with the new directory structure made
if you lack permissions needed to unlink the leaf directory or
file.
"""
head, tail = path.split(new)
if head and tail and not path.exists(head):
makedirs(head)
rename(old, new)
head, tail = path.split(old)
if head and tail:
try:
removedirs(head)
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mapnik/mapnik | f3da900c355e1d15059c4a91b00203dcc9d9f0ef | scons/scons-local-4.1.0/SCons/SConf.py | python | SConfBase.TryBuild | (self, builder, text=None, extension="") | return result | Low level TryBuild implementation. Normally you don't need to
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"""Low level TryBuild implementation. Normally you don't need to
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"""
global _ac_build_counter
# Make sure we have a PSPAWN value, and save the current
# SPAWN value.
try:
self.pspawn = self.env['PSPAWN']
except KeyError:
raise SCons.Errors.UserError('Missing PSPAWN construction variable.')
try:
save_spawn = self.env['SPAWN']
except KeyError:
raise SCons.Errors.UserError('Missing SPAWN construction variable.')
nodesToBeBuilt = []
sourcetext = self.env.Value(text)
self._set_conftest_node(sourcetext)
f = "conftest"
if text is not None:
textSig = SCons.Util.MD5signature(sourcetext)
textSigCounter = str(_ac_build_counter[textSig])
_ac_build_counter[textSig] += 1
f = "_".join([f, textSig, textSigCounter])
textFile = self.confdir.File(f + extension)
self._set_conftest_node(sourcetext)
textFileNode = self.env.SConfSourceBuilder(target=textFile,
source=sourcetext)
nodesToBeBuilt.extend(textFileNode)
source = textFile
target = textFile.File(f + "SConfActionsContentDummyTarget")
self._set_conftest_node(target)
else:
source = None
target = None
action = builder.builder.action.get_contents(target=target, source=[source], env=self.env)
actionsig = SCons.Util.MD5signature(action)
f = "_".join([f, actionsig])
pref = self.env.subst( builder.builder.prefix )
suff = self.env.subst( builder.builder.suffix )
target = self.confdir.File(pref + f + suff)
try:
# Slide our wrapper into the construction environment as
# the SPAWN function.
self.env['SPAWN'] = self.pspawn_wrapper
nodes = builder(target = target, source = source)
if not SCons.Util.is_List(nodes):
nodes = [nodes]
nodesToBeBuilt.extend(nodes)
result = self.BuildNodes(nodesToBeBuilt)
finally:
self.env['SPAWN'] = save_spawn
if result:
self.lastTarget = nodes[0]
else:
self.lastTarget = None
return result | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/traitlets/py3/traitlets/traitlets.py | python | TraitType.from_string | (self, s) | return s | Get a value from a config string
such as an environment variable or CLI arguments.
Traits can override this method to define their own
parsing of config strings.
.. seealso:: item_from_string
.. versionadded:: 5.0 | Get a value from a config string | [
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] | def from_string(self, s):
"""Get a value from a config string
such as an environment variable or CLI arguments.
Traits can override this method to define their own
parsing of config strings.
.. seealso:: item_from_string
.. versionadded:: 5.0
"""
if self.allow_none and s == 'None':
return None
return s | [
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hszhao/PSPNet | cf7e5a99ba37e46118026e96be5821a9bc63bde0 | scripts/cpp_lint.py | python | CleansedLines.NumLines | (self) | return self.num_lines | Returns the number of lines represented. | Returns the number of lines represented. | [
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Z3Prover/z3 | d745d03afdfdf638d66093e2bfbacaf87187f35b | src/api/python/z3/z3.py | python | SeqSort | (s) | return SeqSortRef(Z3_mk_seq_sort(s.ctx_ref(), s.ast), s.ctx) | Create a sequence sort over elements provided in the argument
>>> s = SeqSort(IntSort())
>>> s == Unit(IntVal(1)).sort()
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>>> s = SeqSort(IntSort())
>>> s == Unit(IntVal(1)).sort()
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>>> s = SeqSort(IntSort())
>>> s == Unit(IntVal(1)).sort()
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return SeqSortRef(Z3_mk_seq_sort(s.ctx_ref(), s.ast), s.ctx) | [
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okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_vendor/html5lib/html5parser.py | python | parse | (doc, treebuilder="etree", namespaceHTMLElements=True, **kwargs) | return p.parse(doc, **kwargs) | Parse an HTML document as a string or file-like object into a tree
:arg doc: the document to parse as a string or file-like object
:arg treebuilder: the treebuilder to use when parsing
:arg namespaceHTMLElements: whether or not to namespace HTML elements
:returns: parsed tree
Example:
>>> from html5lib.html5parser import parse
>>> parse('<html><body><p>This is a doc</p></body></html>')
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:arg doc: the document to parse as a string or file-like object
:arg treebuilder: the treebuilder to use when parsing
:arg namespaceHTMLElements: whether or not to namespace HTML elements
:returns: parsed tree
Example:
>>> from html5lib.html5parser import parse
>>> parse('<html><body><p>This is a doc</p></body></html>')
<Element u'{http://www.w3.org/1999/xhtml}html' at 0x7feac4909db0>
"""
tb = treebuilders.getTreeBuilder(treebuilder)
p = HTMLParser(tb, namespaceHTMLElements=namespaceHTMLElements)
return p.parse(doc, **kwargs) | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/_op_impl/tbe/strided_read.py | python | _strided_read_tbe | () | return | StridedRead TBE register | StridedRead TBE register | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBAddress.GetLineEntry | (self) | return _lldb.SBAddress_GetLineEntry(self) | GetLineEntry(self) -> SBLineEntry | GetLineEntry(self) -> SBLineEntry | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/layers/python/layers/feature_column.py | python | _BucketizedColumn.key | (self) | return "{}".format(self) | Returns a string which will be used as a key when we do sorting. | Returns a string which will be used as a key when we do sorting. | [
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DGA-MI-SSI/YaCo | 9b85e6ca1809114c4df1382c11255f7e38408912 | deps/flatbuffers-1.8.0/python/flatbuffers/table.py | python | Table.GetVOffsetTSlot | (self, slot, d) | return off | GetVOffsetTSlot retrieves the VOffsetT that the given vtable location
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/distlib/util.py | python | EventMixin.remove | (self, event, subscriber) | Remove a subscriber for an event.
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] | https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/pip/_vendor/distlib/util.py#L845-L855 | ||
ucbrise/clipper | 9f25e3fc7f8edc891615e81c5b80d3d8aed72608 | clipper_admin/clipper_admin/docker/docker_metric_utils.py | python | setup_metric_config | (query_frontend_metric_name, prom_config_path,
CLIPPER_INTERNAL_METRIC_PORT) | Write to file prometheus.yml after frontend-metric is setup.
:param query_frontend_metric_name: Corresponding image name
:param prom_config_path: Prometheus config file to write in
:param CLIPPER_INTERNAL_METRIC_PORT: Default port.
:return: None | Write to file prometheus.yml after frontend-metric is setup.
:param query_frontend_metric_name: Corresponding image name
:param prom_config_path: Prometheus config file to write in
:param CLIPPER_INTERNAL_METRIC_PORT: Default port.
:return: None | [
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] | def setup_metric_config(query_frontend_metric_name, prom_config_path,
CLIPPER_INTERNAL_METRIC_PORT):
"""
Write to file prometheus.yml after frontend-metric is setup.
:param query_frontend_metric_name: Corresponding image name
:param prom_config_path: Prometheus config file to write in
:param CLIPPER_INTERNAL_METRIC_PORT: Default port.
:return: None
"""
with open(prom_config_path, 'w') as f:
prom_config = _get_prometheus_base_config()
prom_config_query_frontend = {
'job_name':
'query',
'static_configs': [{
'targets': [
'{name}:{port}'.format(
name=query_frontend_metric_name,
port=CLIPPER_INTERNAL_METRIC_PORT)
]
}]
}
prom_config['scrape_configs'].append(prom_config_query_frontend)
yaml.dump(prom_config, f) | [
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] | https://github.com/ucbrise/clipper/blob/9f25e3fc7f8edc891615e81c5b80d3d8aed72608/clipper_admin/clipper_admin/docker/docker_metric_utils.py#L48-L73 |
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