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eventql/eventql
7ca0dbb2e683b525620ea30dc40540a22d5eb227
deps/3rdparty/spidermonkey/mozjs/media/webrtc/trunk/tools/gyp/pylib/gyp/generator/ninja.py
python
OpenOutput
(path, mode='w')
return open(path, mode)
Open |path| for writing, creating directories if necessary.
Open |path| for writing, creating directories if necessary.
[ "Open", "|path|", "for", "writing", "creating", "directories", "if", "necessary", "." ]
def OpenOutput(path, mode='w'): """Open |path| for writing, creating directories if necessary.""" try: os.makedirs(os.path.dirname(path)) except OSError: pass return open(path, mode)
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https://github.com/eventql/eventql/blob/7ca0dbb2e683b525620ea30dc40540a22d5eb227/deps/3rdparty/spidermonkey/mozjs/media/webrtc/trunk/tools/gyp/pylib/gyp/generator/ninja.py#L1295-L1301
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/dateutil/dateutil/utils.py
python
today
(tzinfo=None)
return datetime.combine(dt.date(), time(0, tzinfo=tzinfo))
Returns a :py:class:`datetime` representing the current day at midnight :param tzinfo: The time zone to attach (also used to determine the current day). :return: A :py:class:`datetime.datetime` object representing the current day at midnight.
Returns a :py:class:`datetime` representing the current day at midnight
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def today(tzinfo=None): """ Returns a :py:class:`datetime` representing the current day at midnight :param tzinfo: The time zone to attach (also used to determine the current day). :return: A :py:class:`datetime.datetime` object representing the current day at midnight. """ dt = datetime.now(tzinfo) return datetime.combine(dt.date(), time(0, tzinfo=tzinfo))
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/dateutil/dateutil/utils.py#L13-L26
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
third_party/re2/lib/codereview/codereview.py
python
change
(ui, repo, *pats, **opts)
return
create, edit or delete a change list Create, edit or delete a change list. A change list is a group of files to be reviewed and submitted together, plus a textual description of the change. Change lists are referred to by simple alphanumeric names. Changes must be reviewed before they can be submitted. In the absence of options, the change command opens the change list for editing in the default editor. Deleting a change with the -d or -D flag does not affect the contents of the files listed in that change. To revert the files listed in a change, use hg revert @123456 before running hg change -d 123456.
create, edit or delete a change list
[ "create", "edit", "or", "delete", "a", "change", "list" ]
def change(ui, repo, *pats, **opts): """create, edit or delete a change list Create, edit or delete a change list. A change list is a group of files to be reviewed and submitted together, plus a textual description of the change. Change lists are referred to by simple alphanumeric names. Changes must be reviewed before they can be submitted. In the absence of options, the change command opens the change list for editing in the default editor. Deleting a change with the -d or -D flag does not affect the contents of the files listed in that change. To revert the files listed in a change, use hg revert @123456 before running hg change -d 123456. """ if codereview_disabled: return codereview_disabled dirty = {} if len(pats) > 0 and GoodCLName(pats[0]): name = pats[0] if len(pats) != 1: return "cannot specify CL name and file patterns" pats = pats[1:] cl, err = LoadCL(ui, repo, name, web=True) if err != '': return err if not cl.local and (opts["stdin"] or not opts["stdout"]): return "cannot change non-local CL " + name else: name = "new" cl = CL("new") if repo[None].branch() != "default": return "cannot create CL outside default branch; switch with 'hg update default'" dirty[cl] = True files = ChangedFiles(ui, repo, pats, taken=Taken(ui, repo)) if opts["delete"] or opts["deletelocal"]: if opts["delete"] and opts["deletelocal"]: return "cannot use -d and -D together" flag = "-d" if opts["deletelocal"]: flag = "-D" if name == "new": return "cannot use "+flag+" with file patterns" if opts["stdin"] or opts["stdout"]: return "cannot use "+flag+" with -i or -o" if not cl.local: return "cannot change non-local CL " + name if opts["delete"]: if cl.copied_from: return "original author must delete CL; hg change -D will remove locally" PostMessage(ui, cl.name, "*** Abandoned ***", send_mail=cl.mailed) EditDesc(cl.name, closed=True, private=cl.private) cl.Delete(ui, repo) return if opts["stdin"]: s = sys.stdin.read() clx, line, err = ParseCL(s, name) if err != '': return "error parsing change list: line %d: %s" % (line, err) if clx.desc is not None: cl.desc = clx.desc; dirty[cl] = True if clx.reviewer is not None: cl.reviewer = clx.reviewer dirty[cl] = True if clx.cc is not None: cl.cc = clx.cc dirty[cl] = True if clx.files is not None: cl.files = clx.files dirty[cl] = True if clx.private != cl.private: cl.private = clx.private dirty[cl] = True if not opts["stdin"] and not opts["stdout"]: if name == "new": cl.files = files err = EditCL(ui, repo, cl) if err != "": return err dirty[cl] = True for d, _ in dirty.items(): name = d.name d.Flush(ui, repo) if name == "new": d.Upload(ui, repo, quiet=True) if opts["stdout"]: ui.write(cl.EditorText()) elif opts["pending"]: ui.write(cl.PendingText()) elif name == "new": if ui.quiet: ui.write(cl.name) else: ui.write("CL created: " + cl.url + "\n") return
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/re2/lib/codereview/codereview.py#L1273-L1381
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/importlib/_bootstrap_external.py
python
spec_from_file_location
(name, location=None, *, loader=None, submodule_search_locations=_POPULATE)
return spec
Return a module spec based on a file location. To indicate that the module is a package, set submodule_search_locations to a list of directory paths. An empty list is sufficient, though its not otherwise useful to the import system. The loader must take a spec as its only __init__() arg.
Return a module spec based on a file location.
[ "Return", "a", "module", "spec", "based", "on", "a", "file", "location", "." ]
def spec_from_file_location(name, location=None, *, loader=None, submodule_search_locations=_POPULATE): """Return a module spec based on a file location. To indicate that the module is a package, set submodule_search_locations to a list of directory paths. An empty list is sufficient, though its not otherwise useful to the import system. The loader must take a spec as its only __init__() arg. """ if location is None: # The caller may simply want a partially populated location- # oriented spec. So we set the location to a bogus value and # fill in as much as we can. location = '<unknown>' if hasattr(loader, 'get_filename'): # ExecutionLoader try: location = loader.get_filename(name) except ImportError: pass else: location = _os.fspath(location) # If the location is on the filesystem, but doesn't actually exist, # we could return None here, indicating that the location is not # valid. However, we don't have a good way of testing since an # indirect location (e.g. a zip file or URL) will look like a # non-existent file relative to the filesystem. spec = _bootstrap.ModuleSpec(name, loader, origin=location) spec._set_fileattr = True # Pick a loader if one wasn't provided. if loader is None: for loader_class, suffixes in _get_supported_file_loaders(): if location.endswith(tuple(suffixes)): loader = loader_class(name, location) spec.loader = loader break else: return None # Set submodule_search_paths appropriately. if submodule_search_locations is _POPULATE: # Check the loader. if hasattr(loader, 'is_package'): try: is_package = loader.is_package(name) except ImportError: pass else: if is_package: spec.submodule_search_locations = [] else: spec.submodule_search_locations = submodule_search_locations if spec.submodule_search_locations == []: if location: dirname = _path_split(location)[0] spec.submodule_search_locations.append(dirname) return spec
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/importlib/_bootstrap_external.py#L574-L637
verilog-to-routing/vtr-verilog-to-routing
d9719cf7374821156c3cee31d66991cb85578562
vtr_flow/scripts/python_libs/vtr/log_parse.py
python
RangeAbsPassRequirement.abs_threshold
(self)
return self._abs_threshold
Get absolute threshold
Get absolute threshold
[ "Get", "absolute", "threshold" ]
def abs_threshold(self): """Get absolute threshold""" return self._abs_threshold
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https://github.com/verilog-to-routing/vtr-verilog-to-routing/blob/d9719cf7374821156c3cee31d66991cb85578562/vtr_flow/scripts/python_libs/vtr/log_parse.py#L192-L194
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/python/ops/image_ops_impl.py
python
per_image_standardization
(image)
return image
Linearly scales `image` to have zero mean and unit norm. This op computes `(x - mean) / adjusted_stddev`, where `mean` is the average of all values in image, and `adjusted_stddev = max(stddev, 1.0/sqrt(image.NumElements()))`. `stddev` is the standard deviation of all values in `image`. It is capped away from zero to protect against division by 0 when handling uniform images. Args: image: 3-D tensor of shape `[height, width, channels]`. Returns: The standardized image with same shape as `image`. Raises: ValueError: if the shape of 'image' is incompatible with this function.
Linearly scales `image` to have zero mean and unit norm.
[ "Linearly", "scales", "image", "to", "have", "zero", "mean", "and", "unit", "norm", "." ]
def per_image_standardization(image): """Linearly scales `image` to have zero mean and unit norm. This op computes `(x - mean) / adjusted_stddev`, where `mean` is the average of all values in image, and `adjusted_stddev = max(stddev, 1.0/sqrt(image.NumElements()))`. `stddev` is the standard deviation of all values in `image`. It is capped away from zero to protect against division by 0 when handling uniform images. Args: image: 3-D tensor of shape `[height, width, channels]`. Returns: The standardized image with same shape as `image`. Raises: ValueError: if the shape of 'image' is incompatible with this function. """ image = ops.convert_to_tensor(image, name='image') image = control_flow_ops.with_dependencies( _Check3DImage(image, require_static=False), image) num_pixels = math_ops.reduce_prod(array_ops.shape(image)) image = math_ops.cast(image, dtype=dtypes.float32) image_mean = math_ops.reduce_mean(image) variance = (math_ops.reduce_mean(math_ops.square(image)) - math_ops.square(image_mean)) variance = gen_nn_ops.relu(variance) stddev = math_ops.sqrt(variance) # Apply a minimum normalization that protects us against uniform images. min_stddev = math_ops.rsqrt(math_ops.cast(num_pixels, dtypes.float32)) pixel_value_scale = math_ops.maximum(stddev, min_stddev) pixel_value_offset = image_mean image = math_ops.subtract(image, pixel_value_offset) image = math_ops.div(image, pixel_value_scale) return image
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/ops/image_ops_impl.py#L793-L832
eventql/eventql
7ca0dbb2e683b525620ea30dc40540a22d5eb227
deps/3rdparty/spidermonkey/mozjs/python/configobj/configobj.py
python
Section.itervalues
(self)
return iter(self.values())
D.itervalues() -> an iterator over the values of D
D.itervalues() -> an iterator over the values of D
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def itervalues(self): """D.itervalues() -> an iterator over the values of D""" return iter(self.values())
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https://github.com/eventql/eventql/blob/7ca0dbb2e683b525620ea30dc40540a22d5eb227/deps/3rdparty/spidermonkey/mozjs/python/configobj/configobj.py#L749-L751
rapidsai/cudf
d5b2448fc69f17509304d594f029d0df56984962
python/cudf/cudf/api/extensions/accessor.py
python
register_dataframe_accessor
(name)
return _register_accessor(name, cudf.DataFrame)
{docstring}
{docstring}
[ "{", "docstring", "}" ]
def register_dataframe_accessor(name): """{docstring}""" return _register_accessor(name, cudf.DataFrame)
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https://github.com/rapidsai/cudf/blob/d5b2448fc69f17509304d594f029d0df56984962/python/cudf/cudf/api/extensions/accessor.py#L147-L149
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_controls.py
python
FontPickerEvent.__init__
(self, *args, **kwargs)
__init__(self, Object generator, int id, Font f) -> FontPickerEvent
__init__(self, Object generator, int id, Font f) -> FontPickerEvent
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def __init__(self, *args, **kwargs): """__init__(self, Object generator, int id, Font f) -> FontPickerEvent""" _controls_.FontPickerEvent_swiginit(self,_controls_.new_FontPickerEvent(*args, **kwargs))
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_controls.py#L7281-L7283
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/numbers.py
python
Real.__floordiv__
(self, other)
self // other: The floor() of self/other.
self // other: The floor() of self/other.
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def __floordiv__(self, other): """self // other: The floor() of self/other.""" raise NotImplementedError
[ "def", "__floordiv__", "(", "self", ",", "other", ")", ":", "raise", "NotImplementedError" ]
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/numbers.py#L217-L219
s9xie/DSN
065e49898d239f5c96be558616b2556eabc50351
scripts/cpp_lint.py
python
CheckForMultilineCommentsAndStrings
(filename, clean_lines, linenum, error)
Logs an error if we see /* ... */ or "..." that extend past one line. /* ... */ comments are legit inside macros, for one line. Otherwise, we prefer // comments, so it's ok to warn about the other. Likewise, it's ok for strings to extend across multiple lines, as long as a line continuation character (backslash) terminates each line. Although not currently prohibited by the C++ style guide, it's ugly and unnecessary. We don't do well with either in this lint program, so we warn about both. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. error: The function to call with any errors found.
Logs an error if we see /* ... */ or "..." that extend past one line.
[ "Logs", "an", "error", "if", "we", "see", "/", "*", "...", "*", "/", "or", "...", "that", "extend", "past", "one", "line", "." ]
def CheckForMultilineCommentsAndStrings(filename, clean_lines, linenum, error): """Logs an error if we see /* ... */ or "..." that extend past one line. /* ... */ comments are legit inside macros, for one line. Otherwise, we prefer // comments, so it's ok to warn about the other. Likewise, it's ok for strings to extend across multiple lines, as long as a line continuation character (backslash) terminates each line. Although not currently prohibited by the C++ style guide, it's ugly and unnecessary. We don't do well with either in this lint program, so we warn about both. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. error: The function to call with any errors found. """ line = clean_lines.elided[linenum] # Remove all \\ (escaped backslashes) from the line. They are OK, and the # second (escaped) slash may trigger later \" detection erroneously. line = line.replace('\\\\', '') if line.count('/*') > line.count('*/'): error(filename, linenum, 'readability/multiline_comment', 5, 'Complex multi-line /*...*/-style comment found. ' 'Lint may give bogus warnings. ' 'Consider replacing these with //-style comments, ' 'with #if 0...#endif, ' 'or with more clearly structured multi-line comments.') if (line.count('"') - line.count('\\"')) % 2: error(filename, linenum, 'readability/multiline_string', 5, 'Multi-line string ("...") found. This lint script doesn\'t ' 'do well with such strings, and may give bogus warnings. ' 'Use C++11 raw strings or concatenation instead.')
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https://github.com/s9xie/DSN/blob/065e49898d239f5c96be558616b2556eabc50351/scripts/cpp_lint.py#L1522-L1557
apache/incubator-mxnet
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
python/mxnet/symbol/random.py
python
_random_helper
(random, sampler, params, shape, dtype, kwargs)
Helper function for random generators.
Helper function for random generators.
[ "Helper", "function", "for", "random", "generators", "." ]
def _random_helper(random, sampler, params, shape, dtype, kwargs): """Helper function for random generators.""" if isinstance(params[0], Symbol): for i in params[1:]: assert isinstance(i, Symbol), \ "Distribution parameters must all have the same type, but got " \ "both %s and %s."%(type(params[0]), type(i)) return sampler(*params, shape=shape, dtype=dtype, **kwargs) elif isinstance(params[0], numeric_types): for i in params[1:]: assert isinstance(i, numeric_types), \ "Distribution parameters must all have the same type, but got " \ "both %s and %s."%(type(params[0]), type(i)) return random(*params, shape=shape, dtype=dtype, **kwargs) raise ValueError("Distribution parameters must be either Symbol or numbers, " "but got %s."%type(params[0]))
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https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/symbol/random.py#L29-L45
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/pydoc.py
python
HTMLDoc.namelink
(self, name, *dicts)
return name
Make a link for an identifier, given name-to-URL mappings.
Make a link for an identifier, given name-to-URL mappings.
[ "Make", "a", "link", "for", "an", "identifier", "given", "name", "-", "to", "-", "URL", "mappings", "." ]
def namelink(self, name, *dicts): """Make a link for an identifier, given name-to-URL mappings.""" for dict in dicts: if name in dict: return '<a href="%s">%s</a>' % (dict[name], name) return name
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/pydoc.py#L526-L531
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/client/timeline.py
python
_TensorTracker.last_unref
(self)
return max(self._unref_times)
Last unreference timestamp of this tensor (long integer).
Last unreference timestamp of this tensor (long integer).
[ "Last", "unreference", "timestamp", "of", "this", "tensor", "(", "long", "integer", ")", "." ]
def last_unref(self): """Last unreference timestamp of this tensor (long integer).""" return max(self._unref_times)
[ "def", "last_unref", "(", "self", ")", ":", "return", "max", "(", "self", ".", "_unref_times", ")" ]
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/client/timeline.py#L325-L327
eventql/eventql
7ca0dbb2e683b525620ea30dc40540a22d5eb227
deps/3rdparty/spidermonkey/mozjs/python/psutil/psutil/__init__.py
python
Process.nice
(self, value=None)
Get or set process niceness (priority).
Get or set process niceness (priority).
[ "Get", "or", "set", "process", "niceness", "(", "priority", ")", "." ]
def nice(self, value=None): """Get or set process niceness (priority).""" if value is None: return self._proc.nice_get() else: if not self.is_running(): raise NoSuchProcess(self.pid, self._name) self._proc.nice_set(value)
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https://github.com/eventql/eventql/blob/7ca0dbb2e683b525620ea30dc40540a22d5eb227/deps/3rdparty/spidermonkey/mozjs/python/psutil/psutil/__init__.py#L583-L590
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/grid.py
python
Grid.EnableCellEditControl
(*args, **kwargs)
return _grid.Grid_EnableCellEditControl(*args, **kwargs)
EnableCellEditControl(self, bool enable=True)
EnableCellEditControl(self, bool enable=True)
[ "EnableCellEditControl", "(", "self", "bool", "enable", "=", "True", ")" ]
def EnableCellEditControl(*args, **kwargs): """EnableCellEditControl(self, bool enable=True)""" return _grid.Grid_EnableCellEditControl(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/grid.py#L1346-L1348
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_windows.py
python
Dialog.DoLayoutAdaptation
(*args, **kwargs)
return _windows_.Dialog_DoLayoutAdaptation(*args, **kwargs)
DoLayoutAdaptation(self) -> bool
DoLayoutAdaptation(self) -> bool
[ "DoLayoutAdaptation", "(", "self", ")", "-", ">", "bool" ]
def DoLayoutAdaptation(*args, **kwargs): """DoLayoutAdaptation(self) -> bool""" return _windows_.Dialog_DoLayoutAdaptation(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_windows.py#L819-L821
llvm/llvm-project
ffa6262cb4e2a335d26416fad39a581b4f98c5f4
clang/bindings/python/clang/cindex.py
python
Type.get_align
(self)
return conf.lib.clang_Type_getAlignOf(self)
Retrieve the alignment of the record.
Retrieve the alignment of the record.
[ "Retrieve", "the", "alignment", "of", "the", "record", "." ]
def get_align(self): """ Retrieve the alignment of the record. """ return conf.lib.clang_Type_getAlignOf(self)
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https://github.com/llvm/llvm-project/blob/ffa6262cb4e2a335d26416fad39a581b4f98c5f4/clang/bindings/python/clang/cindex.py#L2379-L2383
apache/kudu
90895ce76590f10730ad7aac3613b69d89ff5422
build-support/iwyu/fix_includes.py
python
_CalculateReorderSpans
(file_lines)
Fills each input_line's reorder_span field. A 'reorder span' is a range of lines (from file_lines) that only has #includes and forward-declares in it (and maybe blank lines, and comments associated with #includes or forward-declares). In particular, it does not include any "real code" besides #includes and forward-declares: no functions, no static variable assignment, no macro #defines, no nothing. We are willing to reorder #includes and namespaces freely inside a reorder span. Calculating reorder_span is easy: they're just the union of contiguous move-spans (with perhaps blank lines and comments thrown in), because move-spans share the 'no actual code' requirement. There's one exception: if any move-span matches the _BARRIER_INCLUDES regexp, it means that we should consider that move-span to be a 'barrier': nothing should get reordered from one side of that move-span to the other. (This is used for #includes that depend on other #includes being before them to function properly.) We do that by putting them into their own reorder span. For lines of type _INCLUDE_RE or _FORWARD_DECLARE_RE, the reorder span is set to the tuple [start_of_span, end_of_span). All other lines have an arbitrary value for the reorder span. Arguments: file_lines: an array of LineInfo objects with .type and .move_span fields filled in.
Fills each input_line's reorder_span field.
[ "Fills", "each", "input_line", "s", "reorder_span", "field", "." ]
def _CalculateReorderSpans(file_lines): """Fills each input_line's reorder_span field. A 'reorder span' is a range of lines (from file_lines) that only has #includes and forward-declares in it (and maybe blank lines, and comments associated with #includes or forward-declares). In particular, it does not include any "real code" besides #includes and forward-declares: no functions, no static variable assignment, no macro #defines, no nothing. We are willing to reorder #includes and namespaces freely inside a reorder span. Calculating reorder_span is easy: they're just the union of contiguous move-spans (with perhaps blank lines and comments thrown in), because move-spans share the 'no actual code' requirement. There's one exception: if any move-span matches the _BARRIER_INCLUDES regexp, it means that we should consider that move-span to be a 'barrier': nothing should get reordered from one side of that move-span to the other. (This is used for #includes that depend on other #includes being before them to function properly.) We do that by putting them into their own reorder span. For lines of type _INCLUDE_RE or _FORWARD_DECLARE_RE, the reorder span is set to the tuple [start_of_span, end_of_span). All other lines have an arbitrary value for the reorder span. Arguments: file_lines: an array of LineInfo objects with .type and .move_span fields filled in. """ # Happily, move_spans are disjoint. Just make sure they're sorted and unique. move_spans = [s.move_span for s in file_lines if s.move_span is not None] sorted_move_spans = sorted(set(move_spans)) i = 0 while i < len(sorted_move_spans): reorder_span_start = sorted_move_spans[i][0] # If we're a 'nosort' include, we're always in a reorder span of # our own. Otherwise, add in the next move span if we're # connected to it only by blank lines. if not _ContainsBarrierInclude(file_lines, sorted_move_spans[i]): while i < len(sorted_move_spans) - 1: move_span_end = sorted_move_spans[i][1] next_move_span_start = sorted_move_spans[i+1][0] if (_LinesAreAllBlank(file_lines, move_span_end, next_move_span_start) and not _ContainsBarrierInclude(file_lines, sorted_move_spans[i+1])): i += 1 else: break reorder_span_end = sorted_move_spans[i][1] # We'll map every line in the span to the span-extent. for line_number in range(reorder_span_start, reorder_span_end): file_lines[line_number].reorder_span = (reorder_span_start, reorder_span_end) i += 1
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https://github.com/apache/kudu/blob/90895ce76590f10730ad7aac3613b69d89ff5422/build-support/iwyu/fix_includes.py#L910-L966
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py3/scipy/signal/windows/windows.py
python
boxcar
(M, sym=True)
return _truncate(w, needs_trunc)
Return a boxcar or rectangular window. Also known as a rectangular window or Dirichlet window, this is equivalent to no window at all. Parameters ---------- M : int Number of points in the output window. If zero or less, an empty array is returned. sym : bool, optional Whether the window is symmetric. (Has no effect for boxcar.) Returns ------- w : ndarray The window, with the maximum value normalized to 1. Examples -------- Plot the window and its frequency response: >>> from scipy import signal >>> from scipy.fftpack import fft, fftshift >>> import matplotlib.pyplot as plt >>> window = signal.boxcar(51) >>> plt.plot(window) >>> plt.title("Boxcar window") >>> plt.ylabel("Amplitude") >>> plt.xlabel("Sample") >>> plt.figure() >>> A = fft(window, 2048) / (len(window)/2.0) >>> freq = np.linspace(-0.5, 0.5, len(A)) >>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max()))) >>> plt.plot(freq, response) >>> plt.axis([-0.5, 0.5, -120, 0]) >>> plt.title("Frequency response of the boxcar window") >>> plt.ylabel("Normalized magnitude [dB]") >>> plt.xlabel("Normalized frequency [cycles per sample]")
Return a boxcar or rectangular window.
[ "Return", "a", "boxcar", "or", "rectangular", "window", "." ]
def boxcar(M, sym=True): """Return a boxcar or rectangular window. Also known as a rectangular window or Dirichlet window, this is equivalent to no window at all. Parameters ---------- M : int Number of points in the output window. If zero or less, an empty array is returned. sym : bool, optional Whether the window is symmetric. (Has no effect for boxcar.) Returns ------- w : ndarray The window, with the maximum value normalized to 1. Examples -------- Plot the window and its frequency response: >>> from scipy import signal >>> from scipy.fftpack import fft, fftshift >>> import matplotlib.pyplot as plt >>> window = signal.boxcar(51) >>> plt.plot(window) >>> plt.title("Boxcar window") >>> plt.ylabel("Amplitude") >>> plt.xlabel("Sample") >>> plt.figure() >>> A = fft(window, 2048) / (len(window)/2.0) >>> freq = np.linspace(-0.5, 0.5, len(A)) >>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max()))) >>> plt.plot(freq, response) >>> plt.axis([-0.5, 0.5, -120, 0]) >>> plt.title("Frequency response of the boxcar window") >>> plt.ylabel("Normalized magnitude [dB]") >>> plt.xlabel("Normalized frequency [cycles per sample]") """ if _len_guards(M): return np.ones(M) M, needs_trunc = _extend(M, sym) w = np.ones(M, float) return _truncate(w, needs_trunc)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py3/scipy/signal/windows/windows.py#L123-L173
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/ipython/py3/IPython/utils/coloransi.py
python
ColorSchemeTable.set_active_scheme
(self,scheme,case_sensitive=0)
Set the currently active scheme. Names are by default compared in a case-insensitive way, but this can be changed by setting the parameter case_sensitive to true.
Set the currently active scheme.
[ "Set", "the", "currently", "active", "scheme", "." ]
def set_active_scheme(self,scheme,case_sensitive=0): """Set the currently active scheme. Names are by default compared in a case-insensitive way, but this can be changed by setting the parameter case_sensitive to true.""" scheme_names = list(self.keys()) if case_sensitive: valid_schemes = scheme_names scheme_test = scheme else: valid_schemes = [s.lower() for s in scheme_names] scheme_test = scheme.lower() try: scheme_idx = valid_schemes.index(scheme_test) except ValueError: raise ValueError('Unrecognized color scheme: ' + scheme + \ '\nValid schemes: '+str(scheme_names).replace("'', ",'')) else: active = scheme_names[scheme_idx] self.active_scheme_name = active self.active_colors = self[active].colors # Now allow using '' as an index for the current active scheme self[''] = self[active]
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/ipython/py3/IPython/utils/coloransi.py#L164-L187
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/ops/control_flow_ops.py
python
ControlFlowContext.ExitResult
(self, result)
Make a list of tensors available in the outer context.
Make a list of tensors available in the outer context.
[ "Make", "a", "list", "of", "tensors", "available", "in", "the", "outer", "context", "." ]
def ExitResult(self, result): """Make a list of tensors available in the outer context.""" if self._outer_context: def fn(x): self._outer_context.AddName(x.name) return x nest.map_structure(fn, result, expand_composites=True)
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/control_flow_ops.py#L766-L772
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/ops/linalg/linear_operator_algebra.py
python
RegisterCholesky.__call__
(self, cholesky_fn)
return cholesky_fn
Perform the Cholesky registration. Args: cholesky_fn: The function to use for the Cholesky. Returns: cholesky_fn Raises: TypeError: if cholesky_fn is not a callable. ValueError: if a Cholesky function has already been registered for the given argument classes.
Perform the Cholesky registration.
[ "Perform", "the", "Cholesky", "registration", "." ]
def __call__(self, cholesky_fn): """Perform the Cholesky registration. Args: cholesky_fn: The function to use for the Cholesky. Returns: cholesky_fn Raises: TypeError: if cholesky_fn is not a callable. ValueError: if a Cholesky function has already been registered for the given argument classes. """ if not callable(cholesky_fn): raise TypeError( "cholesky_fn must be callable, received: {}".format(cholesky_fn)) if self._key in _CHOLESKY_DECOMPS: raise ValueError("Cholesky({}) has already been registered to: {}".format( self._key[0].__name__, _CHOLESKY_DECOMPS[self._key])) _CHOLESKY_DECOMPS[self._key] = cholesky_fn return cholesky_fn
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/linalg/linear_operator_algebra.py#L251-L272
macchina-io/macchina.io
ef24ba0e18379c3dd48fb84e6dbf991101cb8db0
platform/JS/V8/tools/gyp/pylib/gyp/generator/ninja.py
python
ComputeOutputDir
(params)
return os.path.normpath(os.path.join(generator_dir, output_dir))
Returns the path from the toplevel_dir to the build output directory.
Returns the path from the toplevel_dir to the build output directory.
[ "Returns", "the", "path", "from", "the", "toplevel_dir", "to", "the", "build", "output", "directory", "." ]
def ComputeOutputDir(params): """Returns the path from the toplevel_dir to the build output directory.""" # generator_dir: relative path from pwd to where make puts build files. # Makes migrating from make to ninja easier, ninja doesn't put anything here. generator_dir = os.path.relpath(params['options'].generator_output or '.') # output_dir: relative path from generator_dir to the build directory. output_dir = params.get('generator_flags', {}).get('output_dir', 'out') # Relative path from source root to our output files. e.g. "out" return os.path.normpath(os.path.join(generator_dir, output_dir))
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https://github.com/macchina-io/macchina.io/blob/ef24ba0e18379c3dd48fb84e6dbf991101cb8db0/platform/JS/V8/tools/gyp/pylib/gyp/generator/ninja.py#L1704-L1714
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/compiler/pyassem.py
python
PyFlowGraph.flattenGraph
(self)
Arrange the blocks in order and resolve jumps
Arrange the blocks in order and resolve jumps
[ "Arrange", "the", "blocks", "in", "order", "and", "resolve", "jumps" ]
def flattenGraph(self): """Arrange the blocks in order and resolve jumps""" assert self.stage == RAW self.insts = insts = [] pc = 0 begin = {} end = {} for b in self.getBlocksInOrder(): begin[b] = pc for inst in b.getInstructions(): insts.append(inst) if len(inst) == 1: pc = pc + 1 elif inst[0] != "SET_LINENO": # arg takes 2 bytes pc = pc + 3 end[b] = pc pc = 0 for i in range(len(insts)): inst = insts[i] if len(inst) == 1: pc = pc + 1 elif inst[0] != "SET_LINENO": pc = pc + 3 opname = inst[0] if self.hasjrel.has_elt(opname): oparg = inst[1] offset = begin[oparg] - pc insts[i] = opname, offset elif self.hasjabs.has_elt(opname): insts[i] = opname, begin[inst[1]] self.stage = FLAT
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/compiler/pyassem.py#L424-L455
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pandas/py2/pandas/core/arrays/datetimelike.py
python
DatetimeLikeArrayMixin._box_values
(self, values)
return lib.map_infer(values, self._box_func)
apply box func to passed values
apply box func to passed values
[ "apply", "box", "func", "to", "passed", "values" ]
def _box_values(self, values): """ apply box func to passed values """ return lib.map_infer(values, self._box_func)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py2/pandas/core/arrays/datetimelike.py#L342-L346
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/connection.py
python
HTTPConnection._new_conn
(self)
return conn
Establish a socket connection and set nodelay settings on it. :return: New socket connection.
Establish a socket connection and set nodelay settings on it.
[ "Establish", "a", "socket", "connection", "and", "set", "nodelay", "settings", "on", "it", "." ]
def _new_conn(self): """ Establish a socket connection and set nodelay settings on it. :return: New socket connection. """ extra_kw = {} if self.source_address: extra_kw['source_address'] = self.source_address if self.socket_options: extra_kw['socket_options'] = self.socket_options try: conn = connection.create_connection( (self.host, self.port), self.timeout, **extra_kw) except SocketTimeout as e: raise ConnectTimeoutError( self, "Connection to %s timed out. (connect timeout=%s)" % (self.host, self.timeout)) except SocketError as e: raise NewConnectionError( self, "Failed to establish a new connection: %s" % e) return conn
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/connection.py#L127-L152
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/datamodel/packer.py
python
ArgPacker.from_arguments
(self, builder, args)
return values
Unflatten all argument values
Unflatten all argument values
[ "Unflatten", "all", "argument", "values" ]
def from_arguments(self, builder, args): """Unflatten all argument values """ valtree = self._unflattener.unflatten(args) values = [dm.from_argument(builder, val) for dm, val in zip(self._dm_args, valtree) ] return values
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/datamodel/packer.py#L106-L115
mickem/nscp
79f89fdbb6da63f91bc9dedb7aea202fe938f237
scripts/python/lib/google/protobuf/internal/containers.py
python
RepeatedScalarFieldContainer.__delitem__
(self, key)
Deletes the item at the specified position.
Deletes the item at the specified position.
[ "Deletes", "the", "item", "at", "the", "specified", "position", "." ]
def __delitem__(self, key): """Deletes the item at the specified position.""" del self._values[key] self._message_listener.Modified()
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https://github.com/mickem/nscp/blob/79f89fdbb6da63f91bc9dedb7aea202fe938f237/scripts/python/lib/google/protobuf/internal/containers.py#L161-L164
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/jsonschema/exceptions.py
python
ErrorTree.__setitem__
(self, index, value)
Add an error to the tree at the given ``index``.
Add an error to the tree at the given ``index``.
[ "Add", "an", "error", "to", "the", "tree", "at", "the", "given", "index", "." ]
def __setitem__(self, index, value): """ Add an error to the tree at the given ``index``. """ self._contents[index] = value
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/jsonschema/exceptions.py#L271-L275
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/calendar.py
python
GenericCalendarCtrl.EnableYearChange
(*args, **kwargs)
return _calendar.GenericCalendarCtrl_EnableYearChange(*args, **kwargs)
EnableYearChange(self, bool enable=True) This function should be used instead of changing CAL_NO_YEAR_CHANGE style bit directly. It allows or disallows the user to change the year interactively.
EnableYearChange(self, bool enable=True)
[ "EnableYearChange", "(", "self", "bool", "enable", "=", "True", ")" ]
def EnableYearChange(*args, **kwargs): """ EnableYearChange(self, bool enable=True) This function should be used instead of changing CAL_NO_YEAR_CHANGE style bit directly. It allows or disallows the user to change the year interactively. """ return _calendar.GenericCalendarCtrl_EnableYearChange(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/calendar.py#L547-L555
mongodb/mongo
d8ff665343ad29cf286ee2cf4a1960d29371937b
src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/clangxx.py
python
generate
(env)
Add Builders and construction variables for clang++ to an Environment.
Add Builders and construction variables for clang++ to an Environment.
[ "Add", "Builders", "and", "construction", "variables", "for", "clang", "++", "to", "an", "Environment", "." ]
def generate(env): """Add Builders and construction variables for clang++ to an Environment.""" static_obj, shared_obj = SCons.Tool.createObjBuilders(env) SCons.Tool.cxx.generate(env) env['CXX'] = env.Detect(compilers) or 'clang++' # platform specific settings if env['PLATFORM'] == 'aix': env['SHCXXFLAGS'] = SCons.Util.CLVar('$CXXFLAGS -mminimal-toc') env['STATIC_AND_SHARED_OBJECTS_ARE_THE_SAME'] = 1 env['SHOBJSUFFIX'] = '$OBJSUFFIX' elif env['PLATFORM'] == 'hpux': env['SHOBJSUFFIX'] = '.pic.o' elif env['PLATFORM'] == 'sunos': env['SHOBJSUFFIX'] = '.pic.o' elif env['PLATFORM'] == 'win32': # Ensure that we have a proper path for clang++ clangxx = SCons.Tool.find_program_path(env, compilers[0], default_paths=get_clang_install_dirs(env['PLATFORM'])) if clangxx: clangxx_bin_dir = os.path.dirname(clangxx) env.AppendENVPath('PATH', clangxx_bin_dir) # determine compiler version if env['CXX']: pipe = SCons.Action._subproc(env, [env['CXX'], '--version'], stdin='devnull', stderr='devnull', stdout=subprocess.PIPE) if pipe.wait() != 0: return # clang -dumpversion is of no use with pipe.stdout: line = pipe.stdout.readline() if sys.version_info[0] > 2: line = line.decode() match = re.search(r'clang +version +([0-9]+(?:\.[0-9]+)+)', line) if match: env['CXXVERSION'] = match.group(1)
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https://github.com/mongodb/mongo/blob/d8ff665343ad29cf286ee2cf4a1960d29371937b/src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/clangxx.py#L54-L94
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_windows.py
python
Dialog.CanDoLayoutAdaptation
(*args, **kwargs)
return _windows_.Dialog_CanDoLayoutAdaptation(*args, **kwargs)
CanDoLayoutAdaptation(self) -> bool
CanDoLayoutAdaptation(self) -> bool
[ "CanDoLayoutAdaptation", "(", "self", ")", "-", ">", "bool" ]
def CanDoLayoutAdaptation(*args, **kwargs): """CanDoLayoutAdaptation(self) -> bool""" return _windows_.Dialog_CanDoLayoutAdaptation(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_windows.py#L823-L825
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/pickletools.py
python
dis
(pickle, out=None, memo=None, indentlevel=4)
Produce a symbolic disassembly of a pickle. 'pickle' is a file-like object, or string, containing a (at least one) pickle. The pickle is disassembled from the current position, through the first STOP opcode encountered. Optional arg 'out' is a file-like object to which the disassembly is printed. It defaults to sys.stdout. Optional arg 'memo' is a Python dict, used as the pickle's memo. It may be mutated by dis(), if the pickle contains PUT or BINPUT opcodes. Passing the same memo object to another dis() call then allows disassembly to proceed across multiple pickles that were all created by the same pickler with the same memo. Ordinarily you don't need to worry about this. Optional arg indentlevel is the number of blanks by which to indent a new MARK level. It defaults to 4. In addition to printing the disassembly, some sanity checks are made: + All embedded opcode arguments "make sense". + Explicit and implicit pop operations have enough items on the stack. + When an opcode implicitly refers to a markobject, a markobject is actually on the stack. + A memo entry isn't referenced before it's defined. + The markobject isn't stored in the memo. + A memo entry isn't redefined.
Produce a symbolic disassembly of a pickle.
[ "Produce", "a", "symbolic", "disassembly", "of", "a", "pickle", "." ]
def dis(pickle, out=None, memo=None, indentlevel=4): """Produce a symbolic disassembly of a pickle. 'pickle' is a file-like object, or string, containing a (at least one) pickle. The pickle is disassembled from the current position, through the first STOP opcode encountered. Optional arg 'out' is a file-like object to which the disassembly is printed. It defaults to sys.stdout. Optional arg 'memo' is a Python dict, used as the pickle's memo. It may be mutated by dis(), if the pickle contains PUT or BINPUT opcodes. Passing the same memo object to another dis() call then allows disassembly to proceed across multiple pickles that were all created by the same pickler with the same memo. Ordinarily you don't need to worry about this. Optional arg indentlevel is the number of blanks by which to indent a new MARK level. It defaults to 4. In addition to printing the disassembly, some sanity checks are made: + All embedded opcode arguments "make sense". + Explicit and implicit pop operations have enough items on the stack. + When an opcode implicitly refers to a markobject, a markobject is actually on the stack. + A memo entry isn't referenced before it's defined. + The markobject isn't stored in the memo. + A memo entry isn't redefined. """ # Most of the hair here is for sanity checks, but most of it is needed # anyway to detect when a protocol 0 POP takes a MARK off the stack # (which in turn is needed to indent MARK blocks correctly). stack = [] # crude emulation of unpickler stack if memo is None: memo = {} # crude emulation of unpickler memo maxproto = -1 # max protocol number seen markstack = [] # bytecode positions of MARK opcodes indentchunk = ' ' * indentlevel errormsg = None for opcode, arg, pos in genops(pickle): if pos is not None: print >> out, "%5d:" % pos, line = "%-4s %s%s" % (repr(opcode.code)[1:-1], indentchunk * len(markstack), opcode.name) maxproto = max(maxproto, opcode.proto) before = opcode.stack_before # don't mutate after = opcode.stack_after # don't mutate numtopop = len(before) # See whether a MARK should be popped. markmsg = None if markobject in before or (opcode.name == "POP" and stack and stack[-1] is markobject): assert markobject not in after if __debug__: if markobject in before: assert before[-1] is stackslice if markstack: markpos = markstack.pop() if markpos is None: markmsg = "(MARK at unknown opcode offset)" else: markmsg = "(MARK at %d)" % markpos # Pop everything at and after the topmost markobject. while stack[-1] is not markobject: stack.pop() stack.pop() # Stop later code from popping too much. try: numtopop = before.index(markobject) except ValueError: assert opcode.name == "POP" numtopop = 0 else: errormsg = markmsg = "no MARK exists on stack" # Check for correct memo usage. if opcode.name in ("PUT", "BINPUT", "LONG_BINPUT"): assert arg is not None if arg in memo: errormsg = "memo key %r already defined" % arg elif not stack: errormsg = "stack is empty -- can't store into memo" elif stack[-1] is markobject: errormsg = "can't store markobject in the memo" else: memo[arg] = stack[-1] elif opcode.name in ("GET", "BINGET", "LONG_BINGET"): if arg in memo: assert len(after) == 1 after = [memo[arg]] # for better stack emulation else: errormsg = "memo key %r has never been stored into" % arg if arg is not None or markmsg: # make a mild effort to align arguments line += ' ' * (10 - len(opcode.name)) if arg is not None: line += ' ' + repr(arg) if markmsg: line += ' ' + markmsg print >> out, line if errormsg: # Note that we delayed complaining until the offending opcode # was printed. raise ValueError(errormsg) # Emulate the stack effects. if len(stack) < numtopop: raise ValueError("tries to pop %d items from stack with " "only %d items" % (numtopop, len(stack))) if numtopop: del stack[-numtopop:] if markobject in after: assert markobject not in before markstack.append(pos) stack.extend(after) print >> out, "highest protocol among opcodes =", maxproto if stack: raise ValueError("stack not empty after STOP: %r" % stack)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/pickletools.py#L1887-L2021
microsoft/checkedc-clang
a173fefde5d7877b7750e7ce96dd08cf18baebf2
compiler-rt/lib/sanitizer_common/scripts/cpplint.py
python
_CppLintState.ResetErrorCounts
(self)
Sets the module's error statistic back to zero.
Sets the module's error statistic back to zero.
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def ResetErrorCounts(self): """Sets the module's error statistic back to zero.""" self.error_count = 0 self.errors_by_category = {}
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https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/compiler-rt/lib/sanitizer_common/scripts/cpplint.py#L938-L941
apple/swift-lldb
d74be846ef3e62de946df343e8c234bde93a8912
scripts/Python/static-binding/lldb.py
python
SBSymbolContextList.Clear
(self)
return _lldb.SBSymbolContextList_Clear(self)
Clear(SBSymbolContextList self)
Clear(SBSymbolContextList self)
[ "Clear", "(", "SBSymbolContextList", "self", ")" ]
def Clear(self): """Clear(SBSymbolContextList self)""" return _lldb.SBSymbolContextList_Clear(self)
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https://github.com/apple/swift-lldb/blob/d74be846ef3e62de946df343e8c234bde93a8912/scripts/Python/static-binding/lldb.py#L10139-L10141
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/stc.py
python
StyledTextCtrl.RegisterImage
(*args, **kwargs)
return _stc.StyledTextCtrl_RegisterImage(*args, **kwargs)
RegisterImage(self, int type, Bitmap bmp) Register an image for use in autocompletion lists.
RegisterImage(self, int type, Bitmap bmp)
[ "RegisterImage", "(", "self", "int", "type", "Bitmap", "bmp", ")" ]
def RegisterImage(*args, **kwargs): """ RegisterImage(self, int type, Bitmap bmp) Register an image for use in autocompletion lists. """ return _stc.StyledTextCtrl_RegisterImage(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L3203-L3209
eventql/eventql
7ca0dbb2e683b525620ea30dc40540a22d5eb227
deps/3rdparty/spidermonkey/mozjs/build/checksums.py
python
setup_logging
(level=logging.DEBUG)
This function sets up the logging module using a speficiable logging module logging level. The default log level is DEBUG. The output is in the format: <level> - <message> Example: DEBUG - Finished reading in file
This function sets up the logging module using a speficiable logging module logging level. The default log level is DEBUG.
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def setup_logging(level=logging.DEBUG): '''This function sets up the logging module using a speficiable logging module logging level. The default log level is DEBUG. The output is in the format: <level> - <message> Example: DEBUG - Finished reading in file ''' logger = logging.getLogger('checksums.py') logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() handler.setLevel(level) formatter = logging.Formatter("%(levelname)s - %(message)s") handler.setFormatter(formatter) logger.addHandler(handler)
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https://github.com/eventql/eventql/blob/7ca0dbb2e683b525620ea30dc40540a22d5eb227/deps/3rdparty/spidermonkey/mozjs/build/checksums.py#L88-L104
thalium/icebox
99d147d5b9269222225443ce171b4fd46d8985d4
third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py
python
xmlDoc.htmlIsAutoClosed
(self, elem)
return ret
The HTML DTD allows a tag to implicitly close other tags. The list is kept in htmlStartClose array. This function checks if a tag is autoclosed by one of it's child
The HTML DTD allows a tag to implicitly close other tags. The list is kept in htmlStartClose array. This function checks if a tag is autoclosed by one of it's child
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def htmlIsAutoClosed(self, elem): """The HTML DTD allows a tag to implicitly close other tags. The list is kept in htmlStartClose array. This function checks if a tag is autoclosed by one of it's child """ ret = libxml2mod.htmlIsAutoClosed(self._o, elem) return ret
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https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py#L3984-L3989
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/xml/dom/minidom.py
python
parseString
(string, parser=None)
Parse a file into a DOM from a string.
Parse a file into a DOM from a string.
[ "Parse", "a", "file", "into", "a", "DOM", "from", "a", "string", "." ]
def parseString(string, parser=None): """Parse a file into a DOM from a string.""" if parser is None: from xml.dom import expatbuilder return expatbuilder.parseString(string) else: from xml.dom import pulldom return _do_pulldom_parse(pulldom.parseString, (string,), {'parser': parser})
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/xml/dom/minidom.py#L1924-L1932
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/ops/composite/base.py
python
_Tail.__init__
(self, name)
Initialize _Tail.
Initialize _Tail.
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def __init__(self, name): """Initialize _Tail.""" Tail_.__init__(self, name)
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https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/ops/composite/base.py#L830-L832
sdhash/sdhash
b9eff63e4e5867e910f41fd69032bbb1c94a2a5e
external/tools/build/v2/build/virtual_target.py
python
VirtualTarget.depends
(self, d)
Adds additional instances of 'VirtualTarget' that this one depends on.
Adds additional instances of 'VirtualTarget' that this one depends on.
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def depends (self, d): """ Adds additional instances of 'VirtualTarget' that this one depends on. """ self.dependencies_ = unique (self.dependencies_ + d).sort ()
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https://github.com/sdhash/sdhash/blob/b9eff63e4e5867e910f41fd69032bbb1c94a2a5e/external/tools/build/v2/build/virtual_target.py#L281-L285
yuxng/PoseCNN
9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04
lib/datasets/rgbd_scene.py
python
rgbd_scene.depth_path_at
(self, i)
return self.depth_path_from_index(self.image_index[i])
Return the absolute path to depth i in the image sequence.
Return the absolute path to depth i in the image sequence.
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def depth_path_at(self, i): """ Return the absolute path to depth i in the image sequence. """ return self.depth_path_from_index(self.image_index[i])
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https://github.com/yuxng/PoseCNN/blob/9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04/lib/datasets/rgbd_scene.py#L50-L54
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/contrib/slim/python/slim/nets/inception_v3.py
python
_reduced_kernel_size_for_small_input
(input_tensor, kernel_size)
return kernel_size_out
Define kernel size which is automatically reduced for small input. If the shape of the input images is unknown at graph construction time this function assumes that the input images are is large enough. Args: input_tensor: input tensor of size [batch_size, height, width, channels]. kernel_size: desired kernel size of length 2: [kernel_height, kernel_width] Returns: a tensor with the kernel size. TODO(jrru): Make this function work with unknown shapes. Theoretically, this can be done with the code below. Problems are two-fold: (1) If the shape was known, it will be lost. (2) inception.tf.contrib.slim.ops._two_element_tuple cannot handle tensors that define the kernel size. shape = tf.shape(input_tensor) return = tf.stack([tf.minimum(shape[1], kernel_size[0]), tf.minimum(shape[2], kernel_size[1])])
Define kernel size which is automatically reduced for small input.
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def _reduced_kernel_size_for_small_input(input_tensor, kernel_size): """Define kernel size which is automatically reduced for small input. If the shape of the input images is unknown at graph construction time this function assumes that the input images are is large enough. Args: input_tensor: input tensor of size [batch_size, height, width, channels]. kernel_size: desired kernel size of length 2: [kernel_height, kernel_width] Returns: a tensor with the kernel size. TODO(jrru): Make this function work with unknown shapes. Theoretically, this can be done with the code below. Problems are two-fold: (1) If the shape was known, it will be lost. (2) inception.tf.contrib.slim.ops._two_element_tuple cannot handle tensors that define the kernel size. shape = tf.shape(input_tensor) return = tf.stack([tf.minimum(shape[1], kernel_size[0]), tf.minimum(shape[2], kernel_size[1])]) """ shape = input_tensor.get_shape().as_list() if shape[1] is None or shape[2] is None: kernel_size_out = kernel_size else: kernel_size_out = [ min(shape[1], kernel_size[0]), min(shape[2], kernel_size[1]) ] return kernel_size_out
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/contrib/slim/python/slim/nets/inception_v3.py#L644-L674
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/macpath.py
python
abspath
(path)
return normpath(path)
Return an absolute path.
Return an absolute path.
[ "Return", "an", "absolute", "path", "." ]
def abspath(path): """Return an absolute path.""" if not isabs(path): if isinstance(path, _unicode): cwd = os.getcwdu() else: cwd = os.getcwd() path = join(cwd, path) return normpath(path)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/macpath.py#L187-L195
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/platebtn.py
python
PlateButton.__PostEvent
(self)
Post a button event to parent of this control
Post a button event to parent of this control
[ "Post", "a", "button", "event", "to", "parent", "of", "this", "control" ]
def __PostEvent(self): """Post a button event to parent of this control""" if self._style & PB_STYLE_TOGGLE: etype = wx.wxEVT_COMMAND_TOGGLEBUTTON_CLICKED else: etype = wx.wxEVT_COMMAND_BUTTON_CLICKED bevt = wx.CommandEvent(etype, self.GetId()) bevt.SetEventObject(self) bevt.SetString(self.GetLabel()) self.GetEventHandler().ProcessEvent(bevt)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/platebtn.py#L248-L257
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/plat-mac/PixMapWrapper.py
python
PixMapWrapper.fromstring
(self,s,width,height,format=imgformat.macrgb)
Stuff this pixmap with raw pixel data from a string. Supply width, height, and one of the imgformat specifiers.
Stuff this pixmap with raw pixel data from a string. Supply width, height, and one of the imgformat specifiers.
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def fromstring(self,s,width,height,format=imgformat.macrgb): """Stuff this pixmap with raw pixel data from a string. Supply width, height, and one of the imgformat specifiers.""" # we only support 16- and 32-bit mac rgb... # so convert if necessary if format != imgformat.macrgb and format != imgformat.macrgb16: # (LATER!) raise "NotImplementedError", "conversion to macrgb or macrgb16" self.data = s self.bounds = (0,0,width,height) self.cmpCount = 3 self.pixelType = QuickDraw.RGBDirect if format == imgformat.macrgb: self.pixelSize = 32 self.cmpSize = 8 else: self.pixelSize = 16 self.cmpSize = 5 self.rowBytes = width*self.pixelSize/8
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/plat-mac/PixMapWrapper.py#L161-L179
infinidb/infinidb
6c9f5dfdabc41ad80e81ba9e1a4eb0d7271a5d23
writeengine/bulk/bulkload.py
python
find_paths
()
return (bulk_dir, data_dir)
Find DBRoot and BulkRoot.
Find DBRoot and BulkRoot.
[ "Find", "DBRoot", "and", "BulkRoot", "." ]
def find_paths(): """Find DBRoot and BulkRoot.""" try: config_file = os.environ['CALPONT_CONFIG_FILE'] except KeyError: try: logger.info("Environment variable CALPONT_CONFIG_FILE not set, looking for system Calpont.xml") config_file = '/usr/local/Calpont/etc/Calpont.xml' os.lstat(config_file) except: logger.error('No config file available') sys.exit('No config file available') try: xmldoc = xml.dom.minidom.parse(config_file) bulk_node = xmldoc.getElementsByTagName('BulkRoot')[0] db_node = xmldoc.getElementsByTagName('DBRoot1')[0] bulk_dir = bulk_node.childNodes[0].nodeValue data_dir = db_node.childNodes[0].nodeValue except Exception, e: logger.error('Error parsing config file') logger.error(e) sys.exit('Error parsing config file') return (bulk_dir, data_dir)
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https://github.com/infinidb/infinidb/blob/6c9f5dfdabc41ad80e81ba9e1a4eb0d7271a5d23/writeengine/bulk/bulkload.py#L51-L76
windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/sched.py
python
scheduler.queue
(self)
return map(heapq.heappop, [events]*len(events))
An ordered list of upcoming events. Events are named tuples with fields for: time, priority, action, arguments
An ordered list of upcoming events.
[ "An", "ordered", "list", "of", "upcoming", "events", "." ]
def queue(self): """An ordered list of upcoming events. Events are named tuples with fields for: time, priority, action, arguments """ # Use heapq to sort the queue rather than using 'sorted(self._queue)'. # With heapq, two events scheduled at the same time will show in # the actual order they would be retrieved. events = self._queue[:] return map(heapq.heappop, [events]*len(events))
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https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/sched.py#L123-L134
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/training/evaluation.py
python
_get_or_create_eval_step
()
Gets or creates the eval step `Tensor`. Returns: A `Tensor` representing a counter for the evaluation step. Raises: ValueError: If multiple `Tensors` have been added to the `tf.GraphKeys.EVAL_STEP` collection.
Gets or creates the eval step `Tensor`.
[ "Gets", "or", "creates", "the", "eval", "step", "Tensor", "." ]
def _get_or_create_eval_step(): """Gets or creates the eval step `Tensor`. Returns: A `Tensor` representing a counter for the evaluation step. Raises: ValueError: If multiple `Tensors` have been added to the `tf.GraphKeys.EVAL_STEP` collection. """ graph = ops.get_default_graph() eval_steps = graph.get_collection(ops.GraphKeys.EVAL_STEP) if len(eval_steps) == 1: return eval_steps[0] elif len(eval_steps) > 1: raise ValueError('Multiple tensors added to tf.GraphKeys.EVAL_STEP') else: counter = variable_scope.get_variable( 'eval_step', shape=[], dtype=dtypes.int64, initializer=init_ops.zeros_initializer(), trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES, ops.GraphKeys.EVAL_STEP]) return counter
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/training/evaluation.py#L37-L61
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/WebOb/webob/response.py
python
Response.unset_cookie
(self, name, strict=True)
Unset a cookie with the given name (remove it from the response).
Unset a cookie with the given name (remove it from the response).
[ "Unset", "a", "cookie", "with", "the", "given", "name", "(", "remove", "it", "from", "the", "response", ")", "." ]
def unset_cookie(self, name, strict=True): """ Unset a cookie with the given name (remove it from the response). """ existing = self.headers.getall('Set-Cookie') if not existing and not strict: return cookies = Cookie() for header in existing: cookies.load(header) if isinstance(name, text_type): name = name.encode('utf8') if name in cookies: del cookies[name] del self.headers['Set-Cookie'] for m in cookies.values(): self.headerlist.append(('Set-Cookie', m.serialize())) elif strict: raise KeyError("No cookie has been set with the name %r" % name)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/WebOb/webob/response.py#L800-L819
google/fhir
d77f57706c1a168529b0b87ca7ccb1c0113e83c2
go/generate_go_protos.py
python
move_generated_go_protos
(tmp_dir: str)
Responsible for moving the generated go protos to their final destination. Args: tmp_dir: the temporary directory where the proto building and transformations occur.
Responsible for moving the generated go protos to their final destination.
[ "Responsible", "for", "moving", "the", "generated", "go", "protos", "to", "their", "final", "destination", "." ]
def move_generated_go_protos(tmp_dir: str): """Responsible for moving the generated go protos to their final destination. Args: tmp_dir: the temporary directory where the proto building and transformations occur. """ dest_root = _REPO_PATH.value proto_dest_dir = os.path.join(dest_root, "go/proto") shutil.rmtree(proto_dest_dir, ignore_errors=True) shutil.move( os.path.join(tmp_dir, "proto-out/github.com/google/fhir/go/proto"), proto_dest_dir) accessor_out = os.path.join( dest_root, "go/jsonformat/internal/accessor/accessor_test_go_proto") shutil.rmtree(accessor_out, ignore_errors=True) shutil.copytree( os.path.join( tmp_dir, "proto-out/github.com/google/fhir/go/jsonformat/internal/accessor/accessor_test_go_proto" ), accessor_out) protopath_dest_dir = os.path.join( dest_root, "go/jsonformat/internal/protopath/protopathtest_go_proto") shutil.rmtree(protopath_dest_dir, ignore_errors=True) shutil.copytree( os.path.join( tmp_dir, "proto-out/github.com/google/fhir/go/jsonformat/internal/protopath/protopathtest_go_proto" ), protopath_dest_dir)
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https://github.com/google/fhir/blob/d77f57706c1a168529b0b87ca7ccb1c0113e83c2/go/generate_go_protos.py#L37-L67
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/stc.py
python
StyledTextCtrl.AutoCompComplete
(*args, **kwargs)
return _stc.StyledTextCtrl_AutoCompComplete(*args, **kwargs)
AutoCompComplete(self) User has selected an item so remove the list and insert the selection.
AutoCompComplete(self)
[ "AutoCompComplete", "(", "self", ")" ]
def AutoCompComplete(*args, **kwargs): """ AutoCompComplete(self) User has selected an item so remove the list and insert the selection. """ return _stc.StyledTextCtrl_AutoCompComplete(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L3062-L3068
deepmind/open_spiel
4ca53bea32bb2875c7385d215424048ae92f78c8
open_spiel/python/algorithms/psro_v2/psro_v2.py
python
PSROSolver.get_and_update_non_marginalized_meta_strategies
(self, update=True)
return self._non_marginalized_probabilities
Returns the Nash Equilibrium distribution on meta game matrix.
Returns the Nash Equilibrium distribution on meta game matrix.
[ "Returns", "the", "Nash", "Equilibrium", "distribution", "on", "meta", "game", "matrix", "." ]
def get_and_update_non_marginalized_meta_strategies(self, update=True): """Returns the Nash Equilibrium distribution on meta game matrix.""" if update: self.update_meta_strategies() return self._non_marginalized_probabilities
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https://github.com/deepmind/open_spiel/blob/4ca53bea32bb2875c7385d215424048ae92f78c8/open_spiel/python/algorithms/psro_v2/psro_v2.py#L478-L482
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/x86/toolchain/share/gdb/python/gdb/command/frame_filters.py
python
InfoFrameFilter.enabled_string
(state)
Return "Yes" if filter is enabled, otherwise "No".
Return "Yes" if filter is enabled, otherwise "No".
[ "Return", "Yes", "if", "filter", "is", "enabled", "otherwise", "No", "." ]
def enabled_string(state): """Return "Yes" if filter is enabled, otherwise "No".""" if state: return "Yes" else: return "No"
[ "def", "enabled_string", "(", "state", ")", ":", "if", "state", ":", "return", "\"Yes\"", "else", ":", "return", "\"No\"" ]
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/share/gdb/python/gdb/command/frame_filters.py#L52-L57
MegEngine/MegEngine
ce9ad07a27ec909fb8db4dd67943d24ba98fb93a
imperative/python/megengine/module/qat/module.py
python
QATModule.get_activation_dtype
(self)
return self._get_method_result( "get_quantized_dtype", self.act_fake_quant, self.act_observer )
r"""Get activation's quantization dtype as the method from ``qconfig``.
r"""Get activation's quantization dtype as the method from ``qconfig``.
[ "r", "Get", "activation", "s", "quantization", "dtype", "as", "the", "method", "from", "qconfig", "." ]
def get_activation_dtype(self): r"""Get activation's quantization dtype as the method from ``qconfig``.""" return self._get_method_result( "get_quantized_dtype", self.act_fake_quant, self.act_observer )
[ "def", "get_activation_dtype", "(", "self", ")", ":", "return", "self", ".", "_get_method_result", "(", "\"get_quantized_dtype\"", ",", "self", ".", "act_fake_quant", ",", "self", ".", "act_observer", ")" ]
https://github.com/MegEngine/MegEngine/blob/ce9ad07a27ec909fb8db4dd67943d24ba98fb93a/imperative/python/megengine/module/qat/module.py#L140-L144
wanderine/BROCCOLI
ff7613de40d97429ba76ee2948cb5e1d7dd991d0
code/bids/fslinstaller.py
python
FslInstall.install_tar
(self, targz_file)
return FslIResult('', FslIResult.SUCCESS, '')
Install given tar.gz file, use sudo where required
Install given tar.gz file, use sudo where required
[ "Install", "given", "tar", ".", "gz", "file", "use", "sudo", "where", "required" ]
def install_tar(self, targz_file): '''Install given tar.gz file, use sudo where required''' #import tarfile from os import getpid,path from time import time # Check if install location is writable MsgUser.debug("Checking %s is writeable." % (self.location)) if is_writeable(self.location): as_root = False elif is_writeable_as_root(self.location): as_root = True else: return FslIResult(False, FslIResult.ERROR, "Unable to write to target folder (%s)" % (self.location)) MsgUser.message("Installing FSL software...") # Find out how many files to install #tarf = tarfile.open(targz_file, mode='r:gz') #MsgUser.debug("Opened the tar file for reading...") #tarcontents = tarf.getnames() #nfiles = len(tarcontents) #tarf.close() #MsgUser.debug("Calculated the number of install objects as %s" % (nfiles)) # Generate a temporary name - eg fsl-<mypid>-date tempname = '-'.join( ('fsl', str(getpid()), str(time())) ) MsgUser.debug("Untarring to %s into temporary folder %s." % (self.location, tempname)) tempfolder = "/".join((self.location.rstrip('/'),tempname)) a_result = run_cmd("mkdir %s" % (tempfolder), as_root = as_root) if a_result.status == FslIResult.ERROR: return a_result MsgUser.debug("Calling tar -C %s -x -v -f %s" % (tempfolder, targz_file)) tar_cmd = ' '.join(('tar', '-C', tempfolder, '-x', '-o', '-f', targz_file)) #a_result = run_cmd_countlines(tar_cmd, nfiles, tui=False, as_root=as_root) a_result = run_cmd_dropstdout(tar_cmd, as_root=as_root) try: if a_result.status == FslIResult.SUCCESS: new_fsl = "/".join((tempfolder.rstrip("/"), 'fsl')) install_to = "/".join((self.location.rstrip("/"),"fsl")) if path.exists(install_to): # move old one out of way a_result = get_installed_version(install_to) old_version = a_result.result if a_result.status != FslIResult.SUCCESS: MsgUser.warning("The contents of %s doesn't look like an FSL installation! - moving to fsl-0.0.0" % (install_to)) old_fsl = '-'.join((install_to, str(old_version))) if path.exists(old_fsl): MsgUser.debug("Looks like there is another copy of the old version of FSL - deleting...") c_result = safe_delete(old_fsl, as_root) if c_result.status == FslIResult.ERROR: raise InstallFailed(";".join(("Install location already has a %s - I've tried to delete it but failed" % (old_fsl), c_result.message))) a_result = run_cmd(" ".join(('mv', install_to, old_fsl)), as_root) if a_result.status == FslIResult.ERROR: # failed to move the old version if not self.keep: c_result = safe_delete(install_to, as_root) if c_result.status == FslIResult.ERROR: raise InstallFailed(";".join((a_result.message, c_result.message))) else: MsgUser.debug("Failed to move old version - %s, but able to delete it." % (a_result.message)) else: c_result = safe_delete(tempfolder, as_root) if c_result.status == FslIResult.ERROR: MsgUser.debug("Failed to delete %s - %s." % (tempfolder, c_result.message)) raise InstallFailed( ";".join((a_result.message, c_result.message))) else: MsgUser.debug("Deleted temp folder %s - %s." % (tempfolder, c_result.message)) MsgUser.debug("Failed to move old version - %s." % (a_result.message)) raise InstallFailed('Failed to move old version out of way and you requested it was kept.') # Remove old version if requested if self.keep: MsgUser.message("Old version moved to %s" % (old_fsl)) else: c_result = safe_delete(old_fsl, as_root) if c_result.status == FslIResult.ERROR: raise InstallFailed( c_result.message ) else: MsgUser.debug("Removed %s" % (old_fsl)) MsgUser.debug( " ".join(('mv', new_fsl, install_to)) ) a_result = run_cmd(" ".join(('mv', new_fsl, install_to)), as_root) if a_result.status == FslIResult.ERROR: # Unable to move new install into place MsgUser.debug("Move %s into %s failed - %s." % (new_fsl, install_to, a_result.message)) raise InstallFailed('Failed to move new version into place %s' % (a_result.message)) else: MsgUser.debug("Unable to unpack new version - %s." % (a_result.message)) raise InstallFailed('Unable to unpack new version - %s' % (a_result.message)) except InstallFailed, e: # Clean up unpacked version safe_delete(tempfolder,as_root) return FslIResult('', FslIResult.ERROR, str(e)) safe_delete(tempfolder,as_root) MsgUser.debug("Install complete") MsgUser.ok("FSL software installed.") return FslIResult('', FslIResult.SUCCESS, '')
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https://github.com/wanderine/BROCCOLI/blob/ff7613de40d97429ba76ee2948cb5e1d7dd991d0/code/bids/fslinstaller.py#L1419-L1520
KratosMultiphysics/Kratos
0000833054ed0503424eb28205d6508d9ca6cbbc
applications/MultilevelMonteCarloApplication/external_libraries/XMC/xmc/methodDefs_randomGeneratorWrapper/generator.py
python
returnRayleighAndUniform
(*args)
return [rayleigh_rv, uniform_rv]
Return one rayleigh and uniformly distributed random variables with given parameters
Return one rayleigh and uniformly distributed random variables with given parameters
[ "Return", "one", "rayleigh", "and", "uniformly", "distributed", "random", "variables", "with", "given", "parameters" ]
def returnRayleighAndUniform(*args): """ Return one rayleigh and uniformly distributed random variables with given parameters """ rayleigh_rv = np.random.rayleigh(args[0],size=1)[0] uniform_rv = np.random.uniform(args[1], args[2], 1) return [rayleigh_rv, uniform_rv]
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https://github.com/KratosMultiphysics/Kratos/blob/0000833054ed0503424eb28205d6508d9ca6cbbc/applications/MultilevelMonteCarloApplication/external_libraries/XMC/xmc/methodDefs_randomGeneratorWrapper/generator.py#L65-L72
GSORF/Visual-GPS-SLAM
9e327108d6be3fd8dc80c8f3bcc329237bacf230
03_Application/video2bag/img2bag.py
python
CreateBag
(args)
Creates the actual bag file by successively adding images
Creates the actual bag file by successively adding images
[ "Creates", "the", "actual", "bag", "file", "by", "successively", "adding", "images" ]
def CreateBag(args): '''Creates the actual bag file by successively adding images''' all_imgs, left_imgs, right_imgs = GetFilesFromDir(args[0]) if len(all_imgs) <= 0: print("No images found in %s" % args[0]) exit() if len(left_imgs) > 0 and len(right_imgs) > 0: # create bagfile with stereo camera image pairs CreateStereoBag(left_imgs, right_imgs, args[1]) else: # create bagfile with mono camera image stream CreateMonoBag(all_imgs, args[1])
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https://github.com/GSORF/Visual-GPS-SLAM/blob/9e327108d6be3fd8dc80c8f3bcc329237bacf230/03_Application/video2bag/img2bag.py#L128-L140
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/locale.py
python
currency
(val, symbol=True, grouping=False, international=False)
return s.replace('<', '').replace('>', '')
Formats val according to the currency settings in the current locale.
Formats val according to the currency settings in the current locale.
[ "Formats", "val", "according", "to", "the", "currency", "settings", "in", "the", "current", "locale", "." ]
def currency(val, symbol=True, grouping=False, international=False): """Formats val according to the currency settings in the current locale.""" conv = localeconv() # check for illegal values digits = conv[international and 'int_frac_digits' or 'frac_digits'] if digits == 127: raise ValueError("Currency formatting is not possible using " "the 'C' locale.") s = format('%%.%if' % digits, abs(val), grouping, monetary=True) # '<' and '>' are markers if the sign must be inserted between symbol and value s = '<' + s + '>' if symbol: smb = conv[international and 'int_curr_symbol' or 'currency_symbol'] precedes = conv[val<0 and 'n_cs_precedes' or 'p_cs_precedes'] separated = conv[val<0 and 'n_sep_by_space' or 'p_sep_by_space'] if precedes: s = smb + (separated and ' ' or '') + s else: s = s + (separated and ' ' or '') + smb sign_pos = conv[val<0 and 'n_sign_posn' or 'p_sign_posn'] sign = conv[val<0 and 'negative_sign' or 'positive_sign'] if sign_pos == 0: s = '(' + s + ')' elif sign_pos == 1: s = sign + s elif sign_pos == 2: s = s + sign elif sign_pos == 3: s = s.replace('<', sign) elif sign_pos == 4: s = s.replace('>', sign) else: # the default if nothing specified; # this should be the most fitting sign position s = sign + s return s.replace('<', '').replace('>', '')
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/locale.py#L258-L301
PaddlePaddle/PaddleOCR
b756bf5f8c90142e0d89d3db0163965c686b6ffe
ppocr/postprocess/locality_aware_nms.py
python
weighted_merge
(g, p)
return g
Weighted merge.
Weighted merge.
[ "Weighted", "merge", "." ]
def weighted_merge(g, p): """ Weighted merge. """ g[:8] = (g[8] * g[:8] + p[8] * p[:8]) / (g[8] + p[8]) g[8] = (g[8] + p[8]) return g
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https://github.com/PaddlePaddle/PaddleOCR/blob/b756bf5f8c90142e0d89d3db0163965c686b6ffe/ppocr/postprocess/locality_aware_nms.py#L46-L52
apple/turicreate
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
deps/src/libxml2-2.9.1/python/libxml2.py
python
xmlNode.nodePath
(self)
return ret
Build a structure based Path for the given node
Build a structure based Path for the given node
[ "Build", "a", "structure", "based", "Path", "for", "the", "given", "node" ]
def nodePath(self): """Build a structure based Path for the given node """ ret = libxml2mod.xmlGetNodePath(self._o) return ret
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/deps/src/libxml2-2.9.1/python/libxml2.py#L3440-L3443
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/training/tracking/layer_utils.py
python
gather_non_trainable_weights
(trainable, sub_layers, extra_variables)
return weights + non_trainable_extra_variables
Lists the non-trainable weights for an object with sub-layers. Args: trainable: Whether the object collecting the variables is trainable. sub_layers: A flat list of Layer objects owned by this object, to collect variables from. extra_variables: Any extra variables to include. Their `.trainable` property is used to categorize them. Returns: A list of collected non-trainable weights/variables.
Lists the non-trainable weights for an object with sub-layers.
[ "Lists", "the", "non", "-", "trainable", "weights", "for", "an", "object", "with", "sub", "-", "layers", "." ]
def gather_non_trainable_weights(trainable, sub_layers, extra_variables): """Lists the non-trainable weights for an object with sub-layers. Args: trainable: Whether the object collecting the variables is trainable. sub_layers: A flat list of Layer objects owned by this object, to collect variables from. extra_variables: Any extra variables to include. Their `.trainable` property is used to categorize them. Returns: A list of collected non-trainable weights/variables. """ trainable_extra_variables = [] non_trainable_extra_variables = [] for v in extra_variables: if v.trainable: trainable_extra_variables.append(v) else: non_trainable_extra_variables.append(v) weights = [] for layer in sub_layers: weights += layer.non_trainable_weights if not trainable: trainable_weights = [] for layer in sub_layers: trainable_weights += layer.trainable_weights return (trainable_weights + trainable_extra_variables + weights + non_trainable_extra_variables) return weights + non_trainable_extra_variables
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/training/tracking/layer_utils.py#L85-L114
NVIDIA/TensorRT
42805f078052daad1a98bc5965974fcffaad0960
tools/pytorch-quantization/pytorch_quantization/quant_modules.py
python
QuantModuleReplacementHelper.restore_float_modules
(self)
Reverse the effect of monkey patch by using the orginal_func_map to replace back the original modules.
Reverse the effect of monkey patch by using the orginal_func_map to replace back the original modules.
[ "Reverse", "the", "effect", "of", "monkey", "patch", "by", "using", "the", "orginal_func_map", "to", "replace", "back", "the", "original", "modules", "." ]
def restore_float_modules(self): """ Reverse the effect of monkey patch by using the orginal_func_map to replace back the original modules. """ for entry in self.orginal_func_map: setattr(entry.orig_mod, entry.mod_name, entry.replace_mod)
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https://github.com/NVIDIA/TensorRT/blob/42805f078052daad1a98bc5965974fcffaad0960/tools/pytorch-quantization/pytorch_quantization/quant_modules.py#L108-L114
krishauser/Klampt
972cc83ea5befac3f653c1ba20f80155768ad519
Python/klampt/plan/robotcspace.py
python
EmbeddedRobotCSpace.sendPathToController
(self,path,controller)
Sends a planned path so that it is executed correctly by the controller (assumes a fully actuated robot). Args: path (list of Configs): a path in the embedded space or the ambient space, as returned by a planner. controller (SimRobotController): the robot's controller
Sends a planned path so that it is executed correctly by the controller (assumes a fully actuated robot).
[ "Sends", "a", "planned", "path", "so", "that", "it", "is", "executed", "correctly", "by", "the", "controller", "(", "assumes", "a", "fully", "actuated", "robot", ")", "." ]
def sendPathToController(self,path,controller): """Sends a planned path so that it is executed correctly by the controller (assumes a fully actuated robot). Args: path (list of Configs): a path in the embedded space or the ambient space, as returned by a planner. controller (SimRobotController): the robot's controller """ if len(path[0]) == len(self.mapping): path = self.liftPath(path) if hasattr(self.ambientspace,'discretizePath'): path = self.ambientspace.discretizePath(path) self.ambientspace.sendPathToController(path,controller)
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https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/klampt/plan/robotcspace.py#L405-L418
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/python/training/learning_rate_decay.py
python
natural_exp_decay
(learning_rate, global_step, decay_steps, decay_rate, staircase=False, name=None)
Applies natural exponential decay to the initial learning rate. When training a model, it is often recommended to lower the learning rate as the training progresses. This function applies an exponential decay function to a provided initial learning rate. It requires an `global_step` value to compute the decayed learning rate. You can just pass a TensorFlow variable that you increment at each training step. The function returns the decayed learning rate. It is computed as: ```python decayed_learning_rate = learning_rate * exp(-decay_rate * global_step) ``` Example: decay exponentially with a base of 0.96: ```python ... global_step = tf.Variable(0, trainable=False) learning_rate = 0.1 k = 0.5 learning_rate = tf.train.exponential_time_decay(learning_rate, global_step, k) # Passing global_step to minimize() will increment it at each step. learning_step = ( tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` Args: learning_rate: A scalar `float32` or `float64` `Tensor` or a Python number. The initial learning rate. global_step: A Python number. Global step to use for the decay computation. Must not be negative. decay_steps: How often to apply decay. decay_rate: A Python number. The decay rate. staircase: Whether to apply decay in a discrete staircase, as opposed to continuous, fashion. name: String. Optional name of the operation. Defaults to 'ExponentialTimeDecay'. Returns: A scalar `Tensor` of the same type as `learning_rate`. The decayed learning rate. Raises: ValueError: if `global_step` is not supplied.
Applies natural exponential decay to the initial learning rate.
[ "Applies", "natural", "exponential", "decay", "to", "the", "initial", "learning", "rate", "." ]
def natural_exp_decay(learning_rate, global_step, decay_steps, decay_rate, staircase=False, name=None): """Applies natural exponential decay to the initial learning rate. When training a model, it is often recommended to lower the learning rate as the training progresses. This function applies an exponential decay function to a provided initial learning rate. It requires an `global_step` value to compute the decayed learning rate. You can just pass a TensorFlow variable that you increment at each training step. The function returns the decayed learning rate. It is computed as: ```python decayed_learning_rate = learning_rate * exp(-decay_rate * global_step) ``` Example: decay exponentially with a base of 0.96: ```python ... global_step = tf.Variable(0, trainable=False) learning_rate = 0.1 k = 0.5 learning_rate = tf.train.exponential_time_decay(learning_rate, global_step, k) # Passing global_step to minimize() will increment it at each step. learning_step = ( tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` Args: learning_rate: A scalar `float32` or `float64` `Tensor` or a Python number. The initial learning rate. global_step: A Python number. Global step to use for the decay computation. Must not be negative. decay_steps: How often to apply decay. decay_rate: A Python number. The decay rate. staircase: Whether to apply decay in a discrete staircase, as opposed to continuous, fashion. name: String. Optional name of the operation. Defaults to 'ExponentialTimeDecay'. Returns: A scalar `Tensor` of the same type as `learning_rate`. The decayed learning rate. Raises: ValueError: if `global_step` is not supplied. """ if global_step is None: raise ValueError("global_step is required for natural_exp_decay.") with ops.name_scope(name, "NaturalExpDecay", [learning_rate, global_step, decay_rate]) as name: learning_rate = ops.convert_to_tensor(learning_rate, name="learning_rate") dtype = learning_rate.dtype global_step = math_ops.cast(global_step, dtype) decay_steps = math_ops.cast(decay_steps, dtype) decay_rate = math_ops.cast(decay_rate, dtype) p = global_step / decay_steps if staircase: p = math_ops.floor(p) exponent = math_ops.exp(math_ops.multiply(math_ops.negative(decay_rate), p)) return math_ops.multiply(learning_rate, exponent, name=name)
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/training/learning_rate_decay.py#L282-L346
natanielruiz/android-yolo
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
jni-build/jni/include/tensorflow/tensorboard/backend/handler.py
python
TensorboardHandler.do_GET
(self)
Handler for all get requests.
Handler for all get requests.
[ "Handler", "for", "all", "get", "requests", "." ]
def do_GET(self): # pylint: disable=invalid-name """Handler for all get requests.""" parsed_url = urlparse.urlparse(self.path) # Remove a trailing slash, if present. clean_path = parsed_url.path if clean_path.endswith('/'): clean_path = clean_path[:-1] data_handlers = { DATA_PREFIX + SCALARS_ROUTE: self._serve_scalars, DATA_PREFIX + GRAPH_ROUTE: self._serve_graph, DATA_PREFIX + RUN_METADATA_ROUTE: self._serve_run_metadata, DATA_PREFIX + HISTOGRAMS_ROUTE: self._serve_histograms, DATA_PREFIX + COMPRESSED_HISTOGRAMS_ROUTE: self._serve_compressed_histograms, DATA_PREFIX + IMAGES_ROUTE: self._serve_images, DATA_PREFIX + INDIVIDUAL_IMAGE_ROUTE: self._serve_image, DATA_PREFIX + AUDIO_ROUTE: self._serve_audio, DATA_PREFIX + INDIVIDUAL_AUDIO_ROUTE: self._serve_individual_audio, DATA_PREFIX + RUNS_ROUTE: self._serve_runs, '/app.js': self._serve_js } query_params = urlparse.parse_qs(parsed_url.query) # parse_qs returns a list of values for each key; we're only interested in # the first. for key in query_params: value_count = len(query_params[key]) if value_count != 1: self.send_error( 400, 'query parameter %s should have exactly one value, had %d' % (key, value_count)) return query_params[key] = query_params[key][0] if clean_path in data_handlers: data_handlers[clean_path](query_params) elif clean_path in TAB_ROUTES: self._serve_index(query_params) else: self._serve_static_file(clean_path)
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/tensorboard/backend/handler.py#L549-L590
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/python/ops/variable_scope.py
python
VariableScope.__init__
(self, reuse, name="", initializer=None, regularizer=None, caching_device=None, partitioner=None, custom_getter=None, name_scope="", dtype=dtypes.float32, use_resource=None)
Creates a new VariableScope with the given properties.
Creates a new VariableScope with the given properties.
[ "Creates", "a", "new", "VariableScope", "with", "the", "given", "properties", "." ]
def __init__(self, reuse, name="", initializer=None, regularizer=None, caching_device=None, partitioner=None, custom_getter=None, name_scope="", dtype=dtypes.float32, use_resource=None): """Creates a new VariableScope with the given properties.""" self._name = name self._initializer = initializer self._regularizer = regularizer self._reuse = reuse self._caching_device = caching_device self._partitioner = partitioner self._custom_getter = custom_getter self._name_scope = name_scope self._dtype = dtype self._use_resource = use_resource
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/ops/variable_scope.py#L803-L824
kevin-ssy/Optical-Flow-Guided-Feature
07d4501a29002ee7821c38c1820e4a64c1acf6e8
lib/caffe-action/scripts/cpp_lint.py
python
FilesBelongToSameModule
(filename_cc, filename_h)
return files_belong_to_same_module, common_path
Check if these two filenames belong to the same module. The concept of a 'module' here is a as follows: foo.h, foo-inl.h, foo.cc, foo_test.cc and foo_unittest.cc belong to the same 'module' if they are in the same directory. some/path/public/xyzzy and some/path/internal/xyzzy are also considered to belong to the same module here. If the filename_cc contains a longer path than the filename_h, for example, '/absolute/path/to/base/sysinfo.cc', and this file would include 'base/sysinfo.h', this function also produces the prefix needed to open the header. This is used by the caller of this function to more robustly open the header file. We don't have access to the real include paths in this context, so we need this guesswork here. Known bugs: tools/base/bar.cc and base/bar.h belong to the same module according to this implementation. Because of this, this function gives some false positives. This should be sufficiently rare in practice. Args: filename_cc: is the path for the .cc file filename_h: is the path for the header path Returns: Tuple with a bool and a string: bool: True if filename_cc and filename_h belong to the same module. string: the additional prefix needed to open the header file.
Check if these two filenames belong to the same module.
[ "Check", "if", "these", "two", "filenames", "belong", "to", "the", "same", "module", "." ]
def FilesBelongToSameModule(filename_cc, filename_h): """Check if these two filenames belong to the same module. The concept of a 'module' here is a as follows: foo.h, foo-inl.h, foo.cc, foo_test.cc and foo_unittest.cc belong to the same 'module' if they are in the same directory. some/path/public/xyzzy and some/path/internal/xyzzy are also considered to belong to the same module here. If the filename_cc contains a longer path than the filename_h, for example, '/absolute/path/to/base/sysinfo.cc', and this file would include 'base/sysinfo.h', this function also produces the prefix needed to open the header. This is used by the caller of this function to more robustly open the header file. We don't have access to the real include paths in this context, so we need this guesswork here. Known bugs: tools/base/bar.cc and base/bar.h belong to the same module according to this implementation. Because of this, this function gives some false positives. This should be sufficiently rare in practice. Args: filename_cc: is the path for the .cc file filename_h: is the path for the header path Returns: Tuple with a bool and a string: bool: True if filename_cc and filename_h belong to the same module. string: the additional prefix needed to open the header file. """ if not filename_cc.endswith('.cc'): return (False, '') filename_cc = filename_cc[:-len('.cc')] if filename_cc.endswith('_unittest'): filename_cc = filename_cc[:-len('_unittest')] elif filename_cc.endswith('_test'): filename_cc = filename_cc[:-len('_test')] filename_cc = filename_cc.replace('/public/', '/') filename_cc = filename_cc.replace('/internal/', '/') if not filename_h.endswith('.h'): return (False, '') filename_h = filename_h[:-len('.h')] if filename_h.endswith('-inl'): filename_h = filename_h[:-len('-inl')] filename_h = filename_h.replace('/public/', '/') filename_h = filename_h.replace('/internal/', '/') files_belong_to_same_module = filename_cc.endswith(filename_h) common_path = '' if files_belong_to_same_module: common_path = filename_cc[:-len(filename_h)] return files_belong_to_same_module, common_path
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https://github.com/kevin-ssy/Optical-Flow-Guided-Feature/blob/07d4501a29002ee7821c38c1820e4a64c1acf6e8/lib/caffe-action/scripts/cpp_lint.py#L4399-L4451
dscharrer/innoextract
5519d364cc8898f906f6285d81a87ab8c5469cde
cmake/cpplint.py
python
CleanseComments
(line)
return _RE_PATTERN_CLEANSE_LINE_C_COMMENTS.sub('', line)
Removes //-comments and single-line C-style /* */ comments. Args: line: A line of C++ source. Returns: The line with single-line comments removed.
Removes //-comments and single-line C-style /* */ comments.
[ "Removes", "//", "-", "comments", "and", "single", "-", "line", "C", "-", "style", "/", "*", "*", "/", "comments", "." ]
def CleanseComments(line): """Removes //-comments and single-line C-style /* */ comments. Args: line: A line of C++ source. Returns: The line with single-line comments removed. """ commentpos = line.find('//') if commentpos != -1 and not IsCppString(line[:commentpos]): line = line[:commentpos].rstrip() # get rid of /* ... */ return _RE_PATTERN_CLEANSE_LINE_C_COMMENTS.sub('', line)
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https://github.com/dscharrer/innoextract/blob/5519d364cc8898f906f6285d81a87ab8c5469cde/cmake/cpplint.py#L970-L983
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/pydoc.py
python
HTMLDoc.formatvalue
(self, object)
return self.grey('=' + self.repr(object))
Format an argument default value as text.
Format an argument default value as text.
[ "Format", "an", "argument", "default", "value", "as", "text", "." ]
def formatvalue(self, object): """Format an argument default value as text.""" return self.grey('=' + self.repr(object))
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/pydoc.py#L843-L845
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib-tk/Tkinter.py
python
Canvas.itemconfigure
(self, tagOrId, cnf=None, **kw)
return self._configure(('itemconfigure', tagOrId), cnf, kw)
Configure resources of an item TAGORID. The values for resources are specified as keyword arguments. To get an overview about the allowed keyword arguments call the method without arguments.
Configure resources of an item TAGORID.
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def itemconfigure(self, tagOrId, cnf=None, **kw): """Configure resources of an item TAGORID. The values for resources are specified as keyword arguments. To get an overview about the allowed keyword arguments call the method without arguments. """ return self._configure(('itemconfigure', tagOrId), cnf, kw)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib-tk/Tkinter.py#L2342-L2349
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_misc.py
python
Clipboard.Close
(*args, **kwargs)
return _misc_.Clipboard_Close(*args, **kwargs)
Close(self) Closes the clipboard.
Close(self)
[ "Close", "(", "self", ")" ]
def Close(*args, **kwargs): """ Close(self) Closes the clipboard. """ return _misc_.Clipboard_Close(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_misc.py#L5803-L5809
apache/incubator-mxnet
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
python/mxnet/symbol/numpy/linalg.py
python
qr
(a, mode='reduced')
return _npi.qr(a)
r""" Compute the qr factorization of a matrix a. Factor the matrix a as qr, where q is orthonormal and r is upper-triangular. Parameters ---------- a : (..., M, N) _Symbol Matrix or stack of matrices to be qr factored. mode: {‘reduced’, ‘complete’, ‘r’, ‘raw’, ‘full’, ‘economic’}, optional Only default mode, 'reduced', is implemented. If K = min(M, N), then * 'reduced’ : returns q, r with dimensions (M, K), (K, N) (default) Returns ------- q : (..., M, K) _Symbol A matrix or stack of matrices with K orthonormal columns, with K = min(M, N). r : (..., K, N) _Symbol A matrix or stack of upper triangular matrices. Raises ------ MXNetError If factoring fails. Examples -------- >>> from mxnet import np >>> a = np.random.uniform(-10, 10, (2, 2)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.22121978, -0.97522414], [-0.97522414, 0.22121954]]) >>> r array([[-4.4131265 , -7.1255064 ], [ 0. , -0.28771925]]) >>> a = np.random.uniform(-10, 10, (2, 3)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.28376842, -0.9588929 ], [-0.9588929 , 0.28376836]]) >>> r array([[-7.242763 , -0.5673361 , -2.624416 ], [ 0. , -7.297918 , -0.15949416]]) >>> a = np.random.uniform(-10, 10, (3, 2)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.34515655, 0.10919492], [ 0.14765628, -0.97452265], [-0.92685735, -0.19591334]]) >>> r array([[-8.453794, 8.4175 ], [ 0. , 5.430561]])
r""" Compute the qr factorization of a matrix a. Factor the matrix a as qr, where q is orthonormal and r is upper-triangular.
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def qr(a, mode='reduced'): r""" Compute the qr factorization of a matrix a. Factor the matrix a as qr, where q is orthonormal and r is upper-triangular. Parameters ---------- a : (..., M, N) _Symbol Matrix or stack of matrices to be qr factored. mode: {‘reduced’, ‘complete’, ‘r’, ‘raw’, ‘full’, ‘economic’}, optional Only default mode, 'reduced', is implemented. If K = min(M, N), then * 'reduced’ : returns q, r with dimensions (M, K), (K, N) (default) Returns ------- q : (..., M, K) _Symbol A matrix or stack of matrices with K orthonormal columns, with K = min(M, N). r : (..., K, N) _Symbol A matrix or stack of upper triangular matrices. Raises ------ MXNetError If factoring fails. Examples -------- >>> from mxnet import np >>> a = np.random.uniform(-10, 10, (2, 2)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.22121978, -0.97522414], [-0.97522414, 0.22121954]]) >>> r array([[-4.4131265 , -7.1255064 ], [ 0. , -0.28771925]]) >>> a = np.random.uniform(-10, 10, (2, 3)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.28376842, -0.9588929 ], [-0.9588929 , 0.28376836]]) >>> r array([[-7.242763 , -0.5673361 , -2.624416 ], [ 0. , -7.297918 , -0.15949416]]) >>> a = np.random.uniform(-10, 10, (3, 2)) >>> q, r = np.linalg.qr(a) >>> q array([[-0.34515655, 0.10919492], [ 0.14765628, -0.97452265], [-0.92685735, -0.19591334]]) >>> r array([[-8.453794, 8.4175 ], [ 0. , 5.430561]]) """ if mode is not None and mode != 'reduced': raise NotImplementedError("Only default mode='reduced' is implemented.") return _npi.qr(a)
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https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/symbol/numpy/linalg.py#L484-L540
hughperkins/tf-coriander
970d3df6c11400ad68405f22b0c42a52374e94ca
tensorflow/contrib/graph_editor/select.py
python
select_ops_and_ts
(*args, **kwargs)
return ops, ts
Helper to select operations and tensors. Args: *args: list of 1) regular expressions (compiled or not) or 2) (array of) `tf.Operation` 3) (array of) tf.Tensor. Regular expressions matching tensors must start with the comment `"(?#ts)"`, for instance: `"(?#ts)^foo/.*"`. **kwargs: 'graph': `tf.Graph` in which to perform the regex query.This is required when using regex. 'positive_filter': an elem if selected only if `positive_filter(elem)` is `True`. This is optional. Returns: A tuple `(ops, ts)` where: `ops` is a list of `tf.Operation`, and `ts` is a list of `tf.Tensor` Raises: TypeError: if the optional keyword argument graph is not a `tf.Graph` or if an argument in args is not an (array of) `tf.Tensor` or an (array of) `tf.Operation` or a string or a regular expression. ValueError: if one of the keyword arguments is unexpected or if a regular expression is used without passing a graph as a keyword argument.
Helper to select operations and tensors.
[ "Helper", "to", "select", "operations", "and", "tensors", "." ]
def select_ops_and_ts(*args, **kwargs): """Helper to select operations and tensors. Args: *args: list of 1) regular expressions (compiled or not) or 2) (array of) `tf.Operation` 3) (array of) tf.Tensor. Regular expressions matching tensors must start with the comment `"(?#ts)"`, for instance: `"(?#ts)^foo/.*"`. **kwargs: 'graph': `tf.Graph` in which to perform the regex query.This is required when using regex. 'positive_filter': an elem if selected only if `positive_filter(elem)` is `True`. This is optional. Returns: A tuple `(ops, ts)` where: `ops` is a list of `tf.Operation`, and `ts` is a list of `tf.Tensor` Raises: TypeError: if the optional keyword argument graph is not a `tf.Graph` or if an argument in args is not an (array of) `tf.Tensor` or an (array of) `tf.Operation` or a string or a regular expression. ValueError: if one of the keyword arguments is unexpected or if a regular expression is used without passing a graph as a keyword argument. """ ops = select_ops(*args, restrict_ops_regex=False, **kwargs) ts = select_ts(*args, restrict_ts_regex=True, **kwargs) return ops, ts
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https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/contrib/graph_editor/select.py#L746-L771
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/ops/ragged/row_partition.py
python
RowPartition.offsets_in_rows
(self)
return gen_ragged_math_ops.ragged_range( starts=constant_op.constant(0, self.dtype), limits=self.row_lengths(), deltas=constant_op.constant(1, self.dtype)).rt_dense_values
Return the offset of each value. RowPartition takes an array x and converts it into sublists. offsets[i] is the index of x[i] in its sublist. Given a shape, such as: [*,*,*],[*,*],[],[*,*] This returns: 0,1,2,0,1,0,1 Returns: an offset for every value.
Return the offset of each value.
[ "Return", "the", "offset", "of", "each", "value", "." ]
def offsets_in_rows(self): """Return the offset of each value. RowPartition takes an array x and converts it into sublists. offsets[i] is the index of x[i] in its sublist. Given a shape, such as: [*,*,*],[*,*],[],[*,*] This returns: 0,1,2,0,1,0,1 Returns: an offset for every value. """ return gen_ragged_math_ops.ragged_range( starts=constant_op.constant(0, self.dtype), limits=self.row_lengths(), deltas=constant_op.constant(1, self.dtype)).rt_dense_values
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/ragged/row_partition.py#L928-L944
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/coverage/coverage/control.py
python
Coverage.get_data
(self)
return self.data
Get the collected data and reset the collector. Also warn about various problems collecting data. Returns a :class:`coverage.CoverageData`, the collected coverage data. .. versionadded:: 4.0
Get the collected data and reset the collector.
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def get_data(self): """Get the collected data and reset the collector. Also warn about various problems collecting data. Returns a :class:`coverage.CoverageData`, the collected coverage data. .. versionadded:: 4.0 """ self._init() if not self._measured: return self.data self.collector.save_data(self.data) # If there are still entries in the source_pkgs list, then we never # encountered those packages. if self._warn_unimported_source: for pkg in self.source_pkgs: if pkg not in sys.modules: self._warn("Module %s was never imported." % pkg) elif not ( hasattr(sys.modules[pkg], '__file__') and os.path.exists(sys.modules[pkg].__file__) ): self._warn("Module %s has no Python source." % pkg) else: self._warn("Module %s was previously imported, but not measured." % pkg) # Find out if we got any data. if not self.data and self._warn_no_data: self._warn("No data was collected.") # Find files that were never executed at all. for src in self.source: for py_file in find_python_files(src): py_file = files.canonical_filename(py_file) if self.omit_match and self.omit_match.match(py_file): # Turns out this file was omitted, so don't pull it back # in as unexecuted. continue self.data.touch_file(py_file) if self.config.note: self.data.add_run_info(note=self.config.note) self._measured = False return self.data
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/coverage/coverage/control.py#L796-L846
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pandas/py3/pandas/core/computation/pytables.py
python
BinOp.metadata
(self)
return getattr(self.queryables.get(self.lhs), "metadata", None)
the metadata of my field
the metadata of my field
[ "the", "metadata", "of", "my", "field" ]
def metadata(self): """the metadata of my field""" return getattr(self.queryables.get(self.lhs), "metadata", None)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/core/computation/pytables.py#L188-L190
LiquidPlayer/LiquidCore
9405979363f2353ac9a71ad8ab59685dd7f919c9
deps/node-10.15.3/deps/v8/PRESUBMIT.py
python
_CheckNoInlineHeaderIncludesInNormalHeaders
(input_api, output_api)
Attempts to prevent inclusion of inline headers into normal header files. This tries to establish a layering where inline headers can be included by other inline headers or compilation units only.
Attempts to prevent inclusion of inline headers into normal header files. This tries to establish a layering where inline headers can be included by other inline headers or compilation units only.
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def _CheckNoInlineHeaderIncludesInNormalHeaders(input_api, output_api): """Attempts to prevent inclusion of inline headers into normal header files. This tries to establish a layering where inline headers can be included by other inline headers or compilation units only.""" file_inclusion_pattern = r'(?!.+-inl\.h).+\.h' include_directive_pattern = input_api.re.compile(r'#include ".+-inl.h"') include_error = ( 'You are including an inline header (e.g. foo-inl.h) within a normal\n' 'header (e.g. bar.h) file. This violates layering of dependencies.') def FilterFile(affected_file): black_list = (_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) return input_api.FilterSourceFile( affected_file, white_list=(file_inclusion_pattern, ), black_list=black_list) problems = [] for f in input_api.AffectedSourceFiles(FilterFile): local_path = f.LocalPath() for line_number, line in f.ChangedContents(): if (include_directive_pattern.search(line)): problems.append( '%s:%d\n %s' % (local_path, line_number, line.strip())) if problems: return [output_api.PresubmitError(include_error, problems)] else: return []
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https://github.com/LiquidPlayer/LiquidCore/blob/9405979363f2353ac9a71ad8ab59685dd7f919c9/deps/node-10.15.3/deps/v8/PRESUBMIT.py#L214-L243
luliyucoordinate/Leetcode
96afcdc54807d1d184e881a075d1dbf3371e31fb
src/0945-Minimum-Increment-to-Make-Array-Unique/0945.py
python
Solution.minIncrementForUnique
(self, A)
return result
:type A: List[int] :rtype: int
:type A: List[int] :rtype: int
[ ":", "type", "A", ":", "List", "[", "int", "]", ":", "rtype", ":", "int" ]
def minIncrementForUnique(self, A): """ :type A: List[int] :rtype: int """ box, result, max_A = [0]*40000, 0, 0 for a in A: box[a] += 1 if max_A < a: max_A = a for i in range(max_A): if box[i] <= 1: continue ano = box[i] - 1 result += ano box[i+1] += ano box[i] = 1 last_ano = box[max_A] - 1 result += (1 + last_ano)*last_ano//2 return result
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https://github.com/luliyucoordinate/Leetcode/blob/96afcdc54807d1d184e881a075d1dbf3371e31fb/src/0945-Minimum-Increment-to-Make-Array-Unique/0945.py#L2-L23
FreeCAD/FreeCAD
ba42231b9c6889b89e064d6d563448ed81e376ec
src/Mod/Path/PathScripts/PathJob.py
python
ObjectJob.baseCandidates
(cls)
return sorted( [obj for obj in FreeCAD.ActiveDocument.Objects if cls.isBaseCandidate(obj)], key=lambda o: o.Label, )
Answer all objects in the current document which could serve as a Base for a job.
Answer all objects in the current document which could serve as a Base for a job.
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def baseCandidates(cls): """Answer all objects in the current document which could serve as a Base for a job.""" return sorted( [obj for obj in FreeCAD.ActiveDocument.Objects if cls.isBaseCandidate(obj)], key=lambda o: o.Label, )
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https://github.com/FreeCAD/FreeCAD/blob/ba42231b9c6889b89e064d6d563448ed81e376ec/src/Mod/Path/PathScripts/PathJob.py#L818-L823
pmq20/node-packer
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
lts/tools/inspector_protocol/jinja2/ext.py
python
babel_extract
(fileobj, keywords, comment_tags, options)
Babel extraction method for Jinja templates. .. versionchanged:: 2.3 Basic support for translation comments was added. If `comment_tags` is now set to a list of keywords for extraction, the extractor will try to find the best preceeding comment that begins with one of the keywords. For best results, make sure to not have more than one gettext call in one line of code and the matching comment in the same line or the line before. .. versionchanged:: 2.5.1 The `newstyle_gettext` flag can be set to `True` to enable newstyle gettext calls. .. versionchanged:: 2.7 A `silent` option can now be provided. If set to `False` template syntax errors are propagated instead of being ignored. :param fileobj: the file-like object the messages should be extracted from :param keywords: a list of keywords (i.e. function names) that should be recognized as translation functions :param comment_tags: a list of translator tags to search for and include in the results. :param options: a dictionary of additional options (optional) :return: an iterator over ``(lineno, funcname, message, comments)`` tuples. (comments will be empty currently)
Babel extraction method for Jinja templates.
[ "Babel", "extraction", "method", "for", "Jinja", "templates", "." ]
def babel_extract(fileobj, keywords, comment_tags, options): """Babel extraction method for Jinja templates. .. versionchanged:: 2.3 Basic support for translation comments was added. If `comment_tags` is now set to a list of keywords for extraction, the extractor will try to find the best preceeding comment that begins with one of the keywords. For best results, make sure to not have more than one gettext call in one line of code and the matching comment in the same line or the line before. .. versionchanged:: 2.5.1 The `newstyle_gettext` flag can be set to `True` to enable newstyle gettext calls. .. versionchanged:: 2.7 A `silent` option can now be provided. If set to `False` template syntax errors are propagated instead of being ignored. :param fileobj: the file-like object the messages should be extracted from :param keywords: a list of keywords (i.e. function names) that should be recognized as translation functions :param comment_tags: a list of translator tags to search for and include in the results. :param options: a dictionary of additional options (optional) :return: an iterator over ``(lineno, funcname, message, comments)`` tuples. (comments will be empty currently) """ extensions = set() for extension in options.get('extensions', '').split(','): extension = extension.strip() if not extension: continue extensions.add(import_string(extension)) if InternationalizationExtension not in extensions: extensions.add(InternationalizationExtension) def getbool(options, key, default=False): return options.get(key, str(default)).lower() in \ ('1', 'on', 'yes', 'true') silent = getbool(options, 'silent', True) environment = Environment( options.get('block_start_string', BLOCK_START_STRING), options.get('block_end_string', BLOCK_END_STRING), options.get('variable_start_string', VARIABLE_START_STRING), options.get('variable_end_string', VARIABLE_END_STRING), options.get('comment_start_string', COMMENT_START_STRING), options.get('comment_end_string', COMMENT_END_STRING), options.get('line_statement_prefix') or LINE_STATEMENT_PREFIX, options.get('line_comment_prefix') or LINE_COMMENT_PREFIX, getbool(options, 'trim_blocks', TRIM_BLOCKS), getbool(options, 'lstrip_blocks', LSTRIP_BLOCKS), NEWLINE_SEQUENCE, getbool(options, 'keep_trailing_newline', KEEP_TRAILING_NEWLINE), frozenset(extensions), cache_size=0, auto_reload=False ) if getbool(options, 'trimmed'): environment.policies['ext.i18n.trimmed'] = True if getbool(options, 'newstyle_gettext'): environment.newstyle_gettext = True source = fileobj.read().decode(options.get('encoding', 'utf-8')) try: node = environment.parse(source) tokens = list(environment.lex(environment.preprocess(source))) except TemplateSyntaxError as e: if not silent: raise # skip templates with syntax errors return finder = _CommentFinder(tokens, comment_tags) for lineno, func, message in extract_from_ast(node, keywords): yield lineno, func, message, finder.find_comments(lineno)
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https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/tools/inspector_protocol/jinja2/ext.py#L542-L619
forkineye/ESPixelStick
22926f1c0d1131f1369fc7cad405689a095ae3cb
dist/bin/pyserial/serial/tools/hexlify_codec.py
python
hex_decode
(data, errors='strict')
return (unicode(''.join('{:02X} '.format(ord(b)) for b in serial.iterbytes(data))), len(data))
b'@ab' -> '40 41 42
b'
[ "b" ]
def hex_decode(data, errors='strict'): """b'@ab' -> '40 41 42'""" return (unicode(''.join('{:02X} '.format(ord(b)) for b in serial.iterbytes(data))), len(data))
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https://github.com/forkineye/ESPixelStick/blob/22926f1c0d1131f1369fc7cad405689a095ae3cb/dist/bin/pyserial/serial/tools/hexlify_codec.py#L41-L43
SpenceKonde/megaTinyCore
1c4a70b18a149fe6bcb551dfa6db11ca50b8997b
megaavr/tools/libs/serial/tools/miniterm.py
python
Miniterm.update_transformations
(self)
take list of transformation classes and instantiate them for rx and tx
take list of transformation classes and instantiate them for rx and tx
[ "take", "list", "of", "transformation", "classes", "and", "instantiate", "them", "for", "rx", "and", "tx" ]
def update_transformations(self): """take list of transformation classes and instantiate them for rx and tx""" transformations = [EOL_TRANSFORMATIONS[self.eol]] + [TRANSFORMATIONS[f] for f in self.filters] self.tx_transformations = [t() for t in transformations] self.rx_transformations = list(reversed(self.tx_transformations))
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https://github.com/SpenceKonde/megaTinyCore/blob/1c4a70b18a149fe6bcb551dfa6db11ca50b8997b/megaavr/tools/libs/serial/tools/miniterm.py#L398-L403
mantidproject/mantid
03deeb89254ec4289edb8771e0188c2090a02f32
qt/python/mantidqt/mantidqt/widgets/sliceviewer/lineplots.py
python
PixelLinePlot.handle_key
(self, key)
Called by KeyHandler if a key was accepted to perform a region extraction
Called by KeyHandler if a key was accepted to perform a region extraction
[ "Called", "by", "KeyHandler", "if", "a", "key", "was", "accepted", "to", "perform", "a", "region", "extraction" ]
def handle_key(self, key): """ Called by KeyHandler if a key was accepted to perform a region extraction """ if self._cursor_pos is None: return None pixel_transforms = self.PIXEL_TRANSFORM_CLS if key in pixel_transforms: to_next_pixel = pixel_transforms[key](self.plotter.image) to_next_pixel.move_from(self._cursor_pos) else: self.exporter.export_pixel_cut(self._cursor_pos, key)
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqt/mantidqt/widgets/sliceviewer/lineplots.py#L300-L313
Constellation/iv
64c3a9c7c517063f29d90d449180ea8f6f4d946f
tools/cpplint.py
python
CleanseComments
(line)
return _RE_PATTERN_CLEANSE_LINE_C_COMMENTS.sub('', line)
Removes //-comments and single-line C-style /* */ comments. Args: line: A line of C++ source. Returns: The line with single-line comments removed.
Removes //-comments and single-line C-style /* */ comments.
[ "Removes", "//", "-", "comments", "and", "single", "-", "line", "C", "-", "style", "/", "*", "*", "/", "comments", "." ]
def CleanseComments(line): """Removes //-comments and single-line C-style /* */ comments. Args: line: A line of C++ source. Returns: The line with single-line comments removed. """ commentpos = line.find('//') if commentpos != -1 and not IsCppString(line[:commentpos]): line = line[:commentpos].rstrip() # get rid of /* ... */ return _RE_PATTERN_CLEANSE_LINE_C_COMMENTS.sub('', line)
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https://github.com/Constellation/iv/blob/64c3a9c7c517063f29d90d449180ea8f6f4d946f/tools/cpplint.py#L1155-L1168
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/chunk.py
python
Chunk.getsize
(self)
return self.chunksize
Return the size of the current chunk.
Return the size of the current chunk.
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def getsize(self): """Return the size of the current chunk.""" return self.chunksize
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/chunk.py#L82-L84
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_gdi.py
python
Font_SetDefaultEncoding
(*args, **kwargs)
return _gdi_.Font_SetDefaultEncoding(*args, **kwargs)
Font_SetDefaultEncoding(int encoding) Sets the default font encoding.
Font_SetDefaultEncoding(int encoding)
[ "Font_SetDefaultEncoding", "(", "int", "encoding", ")" ]
def Font_SetDefaultEncoding(*args, **kwargs): """ Font_SetDefaultEncoding(int encoding) Sets the default font encoding. """ return _gdi_.Font_SetDefaultEncoding(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_gdi.py#L2627-L2633
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pexpect/pexpect/pty_spawn.py
python
spawn.waitnoecho
(self, timeout=-1)
This waits until the terminal ECHO flag is set False. This returns True if the echo mode is off. This returns False if the ECHO flag was not set False before the timeout. This can be used to detect when the child is waiting for a password. Usually a child application will turn off echo mode when it is waiting for the user to enter a password. For example, instead of expecting the "password:" prompt you can wait for the child to set ECHO off:: p = pexpect.spawn('ssh user@example.com') p.waitnoecho() p.sendline(mypassword) If timeout==-1 then this method will use the value in self.timeout. If timeout==None then this method to block until ECHO flag is False.
This waits until the terminal ECHO flag is set False. This returns True if the echo mode is off. This returns False if the ECHO flag was not set False before the timeout. This can be used to detect when the child is waiting for a password. Usually a child application will turn off echo mode when it is waiting for the user to enter a password. For example, instead of expecting the "password:" prompt you can wait for the child to set ECHO off::
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def waitnoecho(self, timeout=-1): '''This waits until the terminal ECHO flag is set False. This returns True if the echo mode is off. This returns False if the ECHO flag was not set False before the timeout. This can be used to detect when the child is waiting for a password. Usually a child application will turn off echo mode when it is waiting for the user to enter a password. For example, instead of expecting the "password:" prompt you can wait for the child to set ECHO off:: p = pexpect.spawn('ssh user@example.com') p.waitnoecho() p.sendline(mypassword) If timeout==-1 then this method will use the value in self.timeout. If timeout==None then this method to block until ECHO flag is False. ''' if timeout == -1: timeout = self.timeout if timeout is not None: end_time = time.time() + timeout while True: if not self.getecho(): return True if timeout < 0 and timeout is not None: return False if timeout is not None: timeout = end_time - time.time() time.sleep(0.1)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pexpect/pexpect/pty_spawn.py#L344-L372
mapnik/mapnik
f3da900c355e1d15059c4a91b00203dcc9d9f0ef
scons/scons-local-4.1.0/SCons/Node/FS.py
python
RootDir._lookup_abs
(self, p, klass, create=1)
return result
Fast (?) lookup of a *normalized* absolute path. This method is intended for use by internal lookups with already-normalized path data. For general-purpose lookups, use the FS.Entry(), FS.Dir() or FS.File() methods. The caller is responsible for making sure we're passed a normalized absolute path; we merely let Python's dictionary look up and return the One True Node.FS object for the path. If a Node for the specified "p" doesn't already exist, and "create" is specified, the Node may be created after recursive invocation to find or create the parent directory or directories.
Fast (?) lookup of a *normalized* absolute path.
[ "Fast", "(", "?", ")", "lookup", "of", "a", "*", "normalized", "*", "absolute", "path", "." ]
def _lookup_abs(self, p, klass, create=1): """ Fast (?) lookup of a *normalized* absolute path. This method is intended for use by internal lookups with already-normalized path data. For general-purpose lookups, use the FS.Entry(), FS.Dir() or FS.File() methods. The caller is responsible for making sure we're passed a normalized absolute path; we merely let Python's dictionary look up and return the One True Node.FS object for the path. If a Node for the specified "p" doesn't already exist, and "create" is specified, the Node may be created after recursive invocation to find or create the parent directory or directories. """ k = _my_normcase(p) try: result = self._lookupDict[k] except KeyError: if not create: msg = "No such file or directory: '%s' in '%s' (and create is False)" % (p, str(self)) raise SCons.Errors.UserError(msg) # There is no Node for this path name, and we're allowed # to create it. dir_name, file_name = p.rsplit('/',1) dir_node = self._lookup_abs(dir_name, Dir) result = klass(file_name, dir_node, self.fs) # Double-check on disk (as configured) that the Node we # created matches whatever is out there in the real world. result.diskcheck_match() self._lookupDict[k] = result dir_node.entries[_my_normcase(file_name)] = result dir_node.implicit = None else: # There is already a Node for this path name. Allow it to # complain if we were looking for an inappropriate type. result.must_be_same(klass) return result
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https://github.com/mapnik/mapnik/blob/f3da900c355e1d15059c4a91b00203dcc9d9f0ef/scons/scons-local-4.1.0/SCons/Node/FS.py#L2372-L2412
ceph/ceph
959663007321a369c83218414a29bd9dbc8bda3a
src/pybind/mgr/telemetry/module.py
python
Module.diff
(self)
return 0, r, ''
Show the diff between opted-in collection and available collection
Show the diff between opted-in collection and available collection
[ "Show", "the", "diff", "between", "opted", "-", "in", "collection", "and", "available", "collection" ]
def diff(self) -> Tuple[int, str, str]: ''' Show the diff between opted-in collection and available collection ''' diff = [] keys = ['nag'] for c in MODULE_COLLECTION: if not self.is_enabled_collection(c['name']): diff.append({key: val for key, val in c.items() if key not in keys}) r = None if diff == []: r = "Telemetry is up to date" else: r = json.dumps(diff, indent=4, sort_keys=True) return 0, r, ''
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https://github.com/ceph/ceph/blob/959663007321a369c83218414a29bd9dbc8bda3a/src/pybind/mgr/telemetry/module.py#L1358-L1375
snap-stanford/snap-python
d53c51b0a26aa7e3e7400b014cdf728948fde80a
snapx/snapx/classes/coreviews.py
python
AtlasView.__init__
(self, g, n)
Initialize with the input node and graph
Initialize with the input node and graph
[ "Initialize", "with", "the", "input", "node", "and", "graph" ]
def __init__(self, g, n): """Initialize with the input node and graph""" self._graph = g self._node = n if not isinstance(n, int): raise TypeError("Node ID must be int.") if n not in g: raise KeyError("Node must be present in graph.")
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https://github.com/snap-stanford/snap-python/blob/d53c51b0a26aa7e3e7400b014cdf728948fde80a/snapx/snapx/classes/coreviews.py#L23-L31
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/plat-mac/pimp.py
python
PimpPackage.downloadPackageOnly
(self, output=None)
Download a single package, if needed. An MD5 signature is used to determine whether download is needed, and to test that we actually downloaded what we expected. If output is given it is a file-like object that will receive a log of what happens. If anything unforeseen happened the method returns an error message string.
Download a single package, if needed.
[ "Download", "a", "single", "package", "if", "needed", "." ]
def downloadPackageOnly(self, output=None): """Download a single package, if needed. An MD5 signature is used to determine whether download is needed, and to test that we actually downloaded what we expected. If output is given it is a file-like object that will receive a log of what happens. If anything unforeseen happened the method returns an error message string. """ scheme, loc, path, query, frag = urlparse.urlsplit(self._dict['Download-URL']) path = urllib.url2pathname(path) filename = os.path.split(path)[1] self.archiveFilename = os.path.join(self._db.preferences.downloadDir, filename) if not self._archiveOK(): if scheme == 'manual': return "Please download package manually and save as %s" % self.archiveFilename downloader = PimpUrllibDownloader(None, self._db.preferences.downloadDir, watcher=self._db.preferences.watcher) if not downloader.download(self._dict['Download-URL'], self.archiveFilename, output): return "download command failed" if not os.path.exists(self.archiveFilename) and not NO_EXECUTE: return "archive not found after download" if not self._archiveOK(): return "archive does not have correct MD5 checksum"
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/plat-mac/pimp.py#L663-L690
ApolloAuto/apollo-platform
86d9dc6743b496ead18d597748ebabd34a513289
ros/third_party/lib_x86_64/python2.7/dist-packages/rosdep2/rep3.py
python
download_targets_data
(targets_url=None)
return targets_data
Download REP 3 targets file and unmarshal from YAML. DEPRECATED: this function is deprecated. List of targets should be obtained from the rosdistro module. The body of this function is an example. :param target_url: override URL of platform targets file. Defaults to ``REP3_TARGETS_URL``. :raises: :exc:`DownloadFailure` :raises: :exc:`InvalidData` If targets file does not pass cursory validation checks.
Download REP 3 targets file and unmarshal from YAML. DEPRECATED: this function is deprecated. List of targets should be obtained from the rosdistro module. The body of this function is an example.
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def download_targets_data(targets_url=None): """ Download REP 3 targets file and unmarshal from YAML. DEPRECATED: this function is deprecated. List of targets should be obtained from the rosdistro module. The body of this function is an example. :param target_url: override URL of platform targets file. Defaults to ``REP3_TARGETS_URL``. :raises: :exc:`DownloadFailure` :raises: :exc:`InvalidData` If targets file does not pass cursory validation checks. """ warnings.warn("deprecated, use rosdistro instead", PreRep137Warning) if targets_url is None: targets_url = REP3_TARGETS_URL try: f = urlopen(targets_url, timeout=DOWNLOAD_TIMEOUT) text = f.read() f.close() targets_data = yaml.safe_load(text) except Exception as e: raise DownloadFailure("Failed to download target platform data for gbpdistro:\n\t%s"%(str(e))) if type(targets_data) == list: # convert to dictionary new_targets_data = {} for t in targets_data: platform = list(t.keys())[0] new_targets_data[platform] = t[platform] targets_data = new_targets_data return targets_data
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https://github.com/ApolloAuto/apollo-platform/blob/86d9dc6743b496ead18d597748ebabd34a513289/ros/third_party/lib_x86_64/python2.7/dist-packages/rosdep2/rep3.py#L44-L74
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/window/rolling.py
python
Rolling._validate_monotonic
(self)
Validate monotonic (increasing or decreasing).
Validate monotonic (increasing or decreasing).
[ "Validate", "monotonic", "(", "increasing", "or", "decreasing", ")", "." ]
def _validate_monotonic(self): """ Validate monotonic (increasing or decreasing). """ if not (self._on.is_monotonic_increasing or self._on.is_monotonic_decreasing): formatted = self.on if self.on is None: formatted = "index" raise ValueError(f"{formatted} must be monotonic")
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/window/rolling.py#L1869-L1877
eclipse/sumo
7132a9b8b6eea734bdec38479026b4d8c4336d03
tools/contributed/sumopy/plugins/mapmatching/mapmatching.py
python
MobikeImporter.calc_seconds
(self, t_data, sep_date_clock = ' ', sep_date = '/', sep_clock = ':', )
Returns time in seconds after 1/1/1970. Time format for time data string used: 01/07/2018 06:00, SUNTRACTING 7h to meet chinese time
Returns time in seconds after 1/1/1970. Time format for time data string used: 01/07/2018 06:00, SUNTRACTING 7h to meet chinese time
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def calc_seconds(self, t_data, sep_date_clock = ' ', sep_date = '/', sep_clock = ':', ): """ Returns time in seconds after 1/1/1970. Time format for time data string used: 01/07/2018 06:00, SUNTRACTING 7h to meet chinese time """ # if len(t_data.split(sep_date_clock))!=2: return -1 (date, clock) = t_data.split(sep_date_clock) if (len(clock.split( sep_clock))==2)&(len(date.split(sep_date))==3): (day_str,month_str,year_str) = date.split(sep_date) #print ' year_str,month_str,day_str',year_str,month_str,day_str (hours_str,minutes_str) = clock.split(sep_clock) seconds_str = "0" #print ' hours_str,minutes_str,seconds_str',hours_str,minutes_str,seconds_str t = time.mktime(( int(year_str),int(month_str),int(day_str), int(hours_str),int(minutes_str),int(float(seconds_str)),-1,-1,-1))-25200# -7h #print 'calc_seconds',t #print ' t_data' #print ' tupel',int(year_str),int(month_str),int(day_str), int(hours_str),int(minutes_str),int(float(seconds_str)),0,0,0 return int(t) else: return -1
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https://github.com/eclipse/sumo/blob/7132a9b8b6eea734bdec38479026b4d8c4336d03/tools/contributed/sumopy/plugins/mapmatching/mapmatching.py#L4673-L4703
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tarfile.py
python
TarInfo.__init__
(self, name="")
Construct a TarInfo object. name is the optional name of the member.
Construct a TarInfo object. name is the optional name of the member.
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def __init__(self, name=""): """Construct a TarInfo object. name is the optional name of the member. """ self.name = name # member name self.mode = 0o644 # file permissions self.uid = 0 # user id self.gid = 0 # group id self.size = 0 # file size self.mtime = 0 # modification time self.chksum = 0 # header checksum self.type = REGTYPE # member type self.linkname = "" # link name self.uname = "" # user name self.gname = "" # group name self.devmajor = 0 # device major number self.devminor = 0 # device minor number self.offset = 0 # the tar header starts here self.offset_data = 0 # the file's data starts here self.sparse = None # sparse member information self.pax_headers = {}
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tarfile.py#L739-L761
google/syzygy
8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5
third_party/numpy/files/numpy/polynomial/polynomial.py
python
polydiv
(c1, c2)
Divide one polynomial by another. Returns the quotient-with-remainder of two polynomials `c1` / `c2`. The arguments are sequences of coefficients, from lowest order term to highest, e.g., [1,2,3] represents ``1 + 2*x + 3*x**2``. Parameters ---------- c1, c2 : array_like 1-d arrays of polynomial coefficients ordered from low to high. Returns ------- [quo, rem] : ndarrays Of coefficient series representing the quotient and remainder. See Also -------- polyadd, polysub, polymul, polypow Examples -------- >>> import numpy.polynomial as P >>> c1 = (1,2,3) >>> c2 = (3,2,1) >>> P.polydiv(c1,c2) (array([ 3.]), array([-8., -4.])) >>> P.polydiv(c2,c1) (array([ 0.33333333]), array([ 2.66666667, 1.33333333]))
Divide one polynomial by another.
[ "Divide", "one", "polynomial", "by", "another", "." ]
def polydiv(c1, c2): """ Divide one polynomial by another. Returns the quotient-with-remainder of two polynomials `c1` / `c2`. The arguments are sequences of coefficients, from lowest order term to highest, e.g., [1,2,3] represents ``1 + 2*x + 3*x**2``. Parameters ---------- c1, c2 : array_like 1-d arrays of polynomial coefficients ordered from low to high. Returns ------- [quo, rem] : ndarrays Of coefficient series representing the quotient and remainder. See Also -------- polyadd, polysub, polymul, polypow Examples -------- >>> import numpy.polynomial as P >>> c1 = (1,2,3) >>> c2 = (3,2,1) >>> P.polydiv(c1,c2) (array([ 3.]), array([-8., -4.])) >>> P.polydiv(c2,c1) (array([ 0.33333333]), array([ 2.66666667, 1.33333333])) """ # c1, c2 are trimmed copies [c1, c2] = pu.as_series([c1, c2]) if c2[-1] == 0 : raise ZeroDivisionError() len1 = len(c1) len2 = len(c2) if len2 == 1 : return c1/c2[-1], c1[:1]*0 elif len1 < len2 : return c1[:1]*0, c1 else : dlen = len1 - len2 scl = c2[-1] c2 = c2[:-1]/scl i = dlen j = len1 - 1 while i >= 0 : c1[i:j] -= c2*c1[j] i -= 1 j -= 1 return c1[j+1:]/scl, pu.trimseq(c1[:j+1])
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https://github.com/google/syzygy/blob/8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5/third_party/numpy/files/numpy/polynomial/polynomial.py#L341-L395
apple/turicreate
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
src/python/turicreate/toolkits/_mps_utils.py
python
MpsFloatArray.asnumpy
(self)
return _numpy_array_from_ctypes(data_ptr, shape_ptr, dim)
Copy the data from TCMPS into a new numpy ndarray
Copy the data from TCMPS into a new numpy ndarray
[ "Copy", "the", "data", "from", "TCMPS", "into", "a", "new", "numpy", "ndarray" ]
def asnumpy(self): """Copy the data from TCMPS into a new numpy ndarray""" # Create C variables that will serve as out parameters for TCMPS. data_ptr = _ctypes.POINTER(_ctypes.c_float)() # float* data_ptr shape_ptr = _ctypes.POINTER(_ctypes.c_size_t)() # size_t* shape_ptr dim = _ctypes.c_size_t() # size_t dim # Obtain pointers into memory owned by the C++ object self.handle. # Note that this may trigger synchronization with another thread # producing the data. status_code = self._LIB.TCMPSReadFloatArray( self.handle, _ctypes.byref(data_ptr), _ctypes.byref(shape_ptr), _ctypes.byref(dim), ) assert status_code == 0, "Error calling TCMPSReadFloatArray" return _numpy_array_from_ctypes(data_ptr, shape_ptr, dim)
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/src/python/turicreate/toolkits/_mps_utils.py#L276-L295
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/fluid/layers/nn.py
python
hard_sigmoid
(x, slope=0.2, offset=0.5, name=None)
return out
${comment} Parameters: x (${x_type}): ${x_comment} slope (float, optional): ${slope_comment} offset (float, optional): ${offset_comment} name (str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` Returns: ${out_type}: ${out_comment} Examples: .. code-block:: python import paddle.fluid as fluid import paddle paddle.enable_static() data = fluid.layers.fill_constant(shape=[3, 2], value=0.5, dtype='float32') # [[0.5, 0.5], [0.5, 0.5], [0.5, 0.5]] result = fluid.layers.hard_sigmoid(data) # [[0.6, 0.6], [0.6, 0.6], [0.6, 0.6]]
${comment} Parameters: x (${x_type}): ${x_comment} slope (float, optional): ${slope_comment} offset (float, optional): ${offset_comment} name (str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`
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def hard_sigmoid(x, slope=0.2, offset=0.5, name=None): """ ${comment} Parameters: x (${x_type}): ${x_comment} slope (float, optional): ${slope_comment} offset (float, optional): ${offset_comment} name (str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` Returns: ${out_type}: ${out_comment} Examples: .. code-block:: python import paddle.fluid as fluid import paddle paddle.enable_static() data = fluid.layers.fill_constant(shape=[3, 2], value=0.5, dtype='float32') # [[0.5, 0.5], [0.5, 0.5], [0.5, 0.5]] result = fluid.layers.hard_sigmoid(data) # [[0.6, 0.6], [0.6, 0.6], [0.6, 0.6]] """ if in_dygraph_mode(): return _C_ops.hard_sigmoid(x, 'slope', slope, 'offset', offset) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'hard_sigmoid') helper = LayerHelper('hard_sigmoid', **locals()) out = helper.create_variable_for_type_inference(dtype=x.dtype) helper.append_op( type='hard_sigmoid', inputs={'X': x}, outputs={'Out': out}, attrs={'slope': slope, 'offset': offset}) return out
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https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/fluid/layers/nn.py#L9729-L9768