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apple/swift
469f72fdae2ea828b3b6c0d7d62d7e4cf98c4893
utils/build_swift/build_swift/shell.py
python
_normalize_args
(args)
return list(_flatmap(normalize_arg, args))
Normalizes a list of arguments containing one or more strings and CommandWrapper instances into a one-dimensional list of strings.
Normalizes a list of arguments containing one or more strings and CommandWrapper instances into a one-dimensional list of strings.
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def _normalize_args(args): """Normalizes a list of arguments containing one or more strings and CommandWrapper instances into a one-dimensional list of strings. """ if isinstance(args, six.string_types): return shlex.split(args) def normalize_arg(arg): arg = _convert_pathlib_path(arg) if isinstance(arg, six.string_types): return [six.text_type(arg)] if isinstance(arg, AbstractWrapper): return list(map(_convert_pathlib_path, arg.command)) raise ValueError('Invalid argument type: {}'.format( type(arg).__name__)) if isinstance(args, AbstractWrapper): return normalize_arg(args) return list(_flatmap(normalize_arg, args))
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https://github.com/apple/swift/blob/469f72fdae2ea828b3b6c0d7d62d7e4cf98c4893/utils/build_swift/build_swift/shell.py#L148-L170
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/mailbox.py
python
_singlefileMailbox.lock
(self)
Lock the mailbox.
Lock the mailbox.
[ "Lock", "the", "mailbox", "." ]
def lock(self): """Lock the mailbox.""" if not self._locked: _lock_file(self._file) self._locked = True
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/mailbox.py#L640-L644
psi4/psi4
be533f7f426b6ccc263904e55122899b16663395
psi4/driver/driver.py
python
_filter_renamed_methods
(compute, method)
r"""Raises UpgradeHelper when a method has been renamed.
r"""Raises UpgradeHelper when a method has been renamed.
[ "r", "Raises", "UpgradeHelper", "when", "a", "method", "has", "been", "renamed", "." ]
def _filter_renamed_methods(compute, method): r"""Raises UpgradeHelper when a method has been renamed.""" if method == "dcft": raise UpgradeHelper(compute + "('dcft')", compute + "('dct')", 1.4, " All instances of 'dcft' should be replaced with 'dct'.")
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https://github.com/psi4/psi4/blob/be533f7f426b6ccc263904e55122899b16663395/psi4/driver/driver.py#L207-L210
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/mailbox.py
python
Mailbox._dump_message
(self, message, target, mangle_from_=False)
Dump message contents to target file.
Dump message contents to target file.
[ "Dump", "message", "contents", "to", "target", "file", "." ]
def _dump_message(self, message, target, mangle_from_=False): # Most files are opened in binary mode to allow predictable seeking. # To get native line endings on disk, the user-friendly \n line endings # used in strings and by email.Message are translated here. """Dump message contents to target file.""" if isinstance(message, email.message.Message): buffer = StringIO.StringIO() gen = email.generator.Generator(buffer, mangle_from_, 0) gen.flatten(message) buffer.seek(0) target.write(buffer.read().replace('\n', os.linesep)) elif isinstance(message, str): if mangle_from_: message = message.replace('\nFrom ', '\n>From ') message = message.replace('\n', os.linesep) target.write(message) elif hasattr(message, 'read'): while True: line = message.readline() if line == '': break if mangle_from_ and line.startswith('From '): line = '>From ' + line[5:] line = line.replace('\n', os.linesep) target.write(line) else: raise TypeError('Invalid message type: %s' % type(message))
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/mailbox.py#L194-L220
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/optparse.py
python
HelpFormatter.format_option_strings
(self, option)
return ", ".join(opts)
Return a comma-separated list of option strings & metavariables.
Return a comma-separated list of option strings & metavariables.
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def format_option_strings(self, option): """Return a comma-separated list of option strings & metavariables.""" if option.takes_value(): metavar = option.metavar or option.dest.upper() short_opts = [self._short_opt_fmt % (sopt, metavar) for sopt in option._short_opts] long_opts = [self._long_opt_fmt % (lopt, metavar) for lopt in option._long_opts] else: short_opts = option._short_opts long_opts = option._long_opts if self.short_first: opts = short_opts + long_opts else: opts = long_opts + short_opts return ", ".join(opts)
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/optparse.py#L342-L359
LiquidPlayer/LiquidCore
9405979363f2353ac9a71ad8ab59685dd7f919c9
deps/node-10.15.3/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/msvs.py
python
_GetDefines
(config)
return defines
Returns the list of preprocessor definitions for this configuation. Arguments: config: The dictionary that defines the special processing to be done for this configuration. Returns: The list of preprocessor definitions.
Returns the list of preprocessor definitions for this configuation.
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def _GetDefines(config): """Returns the list of preprocessor definitions for this configuation. Arguments: config: The dictionary that defines the special processing to be done for this configuration. Returns: The list of preprocessor definitions. """ defines = [] for d in config.get('defines', []): if type(d) == list: fd = '='.join([str(dpart) for dpart in d]) else: fd = str(d) defines.append(fd) return defines
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https://github.com/LiquidPlayer/LiquidCore/blob/9405979363f2353ac9a71ad8ab59685dd7f919c9/deps/node-10.15.3/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/msvs.py#L1324-L1340
papyrussolution/OpenPapyrus
bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91
Src/OSF/protobuf-3.19.1/python/google/protobuf/descriptor_pool.py
python
DescriptorPool.FindMessageTypeByName
(self, full_name)
return self._descriptors[full_name]
Loads the named descriptor from the pool. Args: full_name (str): The full name of the descriptor to load. Returns: Descriptor: The descriptor for the named type. Raises: KeyError: if the message cannot be found in the pool.
Loads the named descriptor from the pool.
[ "Loads", "the", "named", "descriptor", "from", "the", "pool", "." ]
def FindMessageTypeByName(self, full_name): """Loads the named descriptor from the pool. Args: full_name (str): The full name of the descriptor to load. Returns: Descriptor: The descriptor for the named type. Raises: KeyError: if the message cannot be found in the pool. """ full_name = _NormalizeFullyQualifiedName(full_name) if full_name not in self._descriptors: self._FindFileContainingSymbolInDb(full_name) return self._descriptors[full_name]
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https://github.com/papyrussolution/OpenPapyrus/blob/bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91/Src/OSF/protobuf-3.19.1/python/google/protobuf/descriptor_pool.py#L501-L517
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/_vendor/pyparsing.py
python
ParserElement.setDebugActions
( self, startAction, successAction, exceptionAction )
return self
Enable display of debugging messages while doing pattern matching.
[]
def setDebugActions( self, startAction, successAction, exceptionAction ): """ Enable display of debugging messages while doing pattern matching. """ self.debugActions = (startAction or _defaultStartDebugAction, successAction or _defaultSuccessDebugAction, exceptionAction or _defaultExceptionDebugAction) self.debug = True return self
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/_vendor/pyparsing.py#L4203-L4219
apache/arrow
af33dd1157eb8d7d9bfac25ebf61445b793b7943
dev/archery/archery/cli.py
python
linking
(obj)
Quick and dirty utilities for checking library linkage.
Quick and dirty utilities for checking library linkage.
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def linking(obj): """ Quick and dirty utilities for checking library linkage. """ pass
[ "def", "linking", "(", "obj", ")", ":", "pass" ]
https://github.com/apache/arrow/blob/af33dd1157eb8d7d9bfac25ebf61445b793b7943/dev/archery/archery/cli.py#L914-L918
swift/swift
12d031cf8177fdec0137f9aa7e2912fa23c4416b
3rdParty/SCons/scons-3.0.1/engine/SCons/Environment.py
python
SubstitutionEnvironment._init_special
(self)
Initial the dispatch tables for special handling of special construction variables.
Initial the dispatch tables for special handling of special construction variables.
[ "Initial", "the", "dispatch", "tables", "for", "special", "handling", "of", "special", "construction", "variables", "." ]
def _init_special(self): """Initial the dispatch tables for special handling of special construction variables.""" self._special_del = {} self._special_del['SCANNERS'] = _del_SCANNERS self._special_set = {} for key in reserved_construction_var_names: self._special_set[key] = _set_reserved for key in future_reserved_construction_var_names: self._special_set[key] = _set_future_reserved self._special_set['BUILDERS'] = _set_BUILDERS self._special_set['SCANNERS'] = _set_SCANNERS # Freeze the keys of self._special_set in a list for use by # methods that need to check. (Empirically, list scanning has # gotten better than dict.has_key() in Python 2.5.) self._special_set_keys = list(self._special_set.keys())
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https://github.com/swift/swift/blob/12d031cf8177fdec0137f9aa7e2912fa23c4416b/3rdParty/SCons/scons-3.0.1/engine/SCons/Environment.py#L380-L397
hpi-xnor/BMXNet-v2
af2b1859eafc5c721b1397cef02f946aaf2ce20d
python/mxnet/io/io.py
python
DataIter.reset
(self)
Reset the iterator to the begin of the data.
Reset the iterator to the begin of the data.
[ "Reset", "the", "iterator", "to", "the", "begin", "of", "the", "data", "." ]
def reset(self): """Reset the iterator to the begin of the data.""" pass
[ "def", "reset", "(", "self", ")", ":", "pass" ]
https://github.com/hpi-xnor/BMXNet-v2/blob/af2b1859eafc5c721b1397cef02f946aaf2ce20d/python/mxnet/io/io.py#L206-L208
papyrussolution/OpenPapyrus
bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91
Src/OSF/xapian/xapian-bindings/python3/doxy2swig.py
python
Doxy2SWIG.parse
(self, node)
Parse a given node. This function in turn calls the `parse_<nodeType>` functions which handle the respective nodes.
Parse a given node. This function in turn calls the `parse_<nodeType>` functions which handle the respective nodes.
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def parse(self, node): """Parse a given node. This function in turn calls the `parse_<nodeType>` functions which handle the respective nodes. """ pm = getattr(self, "parse_%s"%node.__class__.__name__) pm(node)
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https://github.com/papyrussolution/OpenPapyrus/blob/bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91/Src/OSF/xapian/xapian-bindings/python3/doxy2swig.py#L87-L94
hfinkel/llvm-project-cxxjit
91084ef018240bbb8e24235ff5cd8c355a9c1a1e
clang/bindings/python/clang/cindex.py
python
TranslationUnit.cursor
(self)
return conf.lib.clang_getTranslationUnitCursor(self)
Retrieve the cursor that represents the given translation unit.
Retrieve the cursor that represents the given translation unit.
[ "Retrieve", "the", "cursor", "that", "represents", "the", "given", "translation", "unit", "." ]
def cursor(self): """Retrieve the cursor that represents the given translation unit.""" return conf.lib.clang_getTranslationUnitCursor(self)
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https://github.com/hfinkel/llvm-project-cxxjit/blob/91084ef018240bbb8e24235ff5cd8c355a9c1a1e/clang/bindings/python/clang/cindex.py#L2872-L2874
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/fluid/dataset.py
python
InMemoryDataset.postprocess_instance
(self)
Divide pv instance and convey it to input_channel. Examples: .. code-block:: python import paddle.fluid as fluid dataset = fluid.DatasetFactory().create_dataset("InMemoryDataset") filelist = ["a.txt", "b.txt"] dataset.set_filelist(filelist) dataset.load_into_memory() dataset.preprocess_instance() exe.train_from_dataset(dataset) dataset.postprocess_instance()
Divide pv instance and convey it to input_channel.
[ "Divide", "pv", "instance", "and", "convey", "it", "to", "input_channel", "." ]
def postprocess_instance(self): """ Divide pv instance and convey it to input_channel. Examples: .. code-block:: python import paddle.fluid as fluid dataset = fluid.DatasetFactory().create_dataset("InMemoryDataset") filelist = ["a.txt", "b.txt"] dataset.set_filelist(filelist) dataset.load_into_memory() dataset.preprocess_instance() exe.train_from_dataset(dataset) dataset.postprocess_instance() """ self.dataset.postprocess_instance()
[ "def", "postprocess_instance", "(", "self", ")", ":", "self", ".", "dataset", ".", "postprocess_instance", "(", ")" ]
https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/fluid/dataset.py#L617-L634
hszhao/PSPNet
cf7e5a99ba37e46118026e96be5821a9bc63bde0
scripts/cpp_lint.py
python
_NestingState.Update
(self, filename, clean_lines, linenum, error)
Update nesting state with current line. 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.
Update nesting state with current line.
[ "Update", "nesting", "state", "with", "current", "line", "." ]
def Update(self, filename, clean_lines, linenum, error): """Update nesting state with current line. 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] # Update pp_stack first self.UpdatePreprocessor(line) # Count parentheses. This is to avoid adding struct arguments to # the nesting stack. if self.stack: inner_block = self.stack[-1] depth_change = line.count('(') - line.count(')') inner_block.open_parentheses += depth_change # Also check if we are starting or ending an inline assembly block. if inner_block.inline_asm in (_NO_ASM, _END_ASM): if (depth_change != 0 and inner_block.open_parentheses == 1 and _MATCH_ASM.match(line)): # Enter assembly block inner_block.inline_asm = _INSIDE_ASM else: # Not entering assembly block. If previous line was _END_ASM, # we will now shift to _NO_ASM state. inner_block.inline_asm = _NO_ASM elif (inner_block.inline_asm == _INSIDE_ASM and inner_block.open_parentheses == 0): # Exit assembly block inner_block.inline_asm = _END_ASM # Consume namespace declaration at the beginning of the line. Do # this in a loop so that we catch same line declarations like this: # namespace proto2 { namespace bridge { class MessageSet; } } while True: # Match start of namespace. The "\b\s*" below catches namespace # declarations even if it weren't followed by a whitespace, this # is so that we don't confuse our namespace checker. The # missing spaces will be flagged by CheckSpacing. namespace_decl_match = Match(r'^\s*namespace\b\s*([:\w]+)?(.*)$', line) if not namespace_decl_match: break new_namespace = _NamespaceInfo(namespace_decl_match.group(1), linenum) self.stack.append(new_namespace) line = namespace_decl_match.group(2) if line.find('{') != -1: new_namespace.seen_open_brace = True line = line[line.find('{') + 1:] # Look for a class declaration in whatever is left of the line # after parsing namespaces. The regexp accounts for decorated classes # such as in: # class LOCKABLE API Object { # }; # # Templates with class arguments may confuse the parser, for example: # template <class T # class Comparator = less<T>, # class Vector = vector<T> > # class HeapQueue { # # Because this parser has no nesting state about templates, by the # time it saw "class Comparator", it may think that it's a new class. # Nested templates have a similar problem: # template < # typename ExportedType, # typename TupleType, # template <typename, typename> class ImplTemplate> # # To avoid these cases, we ignore classes that are followed by '=' or '>' class_decl_match = Match( r'\s*(template\s*<[\w\s<>,:]*>\s*)?' r'(class|struct)\s+([A-Z_]+\s+)*(\w+(?:::\w+)*)' r'(([^=>]|<[^<>]*>|<[^<>]*<[^<>]*>\s*>)*)$', line) if (class_decl_match and (not self.stack or self.stack[-1].open_parentheses == 0)): self.stack.append(_ClassInfo( class_decl_match.group(4), class_decl_match.group(2), clean_lines, linenum)) line = class_decl_match.group(5) # If we have not yet seen the opening brace for the innermost block, # run checks here. if not self.SeenOpenBrace(): self.stack[-1].CheckBegin(filename, clean_lines, linenum, error) # Update access control if we are inside a class/struct if self.stack and isinstance(self.stack[-1], _ClassInfo): classinfo = self.stack[-1] access_match = Match( r'^(.*)\b(public|private|protected|signals)(\s+(?:slots\s*)?)?' r':(?:[^:]|$)', line) if access_match: classinfo.access = access_match.group(2) # Check that access keywords are indented +1 space. Skip this # check if the keywords are not preceded by whitespaces. indent = access_match.group(1) if (len(indent) != classinfo.class_indent + 1 and Match(r'^\s*$', indent)): if classinfo.is_struct: parent = 'struct ' + classinfo.name else: parent = 'class ' + classinfo.name slots = '' if access_match.group(3): slots = access_match.group(3) error(filename, linenum, 'whitespace/indent', 3, '%s%s: should be indented +1 space inside %s' % ( access_match.group(2), slots, parent)) # Consume braces or semicolons from what's left of the line while True: # Match first brace, semicolon, or closed parenthesis. matched = Match(r'^[^{;)}]*([{;)}])(.*)$', line) if not matched: break token = matched.group(1) if token == '{': # If namespace or class hasn't seen a opening brace yet, mark # namespace/class head as complete. Push a new block onto the # stack otherwise. if not self.SeenOpenBrace(): self.stack[-1].seen_open_brace = True else: self.stack.append(_BlockInfo(True)) if _MATCH_ASM.match(line): self.stack[-1].inline_asm = _BLOCK_ASM elif token == ';' or token == ')': # If we haven't seen an opening brace yet, but we already saw # a semicolon, this is probably a forward declaration. Pop # the stack for these. # # Similarly, if we haven't seen an opening brace yet, but we # already saw a closing parenthesis, then these are probably # function arguments with extra "class" or "struct" keywords. # Also pop these stack for these. if not self.SeenOpenBrace(): self.stack.pop() else: # token == '}' # Perform end of block checks and pop the stack. if self.stack: self.stack[-1].CheckEnd(filename, clean_lines, linenum, error) self.stack.pop() line = matched.group(2)
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https://github.com/hszhao/PSPNet/blob/cf7e5a99ba37e46118026e96be5821a9bc63bde0/scripts/cpp_lint.py#L2004-L2158
Jittor/jittor
e9aca0444c2bdc8e2389d99122954cd0903eec46
python/jittor/misc.py
python
index_add_
(x, dim, index, tensor)
Take out each index subscript vector of the dim dimension and add the corresponding tensor variable. Example: x = jt.ones((5,3)) tensor = jt.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) index = jt.array([0,4,2]) x.index_add_(0, index, tensor) print(x) >>> jt.Var([[ 2., 3., 4.], [ 1., 1., 1.], [ 8., 9., 10.], [ 1., 1., 1.], [ 5., 6., 7.]])
Take out each index subscript vector of the dim dimension and add the corresponding tensor variable. Example:
[ "Take", "out", "each", "index", "subscript", "vector", "of", "the", "dim", "dimension", "and", "add", "the", "corresponding", "tensor", "variable", ".", "Example", ":" ]
def index_add_(x, dim, index, tensor): """ Take out each index subscript vector of the dim dimension and add the corresponding tensor variable. Example: x = jt.ones((5,3)) tensor = jt.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) index = jt.array([0,4,2]) x.index_add_(0, index, tensor) print(x) >>> jt.Var([[ 2., 3., 4.], [ 1., 1., 1.], [ 8., 9., 10.], [ 1., 1., 1.], [ 5., 6., 7.]]) """ assert len(index.shape) == 1 assert tensor.shape[0] == index.shape[0] x[(slice(None,),)*dim+(index,)] += tensor
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https://github.com/Jittor/jittor/blob/e9aca0444c2bdc8e2389d99122954cd0903eec46/python/jittor/misc.py#L16-L35
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/tools/docs/pretty_docs.py
python
_build_function_page
(page_info)
return ''.join(parts)
Given a FunctionPageInfo object Return the page as an md string.
Given a FunctionPageInfo object Return the page as an md string.
[ "Given", "a", "FunctionPageInfo", "object", "Return", "the", "page", "as", "an", "md", "string", "." ]
def _build_function_page(page_info): """Given a FunctionPageInfo object Return the page as an md string.""" parts = [_Metadata(page_info.full_name).build_html()] parts.append('# %s\n\n' % page_info.full_name) if len(page_info.aliases) > 1: parts.append('### Aliases:\n\n') parts.extend('* `%s`\n' % name for name in page_info.aliases) parts.append('\n') if page_info.signature is not None: parts.append(_build_signature(page_info)) if page_info.defined_in: parts.append('\n\n') parts.append(str(page_info.defined_in)) parts.append(page_info.guides) parts.append(page_info.doc.docstring) parts.append(_build_function_details(page_info.doc.function_details)) parts.append(_build_compatibility(page_info.doc.compatibility)) return ''.join(parts)
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/tools/docs/pretty_docs.py#L59-L81
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/numpy/py2/numpy/distutils/misc_util.py
python
Configuration.make_config_py
(self,name='__config__')
Generate package __config__.py file containing system_info information used during building the package. This file is installed to the package installation directory.
Generate package __config__.py file containing system_info information used during building the package.
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def make_config_py(self,name='__config__'): """Generate package __config__.py file containing system_info information used during building the package. This file is installed to the package installation directory. """ self.py_modules.append((self.name, name, generate_config_py))
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/numpy/py2/numpy/distutils/misc_util.py#L2055-L2063
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pandas/py3/pandas/core/frame.py
python
DataFrame.itertuples
( self, index: bool = True, name: str | None = "Pandas" )
return zip(*arrays)
Iterate over DataFrame rows as namedtuples. Parameters ---------- index : bool, default True If True, return the index as the first element of the tuple. name : str or None, default "Pandas" The name of the returned namedtuples or None to return regular tuples. Returns ------- iterator An object to iterate over namedtuples for each row in the DataFrame with the first field possibly being the index and following fields being the column values. See Also -------- DataFrame.iterrows : Iterate over DataFrame rows as (index, Series) pairs. DataFrame.items : Iterate over (column name, Series) pairs. Notes ----- The column names will be renamed to positional names if they are invalid Python identifiers, repeated, or start with an underscore. On python versions < 3.7 regular tuples are returned for DataFrames with a large number of columns (>254). Examples -------- >>> df = pd.DataFrame({'num_legs': [4, 2], 'num_wings': [0, 2]}, ... index=['dog', 'hawk']) >>> df num_legs num_wings dog 4 0 hawk 2 2 >>> for row in df.itertuples(): ... print(row) ... Pandas(Index='dog', num_legs=4, num_wings=0) Pandas(Index='hawk', num_legs=2, num_wings=2) By setting the `index` parameter to False we can remove the index as the first element of the tuple: >>> for row in df.itertuples(index=False): ... print(row) ... Pandas(num_legs=4, num_wings=0) Pandas(num_legs=2, num_wings=2) With the `name` parameter set we set a custom name for the yielded namedtuples: >>> for row in df.itertuples(name='Animal'): ... print(row) ... Animal(Index='dog', num_legs=4, num_wings=0) Animal(Index='hawk', num_legs=2, num_wings=2)
Iterate over DataFrame rows as namedtuples.
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def itertuples( self, index: bool = True, name: str | None = "Pandas" ) -> Iterable[tuple[Any, ...]]: """ Iterate over DataFrame rows as namedtuples. Parameters ---------- index : bool, default True If True, return the index as the first element of the tuple. name : str or None, default "Pandas" The name of the returned namedtuples or None to return regular tuples. Returns ------- iterator An object to iterate over namedtuples for each row in the DataFrame with the first field possibly being the index and following fields being the column values. See Also -------- DataFrame.iterrows : Iterate over DataFrame rows as (index, Series) pairs. DataFrame.items : Iterate over (column name, Series) pairs. Notes ----- The column names will be renamed to positional names if they are invalid Python identifiers, repeated, or start with an underscore. On python versions < 3.7 regular tuples are returned for DataFrames with a large number of columns (>254). Examples -------- >>> df = pd.DataFrame({'num_legs': [4, 2], 'num_wings': [0, 2]}, ... index=['dog', 'hawk']) >>> df num_legs num_wings dog 4 0 hawk 2 2 >>> for row in df.itertuples(): ... print(row) ... Pandas(Index='dog', num_legs=4, num_wings=0) Pandas(Index='hawk', num_legs=2, num_wings=2) By setting the `index` parameter to False we can remove the index as the first element of the tuple: >>> for row in df.itertuples(index=False): ... print(row) ... Pandas(num_legs=4, num_wings=0) Pandas(num_legs=2, num_wings=2) With the `name` parameter set we set a custom name for the yielded namedtuples: >>> for row in df.itertuples(name='Animal'): ... print(row) ... Animal(Index='dog', num_legs=4, num_wings=0) Animal(Index='hawk', num_legs=2, num_wings=2) """ arrays = [] fields = list(self.columns) if index: arrays.append(self.index) fields.insert(0, "Index") # use integer indexing because of possible duplicate column names arrays.extend(self.iloc[:, k] for k in range(len(self.columns))) if name is not None: # https://github.com/python/mypy/issues/9046 # error: namedtuple() expects a string literal as the first argument itertuple = collections.namedtuple( # type: ignore[misc] name, fields, rename=True ) return map(itertuple._make, zip(*arrays)) # fallback to regular tuples return zip(*arrays)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/core/frame.py#L1266-L1350
SoarGroup/Soar
a1c5e249499137a27da60533c72969eef3b8ab6b
scons/scons-local-4.1.0/SCons/Tool/tex.py
python
tex_pdf_emitter
(target, source, env)
return (target, source)
An emitter for TeX and LaTeX sources when executing pdftex or pdflatex. It will accept graphics files of types .pdf, .jpg, .png, .gif, and .tif
An emitter for TeX and LaTeX sources when executing pdftex or pdflatex. It will accept graphics files of types .pdf, .jpg, .png, .gif, and .tif
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def tex_pdf_emitter(target, source, env): """An emitter for TeX and LaTeX sources when executing pdftex or pdflatex. It will accept graphics files of types .pdf, .jpg, .png, .gif, and .tif """ (target, source) = tex_emitter_core(target, source, env, LatexGraphics) return (target, source)
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https://github.com/SoarGroup/Soar/blob/a1c5e249499137a27da60533c72969eef3b8ab6b/scons/scons-local-4.1.0/SCons/Tool/tex.py#L617-L624
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/botocore/retries/standard.py
python
ExponentialBackoff.delay_amount
(self, context)
return min( self._random() * (self._base ** (context.attempt_number - 1)), self._max_backoff )
Calculates delay based on exponential backoff. This class implements truncated binary exponential backoff with jitter:: t_i = min(rand(0, 1) * 2 ** attempt, MAX_BACKOFF) where ``i`` is the request attempt (0 based).
Calculates delay based on exponential backoff.
[ "Calculates", "delay", "based", "on", "exponential", "backoff", "." ]
def delay_amount(self, context): """Calculates delay based on exponential backoff. This class implements truncated binary exponential backoff with jitter:: t_i = min(rand(0, 1) * 2 ** attempt, MAX_BACKOFF) where ``i`` is the request attempt (0 based). """ # The context.attempt_number is a 1-based value, but we have # to calculate the delay based on i based a 0-based value. We # want the first delay to just be ``rand(0, 1)``. return min( self._random() * (self._base ** (context.attempt_number - 1)), self._max_backoff )
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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/site-packages/botocore/retries/standard.py#L240-L257
yuxng/PoseCNN
9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04
lib/datasets/ycb_single.py
python
ycb_single.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.
[ "Return", "the", "absolute", "path", "to", "depth", "i", "in", "the", "image", "sequence", "." ]
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/ycb_single.py#L90-L94
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/Jinja2/py3/jinja2/utils.py
python
Cycler.next
(self)
return rv
Return the current item, then advance :attr:`current` to the next item.
Return the current item, then advance :attr:`current` to the next item.
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def next(self) -> t.Any: """Return the current item, then advance :attr:`current` to the next item. """ rv = self.current self.pos = (self.pos + 1) % len(self.items) return rv
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/Jinja2/py3/jinja2/utils.py#L787-L793
microsoft/ivy
9f3c7ecc0b2383129fdd0953e10890d98d09a82d
ivy/ivy_transrel.py
python
conjoin
(clauses1,clauses2,annot_op=None)
return and_clauses(clauses1,rename_distinct(clauses2,clauses1),annot_op=annot_op)
Conjoin clause sets, taking into account skolems
Conjoin clause sets, taking into account skolems
[ "Conjoin", "clause", "sets", "taking", "into", "account", "skolems" ]
def conjoin(clauses1,clauses2,annot_op=None): """ Conjoin clause sets, taking into account skolems """ return and_clauses(clauses1,rename_distinct(clauses2,clauses1),annot_op=annot_op)
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https://github.com/microsoft/ivy/blob/9f3c7ecc0b2383129fdd0953e10890d98d09a82d/ivy/ivy_transrel.py#L356-L358
deepmind/open_spiel
4ca53bea32bb2875c7385d215424048ae92f78c8
open_spiel/python/mfg/games/linear_quadratic.py
python
MFGLinearQuadraticState.rewards
(self)
return [self._rewards()]
Rewards for all players.
Rewards for all players.
[ "Rewards", "for", "all", "players", "." ]
def rewards(self) -> List[float]: """Rewards for all players.""" # For now, only single-population (single-player) mean field games # are supported. return [self._rewards()]
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https://github.com/deepmind/open_spiel/blob/4ca53bea32bb2875c7385d215424048ae92f78c8/open_spiel/python/mfg/games/linear_quadratic.py#L331-L335
devsisters/libquic
8954789a056d8e7d5fcb6452fd1572ca57eb5c4e
cpp.py
python
CPP_to_Python
(s)
return s
Converts a C pre-processor expression into an equivalent Python expression that can be evaluated.
Converts a C pre-processor expression into an equivalent Python expression that can be evaluated.
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def CPP_to_Python(s): """ Converts a C pre-processor expression into an equivalent Python expression that can be evaluated. """ s = CPP_to_Python_Ops_Expression.sub(CPP_to_Python_Ops_Sub, s) for expr, repl in CPP_to_Python_Eval_List: s = expr.sub(repl, s) return s
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https://github.com/devsisters/libquic/blob/8954789a056d8e7d5fcb6452fd1572ca57eb5c4e/cpp.py#L157-L165
mantidproject/mantid
03deeb89254ec4289edb8771e0188c2090a02f32
qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/hfctables.py
python
UBMatrixPeakTable.setup
(self)
return
Init setup :return:
Init setup :return:
[ "Init", "setup", ":", "return", ":" ]
def setup(self): """ Init setup :return: """ self.init_setup(UBMatrixPeakTable.UB_Peak_Table_Setup) self.set_status_column_name('Selected') # define all the _colIndex self._colIndexScan = self._myColumnNameList.index('Scan') self._colIndexSpiceHKL = self._myColumnNameList.index('Spice HKL') self._colIndexCalculatedHKL = self._myColumnNameList.index('Calculated HKL') self._colIndexQSample = self._myColumnNameList.index('Q-Sample') self._colIndexWavelength = self._myColumnNameList.index('Wavelength') self._colIndexError = self._myColumnNameList.index('Error') # set up the width of some columns self.setColumnWidth(self._colIndexSpiceHKL, 240) self.setColumnWidth(self._colIndexCalculatedHKL, 240) self.setColumnWidth(4, 240) return
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/hfctables.py#L1829-L1850
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/protobuf/py3/google/protobuf/internal/well_known_types.py
python
_StrConvert
(value)
return value
Converts value to str if it is not.
Converts value to str if it is not.
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def _StrConvert(value): """Converts value to str if it is not.""" # This file is imported by c extension and some methods like ClearField # requires string for the field name. py2/py3 has different text # type and may use unicode. if not isinstance(value, str): return value.encode('utf-8') return value
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/protobuf/py3/google/protobuf/internal/well_known_types.py#L654-L661
envoyproxy/envoy
65541accdafe255e72310b4298d646e091da2d80
contrib/kafka/filters/network/source/serialization/launcher.py
python
main
()
Serialization composite code generator ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Generates main source code files for composite deserializers. The files are generated, as they are extremely repetitive (composite deserializer for 0..9 sub-deserializers). Usage: launcher.py LOCATION_OF_OUTPUT_FILE where: LOCATION_OF_OUTPUT_FILE : location of 'serialization_composite.h'. Creates 'serialization_composite.h' - header with declarations of CompositeDeserializerWith???Delegates classes. Template used: 'serialization_composite_h.j2'.
Serialization composite code generator ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Generates main source code files for composite deserializers. The files are generated, as they are extremely repetitive (composite deserializer for 0..9 sub-deserializers).
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def main(): """ Serialization composite code generator ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Generates main source code files for composite deserializers. The files are generated, as they are extremely repetitive (composite deserializer for 0..9 sub-deserializers). Usage: launcher.py LOCATION_OF_OUTPUT_FILE where: LOCATION_OF_OUTPUT_FILE : location of 'serialization_composite.h'. Creates 'serialization_composite.h' - header with declarations of CompositeDeserializerWith???Delegates classes. Template used: 'serialization_composite_h.j2'. """ serialization_composite_h_file = os.path.abspath(sys.argv[1]) generator.generate_main_code(serialization_composite_h_file)
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https://github.com/envoyproxy/envoy/blob/65541accdafe255e72310b4298d646e091da2d80/contrib/kafka/filters/network/source/serialization/launcher.py#L10-L29
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_misc.py
python
TimeSpan_Millisecond
(*args)
return _misc_.TimeSpan_Millisecond(*args)
TimeSpan_Millisecond() -> TimeSpan
TimeSpan_Millisecond() -> TimeSpan
[ "TimeSpan_Millisecond", "()", "-", ">", "TimeSpan" ]
def TimeSpan_Millisecond(*args): """TimeSpan_Millisecond() -> TimeSpan""" return _misc_.TimeSpan_Millisecond(*args)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_misc.py#L4560-L4562
baidu/unit-uskit
ee283f3be42a1dadaef80751d4ed4358ee83c2e8
conf/us/demo/conf_generator.py
python
generate_rank_conf
()
Generate rank.conf
Generate rank.conf
[ "Generate", "rank", ".", "conf" ]
def generate_rank_conf(): """ Generate rank.conf """ print('generating rank conf...') with open('./conf_templates/rank.conf.template') as fin, open('rank.conf', 'w') as fout: skill_rank = '\n'.join([' order: "{}"'.format(x) for x in options['skill_rank']]) template = ConfTemplate(fin.read()) print(template.substitute({'skill_rank' : skill_rank}), file=fout)
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https://github.com/baidu/unit-uskit/blob/ee283f3be42a1dadaef80751d4ed4358ee83c2e8/conf/us/demo/conf_generator.py#L107-L115
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py3/scipy/interpolate/interpolate.py
python
interp2d.__call__
(self, x, y, dx=0, dy=0, assume_sorted=False)
return array(z)
Interpolate the function. Parameters ---------- x : 1D array x-coordinates of the mesh on which to interpolate. y : 1D array y-coordinates of the mesh on which to interpolate. dx : int >= 0, < kx Order of partial derivatives in x. dy : int >= 0, < ky Order of partial derivatives in y. assume_sorted : bool, optional If False, values of `x` and `y` can be in any order and they are sorted first. If True, `x` and `y` have to be arrays of monotonically increasing values. Returns ------- z : 2D array with shape (len(y), len(x)) The interpolated values.
Interpolate the function.
[ "Interpolate", "the", "function", "." ]
def __call__(self, x, y, dx=0, dy=0, assume_sorted=False): """Interpolate the function. Parameters ---------- x : 1D array x-coordinates of the mesh on which to interpolate. y : 1D array y-coordinates of the mesh on which to interpolate. dx : int >= 0, < kx Order of partial derivatives in x. dy : int >= 0, < ky Order of partial derivatives in y. assume_sorted : bool, optional If False, values of `x` and `y` can be in any order and they are sorted first. If True, `x` and `y` have to be arrays of monotonically increasing values. Returns ------- z : 2D array with shape (len(y), len(x)) The interpolated values. """ x = atleast_1d(x) y = atleast_1d(y) if x.ndim != 1 or y.ndim != 1: raise ValueError("x and y should both be 1-D arrays") if not assume_sorted: x = np.sort(x) y = np.sort(y) if self.bounds_error or self.fill_value is not None: out_of_bounds_x = (x < self.x_min) | (x > self.x_max) out_of_bounds_y = (y < self.y_min) | (y > self.y_max) any_out_of_bounds_x = np.any(out_of_bounds_x) any_out_of_bounds_y = np.any(out_of_bounds_y) if self.bounds_error and (any_out_of_bounds_x or any_out_of_bounds_y): raise ValueError("Values out of range; x must be in %r, y in %r" % ((self.x_min, self.x_max), (self.y_min, self.y_max))) z = fitpack.bisplev(x, y, self.tck, dx, dy) z = atleast_2d(z) z = transpose(z) if self.fill_value is not None: if any_out_of_bounds_x: z[:, out_of_bounds_x] = self.fill_value if any_out_of_bounds_y: z[out_of_bounds_y, :] = self.fill_value if len(z) == 1: z = z[0] return array(z)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py3/scipy/interpolate/interpolate.py#L260-L319
apache/madlib
be297fe6beada0640f93317e8948834032718e32
src/madpack/upgrade_util.py
python
ChangeHandler._add_to_dict
(cls, src_dict, dest_dict)
Update dictionary with contents of another dictionary This function performs the same function as dict.update except it adds to an existing value (instead of replacing it) if the value is an Iterable.
Update dictionary with contents of another dictionary
[ "Update", "dictionary", "with", "contents", "of", "another", "dictionary" ]
def _add_to_dict(cls, src_dict, dest_dict): """ Update dictionary with contents of another dictionary This function performs the same function as dict.update except it adds to an existing value (instead of replacing it) if the value is an Iterable. """ if src_dict: for k, v in src_dict.items(): if k in dest_dict: if (isinstance(dest_dict[k], Iterable) and isinstance(v, Iterable)): dest_dict[k] += v elif isinstance(dest_dict[k], Iterable): dest_dict[k].append(v) else: dest_dict[k] = v else: dest_dict[k] = v return dest_dict
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https://github.com/apache/madlib/blob/be297fe6beada0640f93317e8948834032718e32/src/madpack/upgrade_util.py#L190-L208
fatih/subvim
241b6d170597857105da219c9b7d36059e9f11fb
vim/base/YouCompleteMe/third_party/jedi/jedi/refactoring.py
python
Refactoring.__init__
(self, change_dct)
:param change_dct: dict(old_path=(new_path, old_lines, new_lines))
:param change_dct: dict(old_path=(new_path, old_lines, new_lines))
[ ":", "param", "change_dct", ":", "dict", "(", "old_path", "=", "(", "new_path", "old_lines", "new_lines", "))" ]
def __init__(self, change_dct): """ :param change_dct: dict(old_path=(new_path, old_lines, new_lines)) """ self.change_dct = change_dct
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https://github.com/fatih/subvim/blob/241b6d170597857105da219c9b7d36059e9f11fb/vim/base/YouCompleteMe/third_party/jedi/jedi/refactoring.py#L26-L30
microsoft/clang
86d4513d3e0daa4d5a29b0b1de7c854ca15f9fe5
bindings/python/clang/cindex.py
python
File.time
(self)
return conf.lib.clang_getFileTime(self)
Return the last modification time of the file.
Return the last modification time of the file.
[ "Return", "the", "last", "modification", "time", "of", "the", "file", "." ]
def time(self): """Return the last modification time of the file.""" return conf.lib.clang_getFileTime(self)
[ "def", "time", "(", "self", ")", ":", "return", "conf", ".", "lib", ".", "clang_getFileTime", "(", "self", ")" ]
https://github.com/microsoft/clang/blob/86d4513d3e0daa4d5a29b0b1de7c854ca15f9fe5/bindings/python/clang/cindex.py#L3089-L3091
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/mapreduce/mapreduce/model.py
python
TransientShardState.from_request
(cls, request)
return cls(mapreduce_spec.params["base_path"], mapreduce_spec, str(request.get("shard_id")), int(request.get("slice_id")), input_reader, initial_input_reader, output_writer=output_writer, retries=int(request.get("retries")), handler=handler)
Create new TransientShardState from webapp request.
Create new TransientShardState from webapp request.
[ "Create", "new", "TransientShardState", "from", "webapp", "request", "." ]
def from_request(cls, request): """Create new TransientShardState from webapp request.""" mapreduce_spec = MapreduceSpec.from_json_str(request.get("mapreduce_spec")) mapper_spec = mapreduce_spec.mapper input_reader_spec_dict = json.loads(request.get("input_reader_state"), cls=json_util.JsonDecoder) input_reader = mapper_spec.input_reader_class().from_json( input_reader_spec_dict) initial_input_reader_spec_dict = json.loads( request.get("initial_input_reader_state"), cls=json_util.JsonDecoder) initial_input_reader = mapper_spec.input_reader_class().from_json( initial_input_reader_spec_dict) output_writer = None if mapper_spec.output_writer_class(): output_writer = mapper_spec.output_writer_class().from_json( json.loads(request.get("output_writer_state", "{}"), cls=json_util.JsonDecoder)) assert isinstance(output_writer, mapper_spec.output_writer_class()), ( "%s.from_json returned an instance of wrong class: %s" % ( mapper_spec.output_writer_class(), output_writer.__class__)) handler = util.try_deserialize_handler(request.get("serialized_handler")) if not handler: handler = mapreduce_spec.mapper.handler return cls(mapreduce_spec.params["base_path"], mapreduce_spec, str(request.get("shard_id")), int(request.get("slice_id")), input_reader, initial_input_reader, output_writer=output_writer, retries=int(request.get("retries")), handler=handler)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/mapreduce/mapreduce/model.py#L820-L855
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_vendor/requests/cookies.py
python
RequestsCookieJar.itervalues
(self)
Dict-like itervalues() that returns an iterator of values of cookies from the jar. .. seealso:: iterkeys() and iteritems().
Dict-like itervalues() that returns an iterator of values of cookies from the jar.
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def itervalues(self): """Dict-like itervalues() that returns an iterator of values of cookies from the jar. .. seealso:: iterkeys() and iteritems(). """ for cookie in iter(self): yield cookie.value
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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/site-packages/pip/_vendor/requests/cookies.py#L235-L242
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/numpy/py3/numpy/distutils/fcompiler/__init__.py
python
FCompiler.customize
(self, dist = None)
Customize Fortran compiler. This method gets Fortran compiler specific information from (i) class definition, (ii) environment, (iii) distutils config files, and (iv) command line (later overrides earlier). This method should be always called after constructing a compiler instance. But not in __init__ because Distribution instance is needed for (iii) and (iv).
Customize Fortran compiler.
[ "Customize", "Fortran", "compiler", "." ]
def customize(self, dist = None): """Customize Fortran compiler. This method gets Fortran compiler specific information from (i) class definition, (ii) environment, (iii) distutils config files, and (iv) command line (later overrides earlier). This method should be always called after constructing a compiler instance. But not in __init__ because Distribution instance is needed for (iii) and (iv). """ log.info('customize %s' % (self.__class__.__name__)) self._is_customised = True self.distutils_vars.use_distribution(dist) self.command_vars.use_distribution(dist) self.flag_vars.use_distribution(dist) self.update_executables() # find_executables takes care of setting the compiler commands, # version_cmd, linker_so, linker_exe, ar, and ranlib self.find_executables() noopt = self.distutils_vars.get('noopt', False) noarch = self.distutils_vars.get('noarch', noopt) debug = self.distutils_vars.get('debug', False) f77 = self.command_vars.compiler_f77 f90 = self.command_vars.compiler_f90 f77flags = [] f90flags = [] freeflags = [] fixflags = [] if f77: f77 = _shell_utils.NativeParser.split(f77) f77flags = self.flag_vars.f77 if f90: f90 = _shell_utils.NativeParser.split(f90) f90flags = self.flag_vars.f90 freeflags = self.flag_vars.free # XXX Assuming that free format is default for f90 compiler. fix = self.command_vars.compiler_fix # NOTE: this and similar examples are probably just # excluding --coverage flag when F90 = gfortran --coverage # instead of putting that flag somewhere more appropriate # this and similar examples where a Fortran compiler # environment variable has been customized by CI or a user # should perhaps eventually be more thoroughly tested and more # robustly handled if fix: fix = _shell_utils.NativeParser.split(fix) fixflags = self.flag_vars.fix + f90flags oflags, aflags, dflags = [], [], [] # examine get_flags_<tag>_<compiler> for extra flags # only add them if the method is different from get_flags_<tag> def get_flags(tag, flags): # note that self.flag_vars.<tag> calls self.get_flags_<tag>() flags.extend(getattr(self.flag_vars, tag)) this_get = getattr(self, 'get_flags_' + tag) for name, c, flagvar in [('f77', f77, f77flags), ('f90', f90, f90flags), ('f90', fix, fixflags)]: t = '%s_%s' % (tag, name) if c and this_get is not getattr(self, 'get_flags_' + t): flagvar.extend(getattr(self.flag_vars, t)) if not noopt: get_flags('opt', oflags) if not noarch: get_flags('arch', aflags) if debug: get_flags('debug', dflags) fflags = self.flag_vars.flags + dflags + oflags + aflags if f77: self.set_commands(compiler_f77=f77+f77flags+fflags) if f90: self.set_commands(compiler_f90=f90+freeflags+f90flags+fflags) if fix: self.set_commands(compiler_fix=fix+fixflags+fflags) #XXX: Do we need LDSHARED->SOSHARED, LDFLAGS->SOFLAGS linker_so = self.linker_so if linker_so: linker_so_flags = self.flag_vars.linker_so if sys.platform.startswith('aix'): python_lib = get_python_lib(standard_lib=1) ld_so_aix = os.path.join(python_lib, 'config', 'ld_so_aix') python_exp = os.path.join(python_lib, 'config', 'python.exp') linker_so = [ld_so_aix] + linker_so + ['-bI:'+python_exp] self.set_commands(linker_so=linker_so+linker_so_flags) linker_exe = self.linker_exe if linker_exe: linker_exe_flags = self.flag_vars.linker_exe self.set_commands(linker_exe=linker_exe+linker_exe_flags) ar = self.command_vars.archiver if ar: arflags = self.flag_vars.ar self.set_commands(archiver=[ar]+arflags) self.set_library_dirs(self.get_library_dirs()) self.set_libraries(self.get_libraries())
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"linker_so_flags", "=", "self", ".", "flag_vars", ".", "linker_so", "if", "sys", ".", "platform", ".", "startswith", "(", "'aix'", ")", ":", "python_lib", "=", "get_python_lib", "(", "standard_lib", "=", "1", ")", "ld_so_aix", "=", "os", ".", "path", ".", "join", "(", "python_lib", ",", "'config'", ",", "'ld_so_aix'", ")", "python_exp", "=", "os", ".", "path", ".", "join", "(", "python_lib", ",", "'config'", ",", "'python.exp'", ")", "linker_so", "=", "[", "ld_so_aix", "]", "+", "linker_so", "+", "[", "'-bI:'", "+", "python_exp", "]", "self", ".", "set_commands", "(", "linker_so", "=", "linker_so", "+", "linker_so_flags", ")", "linker_exe", "=", "self", ".", "linker_exe", "if", "linker_exe", ":", "linker_exe_flags", "=", "self", ".", "flag_vars", ".", "linker_exe", "self", ".", "set_commands", "(", "linker_exe", "=", "linker_exe", "+", "linker_exe_flags", ")", "ar", "=", "self", ".", "command_vars", ".", "archiver", "if", "ar", ":", "arflags", "=", "self", ".", "flag_vars", ".", "ar", "self", ".", "set_commands", "(", "archiver", "=", "[", "ar", "]", "+", "arflags", ")", "self", ".", "set_library_dirs", "(", "self", ".", "get_library_dirs", "(", ")", ")", "self", ".", "set_libraries", "(", "self", ".", "get_libraries", "(", ")", ")" ]
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/numpy/py3/numpy/distutils/fcompiler/__init__.py#L434-L543
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/psutil/_pswindows.py
python
convert_dos_path
(s)
return os.path.join(driveletter, remainder)
r"""Convert paths using native DOS format like: "\Device\HarddiskVolume1\Windows\systemew\file.txt" into: "C:\Windows\systemew\file.txt"
r"""Convert paths using native DOS format like: "\Device\HarddiskVolume1\Windows\systemew\file.txt" into: "C:\Windows\systemew\file.txt"
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def convert_dos_path(s): r"""Convert paths using native DOS format like: "\Device\HarddiskVolume1\Windows\systemew\file.txt" into: "C:\Windows\systemew\file.txt" """ rawdrive = '\\'.join(s.split('\\')[:3]) driveletter = cext.win32_QueryDosDevice(rawdrive) remainder = s[len(rawdrive):] return os.path.join(driveletter, remainder)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/psutil/_pswindows.py#L193-L202
apache/arrow
af33dd1157eb8d7d9bfac25ebf61445b793b7943
python/benchmarks/common.py
python
BuiltinsGenerator.generate_decimal_list
(self, n, none_prob=DEFAULT_NONE_PROB, use_nan=False)
return data
Generate a list of Python Decimals with *none_prob* probability of an entry being None (or NaN if *use_nan* is true).
Generate a list of Python Decimals with *none_prob* probability of an entry being None (or NaN if *use_nan* is true).
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def generate_decimal_list(self, n, none_prob=DEFAULT_NONE_PROB, use_nan=False): """ Generate a list of Python Decimals with *none_prob* probability of an entry being None (or NaN if *use_nan* is true). """ data = [decimal.Decimal('%.9f' % f) for f in self.rnd.uniform(0.0, 1.0, n)] assert len(data) == n self.sprinkle(data, none_prob, value=decimal.Decimal('nan') if use_nan else None) return data
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https://github.com/apache/arrow/blob/af33dd1157eb8d7d9bfac25ebf61445b793b7943/python/benchmarks/common.py#L159-L170
OGRECave/ogre-next
287307980e6de8910f04f3cc0994451b075071fd
Tools/BlenderExport/ogrepkg/gui.py
python
Widget.removeFromParent
(self)
return
Remove this widget from parent widget. Remove a widget from its parent before deleting it. Overwrite this to also remove all button actions separately with a call to <code>self.parent._removeButtonAction()</code>. This is not done in the destructor as Python's garbage collector does not guarantee to delete objects.
Remove this widget from parent widget. Remove a widget from its parent before deleting it. Overwrite this to also remove all button actions separately with a call to <code>self.parent._removeButtonAction()</code>. This is not done in the destructor as Python's garbage collector does not guarantee to delete objects.
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def removeFromParent(self): """Remove this widget from parent widget. Remove a widget from its parent before deleting it. Overwrite this to also remove all button actions separately with a call to <code>self.parent._removeButtonAction()</code>. This is not done in the destructor as Python's garbage collector does not guarantee to delete objects. """ self.parent._removeWidget(self) return
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https://github.com/OGRECave/ogre-next/blob/287307980e6de8910f04f3cc0994451b075071fd/Tools/BlenderExport/ogrepkg/gui.py#L138-L148
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/x86/toolchain/lib/python2.7/wsgiref/handlers.py
python
BaseHandler.send_preamble
(self)
Transmit version/status/date/server, via self._write()
Transmit version/status/date/server, via self._write()
[ "Transmit", "version", "/", "status", "/", "date", "/", "server", "via", "self", ".", "_write", "()" ]
def send_preamble(self): """Transmit version/status/date/server, via self._write()""" if self.origin_server: if self.client_is_modern(): self._write('HTTP/%s %s\r\n' % (self.http_version,self.status)) if 'Date' not in self.headers: self._write( 'Date: %s\r\n' % format_date_time(time.time()) ) if self.server_software and 'Server' not in self.headers: self._write('Server: %s\r\n' % self.server_software) else: self._write('Status: %s\r\n' % self.status)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/wsgiref/handlers.py#L187-L199
hughperkins/tf-coriander
970d3df6c11400ad68405f22b0c42a52374e94ca
tensorflow/python/ops/image_ops.py
python
flip_up_down
(image)
return array_ops.reverse(image, [True, False, False])
Flip an image horizontally (upside down). Outputs the contents of `image` flipped along the first dimension, which is `height`. See also `reverse()`. Args: image: A 3-D tensor of shape `[height, width, channels].` Returns: A 3-D tensor of the same type and shape as `image`. Raises: ValueError: if the shape of `image` not supported.
Flip an image horizontally (upside down).
[ "Flip", "an", "image", "horizontally", "(", "upside", "down", ")", "." ]
def flip_up_down(image): """Flip an image horizontally (upside down). Outputs the contents of `image` flipped along the first dimension, which is `height`. See also `reverse()`. Args: image: A 3-D tensor of shape `[height, width, channels].` Returns: A 3-D tensor of the same type and shape as `image`. Raises: ValueError: if the shape of `image` not supported. """ image = ops.convert_to_tensor(image, name='image') _Check3DImage(image, require_static=False) return array_ops.reverse(image, [True, False, False])
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https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/python/ops/image_ops.py#L382-L401
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scikit-learn/py3/sklearn/linear_model/_logistic.py
python
_logistic_loss
(w, X, y, alpha, sample_weight=None)
return out
Computes the logistic loss. Parameters ---------- w : ndarray of shape (n_features,) or (n_features + 1,) Coefficient vector. X : {array-like, sparse matrix} of shape (n_samples, n_features) Training data. y : ndarray of shape (n_samples,) Array of labels. alpha : float Regularization parameter. alpha is equal to 1 / C. sample_weight : array-like of shape (n_samples,) default=None Array of weights that are assigned to individual samples. If not provided, then each sample is given unit weight. Returns ------- out : float Logistic loss.
Computes the logistic loss.
[ "Computes", "the", "logistic", "loss", "." ]
def _logistic_loss(w, X, y, alpha, sample_weight=None): """Computes the logistic loss. Parameters ---------- w : ndarray of shape (n_features,) or (n_features + 1,) Coefficient vector. X : {array-like, sparse matrix} of shape (n_samples, n_features) Training data. y : ndarray of shape (n_samples,) Array of labels. alpha : float Regularization parameter. alpha is equal to 1 / C. sample_weight : array-like of shape (n_samples,) default=None Array of weights that are assigned to individual samples. If not provided, then each sample is given unit weight. Returns ------- out : float Logistic loss. """ w, c, yz = _intercept_dot(w, X, y) if sample_weight is None: sample_weight = np.ones(y.shape[0]) # Logistic loss is the negative of the log of the logistic function. out = -np.sum(sample_weight * log_logistic(yz)) + .5 * alpha * np.dot(w, w) return out
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scikit-learn/py3/sklearn/linear_model/_logistic.py#L137-L170
albertz/openlierox
d316c14a8eb57848ef56e9bfa7b23a56f694a51b
tools/DedicatedServerVideo/gdata/apps/groups/service.py
python
GroupsService.CreateGroup
(self, group_id, group_name, description, email_permission)
return self._PostProperties(uri, properties)
Create a group. Args: group_id: The ID of the group (e.g. us-sales). group_name: The name of the group. description: A description of the group email_permission: The subscription permission of the group. Returns: A dict containing the result of the create operation.
Create a group.
[ "Create", "a", "group", "." ]
def CreateGroup(self, group_id, group_name, description, email_permission): """Create a group. Args: group_id: The ID of the group (e.g. us-sales). group_name: The name of the group. description: A description of the group email_permission: The subscription permission of the group. Returns: A dict containing the result of the create operation. """ uri = self._ServiceUrl('group', False, group_id, '', '', '', '') properties = {} properties['groupId'] = group_id properties['groupName'] = group_name properties['description'] = description properties['emailPermission'] = email_permission return self._PostProperties(uri, properties)
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https://github.com/albertz/openlierox/blob/d316c14a8eb57848ef56e9bfa7b23a56f694a51b/tools/DedicatedServerVideo/gdata/apps/groups/service.py#L91-L109
apache/thrift
0b29261a4f3c6882ef3b09aae47914f0012b0472
lib/py/src/server/TNonblockingServer.py
python
Connection.is_readable
(self)
return self.status in (WAIT_LEN, WAIT_MESSAGE)
Return True if connection should be added to read list of select
Return True if connection should be added to read list of select
[ "Return", "True", "if", "connection", "should", "be", "added", "to", "read", "list", "of", "select" ]
def is_readable(self): """Return True if connection should be added to read list of select""" return self.status in (WAIT_LEN, WAIT_MESSAGE)
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https://github.com/apache/thrift/blob/0b29261a4f3c6882ef3b09aae47914f0012b0472/lib/py/src/server/TNonblockingServer.py#L214-L216
miyosuda/TensorFlowAndroidMNIST
7b5a4603d2780a8a2834575706e9001977524007
jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/dnn.py
python
DNNRegressor._get_predict_ops
(self, features)
return super(DNNRegressor, self)._get_predict_ops(features)
See base class.
See base class.
[ "See", "base", "class", "." ]
def _get_predict_ops(self, features): """See base class.""" self._validate_dnn_feature_columns(features) return super(DNNRegressor, self)._get_predict_ops(features)
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/dnn.py#L347-L350
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/Pygments/py3/pygments/lexer.py
python
RegexLexer.get_tokens_unprocessed
(self, text, stack=('root',))
Split ``text`` into (tokentype, text) pairs. ``stack`` is the inital stack (default: ``['root']``)
Split ``text`` into (tokentype, text) pairs.
[ "Split", "text", "into", "(", "tokentype", "text", ")", "pairs", "." ]
def get_tokens_unprocessed(self, text, stack=('root',)): """ Split ``text`` into (tokentype, text) pairs. ``stack`` is the inital stack (default: ``['root']``) """ pos = 0 tokendefs = self._tokens statestack = list(stack) statetokens = tokendefs[statestack[-1]] while 1: for rexmatch, action, new_state in statetokens: m = rexmatch(text, pos) if m: if action is not None: if type(action) is _TokenType: yield pos, action, m.group() else: yield from action(self, m) pos = m.end() if new_state is not None: # state transition if isinstance(new_state, tuple): for state in new_state: if state == '#pop': if len(statestack) > 1: statestack.pop() elif state == '#push': statestack.append(statestack[-1]) else: statestack.append(state) elif isinstance(new_state, int): # pop, but keep at least one state on the stack # (random code leading to unexpected pops should # not allow exceptions) if abs(new_state) >= len(statestack): del statestack[1:] else: del statestack[new_state:] elif new_state == '#push': statestack.append(statestack[-1]) else: assert False, "wrong state def: %r" % new_state statetokens = tokendefs[statestack[-1]] break else: # We are here only if all state tokens have been considered # and there was not a match on any of them. try: if text[pos] == '\n': # at EOL, reset state to "root" statestack = ['root'] statetokens = tokendefs['root'] yield pos, Text, '\n' pos += 1 continue yield pos, Error, text[pos] pos += 1 except IndexError: break
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/Pygments/py3/pygments/lexer.py#L617-L676
CRYTEK/CRYENGINE
232227c59a220cbbd311576f0fbeba7bb53b2a8c
Editor/Python/windows/Lib/site-packages/setuptools/__init__.py
python
Command.ensure_string_list
(self, option)
r"""Ensure that 'option' is a list of strings. If 'option' is currently a string, we split it either on /,\s*/ or /\s+/, so "foo bar baz", "foo,bar,baz", and "foo, bar baz" all become ["foo", "bar", "baz"].
r"""Ensure that 'option' is a list of strings. If 'option' is currently a string, we split it either on /,\s*/ or /\s+/, so "foo bar baz", "foo,bar,baz", and "foo, bar baz" all become ["foo", "bar", "baz"].
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def ensure_string_list(self, option): r"""Ensure that 'option' is a list of strings. If 'option' is currently a string, we split it either on /,\s*/ or /\s+/, so "foo bar baz", "foo,bar,baz", and "foo, bar baz" all become ["foo", "bar", "baz"]. """ val = getattr(self, option) if val is None: return elif isinstance(val, string_types): setattr(self, option, re.split(r',\s*|\s+', val)) else: if isinstance(val, list): ok = all(isinstance(v, string_types) for v in val) else: ok = False if not ok: raise DistutilsOptionError( "'%s' must be a list of strings (got %r)" % (option, val))
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https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/setuptools/__init__.py#L176-L195
bigartm/bigartm
47e37f982de87aa67bfd475ff1f39da696b181b3
3rdparty/protobuf-3.0.0/python/google/protobuf/internal/python_message.py
python
_AddReprMethod
(message_descriptor, cls)
Helper for _AddMessageMethods().
Helper for _AddMessageMethods().
[ "Helper", "for", "_AddMessageMethods", "()", "." ]
def _AddReprMethod(message_descriptor, cls): """Helper for _AddMessageMethods().""" def __repr__(self): return text_format.MessageToString(self) cls.__repr__ = __repr__
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https://github.com/bigartm/bigartm/blob/47e37f982de87aa67bfd475ff1f39da696b181b3/3rdparty/protobuf-3.0.0/python/google/protobuf/internal/python_message.py#L988-L992
albertz/openlierox
d316c14a8eb57848ef56e9bfa7b23a56f694a51b
tools/DedicatedServerVideo/atom/mock_http_core.py
python
MockHttpClient._dump
(self)
return output
Provides debug information in a string.
Provides debug information in a string.
[ "Provides", "debug", "information", "in", "a", "string", "." ]
def _dump(self): """Provides debug information in a string.""" output = 'MockHttpClient\n real_client: %s\n cache file name: %s\n' % ( self.real_client, self.get_cache_file_name()) output += ' recordings:\n' i = 0 for recording in self._recordings: output += ' recording %i is for: %s %s\n' % ( i, recording[0].method, str(recording[0].uri)) i += 1 return output
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https://github.com/albertz/openlierox/blob/d316c14a8eb57848ef56e9bfa7b23a56f694a51b/tools/DedicatedServerVideo/atom/mock_http_core.py#L165-L175
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/difflib.py
python
SequenceMatcher.quick_ratio
(self)
return _calculate_ratio(matches, len(self.a) + len(self.b))
Return an upper bound on ratio() relatively quickly. This isn't defined beyond that it is an upper bound on .ratio(), and is faster to compute.
Return an upper bound on ratio() relatively quickly.
[ "Return", "an", "upper", "bound", "on", "ratio", "()", "relatively", "quickly", "." ]
def quick_ratio(self): """Return an upper bound on ratio() relatively quickly. This isn't defined beyond that it is an upper bound on .ratio(), and is faster to compute. """ # viewing a and b as multisets, set matches to the cardinality # of their intersection; this counts the number of matches # without regard to order, so is clearly an upper bound if self.fullbcount is None: self.fullbcount = fullbcount = {} for elt in self.b: fullbcount[elt] = fullbcount.get(elt, 0) + 1 fullbcount = self.fullbcount # avail[x] is the number of times x appears in 'b' less the # number of times we've seen it in 'a' so far ... kinda avail = {} availhas, matches = avail.__contains__, 0 for elt in self.a: if availhas(elt): numb = avail[elt] else: numb = fullbcount.get(elt, 0) avail[elt] = numb - 1 if numb > 0: matches = matches + 1 return _calculate_ratio(matches, len(self.a) + len(self.b))
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/difflib.py#L647-L674
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/zoombar.py
python
ZoomBar.EnableButton
(self, index, enable=True)
return True
Enables/disables the button at position `index`. :param `index`: the index of the button to enable/disable; :param `enable`: ``True`` to enable the button, ``False`` to disable it.
Enables/disables the button at position `index`.
[ "Enables", "/", "disables", "the", "button", "at", "position", "index", "." ]
def EnableButton(self, index, enable=True): """ Enables/disables the button at position `index`. :param `index`: the index of the button to enable/disable; :param `enable`: ``True`` to enable the button, ``False`` to disable it. """ if index < 0 or index >= len(self._buttons): return False self._buttons[index].Enable(enable) self.Refresh() return True
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/zoombar.py#L987-L1001
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/py/filling.py
python
FillingTree.setText
(self, text)
Display information about the current selection.
Display information about the current selection.
[ "Display", "information", "about", "the", "current", "selection", "." ]
def setText(self, text): """Display information about the current selection.""" # This method will likely be replaced by the enclosing app to # do something more interesting, like write to a text control. print text
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/py/filling.py#L232-L237
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/scipy/stats/_multivariate.py
python
special_ortho_group_gen.rvs
(self, dim, size=1, random_state=None)
return H
Draw random samples from SO(N). Parameters ---------- dim : integer Dimension of rotation space (N). size : integer, optional Number of samples to draw (default 1). Returns ------- rvs : ndarray or scalar Random size N-dimensional matrices, dimension (size, dim, dim)
Draw random samples from SO(N).
[ "Draw", "random", "samples", "from", "SO", "(", "N", ")", "." ]
def rvs(self, dim, size=1, random_state=None): """ Draw random samples from SO(N). Parameters ---------- dim : integer Dimension of rotation space (N). size : integer, optional Number of samples to draw (default 1). Returns ------- rvs : ndarray or scalar Random size N-dimensional matrices, dimension (size, dim, dim) """ size = int(size) if size > 1: return np.array([self.rvs(dim, size=1, random_state=random_state) for i in range(size)]) dim = self._process_parameters(dim) random_state = self._get_random_state(random_state) H = np.eye(dim) D = np.ones((dim,)) for n in range(1, dim): x = random_state.normal(size=(dim-n+1,)) D[n-1] = np.sign(x[0]) x[0] -= D[n-1]*np.sqrt((x*x).sum()) # Householder transformation Hx = (np.eye(dim-n+1) - 2.*np.outer(x, x)/(x*x).sum()) mat = np.eye(dim) mat[n-1:, n-1:] = Hx H = np.dot(H, mat) # Fix the last sign such that the determinant is 1 D[-1] = (-1)**(1-(dim % 2))*D.prod() # Equivalent to np.dot(np.diag(D), H) but faster, apparently H = (D*H.T).T return H
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/stats/_multivariate.py#L2729-L2772
microsoft/checkedc-clang
a173fefde5d7877b7750e7ce96dd08cf18baebf2
lldb/third_party/Python/module/pexpect-4.6/pexpect/pty_spawn.py
python
spawn.writelines
(self, sequence)
This calls write() for each element in the sequence. The sequence can be any iterable object producing strings, typically a list of strings. This does not add line separators. There is no return value.
This calls write() for each element in the sequence. The sequence can be any iterable object producing strings, typically a list of strings. This does not add line separators. There is no return value.
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def writelines(self, sequence): '''This calls write() for each element in the sequence. The sequence can be any iterable object producing strings, typically a list of strings. This does not add line separators. There is no return value. ''' for s in sequence: self.write(s)
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https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/lldb/third_party/Python/module/pexpect-4.6/pexpect/pty_spawn.py#L495-L502
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/tools/Editra/src/autocomp/pycomp.py
python
Scope.pop
(self, indent)
return outer
Pop the scope until it is at the level of the given indent. @param indent: indent level to pop scope to @return: scope of given indent level
Pop the scope until it is at the level of the given indent. @param indent: indent level to pop scope to @return: scope of given indent level
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def pop(self, indent): """Pop the scope until it is at the level of the given indent. @param indent: indent level to pop scope to @return: scope of given indent level """ outer = self while outer.parent != None and outer.indent >= indent: outer = outer.parent return outer
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/autocomp/pycomp.py#L511-L521
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/contrib/timeseries/python/timeseries/state_space_models/structural_ensemble.py
python
_replicate_level_trend_models
(multivariate_configuration, univariate_configuration)
return adder_part
Helper function to construct a multivariate level/trend component.
Helper function to construct a multivariate level/trend component.
[ "Helper", "function", "to", "construct", "a", "multivariate", "level", "/", "trend", "component", "." ]
def _replicate_level_trend_models(multivariate_configuration, univariate_configuration): """Helper function to construct a multivariate level/trend component.""" with variable_scope.variable_scope("adder"): # Construct a level and trend model for each feature, with correlated # transition noise. adder_features = [] for feature in range(multivariate_configuration.num_features): with variable_scope.variable_scope("feature{}".format(feature)): adder_features.append(level_trend.AdderStateSpaceModel( configuration=univariate_configuration)) adder_part = state_space_model.StateSpaceCorrelatedFeaturesEnsemble( ensemble_members=adder_features, configuration=multivariate_configuration) return adder_part
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/timeseries/python/timeseries/state_space_models/structural_ensemble.py#L30-L44
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/build/waf-1.7.13/lmbrwaflib/artifacts_cache.py
python
uid
(self)
Override uid computation, and make it to be engine path and 3rdParty path independent
Override uid computation, and make it to be engine path and 3rdParty path independent
[ "Override", "uid", "computation", "and", "make", "it", "to", "be", "engine", "path", "and", "3rdParty", "path", "independent" ]
def uid(self): """ Override uid computation, and make it to be engine path and 3rdParty path independent """ try: return self.uid_ except AttributeError: # this is not a real hot zone, but we want to avoid surprises here m = Utils.md5() up = m.update up(self.__class__.__name__.encode()) for k in self.inputs + self.outputs: s = replace_engine_path_and_tp_root_in_string(self.generator.bld, k.abspath()) up(s) self.uid_ = m.digest() return self.uid_
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/build/waf-1.7.13/lmbrwaflib/artifacts_cache.py#L228-L243
facebook/fboss
60063db1df37c2ec0e7dcd0955c54885ea9bf7f0
build/fbcode_builder/getdeps/manifest.py
python
ManifestParser.update_hash
(self, hasher, ctx)
Compute a hash over the configuration for the given context. The goal is for the hash to change if the config for that context changes, but not if a change is made to the config only for a different platform than that expressed by ctx. The hash is intended to be used to help invalidate a future cache for the third party build products. The hasher argument is a hash object returned from hashlib.
Compute a hash over the configuration for the given context. The goal is for the hash to change if the config for that context changes, but not if a change is made to the config only for a different platform than that expressed by ctx. The hash is intended to be used to help invalidate a future cache for the third party build products. The hasher argument is a hash object returned from hashlib.
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def update_hash(self, hasher, ctx): """Compute a hash over the configuration for the given context. The goal is for the hash to change if the config for that context changes, but not if a change is made to the config only for a different platform than that expressed by ctx. The hash is intended to be used to help invalidate a future cache for the third party build products. The hasher argument is a hash object returned from hashlib.""" for section in sorted(SCHEMA.keys()): hasher.update(section.encode("utf-8")) # Note: at the time of writing, nothing in the implementation # relies on keys in any config section being ordered. # In theory we could have conflicting flags in different # config sections and later flags override earlier flags. # For the purposes of computing a hash we're not super # concerned about this: manifest changes should be rare # enough and we'd rather that this trigger an invalidation # than strive for a cache hit at this time. pairs = self.get_section_as_ordered_pairs(section, ctx) pairs.sort(key=lambda pair: pair[0]) for key, value in pairs: hasher.update(key.encode("utf-8")) if value is not None: hasher.update(value.encode("utf-8"))
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https://github.com/facebook/fboss/blob/60063db1df37c2ec0e7dcd0955c54885ea9bf7f0/build/fbcode_builder/getdeps/manifest.py#L328-L352
krishauser/Klampt
972cc83ea5befac3f653c1ba20f80155768ad519
Python/python2_version/klampt/src/robotsim.py
python
RobotModel.interpolateDeriv
(self, a, b)
return _robotsim.RobotModel_interpolateDeriv(self, a, b)
interpolateDeriv(RobotModel self, doubleVector a, doubleVector b) Returns the configuration derivative at a as you interpolate toward b at unit speed.
interpolateDeriv(RobotModel self, doubleVector a, doubleVector b)
[ "interpolateDeriv", "(", "RobotModel", "self", "doubleVector", "a", "doubleVector", "b", ")" ]
def interpolateDeriv(self, a, b): """ interpolateDeriv(RobotModel self, doubleVector a, doubleVector b) Returns the configuration derivative at a as you interpolate toward b at unit speed. """ return _robotsim.RobotModel_interpolateDeriv(self, a, b)
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https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/python2_version/klampt/src/robotsim.py#L5084-L5094
tfwu/FaceDetection-ConvNet-3D
f9251c48eb40c5aec8fba7455115c355466555be
python/build/lib.linux-x86_64-2.7/mxnet/symbol.py
python
Symbol._get_ndarray_inputs
(arg_key, args, arg_names, allow_missing)
return c_array(NDArrayHandle, arg_handles), arg_arrays
Helper function to get ndarray lists handles from various inputs. Parameters ---------- arg_key : str The name of argument, used for error message. args : list of NDArray or dict of str to NDArray Input arguments to the symbols. If type is list of NDArray, the position is in the same order of arg_names. If type is dict of str to NDArray, then it maps the name of arguments to the corresponding NDArray, args_names : list of string List of argument names. allow_missing : boolean Whether missing argument is allowed. When allowed, the missing handle will be set to None(null) Returns ------- handles : list of NDArrayHandle The positional list of NDArrayHandles generated from input.
Helper function to get ndarray lists handles from various inputs.
[ "Helper", "function", "to", "get", "ndarray", "lists", "handles", "from", "various", "inputs", "." ]
def _get_ndarray_inputs(arg_key, args, arg_names, allow_missing): """Helper function to get ndarray lists handles from various inputs. Parameters ---------- arg_key : str The name of argument, used for error message. args : list of NDArray or dict of str to NDArray Input arguments to the symbols. If type is list of NDArray, the position is in the same order of arg_names. If type is dict of str to NDArray, then it maps the name of arguments to the corresponding NDArray, args_names : list of string List of argument names. allow_missing : boolean Whether missing argument is allowed. When allowed, the missing handle will be set to None(null) Returns ------- handles : list of NDArrayHandle The positional list of NDArrayHandles generated from input. """ # setup args arg_handles = [] arg_arrays = [] if isinstance(args, list): if len(args) != len(arg_names): raise ValueError('Length of %s do not match number of arguments' % arg_key) for narr in args: if not isinstance(narr, NDArray): raise TypeError('Only Accept list of NDArrays or dict of str to NDArray') arg_handles.append(narr.handle) arg_arrays = args elif isinstance(args, dict): for name in arg_names: if name in args: narr = args[name] if not isinstance(narr, NDArray): raise TypeError('Only Accept list of NDArrays or dict of str to NDArray') arg_handles.append(narr.handle) arg_arrays.append(narr) else: if allow_missing: arg_handles.append(None) arg_arrays.append(None) else: raise ValueError('Must specify all the arguments in %s' % arg_key) else: raise TypeError('Only Accept list of NDArrays or dict of str to NDArray') return c_array(NDArrayHandle, arg_handles), arg_arrays
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https://github.com/tfwu/FaceDetection-ConvNet-3D/blob/f9251c48eb40c5aec8fba7455115c355466555be/python/build/lib.linux-x86_64-2.7/mxnet/symbol.py#L535-L588
htcondor/htcondor
4829724575176d1d6c936e4693dfd78a728569b0
src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/skype.py
python
ISkype.CreateSms
(self, MessageType, *TargetNumbers)
return ISmsMessage(chop(self._DoCommand('CREATE SMS %s %s' % (MessageType, ', '.join(TargetNumbers))), 2)[1], self)
Creates an SMS message. @param MessageType: Message type. @type MessageType: L{SMS message type<enums.smsMessageTypeUnknown>} @param TargetNumbers: One or more target SMS numbers. @type TargetNumbers: unicode @return: An sms message object. @rtype: L{ISmsMessage}
Creates an SMS message.
[ "Creates", "an", "SMS", "message", "." ]
def CreateSms(self, MessageType, *TargetNumbers): '''Creates an SMS message. @param MessageType: Message type. @type MessageType: L{SMS message type<enums.smsMessageTypeUnknown>} @param TargetNumbers: One or more target SMS numbers. @type TargetNumbers: unicode @return: An sms message object. @rtype: L{ISmsMessage} ''' return ISmsMessage(chop(self._DoCommand('CREATE SMS %s %s' % (MessageType, ', '.join(TargetNumbers))), 2)[1], self)
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https://github.com/htcondor/htcondor/blob/4829724575176d1d6c936e4693dfd78a728569b0/src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/skype.py#L636-L646
hpi-xnor/BMXNet
ed0b201da6667887222b8e4b5f997c4f6b61943d
python/mxnet/operator.py
python
PythonOp.list_arguments
(self)
return ['data']
Interface for ``list_arguments``. Can override when creating new operators. Returns ------- in_shape : list list of argument shapes in the same order as declared in list_arguments.
Interface for ``list_arguments``. Can override when creating new operators.
[ "Interface", "for", "list_arguments", ".", "Can", "override", "when", "creating", "new", "operators", "." ]
def list_arguments(self): """Interface for ``list_arguments``. Can override when creating new operators. Returns ------- in_shape : list list of argument shapes in the same order as declared in list_arguments. """ return ['data']
[ "def", "list_arguments", "(", "self", ")", ":", "return", "[", "'data'", "]" ]
https://github.com/hpi-xnor/BMXNet/blob/ed0b201da6667887222b8e4b5f997c4f6b61943d/python/mxnet/operator.py#L122-L131
pytorch/pytorch
7176c92687d3cc847cc046bf002269c6949a21c2
torch/nn/functional.py
python
adaptive_max_pool1d_with_indices
( input: Tensor, output_size: BroadcastingList1[int], return_indices: bool = False )
return torch.adaptive_max_pool1d(input, output_size)
r"""Applies a 1D adaptive max pooling over an input signal composed of several input planes. See :class:`~torch.nn.AdaptiveMaxPool1d` for details and output shape. Args: output_size: the target output size (single integer) return_indices: whether to return pooling indices. Default: ``False``
r"""Applies a 1D adaptive max pooling over an input signal composed of several input planes.
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def adaptive_max_pool1d_with_indices( input: Tensor, output_size: BroadcastingList1[int], return_indices: bool = False ) -> Tuple[Tensor, Tensor]: r"""Applies a 1D adaptive max pooling over an input signal composed of several input planes. See :class:`~torch.nn.AdaptiveMaxPool1d` for details and output shape. Args: output_size: the target output size (single integer) return_indices: whether to return pooling indices. Default: ``False`` """ if has_torch_function_unary(input): return handle_torch_function( adaptive_max_pool1d_with_indices, (input,), input, output_size, return_indices=return_indices ) return torch.adaptive_max_pool1d(input, output_size)
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https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/torch/nn/functional.py#L1091-L1107
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/scipy/linalg/special_matrices.py
python
hilbert
(n)
return h
Create a Hilbert matrix of order `n`. Returns the `n` by `n` array with entries `h[i,j] = 1 / (i + j + 1)`. Parameters ---------- n : int The size of the array to create. Returns ------- h : (n, n) ndarray The Hilbert matrix. See Also -------- invhilbert : Compute the inverse of a Hilbert matrix. Notes ----- .. versionadded:: 0.10.0 Examples -------- >>> from scipy.linalg import hilbert >>> hilbert(3) array([[ 1. , 0.5 , 0.33333333], [ 0.5 , 0.33333333, 0.25 ], [ 0.33333333, 0.25 , 0.2 ]])
Create a Hilbert matrix of order `n`.
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def hilbert(n): """ Create a Hilbert matrix of order `n`. Returns the `n` by `n` array with entries `h[i,j] = 1 / (i + j + 1)`. Parameters ---------- n : int The size of the array to create. Returns ------- h : (n, n) ndarray The Hilbert matrix. See Also -------- invhilbert : Compute the inverse of a Hilbert matrix. Notes ----- .. versionadded:: 0.10.0 Examples -------- >>> from scipy.linalg import hilbert >>> hilbert(3) array([[ 1. , 0.5 , 0.33333333], [ 0.5 , 0.33333333, 0.25 ], [ 0.33333333, 0.25 , 0.2 ]]) """ values = 1.0 / (1.0 + np.arange(2 * n - 1)) h = hankel(values[:n], r=values[n - 1:]) return h
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/linalg/special_matrices.py#L654-L689
natanielruiz/android-yolo
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
jni-build/jni/include/tensorflow/python/ops/math_grad.py
python
_BatchMatMul
(op, grad)
return grad_x, grad_y
Returns the gradient of x and y given the gradient of x * y.
Returns the gradient of x and y given the gradient of x * y.
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def _BatchMatMul(op, grad): """Returns the gradient of x and y given the gradient of x * y.""" x = op.inputs[0] y = op.inputs[1] adj_x = op.get_attr("adj_x") adj_y = op.get_attr("adj_y") if not adj_x: if not adj_y: grad_x = math_ops.batch_matmul(grad, y, False, True) grad_y = math_ops.batch_matmul(x, grad, True, False) else: grad_x = math_ops.batch_matmul(grad, y, False, False) grad_y = math_ops.batch_matmul(grad, x, True, False) else: if not adj_y: grad_x = math_ops.batch_matmul(y, grad, False, True) grad_y = math_ops.batch_matmul(x, grad, False, False) else: grad_x = math_ops.batch_matmul(y, grad, True, True) grad_y = math_ops.batch_matmul(grad, x, True, True) return grad_x, grad_y
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/python/ops/math_grad.py#L706-L728
devsisters/libquic
8954789a056d8e7d5fcb6452fd1572ca57eb5c4e
boringssl/util/generate-asm-lcov.py
python
is_asm
(l)
return True
Returns whether a line should be considered to be an instruction.
Returns whether a line should be considered to be an instruction.
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def is_asm(l): """Returns whether a line should be considered to be an instruction.""" l = l.strip() # Empty lines if l == '': return False # Comments if l.startswith('#'): return False # Assembly Macros if l.startswith('.'): return False # Label if l.endswith(':'): return False return True
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https://github.com/devsisters/libquic/blob/8954789a056d8e7d5fcb6452fd1572ca57eb5c4e/boringssl/util/generate-asm-lcov.py#L33-L48
macchina-io/macchina.io
ef24ba0e18379c3dd48fb84e6dbf991101cb8db0
platform/JS/V8/tools/gyp/pylib/gyp/msvs_emulation.py
python
MsvsSettings.HasExplicitAsmRules
(self, spec)
return self._HasExplicitRuleForExtension(spec, 'asm')
Determine if there's an explicit rule for asm files. When there isn't we need to generate implicit rules to assemble .asm files.
Determine if there's an explicit rule for asm files. When there isn't we need to generate implicit rules to assemble .asm files.
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def HasExplicitAsmRules(self, spec): """Determine if there's an explicit rule for asm files. When there isn't we need to generate implicit rules to assemble .asm files.""" return self._HasExplicitRuleForExtension(spec, 'asm')
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https://github.com/macchina-io/macchina.io/blob/ef24ba0e18379c3dd48fb84e6dbf991101cb8db0/platform/JS/V8/tools/gyp/pylib/gyp/msvs_emulation.py#L847-L850
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/python/framework/dtypes.py
python
DType.is_floating
(self)
return self.is_numpy_compatible and issubclass(self.as_numpy_dtype, np.floating)
Returns whether this is a (non-quantized, real) floating point type.
Returns whether this is a (non-quantized, real) floating point type.
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def is_floating(self): """Returns whether this is a (non-quantized, real) floating point type.""" return self.is_numpy_compatible and issubclass(self.as_numpy_dtype, np.floating)
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/framework/dtypes.py#L141-L144
google/earthenterprise
0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9
earth_enterprise/src/server/wsgi/serve/snippets/util/proto_reflection.py
python
_IsFieldPathPrimitive
(fieldpath, protobuf)
return (not rest) and (fd.type != fd.TYPE_MESSAGE)
Whether the fieldpath is a (true) leaf in protobuf. whether protobuf structurally contains the path and, that it ends at a primitive (ie rejects subtree paths). Args: fieldpath: path of the field within the protobuf protobuf: container of the protobuf Returns: whether the fieldpath ends at a true leaf ie, value field.
Whether the fieldpath is a (true) leaf in protobuf.
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def _IsFieldPathPrimitive(fieldpath, protobuf): """Whether the fieldpath is a (true) leaf in protobuf. whether protobuf structurally contains the path and, that it ends at a primitive (ie rejects subtree paths). Args: fieldpath: path of the field within the protobuf protobuf: container of the protobuf Returns: whether the fieldpath ends at a true leaf ie, value field. """ toks = path_utils.SplitAbstract(path_utils.AsAbstract(fieldpath)) fname, rest = path_utils.FirstRest(toks) fd = protobuf.DESCRIPTOR.fields_by_name.get(fname, None) if fd is None: return False while bool(rest) and fd.type == fd.TYPE_MESSAGE: fname, rest = path_utils.FirstRest(rest) fd = fd.message_type.fields_by_name.get(fname, None) if fd is None: # path contains something not in the protobuf return False # Both ended on a primitive. return (not rest) and (fd.type != fd.TYPE_MESSAGE)
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https://github.com/google/earthenterprise/blob/0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9/earth_enterprise/src/server/wsgi/serve/snippets/util/proto_reflection.py#L320-L344
polyworld/polyworld
eb7e6bbc82fe77ba79e3bc48c3da2ad8c8238c26
scripts/agent/brain.py
python
BrainAnatomy.cxnmatrix
(self)
return cxn
Lazy loading of connection matrix
Lazy loading of connection matrix
[ "Lazy", "loading", "of", "connection", "matrix" ]
def cxnmatrix(self): ''' Lazy loading of connection matrix ''' # Open brain anatomy, clean lines f = open(filename) lines = [ x.strip('\n; ') for x in f.readlines()] lines = lines[1:] f.close() assert len(lines) == self.num_neurons, "#lines != num_neurons" # import all neurons and build the connection matrix with sanity checks cells = [ float(cell) for row in lines for cell in row.split(' ') ] assert len(cells) == self.num_neurons*self.num_neurons,\ "Did not find a square matrix in anatomy file" cxn = array(cells).reshape(self.num_neurons, self.num_neurons) assert -self.max_weight <= self.cxn.all() <= self.max_weight,\ "anatomy matrix wasn't within [-max_weight,max_weight]" return cxn
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https://github.com/polyworld/polyworld/blob/eb7e6bbc82fe77ba79e3bc48c3da2ad8c8238c26/scripts/agent/brain.py#L42-L62
mongodb/mongo
d8ff665343ad29cf286ee2cf4a1960d29371937b
src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/msginit.py
python
_optional_no_translator_flag
(env)
Return '--no-translator' flag if we run *msginit(1)* in non-interactive mode.
Return '--no-translator' flag if we run *msginit(1)* in non-interactive mode.
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def _optional_no_translator_flag(env): """ Return '--no-translator' flag if we run *msginit(1)* in non-interactive mode.""" import SCons.Util if 'POAUTOINIT' in env: autoinit = env['POAUTOINIT'] else: autoinit = False if autoinit: return [SCons.Util.CLVar('--no-translator')] else: return [SCons.Util.CLVar('')]
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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/msginit.py#L34-L45
baidu/bigflow
449245016c0df7d1252e85581e588bfc60cefad3
bigflow_python/python/bigflow/transforms.py
python
cogroup
(*pcollections, **options)
return bigflow.transform_impls.cogroup.cogroup(*pcollections, **options)
对传入的所有pcollection进行协同分组。 cogroup要求所有传入的PCollection的每个元素都是一个(k, v)对, cogroup会用k来作为分组的key,对多个输入PCollection进行协同分组, 返回一个PTable表示分组结果。 这个返回的PTable的每个value为一个tuple,tuple的每个元素是一个PCollection, 其中第n个PCollection表示输入的第n个PCollection在当前key下的全部数据。 如果某个输入PCollection在某个key下无数据,则对应的PCollection为一个空PCollection。 目前不能像group_by指定key_extractor。 group_by_key可以理解成是cogroup只传有一个参数的特殊情况。 Args: *pcollections: 输入PCollection **options: 可配置选项 Returns: PTable: 分组结果 >>> from bigflow import transforms >>> _p1 = _pipeline.parallelize([("A", 1), ("A", 2), ("B", 3)]) >>> _p2 = _pipeline.parallelize([("A", 4)]) >>> _p = transforms.cogroup(_p1, _p2) # _p的值为{"A": ([1, 2], [4]), "B": ([3], [])} ,但由于实现难度较大,PTable的value为tuple of PCollection时的get操作暂不支持。 >>> _p.apply_values(lambda x, y: transforms.union(x, y)).get() {"A": [1, 2, 4], "B": [3]} >>> def distinct_and_join(p, q): # 去重,并join ... return p.cogroup(q) \\ ... .apply_values(lambda a, b: (a.distinct(), b.distinct())) \\ ... .apply_values(transforms.cartesian) \\ ... .flatten() >>> _p1 = _pipeline.parallelize([("A", 1), ("A", 2), ("A", 1), ("C", 1)]) >>> _p2 = _pipeline.parallelize([("A", 3), ("A", 3), ("B", 2)]) >>> print distinct_and_join(_p1, _p2).get() [("A", (1, 3)), ("A", (2, 3))] >>> # 未来bigflow会自动将p.distinct().join(q.distinct())优化成上边的样子(正在进行中) >>> def semi_join(p, q): # 同key的join结果只输出一条 ... return p.cogroup(q) \\ ... .apply_values(lambda a, b: (a.take(1), b.take(1))) \\ ... .apply_values(transforms.cartesian) \\ ... .flatten() >>> print semi_join(_p1, _p2).get() [("A", (1, 3))]
对传入的所有pcollection进行协同分组。
[ "对传入的所有pcollection进行协同分组。" ]
def cogroup(*pcollections, **options): """ 对传入的所有pcollection进行协同分组。 cogroup要求所有传入的PCollection的每个元素都是一个(k, v)对, cogroup会用k来作为分组的key,对多个输入PCollection进行协同分组, 返回一个PTable表示分组结果。 这个返回的PTable的每个value为一个tuple,tuple的每个元素是一个PCollection, 其中第n个PCollection表示输入的第n个PCollection在当前key下的全部数据。 如果某个输入PCollection在某个key下无数据,则对应的PCollection为一个空PCollection。 目前不能像group_by指定key_extractor。 group_by_key可以理解成是cogroup只传有一个参数的特殊情况。 Args: *pcollections: 输入PCollection **options: 可配置选项 Returns: PTable: 分组结果 >>> from bigflow import transforms >>> _p1 = _pipeline.parallelize([("A", 1), ("A", 2), ("B", 3)]) >>> _p2 = _pipeline.parallelize([("A", 4)]) >>> _p = transforms.cogroup(_p1, _p2) # _p的值为{"A": ([1, 2], [4]), "B": ([3], [])} ,但由于实现难度较大,PTable的value为tuple of PCollection时的get操作暂不支持。 >>> _p.apply_values(lambda x, y: transforms.union(x, y)).get() {"A": [1, 2, 4], "B": [3]} >>> def distinct_and_join(p, q): # 去重,并join ... return p.cogroup(q) \\ ... .apply_values(lambda a, b: (a.distinct(), b.distinct())) \\ ... .apply_values(transforms.cartesian) \\ ... .flatten() >>> _p1 = _pipeline.parallelize([("A", 1), ("A", 2), ("A", 1), ("C", 1)]) >>> _p2 = _pipeline.parallelize([("A", 3), ("A", 3), ("B", 2)]) >>> print distinct_and_join(_p1, _p2).get() [("A", (1, 3)), ("A", (2, 3))] >>> # 未来bigflow会自动将p.distinct().join(q.distinct())优化成上边的样子(正在进行中) >>> def semi_join(p, q): # 同key的join结果只输出一条 ... return p.cogroup(q) \\ ... .apply_values(lambda a, b: (a.take(1), b.take(1))) \\ ... .apply_values(transforms.cartesian) \\ ... .flatten() >>> print semi_join(_p1, _p2).get() [("A", (1, 3))] """ import bigflow.transform_impls.cogroup return bigflow.transform_impls.cogroup.cogroup(*pcollections, **options)
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https://github.com/baidu/bigflow/blob/449245016c0df7d1252e85581e588bfc60cefad3/bigflow_python/python/bigflow/transforms.py#L146-L198
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/xml/sax/xmlreader.py
python
XMLReader.getEntityResolver
(self)
return self._ent_handler
Returns the current EntityResolver.
Returns the current EntityResolver.
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def getEntityResolver(self): "Returns the current EntityResolver." return self._ent_handler
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/xml/sax/xmlreader.py#L50-L52
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/asyncio/sslproto.py
python
_SSLProtocolTransport.get_write_buffer_size
(self)
return self._ssl_protocol._transport.get_write_buffer_size()
Return the current size of the write buffer.
Return the current size of the write buffer.
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def get_write_buffer_size(self): """Return the current size of the write buffer.""" return self._ssl_protocol._transport.get_write_buffer_size()
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/asyncio/sslproto.py#L366-L368
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/pydoc.py
python
HTMLDoc.markup
(self, text, escape=None, funcs={}, classes={}, methods={})
return ''.join(results)
Mark up some plain text, given a context of symbols to look for. Each context dictionary maps object names to anchor names.
Mark up some plain text, given a context of symbols to look for. Each context dictionary maps object names to anchor names.
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def markup(self, text, escape=None, funcs={}, classes={}, methods={}): """Mark up some plain text, given a context of symbols to look for. Each context dictionary maps object names to anchor names.""" escape = escape or self.escape results = [] here = 0 pattern = re.compile(r'\b((http|ftp)://\S+[\w/]|' r'RFC[- ]?(\d+)|' r'PEP[- ]?(\d+)|' r'(self\.)?(\w+))') while True: match = pattern.search(text, here) if not match: break start, end = match.span() results.append(escape(text[here:start])) all, scheme, rfc, pep, selfdot, name = match.groups() if scheme: url = escape(all).replace('"', '&quot;') results.append('<a href="%s">%s</a>' % (url, url)) elif rfc: url = 'http://www.rfc-editor.org/rfc/rfc%d.txt' % int(rfc) results.append('<a href="%s">%s</a>' % (url, escape(all))) elif pep: url = 'http://www.python.org/dev/peps/pep-%04d/' % int(pep) results.append('<a href="%s">%s</a>' % (url, escape(all))) elif selfdot: # Create a link for methods like 'self.method(...)' # and use <strong> for attributes like 'self.attr' if text[end:end+1] == '(': results.append('self.' + self.namelink(name, methods)) else: results.append('self.<strong>%s</strong>' % name) elif text[end:end+1] == '(': results.append(self.namelink(name, methods, funcs, classes)) else: results.append(self.namelink(name, classes)) here = end results.append(escape(text[here:])) return ''.join(results)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/pydoc.py#L587-L626
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/aui/auibook.py
python
AuiNotebook.RemovePage
(self, page_idx)
return True
Removes a page, without deleting the window pointer. :param integer `page_idx`: the page index to be removed. :note: :meth:`RemovePage` removes a tab from the multi-notebook, but does not destroy the window. :see: :meth:`DeletePage`
Removes a page, without deleting the window pointer.
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def RemovePage(self, page_idx): """ Removes a page, without deleting the window pointer. :param integer `page_idx`: the page index to be removed. :note: :meth:`RemovePage` removes a tab from the multi-notebook, but does not destroy the window. :see: :meth:`DeletePage` """ # save active window pointer active_wnd = None if self._curpage >= 0: active_wnd = self._tabs.GetWindowFromIdx(self._curpage) # save pointer of window being deleted wnd = self._tabs.GetWindowFromIdx(page_idx) new_active = None # make sure we found the page if not wnd: return False # find out which onscreen tab ctrl owns this tab ctrl, ctrl_idx = self.FindTab(wnd) if not ctrl: return False currentPage = ctrl.GetPage(ctrl_idx) is_curpage = (self._curpage == page_idx) is_active_in_split = currentPage.active # remove the tab from main catalog if not self._tabs.RemovePage(wnd): return False # remove the tab from the onscreen tab ctrl ctrl.RemovePage(wnd) if is_active_in_split: ctrl_new_page_count = ctrl.GetPageCount() if ctrl_idx >= ctrl_new_page_count: ctrl_idx = ctrl_new_page_count - 1 if ctrl_idx >= 0 and ctrl_idx < ctrl.GetPageCount(): ctrl_idx = self.FindNextActiveTab(ctrl_idx, ctrl) # set new page as active in the tab split ctrl.SetActivePage(ctrl_idx) # if the page deleted was the current page for the # entire tab control, then record the window # pointer of the new active page for activation if is_curpage: new_active = ctrl.GetWindowFromIdx(ctrl_idx) else: # we are not deleting the active page, so keep it the same new_active = active_wnd if not new_active: # we haven't yet found a new page to active, # so select the next page from the main tab # catalogue if 0 <= page_idx < self._tabs.GetPageCount(): new_active = self._tabs.GetPage(page_idx).window if not new_active and self._tabs.GetPageCount() > 0: new_active = self._tabs.GetPage(0).window self.RemoveEmptyTabFrames() # set new active pane if new_active: if not self.IsBeingDeleted(): self._curpage = -1 self.SetSelectionToWindow(new_active) else: self._curpage = -1 self._tabs.SetNoneActive() return True
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/aui/auibook.py#L3527-L3616
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/xrc.py
python
XmlProperty.__init__
(self, *args, **kwargs)
__init__(self, String name=EmptyString, String value=EmptyString, XmlProperty next=None) -> XmlProperty
__init__(self, String name=EmptyString, String value=EmptyString, XmlProperty next=None) -> XmlProperty
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def __init__(self, *args, **kwargs): """ __init__(self, String name=EmptyString, String value=EmptyString, XmlProperty next=None) -> XmlProperty """ _xrc.XmlProperty_swiginit(self,_xrc.new_XmlProperty(*args, **kwargs))
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/xrc.py#L310-L315
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/decimal.py
python
Context.to_integral_value
(self, a)
return a.to_integral_value(context=self)
Rounds to an integer. When the operand has a negative exponent, the result is the same as using the quantize() operation using the given operand as the left-hand-operand, 1E+0 as the right-hand-operand, and the precision of the operand as the precision setting, except that no flags will be set. The rounding mode is taken from the context. >>> ExtendedContext.to_integral_value(Decimal('2.1')) Decimal('2') >>> ExtendedContext.to_integral_value(Decimal('100')) Decimal('100') >>> ExtendedContext.to_integral_value(Decimal('100.0')) Decimal('100') >>> ExtendedContext.to_integral_value(Decimal('101.5')) Decimal('102') >>> ExtendedContext.to_integral_value(Decimal('-101.5')) Decimal('-102') >>> ExtendedContext.to_integral_value(Decimal('10E+5')) Decimal('1.0E+6') >>> ExtendedContext.to_integral_value(Decimal('7.89E+77')) Decimal('7.89E+77') >>> ExtendedContext.to_integral_value(Decimal('-Inf')) Decimal('-Infinity')
Rounds to an integer.
[ "Rounds", "to", "an", "integer", "." ]
def to_integral_value(self, a): """Rounds to an integer. When the operand has a negative exponent, the result is the same as using the quantize() operation using the given operand as the left-hand-operand, 1E+0 as the right-hand-operand, and the precision of the operand as the precision setting, except that no flags will be set. The rounding mode is taken from the context. >>> ExtendedContext.to_integral_value(Decimal('2.1')) Decimal('2') >>> ExtendedContext.to_integral_value(Decimal('100')) Decimal('100') >>> ExtendedContext.to_integral_value(Decimal('100.0')) Decimal('100') >>> ExtendedContext.to_integral_value(Decimal('101.5')) Decimal('102') >>> ExtendedContext.to_integral_value(Decimal('-101.5')) Decimal('-102') >>> ExtendedContext.to_integral_value(Decimal('10E+5')) Decimal('1.0E+6') >>> ExtendedContext.to_integral_value(Decimal('7.89E+77')) Decimal('7.89E+77') >>> ExtendedContext.to_integral_value(Decimal('-Inf')) Decimal('-Infinity') """ a = _convert_other(a, raiseit=True) return a.to_integral_value(context=self)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/decimal.py#L5406-L5433
NGSolve/ngsolve
4a22558b6d5852f3d7e6cd86f1233b1ad716f395
python/krylovspace.py
python
MinRes
(mat, rhs, pre=None, sol=None, maxsteps = 100, printrates = True, initialize = True, tol = 1e-7)
return MinResSolver(mat=mat, pre=pre, maxiter=maxsteps, printrates=printrates, tol=tol).Solve(rhs=rhs, sol=sol, initialize=initialize)
Minimal Residuum method Parameters ---------- mat : Matrix The left hand side of the equation to solve rhs : Vector The right hand side of the equation. pre : Preconditioner If provided the preconditioner is used. sol : Vector Start vector for MinRes method, if initialize is set False. Gets overwritten by the solution vector. If sol = None then a new vector is created. maxsteps : int Number of maximal steps for MinRes. If the maximal number is reached before the tolerance is reached MinRes stops. printrates : bool If set to True then the error of the iterations is displayed. initialize : bool If set to True then the initial guess for the MinRes method is set to zero. Otherwise the values of the vector sol, if prevented, is used. tol : double Tolerance of the residuum. MinRes stops if tolerance is reached. Returns ------- (vector) Solution vector of the MinRes method.
Minimal Residuum method
[ "Minimal", "Residuum", "method" ]
def MinRes(mat, rhs, pre=None, sol=None, maxsteps = 100, printrates = True, initialize = True, tol = 1e-7): """Minimal Residuum method Parameters ---------- mat : Matrix The left hand side of the equation to solve rhs : Vector The right hand side of the equation. pre : Preconditioner If provided the preconditioner is used. sol : Vector Start vector for MinRes method, if initialize is set False. Gets overwritten by the solution vector. If sol = None then a new vector is created. maxsteps : int Number of maximal steps for MinRes. If the maximal number is reached before the tolerance is reached MinRes stops. printrates : bool If set to True then the error of the iterations is displayed. initialize : bool If set to True then the initial guess for the MinRes method is set to zero. Otherwise the values of the vector sol, if prevented, is used. tol : double Tolerance of the residuum. MinRes stops if tolerance is reached. Returns ------- (vector) Solution vector of the MinRes method. """ return MinResSolver(mat=mat, pre=pre, maxiter=maxsteps, printrates=printrates, tol=tol).Solve(rhs=rhs, sol=sol, initialize=initialize)
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https://github.com/NGSolve/ngsolve/blob/4a22558b6d5852f3d7e6cd86f1233b1ad716f395/python/krylovspace.py#L558-L599
pytorch/pytorch
7176c92687d3cc847cc046bf002269c6949a21c2
torch/fx/experimental/fx2trt/converters/converter_utils.py
python
get_axes_for_reduce_op
( dim: Union[int, Sequence[int]], has_implicit_batch_dimension: bool, )
return axes
TensorRT reduce layer relies on the binary representation of axes to determine which dims to reduce. For example, if we want to reduce on dim 1 and 2 then axes should be 6(110). Args: dim (Union[int, Sequence[int]]): An integer or a sequence of integers that will be used to generate axes for TensorRT. has_implicit_batch_dimension (bool): Whether the TensorRT network is using implicit batch dimension. Returns: An integer which binary form can be used as axes for TensorRT reduce layer.
TensorRT reduce layer relies on the binary representation of axes to determine which dims to reduce. For example, if we want to reduce on dim 1 and 2 then axes should be 6(110).
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def get_axes_for_reduce_op( dim: Union[int, Sequence[int]], has_implicit_batch_dimension: bool, ) -> int: """ TensorRT reduce layer relies on the binary representation of axes to determine which dims to reduce. For example, if we want to reduce on dim 1 and 2 then axes should be 6(110). Args: dim (Union[int, Sequence[int]]): An integer or a sequence of integers that will be used to generate axes for TensorRT. has_implicit_batch_dimension (bool): Whether the TensorRT network is using implicit batch dimension. Returns: An integer which binary form can be used as axes for TensorRT reduce layer. """ if isinstance(dim, int): dim = (dim,) if has_implicit_batch_dimension: assert 0 not in dim, "Can't reduce over batch dimension when it's implicit." axes = 0 for d in dim: axes |= 1 << (d - (1 if has_implicit_batch_dimension else 0)) return axes
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https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/torch/fx/experimental/fx2trt/converters/converter_utils.py#L135-L164
ApolloAuto/apollo-platform
86d9dc6743b496ead18d597748ebabd34a513289
ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/compat/_inspect.py
python
strseq
(object, convert, join=joinseq)
Recursively walk a sequence, stringifying each element.
Recursively walk a sequence, stringifying each element.
[ "Recursively", "walk", "a", "sequence", "stringifying", "each", "element", "." ]
def strseq(object, convert, join=joinseq): """Recursively walk a sequence, stringifying each element.""" if type(object) in [list, tuple]: return join([strseq(_o, convert, join) for _o in object]) else: return convert(object)
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https://github.com/ApolloAuto/apollo-platform/blob/86d9dc6743b496ead18d597748ebabd34a513289/ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/compat/_inspect.py#L152-L157
miyosuda/TensorFlowAndroidMNIST
7b5a4603d2780a8a2834575706e9001977524007
jni-build/jni/include/tensorflow/python/framework/errors.py
python
FailedPreconditionError.__init__
(self, node_def, op, message)
Creates a `FailedPreconditionError`.
Creates a `FailedPreconditionError`.
[ "Creates", "a", "FailedPreconditionError", "." ]
def __init__(self, node_def, op, message): """Creates a `FailedPreconditionError`.""" super(FailedPreconditionError, self).__init__(node_def, op, message, FAILED_PRECONDITION)
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/python/framework/errors.py#L310-L313
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/xrc.py
python
XmlResource.InsertHandler
(*args, **kwargs)
return _xrc.XmlResource_InsertHandler(*args, **kwargs)
InsertHandler(self, XmlResourceHandler handler)
InsertHandler(self, XmlResourceHandler handler)
[ "InsertHandler", "(", "self", "XmlResourceHandler", "handler", ")" ]
def InsertHandler(*args, **kwargs): """InsertHandler(self, XmlResourceHandler handler)""" return _xrc.XmlResource_InsertHandler(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/xrc.py#L106-L108
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/stc.py
python
StyledTextCtrl.LineScroll
(*args, **kwargs)
return _stc.StyledTextCtrl_LineScroll(*args, **kwargs)
LineScroll(self, int columns, int lines) Scroll horizontally and vertically.
LineScroll(self, int columns, int lines)
[ "LineScroll", "(", "self", "int", "columns", "int", "lines", ")" ]
def LineScroll(*args, **kwargs): """ LineScroll(self, int columns, int lines) Scroll horizontally and vertically. """ return _stc.StyledTextCtrl_LineScroll(*args, **kwargs)
[ "def", "LineScroll", "(", "*", "args", ",", "*", "*", "kwargs", ")", ":", "return", "_stc", ".", "StyledTextCtrl_LineScroll", "(", "*", "args", ",", "*", "*", "kwargs", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L3617-L3623
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/telemetry/third_party/pyserial/serial/urlhandler/protocol_loop.py
python
LoopbackSerial._reconfigurePort
(self)
Set communication parameters on opened port. for the loop:// protocol all settings are ignored!
Set communication parameters on opened port. for the loop:// protocol all settings are ignored!
[ "Set", "communication", "parameters", "on", "opened", "port", ".", "for", "the", "loop", ":", "//", "protocol", "all", "settings", "are", "ignored!" ]
def _reconfigurePort(self): """Set communication parameters on opened port. for the loop:// protocol all settings are ignored!""" # not that's it of any real use, but it helps in the unit tests if not isinstance(self._baudrate, (int, long)) or not 0 < self._baudrate < 2**32: raise ValueError("invalid baudrate: %r" % (self._baudrate)) if self.logger: self.logger.info('_reconfigurePort()')
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/telemetry/third_party/pyserial/serial/urlhandler/protocol_loop.py#L65-L72
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pandas/py2/pandas/core/series.py
python
Series.__array_prepare__
(self, result, context=None)
return result
Gets called prior to a ufunc.
Gets called prior to a ufunc.
[ "Gets", "called", "prior", "to", "a", "ufunc", "." ]
def __array_prepare__(self, result, context=None): """ Gets called prior to a ufunc. """ # nice error message for non-ufunc types if (context is not None and (not isinstance(self._values, (np.ndarray, ExtensionArray)) or isinstance(self._values, Categorical))): obj = context[1][0] raise TypeError("{obj} with dtype {dtype} cannot perform " "the numpy op {op}".format( obj=type(obj).__name__, dtype=getattr(obj, 'dtype', None), op=context[0].__name__)) return result
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py2/pandas/core/series.py#L737-L752
pmq20/node-packer
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
lts/deps/v8/third_party/jinja2/environment.py
python
Environment.get_template
(self, name, parent=None, globals=None)
return self._load_template(name, self.make_globals(globals))
Load a template from the loader. If a loader is configured this method asks the loader for the template and returns a :class:`Template`. If the `parent` parameter is not `None`, :meth:`join_path` is called to get the real template name before loading. The `globals` parameter can be used to provide template wide globals. These variables are available in the context at render time. If the template does not exist a :exc:`TemplateNotFound` exception is raised. .. versionchanged:: 2.4 If `name` is a :class:`Template` object it is returned from the function unchanged.
Load a template from the loader. If a loader is configured this method asks the loader for the template and returns a :class:`Template`. If the `parent` parameter is not `None`, :meth:`join_path` is called to get the real template name before loading.
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def get_template(self, name, parent=None, globals=None): """Load a template from the loader. If a loader is configured this method asks the loader for the template and returns a :class:`Template`. If the `parent` parameter is not `None`, :meth:`join_path` is called to get the real template name before loading. The `globals` parameter can be used to provide template wide globals. These variables are available in the context at render time. If the template does not exist a :exc:`TemplateNotFound` exception is raised. .. versionchanged:: 2.4 If `name` is a :class:`Template` object it is returned from the function unchanged. """ if isinstance(name, Template): return name if parent is not None: name = self.join_path(name, parent) return self._load_template(name, self.make_globals(globals))
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https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/deps/v8/third_party/jinja2/environment.py#L810-L830
krishauser/Klampt
972cc83ea5befac3f653c1ba20f80155768ad519
Python/klampt/robotsim.py
python
Mass.getMass
(self)
return _robotsim.Mass_getMass(self)
r"""
r"""
[ "r" ]
def getMass(self) ->float: r""" """ return _robotsim.Mass_getMass(self)
[ "def", "getMass", "(", "self", ")", "->", "float", ":", "return", "_robotsim", ".", "Mass_getMass", "(", "self", ")" ]
https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/klampt/robotsim.py#L3783-L3786
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/train/callback/_summary_collector.py
python
SummaryCollector._save_metadata
(self, step_per_epoch, unit, num_samples, landscape_size, create_landscape)
Save meta data to json file.
Save meta data to json file.
[ "Save", "meta", "data", "to", "json", "file", "." ]
def _save_metadata(self, step_per_epoch, unit, num_samples, landscape_size, create_landscape): """Save meta data to json file.""" data = { "epoch_group": self._epoch_group, "model_params_file_map": self._model_params_file_map, "step_per_epoch": step_per_epoch, "unit": unit, "num_samples": num_samples, "landscape_size": landscape_size, "create_landscape": create_landscape } meta_path = os.path.join(self._ckpt_dir, 'train_metadata.json') try: with open(meta_path, 'w') as file: json.dump(data, file) os.chmod(meta_path, stat.S_IRUSR) except OSError as e: logger.error("Write meta data %s failed, detail: %s" % (meta_path, str(e)))
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https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/train/callback/_summary_collector.py#L575-L592
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_controls.py
python
TreeCtrl.IsVisible
(*args, **kwargs)
return _controls_.TreeCtrl_IsVisible(*args, **kwargs)
IsVisible(self, TreeItemId item) -> bool
IsVisible(self, TreeItemId item) -> bool
[ "IsVisible", "(", "self", "TreeItemId", "item", ")", "-", ">", "bool" ]
def IsVisible(*args, **kwargs): """IsVisible(self, TreeItemId item) -> bool""" return _controls_.TreeCtrl_IsVisible(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_controls.py#L5331-L5333
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/ops/operations/nn_ops.py
python
MaxPool3D.__init__
(self, kernel_size=1, strides=1, pad_mode="VALID", pad_list=0, ceil_mode=None, data_format="NCDHW")
Initialize MaxPool3D.
Initialize MaxPool3D.
[ "Initialize", "MaxPool3D", "." ]
def __init__(self, kernel_size=1, strides=1, pad_mode="VALID", pad_list=0, ceil_mode=None, data_format="NCDHW"): """Initialize MaxPool3D.""" self.init_prim_io_names(inputs=['x'], outputs=['output']) validator.check_value_type('kernel_size', kernel_size, [int, tuple], self.name) validator.check_value_type('strides', strides, [int, tuple], self.name) validator.check_value_type('pad_mode', pad_mode, [str], self.name) self.pad_mode = validator.check_string(pad_mode.upper(), ['VALID', 'SAME', 'PAD'], 'pad_mode', self.name) if pad_mode.upper() == "PAD": self.pad_mode = "CALCULATED" self.add_prim_attr("pad_mode", self.pad_mode) self.data_format = validator.check_string(data_format, ['NCDHW'], 'data_format', self.name) self.kernel_size = _check_3d_int_or_tuple("kernel_size", kernel_size, self.name, allow_five=False, ret_five=True) self.add_prim_attr("kernel_size", self.kernel_size) self.strides = _check_3d_int_or_tuple("strides", strides, self.name, allow_five=False, ret_five=True) self.add_prim_attr("strides", self.strides) if ceil_mode is None: self.ceil_mode = not self.pad_mode == "CALCULATED" else: self.ceil_mode = validator.check_value_type('ceil_mode', ceil_mode, [bool], self.name) if self.pad_mode != "CALCULATED": raise ValueError("When the 'pad_mode' is 'same' or 'valid', the 'ceil_mode' only supports 'None'.") self.add_prim_attr("ceil_mode", int(self.ceil_mode)) validator.check_value_type('pad_list', pad_list, (int, tuple), self.name) self.pad_list = pad_list if isinstance(self.pad_list, int): self.pad_list = (self.pad_list,) * 6 if len(self.pad_list) == 3: self.pad_list = (pad_list[0], pad_list[0], pad_list[1], pad_list[1], pad_list[2], pad_list[2]) if len(self.pad_list) != 3 and len(self.pad_list) != 6: raise ValueError(f"For '{self.name}', attr 'pad_list' should be an positive int number or a tuple of " f"three or six positive int numbers, but got {len(self.pad_list)} numbers.") if self.pad_mode != 'CALCULATED' and self.pad_list != (0, 0, 0, 0, 0, 0): raise ValueError(f"For '{self.name}', the 'pad_list' must be zero or (0, 0, 0, 0, 0, 0) when 'pad_mode' " f"is not \"pad\", but got 'pad_list' is {pad_list} and 'pad_mode' is {pad_mode}.") if self.pad_mode == 'CALCULATED': for item in self.pad_list: validator.check_non_negative_int(item, 'pad_list item', self.name) self.add_prim_attr("pad_list", self.pad_list)
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https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/ops/operations/nn_ops.py#L1815-L1854
smilehao/xlua-framework
a03801538be2b0e92d39332d445b22caca1ef61f
ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/build/lib/google/protobuf/text_format.py
python
_Tokenizer.ConsumeString
(self)
Consumes a string value. Returns: The string parsed. Raises: ParseError: If a string value couldn't be consumed.
Consumes a string value.
[ "Consumes", "a", "string", "value", "." ]
def ConsumeString(self): """Consumes a string value. Returns: The string parsed. Raises: ParseError: If a string value couldn't be consumed. """ bytes = self.ConsumeByteString() try: return unicode(bytes, 'utf-8') except UnicodeDecodeError, e: raise self._StringParseError(e)
[ "def", "ConsumeString", "(", "self", ")", ":", "bytes", "=", "self", ".", "ConsumeByteString", "(", ")", "try", ":", "return", "unicode", "(", "bytes", ",", "'utf-8'", ")", "except", "UnicodeDecodeError", ",", "e", ":", "raise", "self", ".", "_StringParseError", "(", "e", ")" ]
https://github.com/smilehao/xlua-framework/blob/a03801538be2b0e92d39332d445b22caca1ef61f/ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/build/lib/google/protobuf/text_format.py#L491-L504
wyrover/book-code
7f4883d9030d553bc6bcfa3da685e34789839900
3rdparty/protobuf/python/google/protobuf/internal/containers.py
python
MessageMap.__init__
(self, message_listener, message_descriptor, key_checker)
Args: message_listener: A MessageListener implementation. The ScalarMap will call this object's Modified() method when it is modified. key_checker: A type_checkers.ValueChecker instance to run on keys inserted into this container. value_checker: A type_checkers.ValueChecker instance to run on values inserted into this container.
Args: message_listener: A MessageListener implementation. The ScalarMap will call this object's Modified() method when it is modified. key_checker: A type_checkers.ValueChecker instance to run on keys inserted into this container. value_checker: A type_checkers.ValueChecker instance to run on values inserted into this container.
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def __init__(self, message_listener, message_descriptor, key_checker): """ Args: message_listener: A MessageListener implementation. The ScalarMap will call this object's Modified() method when it is modified. key_checker: A type_checkers.ValueChecker instance to run on keys inserted into this container. value_checker: A type_checkers.ValueChecker instance to run on values inserted into this container. """ self._message_listener = message_listener self._message_descriptor = message_descriptor self._key_checker = key_checker self._values = {}
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https://github.com/wyrover/book-code/blob/7f4883d9030d553bc6bcfa3da685e34789839900/3rdparty/protobuf/python/google/protobuf/internal/containers.py#L525-L539
mongodb/mongo
d8ff665343ad29cf286ee2cf4a1960d29371937b
buildscripts/resmokelib/core/process.py
python
Process.as_command
(self)
return " ".join(sb)
Return an equivalent command line invocation of the process.
Return an equivalent command line invocation of the process.
[ "Return", "an", "equivalent", "command", "line", "invocation", "of", "the", "process", "." ]
def as_command(self): """Return an equivalent command line invocation of the process.""" default_env = os.environ env_diff = self.env.copy() # Remove environment variables that appear in both 'os.environ' and 'self.env'. for env_var in default_env: if env_var in env_diff and env_diff[env_var] == default_env[env_var]: del env_diff[env_var] sb = [] # String builder. for env_var in env_diff: sb.append(quote("%s=%s" % (env_var, env_diff[env_var]))) sb.extend(map(quote, self.args)) return " ".join(sb)
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https://github.com/mongodb/mongo/blob/d8ff665343ad29cf286ee2cf4a1960d29371937b/buildscripts/resmokelib/core/process.py#L262-L278
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/propgrid.py
python
PropertyGridInterface.SetPropertyValueString
(*args, **kwargs)
return _propgrid.PropertyGridInterface_SetPropertyValueString(*args, **kwargs)
SetPropertyValueString(self, PGPropArg id, String value)
SetPropertyValueString(self, PGPropArg id, String value)
[ "SetPropertyValueString", "(", "self", "PGPropArg", "id", "String", "value", ")" ]
def SetPropertyValueString(*args, **kwargs): """SetPropertyValueString(self, PGPropArg id, String value)""" return _propgrid.PropertyGridInterface_SetPropertyValueString(*args, **kwargs)
[ "def", "SetPropertyValueString", "(", "*", "args", ",", "*", "*", "kwargs", ")", ":", "return", "_propgrid", ".", "PropertyGridInterface_SetPropertyValueString", "(", "*", "args", ",", "*", "*", "kwargs", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/propgrid.py#L1449-L1451
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/ops/distributions/util.py
python
_smallest_integer_by_dtype
(dt)
return -1 * _largest_integer_by_dtype(dt)
Helper returning the smallest integer exactly representable by dtype.
Helper returning the smallest integer exactly representable by dtype.
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def _smallest_integer_by_dtype(dt): """Helper returning the smallest integer exactly representable by dtype.""" if not _is_known_dtype(dt): raise TypeError("Unrecognized dtype: {}".format(dt.name)) if _is_known_unsigned_by_dtype(dt): return 0 return -1 * _largest_integer_by_dtype(dt)
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/distributions/util.py#L282-L288
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/while_v2_indexed_slices_rewriter.py
python
_create_grad_indexed_slices_init
(grad_output_slices, forward_input)
return ops.IndexedSlices(values=values, indices=indices, dense_shape=shape)
Creates an IndexedSlices to pass as input to the while grad function. Args: grad_output_slices: IndexedSlices. The corresponding while grad function output. forward_input: Tensor. The corresonding input to the forward while op. Returns: Zeros IndexedSlices, created in current Graph.
Creates an IndexedSlices to pass as input to the while grad function.
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def _create_grad_indexed_slices_init(grad_output_slices, forward_input): """Creates an IndexedSlices to pass as input to the while grad function. Args: grad_output_slices: IndexedSlices. The corresponding while grad function output. forward_input: Tensor. The corresonding input to the forward while op. Returns: Zeros IndexedSlices, created in current Graph. """ assert isinstance(grad_output_slices, ops.IndexedSlices) assert isinstance(forward_input, ops.Tensor) values_out = grad_output_slices.values indices_out = grad_output_slices.indices # Create the initial values tensor. if values_out.shape.is_fully_defined(): values_shape = tensor_shape.TensorShape([0] + values_out.shape.as_list()[1:]) values = array_ops.zeros(values_shape, dtype=values_out.dtype, name="values_init") else: if forward_input.dtype == dtypes.resource: forward_shape = gen_resource_variable_ops.variable_shape(forward_input) else: forward_shape = array_ops.shape(forward_input) values_shape = array_ops.concat([[0], forward_shape[1:]], 0) values = array_ops.zeros(values_shape, dtype=values_out.dtype, name="values_init") # Create the initial indices tensor. indices = constant_op.constant([], indices_out.dtype, name="indices_init") # Create the initial dense_shape tensor. We assume is the same shape as # forward_input, since captured tensors don't change shape across loop # iterations. if forward_input.dtype == dtypes.resource: shape = gen_resource_variable_ops.variable_shape(forward_input, name="shape_init") else: shape = array_ops.shape(forward_input, name="shape_init") return ops.IndexedSlices(values=values, indices=indices, dense_shape=shape)
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/while_v2_indexed_slices_rewriter.py#L158-L201
chromiumembedded/cef
80caf947f3fe2210e5344713c5281d8af9bdc295
tools/yapf/yapf/yapflib/reformatter.py
python
_LineContainsI18n
(uwline)
return False
Return true if there are i18n comments or function calls in the line. I18n comments and pseudo-function calls are closely related. They cannot be moved apart without breaking i18n. Arguments: uwline: (unwrapped_line.UnwrappedLine) The line currently being formatted. Returns: True if the line contains i18n comments or function calls. False otherwise.
Return true if there are i18n comments or function calls in the line.
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def _LineContainsI18n(uwline): """Return true if there are i18n comments or function calls in the line. I18n comments and pseudo-function calls are closely related. They cannot be moved apart without breaking i18n. Arguments: uwline: (unwrapped_line.UnwrappedLine) The line currently being formatted. Returns: True if the line contains i18n comments or function calls. False otherwise. """ if style.Get('I18N_COMMENT'): for tok in uwline.tokens: if tok.is_comment and re.match(style.Get('I18N_COMMENT'), tok.value): # Contains an i18n comment. return True if style.Get('I18N_FUNCTION_CALL'): length = len(uwline.tokens) index = 0 while index < length - 1: if (uwline.tokens[index + 1].value == '(' and uwline.tokens[index].value in style.Get('I18N_FUNCTION_CALL')): return True index += 1 return False
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https://github.com/chromiumembedded/cef/blob/80caf947f3fe2210e5344713c5281d8af9bdc295/tools/yapf/yapf/yapflib/reformatter.py#L177-L204