nwo stringlengths 5 86 | sha stringlengths 40 40 | path stringlengths 4 189 | language stringclasses 1 value | identifier stringlengths 1 94 | parameters stringlengths 2 4.03k | argument_list stringclasses 1 value | return_statement stringlengths 0 11.5k | docstring stringlengths 1 33.2k | docstring_summary stringlengths 0 5.15k | docstring_tokens list | function stringlengths 34 151k | function_tokens list | url stringlengths 90 278 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/uuid.py | python | _unixdll_getnode | () | return UUID(bytes=_buffer.raw).node | Get the hardware address on Unix using ctypes. | Get the hardware address on Unix using ctypes. | [
"Get",
"the",
"hardware",
"address",
"on",
"Unix",
"using",
"ctypes",
"."
] | def _unixdll_getnode():
"""Get the hardware address on Unix using ctypes."""
_buffer = ctypes.create_string_buffer(16)
_uuid_generate_time(_buffer)
return UUID(bytes=_buffer.raw).node | [
"def",
"_unixdll_getnode",
"(",
")",
":",
"_buffer",
"=",
"ctypes",
".",
"create_string_buffer",
"(",
"16",
")",
"_uuid_generate_time",
"(",
"_buffer",
")",
"return",
"UUID",
"(",
"bytes",
"=",
"_buffer",
".",
"raw",
")",
".",
"node"
] | https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/uuid.py#L442-L446 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_controls.py | python | CheckListBox.GetChecked | (self) | return tuple([i for i in range(self.Count) if self.IsChecked(i)]) | GetChecked(self)
Return a tuple of integers corresponding to the checked items in
the control, based on `IsChecked`. | GetChecked(self) | [
"GetChecked",
"(",
"self",
")"
] | def GetChecked(self):
"""
GetChecked(self)
Return a tuple of integers corresponding to the checked items in
the control, based on `IsChecked`.
"""
return tuple([i for i in range(self.Count) if self.IsChecked(i)]) | [
"def",
"GetChecked",
"(",
"self",
")",
":",
"return",
"tuple",
"(",
"[",
"i",
"for",
"i",
"in",
"range",
"(",
"self",
".",
"Count",
")",
"if",
"self",
".",
"IsChecked",
"(",
"i",
")",
"]",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_controls.py#L1334-L1341 | |
isl-org/Open3D | 79aec3ddde6a571ce2f28e4096477e52ec465244 | util/check_style.py | python | _find_clang_format | () | return clang_format_bin | Find clang-format:
- not found: throw exception
- version mismatch: print warning | Find clang-format:
- not found: throw exception
- version mismatch: print warning | [
"Find",
"clang",
"-",
"format",
":",
"-",
"not",
"found",
":",
"throw",
"exception",
"-",
"version",
"mismatch",
":",
"print",
"warning"
] | def _find_clang_format():
"""
Find clang-format:
- not found: throw exception
- version mismatch: print warning
"""
preferred_clang_format_name = "clang-format-10"
preferred_version_major = 10
clang_format_bin = shutil.which(preferred_clang_format_name)
if clang_format_bin is None:
clang_format_bin = shutil.which("clang-format")
if clang_format_bin is None:
raise RuntimeError(
"clang-format not found. "
"See http://www.open3d.org/docs/release/contribute/styleguide.html#style-guide "
"for help on clang-format installation.")
version_str = subprocess.check_output([clang_format_bin, "--version"
]).decode("utf-8").strip()
try:
m = re.match("^clang-format version ([0-9.]*).*$", version_str)
if m:
version_str = m.group(1)
version_str_token = version_str.split(".")
major = int(version_str_token[0])
if major != preferred_version_major:
print("Warning: {} required, but got {}.".format(
preferred_clang_format_name, version_str))
else:
raise
except:
print("Warning: failed to parse clang-format version {}, "
"please ensure {} is used.".format(version_str,
preferred_clang_format_name))
print("Using clang-format version {}.".format(version_str))
return clang_format_bin | [
"def",
"_find_clang_format",
"(",
")",
":",
"preferred_clang_format_name",
"=",
"\"clang-format-10\"",
"preferred_version_major",
"=",
"10",
"clang_format_bin",
"=",
"shutil",
".",
"which",
"(",
"preferred_clang_format_name",
")",
"if",
"clang_format_bin",
"is",
"None",
":",
"clang_format_bin",
"=",
"shutil",
".",
"which",
"(",
"\"clang-format\"",
")",
"if",
"clang_format_bin",
"is",
"None",
":",
"raise",
"RuntimeError",
"(",
"\"clang-format not found. \"",
"\"See http://www.open3d.org/docs/release/contribute/styleguide.html#style-guide \"",
"\"for help on clang-format installation.\"",
")",
"version_str",
"=",
"subprocess",
".",
"check_output",
"(",
"[",
"clang_format_bin",
",",
"\"--version\"",
"]",
")",
".",
"decode",
"(",
"\"utf-8\"",
")",
".",
"strip",
"(",
")",
"try",
":",
"m",
"=",
"re",
".",
"match",
"(",
"\"^clang-format version ([0-9.]*).*$\"",
",",
"version_str",
")",
"if",
"m",
":",
"version_str",
"=",
"m",
".",
"group",
"(",
"1",
")",
"version_str_token",
"=",
"version_str",
".",
"split",
"(",
"\".\"",
")",
"major",
"=",
"int",
"(",
"version_str_token",
"[",
"0",
"]",
")",
"if",
"major",
"!=",
"preferred_version_major",
":",
"print",
"(",
"\"Warning: {} required, but got {}.\"",
".",
"format",
"(",
"preferred_clang_format_name",
",",
"version_str",
")",
")",
"else",
":",
"raise",
"except",
":",
"print",
"(",
"\"Warning: failed to parse clang-format version {}, \"",
"\"please ensure {} is used.\"",
".",
"format",
"(",
"version_str",
",",
"preferred_clang_format_name",
")",
")",
"print",
"(",
"\"Using clang-format version {}.\"",
".",
"format",
"(",
"version_str",
")",
")",
"return",
"clang_format_bin"
] | https://github.com/isl-org/Open3D/blob/79aec3ddde6a571ce2f28e4096477e52ec465244/util/check_style.py#L110-L145 | |
deepmind/open_spiel | 4ca53bea32bb2875c7385d215424048ae92f78c8 | open_spiel/python/mfg/games/dynamic_routing.py | python | MeanFieldRoutingGame.make_py_observer | (self, iig_obs_type=None, params=None) | return IIGObserverForPublicInfoGame(iig_obs_type, params) | Returns a NetworkObserver object used for observing game state. | Returns a NetworkObserver object used for observing game state. | [
"Returns",
"a",
"NetworkObserver",
"object",
"used",
"for",
"observing",
"game",
"state",
"."
] | def make_py_observer(self, iig_obs_type=None, params=None):
"""Returns a NetworkObserver object used for observing game state."""
if ((iig_obs_type is None) or
(iig_obs_type.public_info and not iig_obs_type.perfect_recall)):
return NetworkObserver(self.network.num_actions(), self.max_game_length())
return IIGObserverForPublicInfoGame(iig_obs_type, params) | [
"def",
"make_py_observer",
"(",
"self",
",",
"iig_obs_type",
"=",
"None",
",",
"params",
"=",
"None",
")",
":",
"if",
"(",
"(",
"iig_obs_type",
"is",
"None",
")",
"or",
"(",
"iig_obs_type",
".",
"public_info",
"and",
"not",
"iig_obs_type",
".",
"perfect_recall",
")",
")",
":",
"return",
"NetworkObserver",
"(",
"self",
".",
"network",
".",
"num_actions",
"(",
")",
",",
"self",
".",
"max_game_length",
"(",
")",
")",
"return",
"IIGObserverForPublicInfoGame",
"(",
"iig_obs_type",
",",
"params",
")"
] | https://github.com/deepmind/open_spiel/blob/4ca53bea32bb2875c7385d215424048ae92f78c8/open_spiel/python/mfg/games/dynamic_routing.py#L146-L151 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextParagraphLayoutBox.GetRichTextCtrl | (*args, **kwargs) | return _richtext.RichTextParagraphLayoutBox_GetRichTextCtrl(*args, **kwargs) | GetRichTextCtrl(self) -> RichTextCtrl | GetRichTextCtrl(self) -> RichTextCtrl | [
"GetRichTextCtrl",
"(",
"self",
")",
"-",
">",
"RichTextCtrl"
] | def GetRichTextCtrl(*args, **kwargs):
"""GetRichTextCtrl(self) -> RichTextCtrl"""
return _richtext.RichTextParagraphLayoutBox_GetRichTextCtrl(*args, **kwargs) | [
"def",
"GetRichTextCtrl",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_richtext",
".",
"RichTextParagraphLayoutBox_GetRichTextCtrl",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/richtext.py#L1616-L1618 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/propgrid.py | python | PropertyGridInterface.Insert | (*args) | return _propgrid.PropertyGridInterface_Insert(*args) | Insert(self, PGPropArg priorThis, PGProperty newproperty) -> PGProperty
Insert(self, PGPropArg parent, int index, PGProperty newproperty) -> PGProperty | Insert(self, PGPropArg priorThis, PGProperty newproperty) -> PGProperty
Insert(self, PGPropArg parent, int index, PGProperty newproperty) -> PGProperty | [
"Insert",
"(",
"self",
"PGPropArg",
"priorThis",
"PGProperty",
"newproperty",
")",
"-",
">",
"PGProperty",
"Insert",
"(",
"self",
"PGPropArg",
"parent",
"int",
"index",
"PGProperty",
"newproperty",
")",
"-",
">",
"PGProperty"
] | def Insert(*args):
"""
Insert(self, PGPropArg priorThis, PGProperty newproperty) -> PGProperty
Insert(self, PGPropArg parent, int index, PGProperty newproperty) -> PGProperty
"""
return _propgrid.PropertyGridInterface_Insert(*args) | [
"def",
"Insert",
"(",
"*",
"args",
")",
":",
"return",
"_propgrid",
".",
"PropertyGridInterface_Insert",
"(",
"*",
"args",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/propgrid.py#L1297-L1302 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/difflib.py | python | SequenceMatcher.get_opcodes | (self) | return answer | Return list of 5-tuples describing how to turn a into b.
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
tuple preceding it, and likewise for j1 == the previous j2.
The tags are strings, with these meanings:
'replace': a[i1:i2] should be replaced by b[j1:j2]
'delete': a[i1:i2] should be deleted.
Note that j1==j2 in this case.
'insert': b[j1:j2] should be inserted at a[i1:i1].
Note that i1==i2 in this case.
'equal': a[i1:i2] == b[j1:j2]
>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
... print(("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2])))
delete a[0:1] (q) b[0:0] ()
equal a[1:3] (ab) b[0:2] (ab)
replace a[3:4] (x) b[2:3] (y)
equal a[4:6] (cd) b[3:5] (cd)
insert a[6:6] () b[5:6] (f) | Return list of 5-tuples describing how to turn a into b. | [
"Return",
"list",
"of",
"5",
"-",
"tuples",
"describing",
"how",
"to",
"turn",
"a",
"into",
"b",
"."
] | def get_opcodes(self):
"""Return list of 5-tuples describing how to turn a into b.
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
tuple preceding it, and likewise for j1 == the previous j2.
The tags are strings, with these meanings:
'replace': a[i1:i2] should be replaced by b[j1:j2]
'delete': a[i1:i2] should be deleted.
Note that j1==j2 in this case.
'insert': b[j1:j2] should be inserted at a[i1:i1].
Note that i1==i2 in this case.
'equal': a[i1:i2] == b[j1:j2]
>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
... print(("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2])))
delete a[0:1] (q) b[0:0] ()
equal a[1:3] (ab) b[0:2] (ab)
replace a[3:4] (x) b[2:3] (y)
equal a[4:6] (cd) b[3:5] (cd)
insert a[6:6] () b[5:6] (f)
"""
if self.opcodes is not None:
return self.opcodes
i = j = 0
self.opcodes = answer = []
for ai, bj, size in self.get_matching_blocks():
# invariant: we've pumped out correct diffs to change
# a[:i] into b[:j], and the next matching block is
# a[ai:ai+size] == b[bj:bj+size]. So we need to pump
# out a diff to change a[i:ai] into b[j:bj], pump out
# the matching block, and move (i,j) beyond the match
tag = ''
if i < ai and j < bj:
tag = 'replace'
elif i < ai:
tag = 'delete'
elif j < bj:
tag = 'insert'
if tag:
answer.append( (tag, i, ai, j, bj) )
i, j = ai+size, bj+size
# the list of matching blocks is terminated by a
# sentinel with size 0
if size:
answer.append( ('equal', ai, i, bj, j) )
return answer | [
"def",
"get_opcodes",
"(",
"self",
")",
":",
"if",
"self",
".",
"opcodes",
"is",
"not",
"None",
":",
"return",
"self",
".",
"opcodes",
"i",
"=",
"j",
"=",
"0",
"self",
".",
"opcodes",
"=",
"answer",
"=",
"[",
"]",
"for",
"ai",
",",
"bj",
",",
"size",
"in",
"self",
".",
"get_matching_blocks",
"(",
")",
":",
"# invariant: we've pumped out correct diffs to change",
"# a[:i] into b[:j], and the next matching block is",
"# a[ai:ai+size] == b[bj:bj+size]. So we need to pump",
"# out a diff to change a[i:ai] into b[j:bj], pump out",
"# the matching block, and move (i,j) beyond the match",
"tag",
"=",
"''",
"if",
"i",
"<",
"ai",
"and",
"j",
"<",
"bj",
":",
"tag",
"=",
"'replace'",
"elif",
"i",
"<",
"ai",
":",
"tag",
"=",
"'delete'",
"elif",
"j",
"<",
"bj",
":",
"tag",
"=",
"'insert'",
"if",
"tag",
":",
"answer",
".",
"append",
"(",
"(",
"tag",
",",
"i",
",",
"ai",
",",
"j",
",",
"bj",
")",
")",
"i",
",",
"j",
"=",
"ai",
"+",
"size",
",",
"bj",
"+",
"size",
"# the list of matching blocks is terminated by a",
"# sentinel with size 0",
"if",
"size",
":",
"answer",
".",
"append",
"(",
"(",
"'equal'",
",",
"ai",
",",
"i",
",",
"bj",
",",
"j",
")",
")",
"return",
"answer"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/difflib.py#L517-L570 | |
facebook/ThreatExchange | 31914a51820c73c8a0daffe62ccca29a6e3d359e | hasher-matcher-actioner/hmalib/common/models/bank.py | python | BanksTable.add_bank_member_signal | (
self,
bank_id: str,
bank_member_id: str,
signal_type: t.Type[SignalType],
signal_value: str,
) | return member_signal | Adds a BankMemberSignal entry. First, identifies if a signal for the
corresponding (type, value) tuple exists, if so, reuses it, it not,
creates a new one.
Returns a BankMemberSignal object. Clients **should not** care whether
this is a new signal_id or not.
This check is being done here because signal uniqueness is enforced by
the same table. If this were being done in a different table/store, we
could be doing the check at a different layer eg.
hmalib.banks.bank_operations. | Adds a BankMemberSignal entry. First, identifies if a signal for the
corresponding (type, value) tuple exists, if so, reuses it, it not,
creates a new one. | [
"Adds",
"a",
"BankMemberSignal",
"entry",
".",
"First",
"identifies",
"if",
"a",
"signal",
"for",
"the",
"corresponding",
"(",
"type",
"value",
")",
"tuple",
"exists",
"if",
"so",
"reuses",
"it",
"it",
"not",
"creates",
"a",
"new",
"one",
"."
] | def add_bank_member_signal(
self,
bank_id: str,
bank_member_id: str,
signal_type: t.Type[SignalType],
signal_value: str,
) -> BankMemberSignal:
"""
Adds a BankMemberSignal entry. First, identifies if a signal for the
corresponding (type, value) tuple exists, if so, reuses it, it not,
creates a new one.
Returns a BankMemberSignal object. Clients **should not** care whether
this is a new signal_id or not.
This check is being done here because signal uniqueness is enforced by
the same table. If this were being done in a different table/store, we
could be doing the check at a different layer eg.
hmalib.banks.bank_operations.
"""
# First, we get a unique signal_id!
signal_id = BankedSignalEntry.get_unique(
self._table, signal_type=signal_type, signal_value=signal_value
).signal_id
# Next, we create the bank member signal
member_signal = BankMemberSignal(
bank_id=bank_id,
bank_member_id=bank_member_id,
signal_id=signal_id,
signal_type=signal_type,
signal_value=signal_value,
updated_at=datetime.now(),
)
member_signal.write_to_table(self._table)
return member_signal | [
"def",
"add_bank_member_signal",
"(",
"self",
",",
"bank_id",
":",
"str",
",",
"bank_member_id",
":",
"str",
",",
"signal_type",
":",
"t",
".",
"Type",
"[",
"SignalType",
"]",
",",
"signal_value",
":",
"str",
",",
")",
"->",
"BankMemberSignal",
":",
"# First, we get a unique signal_id!",
"signal_id",
"=",
"BankedSignalEntry",
".",
"get_unique",
"(",
"self",
".",
"_table",
",",
"signal_type",
"=",
"signal_type",
",",
"signal_value",
"=",
"signal_value",
")",
".",
"signal_id",
"# Next, we create the bank member signal",
"member_signal",
"=",
"BankMemberSignal",
"(",
"bank_id",
"=",
"bank_id",
",",
"bank_member_id",
"=",
"bank_member_id",
",",
"signal_id",
"=",
"signal_id",
",",
"signal_type",
"=",
"signal_type",
",",
"signal_value",
"=",
"signal_value",
",",
"updated_at",
"=",
"datetime",
".",
"now",
"(",
")",
",",
")",
"member_signal",
".",
"write_to_table",
"(",
"self",
".",
"_table",
")",
"return",
"member_signal"
] | https://github.com/facebook/ThreatExchange/blob/31914a51820c73c8a0daffe62ccca29a6e3d359e/hasher-matcher-actioner/hmalib/common/models/bank.py#L587-L622 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_vendor/distlib/database.py | python | InstalledDistribution.write_installed_files | (self, paths, prefix, dry_run=False) | return record_path | Writes the ``RECORD`` file, using the ``paths`` iterable passed in. Any
existing ``RECORD`` file is silently overwritten.
prefix is used to determine when to write absolute paths. | Writes the ``RECORD`` file, using the ``paths`` iterable passed in. Any
existing ``RECORD`` file is silently overwritten. | [
"Writes",
"the",
"RECORD",
"file",
"using",
"the",
"paths",
"iterable",
"passed",
"in",
".",
"Any",
"existing",
"RECORD",
"file",
"is",
"silently",
"overwritten",
"."
] | def write_installed_files(self, paths, prefix, dry_run=False):
"""
Writes the ``RECORD`` file, using the ``paths`` iterable passed in. Any
existing ``RECORD`` file is silently overwritten.
prefix is used to determine when to write absolute paths.
"""
prefix = os.path.join(prefix, '')
base = os.path.dirname(self.path)
base_under_prefix = base.startswith(prefix)
base = os.path.join(base, '')
record_path = self.get_distinfo_file('RECORD')
logger.info('creating %s', record_path)
if dry_run:
return None
with CSVWriter(record_path) as writer:
for path in paths:
if os.path.isdir(path) or path.endswith(('.pyc', '.pyo')):
# do not put size and hash, as in PEP-376
hash_value = size = ''
else:
size = '%d' % os.path.getsize(path)
with open(path, 'rb') as fp:
hash_value = self.get_hash(fp.read())
if path.startswith(base) or (base_under_prefix and
path.startswith(prefix)):
path = os.path.relpath(path, base)
writer.writerow((path, hash_value, size))
# add the RECORD file itself
if record_path.startswith(base):
record_path = os.path.relpath(record_path, base)
writer.writerow((record_path, '', ''))
return record_path | [
"def",
"write_installed_files",
"(",
"self",
",",
"paths",
",",
"prefix",
",",
"dry_run",
"=",
"False",
")",
":",
"prefix",
"=",
"os",
".",
"path",
".",
"join",
"(",
"prefix",
",",
"''",
")",
"base",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"self",
".",
"path",
")",
"base_under_prefix",
"=",
"base",
".",
"startswith",
"(",
"prefix",
")",
"base",
"=",
"os",
".",
"path",
".",
"join",
"(",
"base",
",",
"''",
")",
"record_path",
"=",
"self",
".",
"get_distinfo_file",
"(",
"'RECORD'",
")",
"logger",
".",
"info",
"(",
"'creating %s'",
",",
"record_path",
")",
"if",
"dry_run",
":",
"return",
"None",
"with",
"CSVWriter",
"(",
"record_path",
")",
"as",
"writer",
":",
"for",
"path",
"in",
"paths",
":",
"if",
"os",
".",
"path",
".",
"isdir",
"(",
"path",
")",
"or",
"path",
".",
"endswith",
"(",
"(",
"'.pyc'",
",",
"'.pyo'",
")",
")",
":",
"# do not put size and hash, as in PEP-376",
"hash_value",
"=",
"size",
"=",
"''",
"else",
":",
"size",
"=",
"'%d'",
"%",
"os",
".",
"path",
".",
"getsize",
"(",
"path",
")",
"with",
"open",
"(",
"path",
",",
"'rb'",
")",
"as",
"fp",
":",
"hash_value",
"=",
"self",
".",
"get_hash",
"(",
"fp",
".",
"read",
"(",
")",
")",
"if",
"path",
".",
"startswith",
"(",
"base",
")",
"or",
"(",
"base_under_prefix",
"and",
"path",
".",
"startswith",
"(",
"prefix",
")",
")",
":",
"path",
"=",
"os",
".",
"path",
".",
"relpath",
"(",
"path",
",",
"base",
")",
"writer",
".",
"writerow",
"(",
"(",
"path",
",",
"hash_value",
",",
"size",
")",
")",
"# add the RECORD file itself",
"if",
"record_path",
".",
"startswith",
"(",
"base",
")",
":",
"record_path",
"=",
"os",
".",
"path",
".",
"relpath",
"(",
"record_path",
",",
"base",
")",
"writer",
".",
"writerow",
"(",
"(",
"record_path",
",",
"''",
",",
"''",
")",
")",
"return",
"record_path"
] | 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/distlib/database.py#L673-L706 | |
BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/urllib.py | python | proxy_bypass_environment | (host) | return 0 | Test if proxies should not be used for a particular host.
Checks the environment for a variable named no_proxy, which should
be a list of DNS suffixes separated by commas, or '*' for all hosts. | Test if proxies should not be used for a particular host. | [
"Test",
"if",
"proxies",
"should",
"not",
"be",
"used",
"for",
"a",
"particular",
"host",
"."
] | def proxy_bypass_environment(host):
"""Test if proxies should not be used for a particular host.
Checks the environment for a variable named no_proxy, which should
be a list of DNS suffixes separated by commas, or '*' for all hosts.
"""
no_proxy = os.environ.get('no_proxy', '') or os.environ.get('NO_PROXY', '')
# '*' is special case for always bypass
if no_proxy == '*':
return 1
# strip port off host
hostonly, port = splitport(host)
# check if the host ends with any of the DNS suffixes
for name in no_proxy.split(','):
if name and (hostonly.endswith(name) or host.endswith(name)):
return 1
# otherwise, don't bypass
return 0 | [
"def",
"proxy_bypass_environment",
"(",
"host",
")",
":",
"no_proxy",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"'no_proxy'",
",",
"''",
")",
"or",
"os",
".",
"environ",
".",
"get",
"(",
"'NO_PROXY'",
",",
"''",
")",
"# '*' is special case for always bypass",
"if",
"no_proxy",
"==",
"'*'",
":",
"return",
"1",
"# strip port off host",
"hostonly",
",",
"port",
"=",
"splitport",
"(",
"host",
")",
"# check if the host ends with any of the DNS suffixes",
"for",
"name",
"in",
"no_proxy",
".",
"split",
"(",
"','",
")",
":",
"if",
"name",
"and",
"(",
"hostonly",
".",
"endswith",
"(",
"name",
")",
"or",
"host",
".",
"endswith",
"(",
"name",
")",
")",
":",
"return",
"1",
"# otherwise, don't bypass",
"return",
"0"
] | https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/urllib.py#L1312-L1329 | |
emscripten-core/emscripten | 0d413d3c5af8b28349682496edc14656f5700c2f | third_party/ply/example/ansic/cparse.py | python | p_expression_statement | (t) | expression_statement : expression_opt SEMI | expression_statement : expression_opt SEMI | [
"expression_statement",
":",
"expression_opt",
"SEMI"
] | def p_expression_statement(t):
'expression_statement : expression_opt SEMI'
pass | [
"def",
"p_expression_statement",
"(",
"t",
")",
":",
"pass"
] | https://github.com/emscripten-core/emscripten/blob/0d413d3c5af8b28349682496edc14656f5700c2f/third_party/ply/example/ansic/cparse.py#L479-L481 | ||
BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/distutils/command/install.py | python | install.create_home_path | (self) | Create directories under ~ | Create directories under ~ | [
"Create",
"directories",
"under",
"~"
] | def create_home_path(self):
"""Create directories under ~
"""
if not self.user:
return
home = convert_path(os.path.expanduser("~"))
for name, path in self.config_vars.iteritems():
if path.startswith(home) and not os.path.isdir(path):
self.debug_print("os.makedirs('%s', 0700)" % path)
os.makedirs(path, 0700) | [
"def",
"create_home_path",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"user",
":",
"return",
"home",
"=",
"convert_path",
"(",
"os",
".",
"path",
".",
"expanduser",
"(",
"\"~\"",
")",
")",
"for",
"name",
",",
"path",
"in",
"self",
".",
"config_vars",
".",
"iteritems",
"(",
")",
":",
"if",
"path",
".",
"startswith",
"(",
"home",
")",
"and",
"not",
"os",
".",
"path",
".",
"isdir",
"(",
"path",
")",
":",
"self",
".",
"debug_print",
"(",
"\"os.makedirs('%s', 0700)\"",
"%",
"path",
")",
"os",
".",
"makedirs",
"(",
"path",
",",
"0700",
")"
] | https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/distutils/command/install.py#L560-L569 | ||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/idlelib/AutoComplete.py | python | AutoComplete.fetch_completions | (self, what, mode) | Return a pair of lists of completions for something. The first list
is a sublist of the second. Both are sorted.
If there is a Python subprocess, get the comp. list there. Otherwise,
either fetch_completions() is running in the subprocess itself or it
was called in an IDLE EditorWindow before any script had been run.
The subprocess environment is that of the most recently run script. If
two unrelated modules are being edited some calltips in the current
module may be inoperative if the module was not the last to run. | Return a pair of lists of completions for something. The first list
is a sublist of the second. Both are sorted. | [
"Return",
"a",
"pair",
"of",
"lists",
"of",
"completions",
"for",
"something",
".",
"The",
"first",
"list",
"is",
"a",
"sublist",
"of",
"the",
"second",
".",
"Both",
"are",
"sorted",
"."
] | def fetch_completions(self, what, mode):
"""Return a pair of lists of completions for something. The first list
is a sublist of the second. Both are sorted.
If there is a Python subprocess, get the comp. list there. Otherwise,
either fetch_completions() is running in the subprocess itself or it
was called in an IDLE EditorWindow before any script had been run.
The subprocess environment is that of the most recently run script. If
two unrelated modules are being edited some calltips in the current
module may be inoperative if the module was not the last to run.
"""
try:
rpcclt = self.editwin.flist.pyshell.interp.rpcclt
except:
rpcclt = None
if rpcclt:
return rpcclt.remotecall("exec", "get_the_completion_list",
(what, mode), {})
else:
if mode == COMPLETE_ATTRIBUTES:
if what == "":
namespace = __main__.__dict__.copy()
namespace.update(__main__.__builtins__.__dict__)
bigl = eval("dir()", namespace)
bigl.sort()
if "__all__" in bigl:
smalll = sorted(eval("__all__", namespace))
else:
smalll = [s for s in bigl if s[:1] != '_']
else:
try:
entity = self.get_entity(what)
bigl = dir(entity)
bigl.sort()
if "__all__" in bigl:
smalll = sorted(entity.__all__)
else:
smalll = [s for s in bigl if s[:1] != '_']
except:
return [], []
elif mode == COMPLETE_FILES:
if what == "":
what = "."
try:
expandedpath = os.path.expanduser(what)
bigl = os.listdir(expandedpath)
bigl.sort()
smalll = [s for s in bigl if s[:1] != '.']
except OSError:
return [], []
if not smalll:
smalll = bigl
return smalll, bigl | [
"def",
"fetch_completions",
"(",
"self",
",",
"what",
",",
"mode",
")",
":",
"try",
":",
"rpcclt",
"=",
"self",
".",
"editwin",
".",
"flist",
".",
"pyshell",
".",
"interp",
".",
"rpcclt",
"except",
":",
"rpcclt",
"=",
"None",
"if",
"rpcclt",
":",
"return",
"rpcclt",
".",
"remotecall",
"(",
"\"exec\"",
",",
"\"get_the_completion_list\"",
",",
"(",
"what",
",",
"mode",
")",
",",
"{",
"}",
")",
"else",
":",
"if",
"mode",
"==",
"COMPLETE_ATTRIBUTES",
":",
"if",
"what",
"==",
"\"\"",
":",
"namespace",
"=",
"__main__",
".",
"__dict__",
".",
"copy",
"(",
")",
"namespace",
".",
"update",
"(",
"__main__",
".",
"__builtins__",
".",
"__dict__",
")",
"bigl",
"=",
"eval",
"(",
"\"dir()\"",
",",
"namespace",
")",
"bigl",
".",
"sort",
"(",
")",
"if",
"\"__all__\"",
"in",
"bigl",
":",
"smalll",
"=",
"sorted",
"(",
"eval",
"(",
"\"__all__\"",
",",
"namespace",
")",
")",
"else",
":",
"smalll",
"=",
"[",
"s",
"for",
"s",
"in",
"bigl",
"if",
"s",
"[",
":",
"1",
"]",
"!=",
"'_'",
"]",
"else",
":",
"try",
":",
"entity",
"=",
"self",
".",
"get_entity",
"(",
"what",
")",
"bigl",
"=",
"dir",
"(",
"entity",
")",
"bigl",
".",
"sort",
"(",
")",
"if",
"\"__all__\"",
"in",
"bigl",
":",
"smalll",
"=",
"sorted",
"(",
"entity",
".",
"__all__",
")",
"else",
":",
"smalll",
"=",
"[",
"s",
"for",
"s",
"in",
"bigl",
"if",
"s",
"[",
":",
"1",
"]",
"!=",
"'_'",
"]",
"except",
":",
"return",
"[",
"]",
",",
"[",
"]",
"elif",
"mode",
"==",
"COMPLETE_FILES",
":",
"if",
"what",
"==",
"\"\"",
":",
"what",
"=",
"\".\"",
"try",
":",
"expandedpath",
"=",
"os",
".",
"path",
".",
"expanduser",
"(",
"what",
")",
"bigl",
"=",
"os",
".",
"listdir",
"(",
"expandedpath",
")",
"bigl",
".",
"sort",
"(",
")",
"smalll",
"=",
"[",
"s",
"for",
"s",
"in",
"bigl",
"if",
"s",
"[",
":",
"1",
"]",
"!=",
"'.'",
"]",
"except",
"OSError",
":",
"return",
"[",
"]",
",",
"[",
"]",
"if",
"not",
"smalll",
":",
"smalll",
"=",
"bigl",
"return",
"smalll",
",",
"bigl"
] | https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/idlelib/AutoComplete.py#L166-L221 | ||
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/layers/python/layers/feature_column.py | python | _BucketizedColumn.to_sparse_tensor | (self, input_tensor) | return sparse_id_values | Creates a SparseTensor from the bucketized Tensor. | Creates a SparseTensor from the bucketized Tensor. | [
"Creates",
"a",
"SparseTensor",
"from",
"the",
"bucketized",
"Tensor",
"."
] | def to_sparse_tensor(self, input_tensor):
"""Creates a SparseTensor from the bucketized Tensor."""
dimension = self.source_column.dimension
batch_size = array_ops.shape(input_tensor, name="shape")[0]
if dimension > 1:
i1 = array_ops.reshape(
array_ops.tile(
array_ops.expand_dims(
math_ops.range(0, batch_size), 1, name="expand_dims"),
[1, dimension],
name="tile"), [-1],
name="reshape")
i2 = array_ops.tile(
math_ops.range(0, dimension), [batch_size], name="tile")
# Flatten the bucket indices and unique them across dimensions
# E.g. 2nd dimension indices will range from k to 2*k-1 with k buckets
bucket_indices = array_ops.reshape(
input_tensor, [-1], name="reshape") + self.length * i2
else:
# Simpler indices when dimension=1
i1 = math_ops.range(0, batch_size)
i2 = array_ops.zeros([batch_size], dtype=dtypes.int32, name="zeros")
bucket_indices = array_ops.reshape(input_tensor, [-1], name="reshape")
indices = math_ops.to_int64(array_ops.transpose(array_ops.stack((i1, i2))))
shape = math_ops.to_int64(array_ops.stack([batch_size, dimension]))
sparse_id_values = sparse_tensor_py.SparseTensor(
indices, bucket_indices, shape)
return sparse_id_values | [
"def",
"to_sparse_tensor",
"(",
"self",
",",
"input_tensor",
")",
":",
"dimension",
"=",
"self",
".",
"source_column",
".",
"dimension",
"batch_size",
"=",
"array_ops",
".",
"shape",
"(",
"input_tensor",
",",
"name",
"=",
"\"shape\"",
")",
"[",
"0",
"]",
"if",
"dimension",
">",
"1",
":",
"i1",
"=",
"array_ops",
".",
"reshape",
"(",
"array_ops",
".",
"tile",
"(",
"array_ops",
".",
"expand_dims",
"(",
"math_ops",
".",
"range",
"(",
"0",
",",
"batch_size",
")",
",",
"1",
",",
"name",
"=",
"\"expand_dims\"",
")",
",",
"[",
"1",
",",
"dimension",
"]",
",",
"name",
"=",
"\"tile\"",
")",
",",
"[",
"-",
"1",
"]",
",",
"name",
"=",
"\"reshape\"",
")",
"i2",
"=",
"array_ops",
".",
"tile",
"(",
"math_ops",
".",
"range",
"(",
"0",
",",
"dimension",
")",
",",
"[",
"batch_size",
"]",
",",
"name",
"=",
"\"tile\"",
")",
"# Flatten the bucket indices and unique them across dimensions",
"# E.g. 2nd dimension indices will range from k to 2*k-1 with k buckets",
"bucket_indices",
"=",
"array_ops",
".",
"reshape",
"(",
"input_tensor",
",",
"[",
"-",
"1",
"]",
",",
"name",
"=",
"\"reshape\"",
")",
"+",
"self",
".",
"length",
"*",
"i2",
"else",
":",
"# Simpler indices when dimension=1",
"i1",
"=",
"math_ops",
".",
"range",
"(",
"0",
",",
"batch_size",
")",
"i2",
"=",
"array_ops",
".",
"zeros",
"(",
"[",
"batch_size",
"]",
",",
"dtype",
"=",
"dtypes",
".",
"int32",
",",
"name",
"=",
"\"zeros\"",
")",
"bucket_indices",
"=",
"array_ops",
".",
"reshape",
"(",
"input_tensor",
",",
"[",
"-",
"1",
"]",
",",
"name",
"=",
"\"reshape\"",
")",
"indices",
"=",
"math_ops",
".",
"to_int64",
"(",
"array_ops",
".",
"transpose",
"(",
"array_ops",
".",
"stack",
"(",
"(",
"i1",
",",
"i2",
")",
")",
")",
")",
"shape",
"=",
"math_ops",
".",
"to_int64",
"(",
"array_ops",
".",
"stack",
"(",
"[",
"batch_size",
",",
"dimension",
"]",
")",
")",
"sparse_id_values",
"=",
"sparse_tensor_py",
".",
"SparseTensor",
"(",
"indices",
",",
"bucket_indices",
",",
"shape",
")",
"return",
"sparse_id_values"
] | https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/contrib/layers/python/layers/feature_column.py#L2057-L2087 | |
klzgrad/naiveproxy | ed2c513637c77b18721fe428d7ed395b4d284c83 | src/tools/grit/grit/format/data_pack.py | python | RePack | (output_file,
input_files,
allowlist_file=None,
suppress_removed_key_output=False,
output_info_filepath=None) | Write a new data pack file by combining input pack files.
Args:
output_file: path to the new data pack file.
input_files: a list of paths to the data pack files to combine.
allowlist_file: path to the file that contains the list of resource IDs
that should be kept in the output file or None to include
all resources.
suppress_removed_key_output: allows the caller to suppress the output from
RePackFromDataPackStrings.
output_info_file: If not None, specify the output .info filepath.
Raises:
KeyError: if there are duplicate keys or resource encoding is
inconsistent. | Write a new data pack file by combining input pack files. | [
"Write",
"a",
"new",
"data",
"pack",
"file",
"by",
"combining",
"input",
"pack",
"files",
"."
] | def RePack(output_file,
input_files,
allowlist_file=None,
suppress_removed_key_output=False,
output_info_filepath=None):
"""Write a new data pack file by combining input pack files.
Args:
output_file: path to the new data pack file.
input_files: a list of paths to the data pack files to combine.
allowlist_file: path to the file that contains the list of resource IDs
that should be kept in the output file or None to include
all resources.
suppress_removed_key_output: allows the caller to suppress the output from
RePackFromDataPackStrings.
output_info_file: If not None, specify the output .info filepath.
Raises:
KeyError: if there are duplicate keys or resource encoding is
inconsistent.
"""
input_data_packs = [ReadDataPack(filename) for filename in input_files]
input_info_files = [filename + '.info' for filename in input_files]
allowlist = None
if allowlist_file:
lines = util.ReadFile(allowlist_file, 'utf-8').strip().splitlines()
if not lines:
raise Exception('Allowlist file should not be empty')
allowlist = set(int(x) for x in lines)
inputs = [(p.resources, p.encoding) for p in input_data_packs]
resources, encoding = RePackFromDataPackStrings(inputs, allowlist,
suppress_removed_key_output)
WriteDataPack(resources, output_file, encoding)
if output_info_filepath is None:
output_info_filepath = output_file + '.info'
with open(output_info_filepath, 'w') as output_info_file:
for filename in input_info_files:
with open(filename, 'r') as info_file:
output_info_file.writelines(info_file.readlines()) | [
"def",
"RePack",
"(",
"output_file",
",",
"input_files",
",",
"allowlist_file",
"=",
"None",
",",
"suppress_removed_key_output",
"=",
"False",
",",
"output_info_filepath",
"=",
"None",
")",
":",
"input_data_packs",
"=",
"[",
"ReadDataPack",
"(",
"filename",
")",
"for",
"filename",
"in",
"input_files",
"]",
"input_info_files",
"=",
"[",
"filename",
"+",
"'.info'",
"for",
"filename",
"in",
"input_files",
"]",
"allowlist",
"=",
"None",
"if",
"allowlist_file",
":",
"lines",
"=",
"util",
".",
"ReadFile",
"(",
"allowlist_file",
",",
"'utf-8'",
")",
".",
"strip",
"(",
")",
".",
"splitlines",
"(",
")",
"if",
"not",
"lines",
":",
"raise",
"Exception",
"(",
"'Allowlist file should not be empty'",
")",
"allowlist",
"=",
"set",
"(",
"int",
"(",
"x",
")",
"for",
"x",
"in",
"lines",
")",
"inputs",
"=",
"[",
"(",
"p",
".",
"resources",
",",
"p",
".",
"encoding",
")",
"for",
"p",
"in",
"input_data_packs",
"]",
"resources",
",",
"encoding",
"=",
"RePackFromDataPackStrings",
"(",
"inputs",
",",
"allowlist",
",",
"suppress_removed_key_output",
")",
"WriteDataPack",
"(",
"resources",
",",
"output_file",
",",
"encoding",
")",
"if",
"output_info_filepath",
"is",
"None",
":",
"output_info_filepath",
"=",
"output_file",
"+",
"'.info'",
"with",
"open",
"(",
"output_info_filepath",
",",
"'w'",
")",
"as",
"output_info_file",
":",
"for",
"filename",
"in",
"input_info_files",
":",
"with",
"open",
"(",
"filename",
",",
"'r'",
")",
"as",
"info_file",
":",
"output_info_file",
".",
"writelines",
"(",
"info_file",
".",
"readlines",
"(",
")",
")"
] | https://github.com/klzgrad/naiveproxy/blob/ed2c513637c77b18721fe428d7ed395b4d284c83/src/tools/grit/grit/format/data_pack.py#L221-L259 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/parso/py2/parso/python/tree.py | python | ImportFrom.get_paths | (self) | return [dotted + [name] for name, alias in self._as_name_tuples()] | The import paths defined in an import statement. Typically an array
like this: ``[<Name: datetime>, <Name: date>]``.
:return list of list of Name: | The import paths defined in an import statement. Typically an array
like this: ``[<Name: datetime>, <Name: date>]``. | [
"The",
"import",
"paths",
"defined",
"in",
"an",
"import",
"statement",
".",
"Typically",
"an",
"array",
"like",
"this",
":",
"[",
"<Name",
":",
"datetime",
">",
"<Name",
":",
"date",
">",
"]",
"."
] | def get_paths(self):
"""
The import paths defined in an import statement. Typically an array
like this: ``[<Name: datetime>, <Name: date>]``.
:return list of list of Name:
"""
dotted = self.get_from_names()
if self.children[-1] == '*':
return [dotted]
return [dotted + [name] for name, alias in self._as_name_tuples()] | [
"def",
"get_paths",
"(",
"self",
")",
":",
"dotted",
"=",
"self",
".",
"get_from_names",
"(",
")",
"if",
"self",
".",
"children",
"[",
"-",
"1",
"]",
"==",
"'*'",
":",
"return",
"[",
"dotted",
"]",
"return",
"[",
"dotted",
"+",
"[",
"name",
"]",
"for",
"name",
",",
"alias",
"in",
"self",
".",
"_as_name_tuples",
"(",
")",
"]"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/parso/py2/parso/python/tree.py#L907-L918 | |
sigmaai/self-driving-golf-cart | 8d891600af3d851add27a10ae45cf3c2108bb87c | ros/src/ros_carla_bridge/carla_ros_bridge/src/carla_ros_bridge/bridge.py | python | CarlaRosBridge.run | (self) | Run the bridge functionality.
Registers on shutdown callback at rospy and spins ROS.
:return: | Run the bridge functionality. | [
"Run",
"the",
"bridge",
"functionality",
"."
] | def run(self):
"""
Run the bridge functionality.
Registers on shutdown callback at rospy and spins ROS.
:return:
"""
rospy.on_shutdown(self.on_shutdown)
rospy.spin() | [
"def",
"run",
"(",
"self",
")",
":",
"rospy",
".",
"on_shutdown",
"(",
"self",
".",
"on_shutdown",
")",
"rospy",
".",
"spin",
"(",
")"
] | https://github.com/sigmaai/self-driving-golf-cart/blob/8d891600af3d851add27a10ae45cf3c2108bb87c/ros/src/ros_carla_bridge/carla_ros_bridge/src/carla_ros_bridge/bridge.py#L418-L427 | ||
facebookincubator/BOLT | 88c70afe9d388ad430cc150cc158641701397f70 | openmp/runtime/tools/summarizeStats.py | python | setRadarFigure | (titles) | return {'ax':ax, 'theta':theta} | Set the attributes for the radar plots | Set the attributes for the radar plots | [
"Set",
"the",
"attributes",
"for",
"the",
"radar",
"plots"
] | def setRadarFigure(titles):
"""Set the attributes for the radar plots"""
fig = plt.figure(figsize=(9,9))
rect = [0.1, 0.1, 0.8, 0.8]
labels = [0.2, 0.4, 0.6, 0.8, 1, 2, 3, 4, 5, 10]
matplotlib.rcParams.update({'font.size':13})
theta = radar_factory(len(titles))
ax = fig.add_axes(rect, projection='radar')
ax.set_rgrids(labels)
ax.set_varlabels(titles)
ax.text(theta[2], 1, "Linear->Log", horizontalalignment='center', color='green', fontsize=18)
return {'ax':ax, 'theta':theta} | [
"def",
"setRadarFigure",
"(",
"titles",
")",
":",
"fig",
"=",
"plt",
".",
"figure",
"(",
"figsize",
"=",
"(",
"9",
",",
"9",
")",
")",
"rect",
"=",
"[",
"0.1",
",",
"0.1",
",",
"0.8",
",",
"0.8",
"]",
"labels",
"=",
"[",
"0.2",
",",
"0.4",
",",
"0.6",
",",
"0.8",
",",
"1",
",",
"2",
",",
"3",
",",
"4",
",",
"5",
",",
"10",
"]",
"matplotlib",
".",
"rcParams",
".",
"update",
"(",
"{",
"'font.size'",
":",
"13",
"}",
")",
"theta",
"=",
"radar_factory",
"(",
"len",
"(",
"titles",
")",
")",
"ax",
"=",
"fig",
".",
"add_axes",
"(",
"rect",
",",
"projection",
"=",
"'radar'",
")",
"ax",
".",
"set_rgrids",
"(",
"labels",
")",
"ax",
".",
"set_varlabels",
"(",
"titles",
")",
"ax",
".",
"text",
"(",
"theta",
"[",
"2",
"]",
",",
"1",
",",
"\"Linear->Log\"",
",",
"horizontalalignment",
"=",
"'center'",
",",
"color",
"=",
"'green'",
",",
"fontsize",
"=",
"18",
")",
"return",
"{",
"'ax'",
":",
"ax",
",",
"'theta'",
":",
"theta",
"}"
] | https://github.com/facebookincubator/BOLT/blob/88c70afe9d388ad430cc150cc158641701397f70/openmp/runtime/tools/summarizeStats.py#L177-L188 | |
GoSSIP-SJTU/TripleDoggy | 03648d6b19c812504b14e8b98c8c7b3f443f4e54 | tools/clang/bindings/python/clang/cindex.py | python | Cursor.is_const_method | (self) | return conf.lib.clang_CXXMethod_isConst(self) | Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'. | Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'. | [
"Returns",
"True",
"if",
"the",
"cursor",
"refers",
"to",
"a",
"C",
"++",
"member",
"function",
"or",
"member",
"function",
"template",
"that",
"is",
"declared",
"const",
"."
] | def is_const_method(self):
"""Returns True if the cursor refers to a C++ member function or member
function template that is declared 'const'.
"""
return conf.lib.clang_CXXMethod_isConst(self) | [
"def",
"is_const_method",
"(",
"self",
")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_CXXMethod_isConst",
"(",
"self",
")"
] | https://github.com/GoSSIP-SJTU/TripleDoggy/blob/03648d6b19c812504b14e8b98c8c7b3f443f4e54/tools/clang/bindings/python/clang/cindex.py#L1426-L1430 | |
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/cluster/_agglomerative.py | python | _single_linkage_tree | (connectivity, n_samples, n_nodes, n_clusters,
n_connected_components, return_distance) | return children_, n_connected_components, n_samples, parent | Perform single linkage clustering on sparse data via the minimum
spanning tree from scipy.sparse.csgraph, then using union-find to label.
The parent array is then generated by walking through the tree. | Perform single linkage clustering on sparse data via the minimum
spanning tree from scipy.sparse.csgraph, then using union-find to label.
The parent array is then generated by walking through the tree. | [
"Perform",
"single",
"linkage",
"clustering",
"on",
"sparse",
"data",
"via",
"the",
"minimum",
"spanning",
"tree",
"from",
"scipy",
".",
"sparse",
".",
"csgraph",
"then",
"using",
"union",
"-",
"find",
"to",
"label",
".",
"The",
"parent",
"array",
"is",
"then",
"generated",
"by",
"walking",
"through",
"the",
"tree",
"."
] | def _single_linkage_tree(connectivity, n_samples, n_nodes, n_clusters,
n_connected_components, return_distance):
"""
Perform single linkage clustering on sparse data via the minimum
spanning tree from scipy.sparse.csgraph, then using union-find to label.
The parent array is then generated by walking through the tree.
"""
from scipy.sparse.csgraph import minimum_spanning_tree
# explicitly cast connectivity to ensure safety
connectivity = connectivity.astype('float64',
**_astype_copy_false(connectivity))
# Ensure zero distances aren't ignored by setting them to "epsilon"
epsilon_value = np.finfo(dtype=connectivity.data.dtype).eps
connectivity.data[connectivity.data == 0] = epsilon_value
# Use scipy.sparse.csgraph to generate a minimum spanning tree
mst = minimum_spanning_tree(connectivity.tocsr())
# Convert the graph to scipy.cluster.hierarchy array format
mst = mst.tocoo()
# Undo the epsilon values
mst.data[mst.data == epsilon_value] = 0
mst_array = np.vstack([mst.row, mst.col, mst.data]).T
# Sort edges of the min_spanning_tree by weight
mst_array = mst_array[np.argsort(mst_array.T[2]), :]
# Convert edge list into standard hierarchical clustering format
single_linkage_tree = _hierarchical._single_linkage_label(mst_array)
children_ = single_linkage_tree[:, :2].astype(np.int)
# Compute parents
parent = np.arange(n_nodes, dtype=np.intp)
for i, (left, right) in enumerate(children_, n_samples):
if n_clusters is not None and i >= n_nodes:
break
if left < n_nodes:
parent[left] = i
if right < n_nodes:
parent[right] = i
if return_distance:
distances = single_linkage_tree[:, 2]
return children_, n_connected_components, n_samples, parent, distances
return children_, n_connected_components, n_samples, parent | [
"def",
"_single_linkage_tree",
"(",
"connectivity",
",",
"n_samples",
",",
"n_nodes",
",",
"n_clusters",
",",
"n_connected_components",
",",
"return_distance",
")",
":",
"from",
"scipy",
".",
"sparse",
".",
"csgraph",
"import",
"minimum_spanning_tree",
"# explicitly cast connectivity to ensure safety",
"connectivity",
"=",
"connectivity",
".",
"astype",
"(",
"'float64'",
",",
"*",
"*",
"_astype_copy_false",
"(",
"connectivity",
")",
")",
"# Ensure zero distances aren't ignored by setting them to \"epsilon\"",
"epsilon_value",
"=",
"np",
".",
"finfo",
"(",
"dtype",
"=",
"connectivity",
".",
"data",
".",
"dtype",
")",
".",
"eps",
"connectivity",
".",
"data",
"[",
"connectivity",
".",
"data",
"==",
"0",
"]",
"=",
"epsilon_value",
"# Use scipy.sparse.csgraph to generate a minimum spanning tree",
"mst",
"=",
"minimum_spanning_tree",
"(",
"connectivity",
".",
"tocsr",
"(",
")",
")",
"# Convert the graph to scipy.cluster.hierarchy array format",
"mst",
"=",
"mst",
".",
"tocoo",
"(",
")",
"# Undo the epsilon values",
"mst",
".",
"data",
"[",
"mst",
".",
"data",
"==",
"epsilon_value",
"]",
"=",
"0",
"mst_array",
"=",
"np",
".",
"vstack",
"(",
"[",
"mst",
".",
"row",
",",
"mst",
".",
"col",
",",
"mst",
".",
"data",
"]",
")",
".",
"T",
"# Sort edges of the min_spanning_tree by weight",
"mst_array",
"=",
"mst_array",
"[",
"np",
".",
"argsort",
"(",
"mst_array",
".",
"T",
"[",
"2",
"]",
")",
",",
":",
"]",
"# Convert edge list into standard hierarchical clustering format",
"single_linkage_tree",
"=",
"_hierarchical",
".",
"_single_linkage_label",
"(",
"mst_array",
")",
"children_",
"=",
"single_linkage_tree",
"[",
":",
",",
":",
"2",
"]",
".",
"astype",
"(",
"np",
".",
"int",
")",
"# Compute parents",
"parent",
"=",
"np",
".",
"arange",
"(",
"n_nodes",
",",
"dtype",
"=",
"np",
".",
"intp",
")",
"for",
"i",
",",
"(",
"left",
",",
"right",
")",
"in",
"enumerate",
"(",
"children_",
",",
"n_samples",
")",
":",
"if",
"n_clusters",
"is",
"not",
"None",
"and",
"i",
">=",
"n_nodes",
":",
"break",
"if",
"left",
"<",
"n_nodes",
":",
"parent",
"[",
"left",
"]",
"=",
"i",
"if",
"right",
"<",
"n_nodes",
":",
"parent",
"[",
"right",
"]",
"=",
"i",
"if",
"return_distance",
":",
"distances",
"=",
"single_linkage_tree",
"[",
":",
",",
"2",
"]",
"return",
"children_",
",",
"n_connected_components",
",",
"n_samples",
",",
"parent",
",",
"distances",
"return",
"children_",
",",
"n_connected_components",
",",
"n_samples",
",",
"parent"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scikit-learn/py3/sklearn/cluster/_agglomerative.py#L82-L130 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/generic.py | python | NDFrame._constructor_sliced | (self) | Used when a manipulation result has one lower dimension(s) as the
original, such as DataFrame single columns slicing. | Used when a manipulation result has one lower dimension(s) as the
original, such as DataFrame single columns slicing. | [
"Used",
"when",
"a",
"manipulation",
"result",
"has",
"one",
"lower",
"dimension",
"(",
"s",
")",
"as",
"the",
"original",
"such",
"as",
"DataFrame",
"single",
"columns",
"slicing",
"."
] | def _constructor_sliced(self):
"""Used when a manipulation result has one lower dimension(s) as the
original, such as DataFrame single columns slicing.
"""
raise AbstractMethodError(self) | [
"def",
"_constructor_sliced",
"(",
"self",
")",
":",
"raise",
"AbstractMethodError",
"(",
"self",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/generic.py#L281-L285 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tkinter/__init__.py | python | Misc.pack_slaves | (self) | return [self._nametowidget(x) for x in
self.tk.splitlist(
self.tk.call('pack', 'slaves', self._w))] | Return a list of all slaves of this widget
in its packing order. | Return a list of all slaves of this widget
in its packing order. | [
"Return",
"a",
"list",
"of",
"all",
"slaves",
"of",
"this",
"widget",
"in",
"its",
"packing",
"order",
"."
] | def pack_slaves(self):
"""Return a list of all slaves of this widget
in its packing order."""
return [self._nametowidget(x) for x in
self.tk.splitlist(
self.tk.call('pack', 'slaves', self._w))] | [
"def",
"pack_slaves",
"(",
"self",
")",
":",
"return",
"[",
"self",
".",
"_nametowidget",
"(",
"x",
")",
"for",
"x",
"in",
"self",
".",
"tk",
".",
"splitlist",
"(",
"self",
".",
"tk",
".",
"call",
"(",
"'pack'",
",",
"'slaves'",
",",
"self",
".",
"_w",
")",
")",
"]"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tkinter/__init__.py#L1521-L1526 | |
miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/layers/python/layers/feature_column.py | python | sparse_column_with_integerized_feature | (column_name,
bucket_size,
combiner="sum",
dtype=dtypes.int64) | return _SparseColumnIntegerized(column_name,
bucket_size,
combiner=combiner,
dtype=dtype) | Creates an integerized _SparseColumn.
Use this when your features are already pre-integerized into int64 IDs.
output_id = input_feature
Args:
column_name: A string defining sparse column name.
bucket_size: An int that is > 1. The number of buckets. It should be bigger
than maximum feature. In other words features in this column should be an
int64 in range [0, bucket_size)
combiner: A string specifying how to reduce if the sparse column is
multivalent. Currently "mean", "sqrtn" and "sum" are supported, with
"sum" the default:
* "sum": do not normalize features in the column
* "mean": do l1 normalization on features in the column
* "sqrtn": do l2 normalization on features in the column
For more information: `tf.embedding_lookup_sparse`.
dtype: Type of features. It should be an integer type. Default value is
dtypes.int64.
Returns:
An integerized _SparseColumn definition.
Raises:
ValueError: bucket_size is not greater than 1.
ValueError: dtype is not integer. | Creates an integerized _SparseColumn. | [
"Creates",
"an",
"integerized",
"_SparseColumn",
"."
] | def sparse_column_with_integerized_feature(column_name,
bucket_size,
combiner="sum",
dtype=dtypes.int64):
"""Creates an integerized _SparseColumn.
Use this when your features are already pre-integerized into int64 IDs.
output_id = input_feature
Args:
column_name: A string defining sparse column name.
bucket_size: An int that is > 1. The number of buckets. It should be bigger
than maximum feature. In other words features in this column should be an
int64 in range [0, bucket_size)
combiner: A string specifying how to reduce if the sparse column is
multivalent. Currently "mean", "sqrtn" and "sum" are supported, with
"sum" the default:
* "sum": do not normalize features in the column
* "mean": do l1 normalization on features in the column
* "sqrtn": do l2 normalization on features in the column
For more information: `tf.embedding_lookup_sparse`.
dtype: Type of features. It should be an integer type. Default value is
dtypes.int64.
Returns:
An integerized _SparseColumn definition.
Raises:
ValueError: bucket_size is not greater than 1.
ValueError: dtype is not integer.
"""
return _SparseColumnIntegerized(column_name,
bucket_size,
combiner=combiner,
dtype=dtype) | [
"def",
"sparse_column_with_integerized_feature",
"(",
"column_name",
",",
"bucket_size",
",",
"combiner",
"=",
"\"sum\"",
",",
"dtype",
"=",
"dtypes",
".",
"int64",
")",
":",
"return",
"_SparseColumnIntegerized",
"(",
"column_name",
",",
"bucket_size",
",",
"combiner",
"=",
"combiner",
",",
"dtype",
"=",
"dtype",
")"
] | https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/contrib/layers/python/layers/feature_column.py#L314-L348 | |
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/engine/training_v2.py | python | _process_inputs | (model,
x,
y,
batch_size=None,
epochs=1,
sample_weights=None,
class_weights=None,
shuffle=False,
steps=None,
distribution_strategy=None,
max_queue_size=10,
workers=1,
use_multiprocessing=False) | return adapter | Process the inputs for fit/eval/predict(). | Process the inputs for fit/eval/predict(). | [
"Process",
"the",
"inputs",
"for",
"fit",
"/",
"eval",
"/",
"predict",
"()",
"."
] | def _process_inputs(model,
x,
y,
batch_size=None,
epochs=1,
sample_weights=None,
class_weights=None,
shuffle=False,
steps=None,
distribution_strategy=None,
max_queue_size=10,
workers=1,
use_multiprocessing=False):
"""Process the inputs for fit/eval/predict()."""
adapter_cls = data_adapter.select_data_adapter(x, y)
if adapter_cls in _ADAPTER_FOR_STANDARDIZE_USER_DATA:
x, y, sample_weights = model._standardize_user_data(
x,
y,
sample_weight=sample_weights,
class_weight=class_weights,
batch_size=batch_size,
check_steps=False,
steps=steps)
adapter = adapter_cls(
x,
y,
batch_size=batch_size,
epochs=epochs,
steps=steps,
sample_weights=sample_weights,
shuffle=shuffle,
distribution_strategy=distribution_strategy,
max_queue_size=max_queue_size,
workers=workers,
use_multiprocessing=use_multiprocessing)
# As a fallback for the data type that does not work with
# _standardize_user_data, use the _prepare_model_with_inputs.
if adapter_cls not in _ADAPTER_FOR_STANDARDIZE_USER_DATA:
training_v2_utils._prepare_model_with_inputs(model, adapter.get_dataset())
return adapter | [
"def",
"_process_inputs",
"(",
"model",
",",
"x",
",",
"y",
",",
"batch_size",
"=",
"None",
",",
"epochs",
"=",
"1",
",",
"sample_weights",
"=",
"None",
",",
"class_weights",
"=",
"None",
",",
"shuffle",
"=",
"False",
",",
"steps",
"=",
"None",
",",
"distribution_strategy",
"=",
"None",
",",
"max_queue_size",
"=",
"10",
",",
"workers",
"=",
"1",
",",
"use_multiprocessing",
"=",
"False",
")",
":",
"adapter_cls",
"=",
"data_adapter",
".",
"select_data_adapter",
"(",
"x",
",",
"y",
")",
"if",
"adapter_cls",
"in",
"_ADAPTER_FOR_STANDARDIZE_USER_DATA",
":",
"x",
",",
"y",
",",
"sample_weights",
"=",
"model",
".",
"_standardize_user_data",
"(",
"x",
",",
"y",
",",
"sample_weight",
"=",
"sample_weights",
",",
"class_weight",
"=",
"class_weights",
",",
"batch_size",
"=",
"batch_size",
",",
"check_steps",
"=",
"False",
",",
"steps",
"=",
"steps",
")",
"adapter",
"=",
"adapter_cls",
"(",
"x",
",",
"y",
",",
"batch_size",
"=",
"batch_size",
",",
"epochs",
"=",
"epochs",
",",
"steps",
"=",
"steps",
",",
"sample_weights",
"=",
"sample_weights",
",",
"shuffle",
"=",
"shuffle",
",",
"distribution_strategy",
"=",
"distribution_strategy",
",",
"max_queue_size",
"=",
"max_queue_size",
",",
"workers",
"=",
"workers",
",",
"use_multiprocessing",
"=",
"use_multiprocessing",
")",
"# As a fallback for the data type that does not work with",
"# _standardize_user_data, use the _prepare_model_with_inputs.",
"if",
"adapter_cls",
"not",
"in",
"_ADAPTER_FOR_STANDARDIZE_USER_DATA",
":",
"training_v2_utils",
".",
"_prepare_model_with_inputs",
"(",
"model",
",",
"adapter",
".",
"get_dataset",
"(",
")",
")",
"return",
"adapter"
] | https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/engine/training_v2.py#L585-L625 | |
apiaryio/snowcrash | b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3 | tools/gyp/buildbot/buildbot_run.py | python | CallSubProcess | (*args, **kwargs) | Wrapper around subprocess.call which treats errors as build exceptions. | Wrapper around subprocess.call which treats errors as build exceptions. | [
"Wrapper",
"around",
"subprocess",
".",
"call",
"which",
"treats",
"errors",
"as",
"build",
"exceptions",
"."
] | def CallSubProcess(*args, **kwargs):
"""Wrapper around subprocess.call which treats errors as build exceptions."""
with open(os.devnull) as devnull_fd:
retcode = subprocess.call(stdin=devnull_fd, *args, **kwargs)
if retcode != 0:
print '@@@STEP_EXCEPTION@@@'
sys.exit(1) | [
"def",
"CallSubProcess",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"with",
"open",
"(",
"os",
".",
"devnull",
")",
"as",
"devnull_fd",
":",
"retcode",
"=",
"subprocess",
".",
"call",
"(",
"stdin",
"=",
"devnull_fd",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"if",
"retcode",
"!=",
"0",
":",
"print",
"'@@@STEP_EXCEPTION@@@'",
"sys",
".",
"exit",
"(",
"1",
")"
] | https://github.com/apiaryio/snowcrash/blob/b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3/tools/gyp/buildbot/buildbot_run.py#L22-L28 | ||
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/rosgraph/src/rosgraph/masterapi.py | python | Master.getPid | (self) | return self._succeed(self.handle.getPid(self.caller_id)) | Get the PID of this server
@return: serverProcessPID
@rtype: int
@raise rosgraph.masterapi.Error: if Master returns ERROR.
@raise rosgraph.masterapi.Failure: if Master returns FAILURE. | Get the PID of this server | [
"Get",
"the",
"PID",
"of",
"this",
"server"
] | def getPid(self):
"""
Get the PID of this server
@return: serverProcessPID
@rtype: int
@raise rosgraph.masterapi.Error: if Master returns ERROR.
@raise rosgraph.masterapi.Failure: if Master returns FAILURE.
"""
return self._succeed(self.handle.getPid(self.caller_id)) | [
"def",
"getPid",
"(",
"self",
")",
":",
"return",
"self",
".",
"_succeed",
"(",
"self",
".",
"handle",
".",
"getPid",
"(",
"self",
".",
"caller_id",
")",
")"
] | https://github.com/ApolloAuto/apollo-platform/blob/86d9dc6743b496ead18d597748ebabd34a513289/ros/ros_comm/rosgraph/src/rosgraph/masterapi.py#L288-L296 | |
johmathe/shotdetect | 1ecf93a695c96fd7601a41ab5834f1117b9d7d50 | tools/cpplint.py | python | _CppLintState.SetVerboseLevel | (self, level) | return last_verbose_level | Sets the module's verbosity, and returns the previous setting. | Sets the module's verbosity, and returns the previous setting. | [
"Sets",
"the",
"module",
"s",
"verbosity",
"and",
"returns",
"the",
"previous",
"setting",
"."
] | def SetVerboseLevel(self, level):
"""Sets the module's verbosity, and returns the previous setting."""
last_verbose_level = self.verbose_level
self.verbose_level = level
return last_verbose_level | [
"def",
"SetVerboseLevel",
"(",
"self",
",",
"level",
")",
":",
"last_verbose_level",
"=",
"self",
".",
"verbose_level",
"self",
".",
"verbose_level",
"=",
"level",
"return",
"last_verbose_level"
] | https://github.com/johmathe/shotdetect/blob/1ecf93a695c96fd7601a41ab5834f1117b9d7d50/tools/cpplint.py#L511-L515 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/stc.py | python | StyledTextCtrl.GetTag | (*args, **kwargs) | return _stc.StyledTextCtrl_GetTag(*args, **kwargs) | GetTag(self, int tagNumber) -> String | GetTag(self, int tagNumber) -> String | [
"GetTag",
"(",
"self",
"int",
"tagNumber",
")",
"-",
">",
"String"
] | def GetTag(*args, **kwargs):
"""GetTag(self, int tagNumber) -> String"""
return _stc.StyledTextCtrl_GetTag(*args, **kwargs) | [
"def",
"GetTag",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_stc",
".",
"StyledTextCtrl_GetTag",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L4285-L4287 | |
SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/nyan/import_tree.py | python | ImportTree.expand_from_object | (self, nyan_object) | Expands the tree from a nyan object.
:param nyan_object: A nyan object.
:type nyan_object: .nyan_structs.NyanObject | Expands the tree from a nyan object. | [
"Expands",
"the",
"tree",
"from",
"a",
"nyan",
"object",
"."
] | def expand_from_object(self, nyan_object):
"""
Expands the tree from a nyan object.
:param nyan_object: A nyan object.
:type nyan_object: .nyan_structs.NyanObject
"""
# Process the object
fqon = nyan_object.get_fqon()
if fqon[0] != "engine":
current_node = self.root
node_type = NodeType.OBJECT
for node_str in fqon:
if current_node.has_child(node_str):
# Choose the already created node
current_node = current_node.get_child(node_str)
else:
# Add a new node
new_node = Node(node_str, node_type, current_node)
current_node.add_child(new_node)
current_node = new_node
else:
# Workaround for API objects because they are not loaded
# from files currently.
# TODO: Remove workaround when API is loaded from files.
current_node = self.root
index = 0
while index < len(fqon):
node_str = fqon[index]
if current_node.has_child(node_str):
# Choose the already created node
current_node = current_node.get_child(node_str)
else:
# Add a new node
if node_str[0].islower():
# By convention, directory and file names are lower case
# We can check for that to determine the node type.
node_type = NodeType.FILESYS
else:
node_type = NodeType.OBJECT
new_node = Node(node_str, node_type, current_node)
current_node.add_child(new_node)
current_node = new_node
index += 1
# Recursively search the nyan objects for nested objects
unsearched_objects = []
unsearched_objects.extend(nyan_object.get_nested_objects())
found_nested_objects = []
while len(unsearched_objects) > 0:
current_nested_object = unsearched_objects[0]
unsearched_objects.extend(current_nested_object.get_nested_objects())
found_nested_objects.append(current_nested_object)
unsearched_objects.remove(current_nested_object)
# Process fqons of the nested objects
for nested_object in found_nested_objects:
current_node = self.root
node_type = NodeType.NESTED
fqon = nested_object.get_fqon()
for node_str in fqon:
if current_node.has_child(node_str):
# Choose the already created node
current_node = current_node.get_child(node_str)
else:
# Add a new node
new_node = Node(node_str, node_type, current_node)
current_node.add_child(new_node)
current_node = new_node | [
"def",
"expand_from_object",
"(",
"self",
",",
"nyan_object",
")",
":",
"# Process the object",
"fqon",
"=",
"nyan_object",
".",
"get_fqon",
"(",
")",
"if",
"fqon",
"[",
"0",
"]",
"!=",
"\"engine\"",
":",
"current_node",
"=",
"self",
".",
"root",
"node_type",
"=",
"NodeType",
".",
"OBJECT",
"for",
"node_str",
"in",
"fqon",
":",
"if",
"current_node",
".",
"has_child",
"(",
"node_str",
")",
":",
"# Choose the already created node",
"current_node",
"=",
"current_node",
".",
"get_child",
"(",
"node_str",
")",
"else",
":",
"# Add a new node",
"new_node",
"=",
"Node",
"(",
"node_str",
",",
"node_type",
",",
"current_node",
")",
"current_node",
".",
"add_child",
"(",
"new_node",
")",
"current_node",
"=",
"new_node",
"else",
":",
"# Workaround for API objects because they are not loaded",
"# from files currently.",
"# TODO: Remove workaround when API is loaded from files.",
"current_node",
"=",
"self",
".",
"root",
"index",
"=",
"0",
"while",
"index",
"<",
"len",
"(",
"fqon",
")",
":",
"node_str",
"=",
"fqon",
"[",
"index",
"]",
"if",
"current_node",
".",
"has_child",
"(",
"node_str",
")",
":",
"# Choose the already created node",
"current_node",
"=",
"current_node",
".",
"get_child",
"(",
"node_str",
")",
"else",
":",
"# Add a new node",
"if",
"node_str",
"[",
"0",
"]",
".",
"islower",
"(",
")",
":",
"# By convention, directory and file names are lower case",
"# We can check for that to determine the node type.",
"node_type",
"=",
"NodeType",
".",
"FILESYS",
"else",
":",
"node_type",
"=",
"NodeType",
".",
"OBJECT",
"new_node",
"=",
"Node",
"(",
"node_str",
",",
"node_type",
",",
"current_node",
")",
"current_node",
".",
"add_child",
"(",
"new_node",
")",
"current_node",
"=",
"new_node",
"index",
"+=",
"1",
"# Recursively search the nyan objects for nested objects",
"unsearched_objects",
"=",
"[",
"]",
"unsearched_objects",
".",
"extend",
"(",
"nyan_object",
".",
"get_nested_objects",
"(",
")",
")",
"found_nested_objects",
"=",
"[",
"]",
"while",
"len",
"(",
"unsearched_objects",
")",
">",
"0",
":",
"current_nested_object",
"=",
"unsearched_objects",
"[",
"0",
"]",
"unsearched_objects",
".",
"extend",
"(",
"current_nested_object",
".",
"get_nested_objects",
"(",
")",
")",
"found_nested_objects",
".",
"append",
"(",
"current_nested_object",
")",
"unsearched_objects",
".",
"remove",
"(",
"current_nested_object",
")",
"# Process fqons of the nested objects",
"for",
"nested_object",
"in",
"found_nested_objects",
":",
"current_node",
"=",
"self",
".",
"root",
"node_type",
"=",
"NodeType",
".",
"NESTED",
"fqon",
"=",
"nested_object",
".",
"get_fqon",
"(",
")",
"for",
"node_str",
"in",
"fqon",
":",
"if",
"current_node",
".",
"has_child",
"(",
"node_str",
")",
":",
"# Choose the already created node",
"current_node",
"=",
"current_node",
".",
"get_child",
"(",
"node_str",
")",
"else",
":",
"# Add a new node",
"new_node",
"=",
"Node",
"(",
"node_str",
",",
"node_type",
",",
"current_node",
")",
"current_node",
".",
"add_child",
"(",
"new_node",
")",
"current_node",
"=",
"new_node"
] | https://github.com/SFTtech/openage/blob/d6a08c53c48dc1e157807471df92197f6ca9e04d/openage/nyan/import_tree.py#L70-L150 | ||
ablab/spades | 3a754192b88540524ce6fb69eef5ea9273a38465 | assembler/ext/src/python_libs/pyyaml2/__init__.py | python | add_representer | (data_type, representer, Dumper=Dumper) | Add a representer for the given type.
Representer is a function accepting a Dumper instance
and an instance of the given data type
and producing the corresponding representation node. | Add a representer for the given type.
Representer is a function accepting a Dumper instance
and an instance of the given data type
and producing the corresponding representation node. | [
"Add",
"a",
"representer",
"for",
"the",
"given",
"type",
".",
"Representer",
"is",
"a",
"function",
"accepting",
"a",
"Dumper",
"instance",
"and",
"an",
"instance",
"of",
"the",
"given",
"data",
"type",
"and",
"producing",
"the",
"corresponding",
"representation",
"node",
"."
] | def add_representer(data_type, representer, Dumper=Dumper):
"""
Add a representer for the given type.
Representer is a function accepting a Dumper instance
and an instance of the given data type
and producing the corresponding representation node.
"""
Dumper.add_representer(data_type, representer) | [
"def",
"add_representer",
"(",
"data_type",
",",
"representer",
",",
"Dumper",
"=",
"Dumper",
")",
":",
"Dumper",
".",
"add_representer",
"(",
"data_type",
",",
"representer",
")"
] | https://github.com/ablab/spades/blob/3a754192b88540524ce6fb69eef5ea9273a38465/assembler/ext/src/python_libs/pyyaml2/__init__.py#L266-L273 | ||
apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/ndarray/ndarray.py | python | NDArray.to_dlpack_for_write | (self) | return to_dlpack_for_write(self) | Returns a reference view of NDArray that represents as DLManagedTensor until
all previous read/write operations on the current array are finished.
Returns
-------
PyCapsule (the pointer of DLManagedTensor)
a reference view of NDArray that represents as DLManagedTensor.
Examples
--------
>>> x = mx.nd.ones((2,3))
>>> w = mx.nd.to_dlpack_for_write(x)
>>> type(w)
<class 'PyCapsule'>
>>> u = mx.nd.from_dlpack(w)
>>> u += 1
>>> x
[[2. 2. 2.]
[2. 2. 2.]]
<NDArray 2x3 @cpu(0)> | Returns a reference view of NDArray that represents as DLManagedTensor until
all previous read/write operations on the current array are finished. | [
"Returns",
"a",
"reference",
"view",
"of",
"NDArray",
"that",
"represents",
"as",
"DLManagedTensor",
"until",
"all",
"previous",
"read",
"/",
"write",
"operations",
"on",
"the",
"current",
"array",
"are",
"finished",
"."
] | def to_dlpack_for_write(self):
"""Returns a reference view of NDArray that represents as DLManagedTensor until
all previous read/write operations on the current array are finished.
Returns
-------
PyCapsule (the pointer of DLManagedTensor)
a reference view of NDArray that represents as DLManagedTensor.
Examples
--------
>>> x = mx.nd.ones((2,3))
>>> w = mx.nd.to_dlpack_for_write(x)
>>> type(w)
<class 'PyCapsule'>
>>> u = mx.nd.from_dlpack(w)
>>> u += 1
>>> x
[[2. 2. 2.]
[2. 2. 2.]]
<NDArray 2x3 @cpu(0)>
"""
return to_dlpack_for_write(self) | [
"def",
"to_dlpack_for_write",
"(",
"self",
")",
":",
"return",
"to_dlpack_for_write",
"(",
"self",
")"
] | https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/ndarray/ndarray.py#L2998-L3020 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/array_analysis.py | python | SymbolicEquivSet._insert | (self, objs) | return True | Overload _insert method to handle ind changes between relative
objects. Returns True if some change is made, false otherwise. | Overload _insert method to handle ind changes between relative
objects. Returns True if some change is made, false otherwise. | [
"Overload",
"_insert",
"method",
"to",
"handle",
"ind",
"changes",
"between",
"relative",
"objects",
".",
"Returns",
"True",
"if",
"some",
"change",
"is",
"made",
"false",
"otherwise",
"."
] | def _insert(self, objs):
"""Overload _insert method to handle ind changes between relative
objects. Returns True if some change is made, false otherwise.
"""
indset = set()
uniqs = set()
for obj in objs:
ind = self._get_ind(obj)
if ind == -1:
uniqs.add(obj)
elif not (ind in indset):
uniqs.add(obj)
indset.add(ind)
if len(uniqs) <= 1:
return False
uniqs = list(uniqs)
super(SymbolicEquivSet, self)._insert(uniqs)
objs = self.ind_to_obj[self._get_ind(uniqs[0])]
# New equivalence guided by def_by and ref_by
offset_dict = {}
def get_or_set(d, k):
if k in d:
v = d[k]
else:
v = []
d[k] = v
return v
for obj in objs:
if obj in self.def_by:
value = self.def_by[obj]
if isinstance(value, tuple):
(name, offset) = value
get_or_set(offset_dict, -offset).append(name)
if name in self.ref_by: # relative to name
for (v, i) in self.ref_by[name]:
get_or_set(offset_dict, -(offset+i)).append(v)
if obj in self.ref_by:
for (name, offset) in self.ref_by[obj]:
get_or_set(offset_dict, offset).append(name)
for names in offset_dict.values():
self._insert(names)
return True | [
"def",
"_insert",
"(",
"self",
",",
"objs",
")",
":",
"indset",
"=",
"set",
"(",
")",
"uniqs",
"=",
"set",
"(",
")",
"for",
"obj",
"in",
"objs",
":",
"ind",
"=",
"self",
".",
"_get_ind",
"(",
"obj",
")",
"if",
"ind",
"==",
"-",
"1",
":",
"uniqs",
".",
"add",
"(",
"obj",
")",
"elif",
"not",
"(",
"ind",
"in",
"indset",
")",
":",
"uniqs",
".",
"add",
"(",
"obj",
")",
"indset",
".",
"add",
"(",
"ind",
")",
"if",
"len",
"(",
"uniqs",
")",
"<=",
"1",
":",
"return",
"False",
"uniqs",
"=",
"list",
"(",
"uniqs",
")",
"super",
"(",
"SymbolicEquivSet",
",",
"self",
")",
".",
"_insert",
"(",
"uniqs",
")",
"objs",
"=",
"self",
".",
"ind_to_obj",
"[",
"self",
".",
"_get_ind",
"(",
"uniqs",
"[",
"0",
"]",
")",
"]",
"# New equivalence guided by def_by and ref_by",
"offset_dict",
"=",
"{",
"}",
"def",
"get_or_set",
"(",
"d",
",",
"k",
")",
":",
"if",
"k",
"in",
"d",
":",
"v",
"=",
"d",
"[",
"k",
"]",
"else",
":",
"v",
"=",
"[",
"]",
"d",
"[",
"k",
"]",
"=",
"v",
"return",
"v",
"for",
"obj",
"in",
"objs",
":",
"if",
"obj",
"in",
"self",
".",
"def_by",
":",
"value",
"=",
"self",
".",
"def_by",
"[",
"obj",
"]",
"if",
"isinstance",
"(",
"value",
",",
"tuple",
")",
":",
"(",
"name",
",",
"offset",
")",
"=",
"value",
"get_or_set",
"(",
"offset_dict",
",",
"-",
"offset",
")",
".",
"append",
"(",
"name",
")",
"if",
"name",
"in",
"self",
".",
"ref_by",
":",
"# relative to name",
"for",
"(",
"v",
",",
"i",
")",
"in",
"self",
".",
"ref_by",
"[",
"name",
"]",
":",
"get_or_set",
"(",
"offset_dict",
",",
"-",
"(",
"offset",
"+",
"i",
")",
")",
".",
"append",
"(",
"v",
")",
"if",
"obj",
"in",
"self",
".",
"ref_by",
":",
"for",
"(",
"name",
",",
"offset",
")",
"in",
"self",
".",
"ref_by",
"[",
"obj",
"]",
":",
"get_or_set",
"(",
"offset_dict",
",",
"offset",
")",
".",
"append",
"(",
"name",
")",
"for",
"names",
"in",
"offset_dict",
".",
"values",
"(",
")",
":",
"self",
".",
"_insert",
"(",
"names",
")",
"return",
"True"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/array_analysis.py#L854-L896 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/richtext.py | python | RichTextCtrl.SetDragStartTime | (*args, **kwargs) | return _richtext.RichTextCtrl_SetDragStartTime(*args, **kwargs) | SetDragStartTime(self, DateTime st) | SetDragStartTime(self, DateTime st) | [
"SetDragStartTime",
"(",
"self",
"DateTime",
"st",
")"
] | def SetDragStartTime(*args, **kwargs):
"""SetDragStartTime(self, DateTime st)"""
return _richtext.RichTextCtrl_SetDragStartTime(*args, **kwargs) | [
"def",
"SetDragStartTime",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_richtext",
".",
"RichTextCtrl_SetDragStartTime",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/richtext.py#L3057-L3059 | |
hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/contrib/onnx/mx2onnx/_op_translations.py | python | convert_broadcast_lesser | (node, **kwargs) | return create_basic_op_node('Less', node, kwargs) | Map MXNet's broadcast_lesser operator attributes to onnx's Less operator
and return the created node. | Map MXNet's broadcast_lesser operator attributes to onnx's Less operator
and return the created node. | [
"Map",
"MXNet",
"s",
"broadcast_lesser",
"operator",
"attributes",
"to",
"onnx",
"s",
"Less",
"operator",
"and",
"return",
"the",
"created",
"node",
"."
] | def convert_broadcast_lesser(node, **kwargs):
"""Map MXNet's broadcast_lesser operator attributes to onnx's Less operator
and return the created node.
"""
return create_basic_op_node('Less', node, kwargs) | [
"def",
"convert_broadcast_lesser",
"(",
"node",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"create_basic_op_node",
"(",
"'Less'",
",",
"node",
",",
"kwargs",
")"
] | https://github.com/hpi-xnor/BMXNet-v2/blob/af2b1859eafc5c721b1397cef02f946aaf2ce20d/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py#L1762-L1766 | |
eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/sumolib/output/convert/phem.py | python | net2str | (net, outSTRM) | return sIDm | Writes the network object given as "inpNET" as a .str file readable by PHEM.
Returns a map from the SUMO-road id to the generated numerical id used by PHEM.
The following may be a matter of changes:
- currently, only the positions of the start and the end nodes are written,
the geometry of the edge as defined in the SUMO-network is not exported.
A map between the edge id and a segment to a numerical id would be necessary | Writes the network object given as "inpNET" as a .str file readable by PHEM.
Returns a map from the SUMO-road id to the generated numerical id used by PHEM. | [
"Writes",
"the",
"network",
"object",
"given",
"as",
"inpNET",
"as",
"a",
".",
"str",
"file",
"readable",
"by",
"PHEM",
".",
"Returns",
"a",
"map",
"from",
"the",
"SUMO",
"-",
"road",
"id",
"to",
"the",
"generated",
"numerical",
"id",
"used",
"by",
"PHEM",
"."
] | def net2str(net, outSTRM):
"""
Writes the network object given as "inpNET" as a .str file readable by PHEM.
Returns a map from the SUMO-road id to the generated numerical id used by PHEM.
The following may be a matter of changes:
- currently, only the positions of the start and the end nodes are written,
the geometry of the edge as defined in the SUMO-network is not exported.
A map between the edge id and a segment to a numerical id would be necessary
"""
if outSTRM is not None:
print("Str-Id,Sp,SegAnX,SegEnX,SegAnY,SegEnY", file=outSTRM)
sIDm = sumolib._Running()
for e in net._edges:
eid = sIDm.g(e._id)
if outSTRM is not None:
c1 = e._from._coord
c2 = e._to._coord
print("%s,%s,%s,%s,%s,%s" %
(eid, len(e._lanes), c1[0], c2[0], c1[1], c2[1]), file=outSTRM)
return sIDm | [
"def",
"net2str",
"(",
"net",
",",
"outSTRM",
")",
":",
"if",
"outSTRM",
"is",
"not",
"None",
":",
"print",
"(",
"\"Str-Id,Sp,SegAnX,SegEnX,SegAnY,SegEnY\"",
",",
"file",
"=",
"outSTRM",
")",
"sIDm",
"=",
"sumolib",
".",
"_Running",
"(",
")",
"for",
"e",
"in",
"net",
".",
"_edges",
":",
"eid",
"=",
"sIDm",
".",
"g",
"(",
"e",
".",
"_id",
")",
"if",
"outSTRM",
"is",
"not",
"None",
":",
"c1",
"=",
"e",
".",
"_from",
".",
"_coord",
"c2",
"=",
"e",
".",
"_to",
".",
"_coord",
"print",
"(",
"\"%s,%s,%s,%s,%s,%s\"",
"%",
"(",
"eid",
",",
"len",
"(",
"e",
".",
"_lanes",
")",
",",
"c1",
"[",
"0",
"]",
",",
"c2",
"[",
"0",
"]",
",",
"c1",
"[",
"1",
"]",
",",
"c2",
"[",
"1",
"]",
")",
",",
"file",
"=",
"outSTRM",
")",
"return",
"sIDm"
] | https://github.com/eclipse/sumo/blob/7132a9b8b6eea734bdec38479026b4d8c4336d03/tools/sumolib/output/convert/phem.py#L62-L82 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/distutils/dep_util.py | python | newer | (source, target) | return mtime1 > mtime2 | Return true if 'source' exists and is more recently modified than
'target', or if 'source' exists and 'target' doesn't. Return false if
both exist and 'target' is the same age or younger than 'source'.
Raise DistutilsFileError if 'source' does not exist. | Return true if 'source' exists and is more recently modified than
'target', or if 'source' exists and 'target' doesn't. Return false if
both exist and 'target' is the same age or younger than 'source'.
Raise DistutilsFileError if 'source' does not exist. | [
"Return",
"true",
"if",
"source",
"exists",
"and",
"is",
"more",
"recently",
"modified",
"than",
"target",
"or",
"if",
"source",
"exists",
"and",
"target",
"doesn",
"t",
".",
"Return",
"false",
"if",
"both",
"exist",
"and",
"target",
"is",
"the",
"same",
"age",
"or",
"younger",
"than",
"source",
".",
"Raise",
"DistutilsFileError",
"if",
"source",
"does",
"not",
"exist",
"."
] | def newer (source, target):
"""Return true if 'source' exists and is more recently modified than
'target', or if 'source' exists and 'target' doesn't. Return false if
both exist and 'target' is the same age or younger than 'source'.
Raise DistutilsFileError if 'source' does not exist.
"""
if not os.path.exists(source):
raise DistutilsFileError("file '%s' does not exist" %
os.path.abspath(source))
if not os.path.exists(target):
return 1
from stat import ST_MTIME
mtime1 = os.stat(source)[ST_MTIME]
mtime2 = os.stat(target)[ST_MTIME]
return mtime1 > mtime2 | [
"def",
"newer",
"(",
"source",
",",
"target",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"source",
")",
":",
"raise",
"DistutilsFileError",
"(",
"\"file '%s' does not exist\"",
"%",
"os",
".",
"path",
".",
"abspath",
"(",
"source",
")",
")",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"target",
")",
":",
"return",
"1",
"from",
"stat",
"import",
"ST_MTIME",
"mtime1",
"=",
"os",
".",
"stat",
"(",
"source",
")",
"[",
"ST_MTIME",
"]",
"mtime2",
"=",
"os",
".",
"stat",
"(",
"target",
")",
"[",
"ST_MTIME",
"]",
"return",
"mtime1",
">",
"mtime2"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/distutils/dep_util.py#L11-L27 | |
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | third_party/gpus/find_cuda_config.py | python | find_cuda_config | () | return result | Returns a dictionary of CUDA library and header file paths. | Returns a dictionary of CUDA library and header file paths. | [
"Returns",
"a",
"dictionary",
"of",
"CUDA",
"library",
"and",
"header",
"file",
"paths",
"."
] | def find_cuda_config():
"""Returns a dictionary of CUDA library and header file paths."""
libraries = [argv.lower() for argv in sys.argv[1:]]
cuda_version = os.environ.get("TF_CUDA_VERSION", "")
base_paths = _list_from_env("TF_CUDA_PATHS",
_get_default_cuda_paths(cuda_version))
base_paths = [path for path in base_paths if os.path.exists(path)]
result = {}
if "cuda" in libraries:
cuda_paths = _list_from_env("CUDA_TOOLKIT_PATH", base_paths)
result.update(_find_cuda_config(cuda_paths, cuda_version))
cuda_version = result["cuda_version"]
cublas_paths = base_paths
if tuple(int(v) for v in cuda_version.split(".")) < (10, 1):
# Before CUDA 10.1, cuBLAS was in the same directory as the toolkit.
cublas_paths = cuda_paths
cublas_version = os.environ.get("TF_CUBLAS_VERSION", "")
result.update(
_find_cublas_config(cublas_paths, cublas_version, cuda_version))
cusolver_paths = base_paths
if tuple(int(v) for v in cuda_version.split(".")) < (11, 0):
cusolver_paths = cuda_paths
cusolver_version = os.environ.get("TF_CUSOLVER_VERSION", "")
result.update(
_find_cusolver_config(cusolver_paths, cusolver_version, cuda_version))
curand_paths = base_paths
if tuple(int(v) for v in cuda_version.split(".")) < (11, 0):
curand_paths = cuda_paths
curand_version = os.environ.get("TF_CURAND_VERSION", "")
result.update(
_find_curand_config(curand_paths, curand_version, cuda_version))
cufft_paths = base_paths
if tuple(int(v) for v in cuda_version.split(".")) < (11, 0):
cufft_paths = cuda_paths
cufft_version = os.environ.get("TF_CUFFT_VERSION", "")
result.update(_find_cufft_config(cufft_paths, cufft_version, cuda_version))
cusparse_paths = base_paths
if tuple(int(v) for v in cuda_version.split(".")) < (11, 0):
cusparse_paths = cuda_paths
cusparse_version = os.environ.get("TF_CUSPARSE_VERSION", "")
result.update(
_find_cusparse_config(cusparse_paths, cusparse_version, cuda_version))
if "cudnn" in libraries:
cudnn_paths = _get_legacy_path("CUDNN_INSTALL_PATH", base_paths)
cudnn_version = os.environ.get("TF_CUDNN_VERSION", "")
result.update(_find_cudnn_config(cudnn_paths, cudnn_version))
if "nccl" in libraries:
nccl_paths = _get_legacy_path("NCCL_INSTALL_PATH", base_paths)
nccl_version = os.environ.get("TF_NCCL_VERSION", "")
result.update(_find_nccl_config(nccl_paths, nccl_version))
if "tensorrt" in libraries:
tensorrt_paths = _get_legacy_path("TENSORRT_INSTALL_PATH", base_paths)
tensorrt_version = os.environ.get("TF_TENSORRT_VERSION", "")
result.update(_find_tensorrt_config(tensorrt_paths, tensorrt_version))
for k, v in result.items():
if k.endswith("_dir") or k.endswith("_path"):
result[k] = _normalize_path(v)
return result | [
"def",
"find_cuda_config",
"(",
")",
":",
"libraries",
"=",
"[",
"argv",
".",
"lower",
"(",
")",
"for",
"argv",
"in",
"sys",
".",
"argv",
"[",
"1",
":",
"]",
"]",
"cuda_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUDA_VERSION\"",
",",
"\"\"",
")",
"base_paths",
"=",
"_list_from_env",
"(",
"\"TF_CUDA_PATHS\"",
",",
"_get_default_cuda_paths",
"(",
"cuda_version",
")",
")",
"base_paths",
"=",
"[",
"path",
"for",
"path",
"in",
"base_paths",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"path",
")",
"]",
"result",
"=",
"{",
"}",
"if",
"\"cuda\"",
"in",
"libraries",
":",
"cuda_paths",
"=",
"_list_from_env",
"(",
"\"CUDA_TOOLKIT_PATH\"",
",",
"base_paths",
")",
"result",
".",
"update",
"(",
"_find_cuda_config",
"(",
"cuda_paths",
",",
"cuda_version",
")",
")",
"cuda_version",
"=",
"result",
"[",
"\"cuda_version\"",
"]",
"cublas_paths",
"=",
"base_paths",
"if",
"tuple",
"(",
"int",
"(",
"v",
")",
"for",
"v",
"in",
"cuda_version",
".",
"split",
"(",
"\".\"",
")",
")",
"<",
"(",
"10",
",",
"1",
")",
":",
"# Before CUDA 10.1, cuBLAS was in the same directory as the toolkit.",
"cublas_paths",
"=",
"cuda_paths",
"cublas_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUBLAS_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_cublas_config",
"(",
"cublas_paths",
",",
"cublas_version",
",",
"cuda_version",
")",
")",
"cusolver_paths",
"=",
"base_paths",
"if",
"tuple",
"(",
"int",
"(",
"v",
")",
"for",
"v",
"in",
"cuda_version",
".",
"split",
"(",
"\".\"",
")",
")",
"<",
"(",
"11",
",",
"0",
")",
":",
"cusolver_paths",
"=",
"cuda_paths",
"cusolver_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUSOLVER_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_cusolver_config",
"(",
"cusolver_paths",
",",
"cusolver_version",
",",
"cuda_version",
")",
")",
"curand_paths",
"=",
"base_paths",
"if",
"tuple",
"(",
"int",
"(",
"v",
")",
"for",
"v",
"in",
"cuda_version",
".",
"split",
"(",
"\".\"",
")",
")",
"<",
"(",
"11",
",",
"0",
")",
":",
"curand_paths",
"=",
"cuda_paths",
"curand_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CURAND_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_curand_config",
"(",
"curand_paths",
",",
"curand_version",
",",
"cuda_version",
")",
")",
"cufft_paths",
"=",
"base_paths",
"if",
"tuple",
"(",
"int",
"(",
"v",
")",
"for",
"v",
"in",
"cuda_version",
".",
"split",
"(",
"\".\"",
")",
")",
"<",
"(",
"11",
",",
"0",
")",
":",
"cufft_paths",
"=",
"cuda_paths",
"cufft_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUFFT_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_cufft_config",
"(",
"cufft_paths",
",",
"cufft_version",
",",
"cuda_version",
")",
")",
"cusparse_paths",
"=",
"base_paths",
"if",
"tuple",
"(",
"int",
"(",
"v",
")",
"for",
"v",
"in",
"cuda_version",
".",
"split",
"(",
"\".\"",
")",
")",
"<",
"(",
"11",
",",
"0",
")",
":",
"cusparse_paths",
"=",
"cuda_paths",
"cusparse_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUSPARSE_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_cusparse_config",
"(",
"cusparse_paths",
",",
"cusparse_version",
",",
"cuda_version",
")",
")",
"if",
"\"cudnn\"",
"in",
"libraries",
":",
"cudnn_paths",
"=",
"_get_legacy_path",
"(",
"\"CUDNN_INSTALL_PATH\"",
",",
"base_paths",
")",
"cudnn_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_CUDNN_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_cudnn_config",
"(",
"cudnn_paths",
",",
"cudnn_version",
")",
")",
"if",
"\"nccl\"",
"in",
"libraries",
":",
"nccl_paths",
"=",
"_get_legacy_path",
"(",
"\"NCCL_INSTALL_PATH\"",
",",
"base_paths",
")",
"nccl_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_NCCL_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_nccl_config",
"(",
"nccl_paths",
",",
"nccl_version",
")",
")",
"if",
"\"tensorrt\"",
"in",
"libraries",
":",
"tensorrt_paths",
"=",
"_get_legacy_path",
"(",
"\"TENSORRT_INSTALL_PATH\"",
",",
"base_paths",
")",
"tensorrt_version",
"=",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_TENSORRT_VERSION\"",
",",
"\"\"",
")",
"result",
".",
"update",
"(",
"_find_tensorrt_config",
"(",
"tensorrt_paths",
",",
"tensorrt_version",
")",
")",
"for",
"k",
",",
"v",
"in",
"result",
".",
"items",
"(",
")",
":",
"if",
"k",
".",
"endswith",
"(",
"\"_dir\"",
")",
"or",
"k",
".",
"endswith",
"(",
"\"_path\"",
")",
":",
"result",
"[",
"k",
"]",
"=",
"_normalize_path",
"(",
"v",
")",
"return",
"result"
] | https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/third_party/gpus/find_cuda_config.py#L566-L634 | |
1989Ryan/Semantic_SLAM | 0284b3f832ca431c494f9c134fe46c40ec86ee38 | Third_Part/PSPNet_Keras_tensorflow/pascal_voc_labels.py | python | generate_color_map | (N=256, normalized=False) | return cmap | from https://gist.github.com/wllhf/a4533e0adebe57e3ed06d4b50c8419ae . | from https://gist.github.com/wllhf/a4533e0adebe57e3ed06d4b50c8419ae . | [
"from",
"https",
":",
"//",
"gist",
".",
"github",
".",
"com",
"/",
"wllhf",
"/",
"a4533e0adebe57e3ed06d4b50c8419ae",
"."
] | def generate_color_map(N=256, normalized=False):
"""from https://gist.github.com/wllhf/a4533e0adebe57e3ed06d4b50c8419ae ."""
def bitget(byteval, idx):
return ((byteval & (1 << idx)) != 0)
dtype = 'float32' if normalized else 'uint8'
cmap = np.zeros((N, 3), dtype=dtype)
for i in range(N):
r = g = b = 0
c = i
for j in range(8):
r = r | (bitget(c, 0) << 7 - j)
g = g | (bitget(c, 1) << 7 - j)
b = b | (bitget(c, 2) << 7 - j)
c = c >> 3
cmap[i] = np.array([r, g, b])
cmap = cmap / 255 if normalized else cmap
return cmap | [
"def",
"generate_color_map",
"(",
"N",
"=",
"256",
",",
"normalized",
"=",
"False",
")",
":",
"def",
"bitget",
"(",
"byteval",
",",
"idx",
")",
":",
"return",
"(",
"(",
"byteval",
"&",
"(",
"1",
"<<",
"idx",
")",
")",
"!=",
"0",
")",
"dtype",
"=",
"'float32'",
"if",
"normalized",
"else",
"'uint8'",
"cmap",
"=",
"np",
".",
"zeros",
"(",
"(",
"N",
",",
"3",
")",
",",
"dtype",
"=",
"dtype",
")",
"for",
"i",
"in",
"range",
"(",
"N",
")",
":",
"r",
"=",
"g",
"=",
"b",
"=",
"0",
"c",
"=",
"i",
"for",
"j",
"in",
"range",
"(",
"8",
")",
":",
"r",
"=",
"r",
"|",
"(",
"bitget",
"(",
"c",
",",
"0",
")",
"<<",
"7",
"-",
"j",
")",
"g",
"=",
"g",
"|",
"(",
"bitget",
"(",
"c",
",",
"1",
")",
"<<",
"7",
"-",
"j",
")",
"b",
"=",
"b",
"|",
"(",
"bitget",
"(",
"c",
",",
"2",
")",
"<<",
"7",
"-",
"j",
")",
"c",
"=",
"c",
">>",
"3",
"cmap",
"[",
"i",
"]",
"=",
"np",
".",
"array",
"(",
"[",
"r",
",",
"g",
",",
"b",
"]",
")",
"cmap",
"=",
"cmap",
"/",
"255",
"if",
"normalized",
"else",
"cmap",
"return",
"cmap"
] | https://github.com/1989Ryan/Semantic_SLAM/blob/0284b3f832ca431c494f9c134fe46c40ec86ee38/Third_Part/PSPNet_Keras_tensorflow/pascal_voc_labels.py#L42-L61 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/polynomial/legendre.py | python | legder | (c, m=1, scl=1, axis=0) | return c | Differentiate a Legendre series.
Returns the Legendre series coefficients `c` differentiated `m` times
along `axis`. At each iteration the result is multiplied by `scl` (the
scaling factor is for use in a linear change of variable). The argument
`c` is an array of coefficients from low to high degree along each
axis, e.g., [1,2,3] represents the series ``1*L_0 + 2*L_1 + 3*L_2``
while [[1,2],[1,2]] represents ``1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) +
2*L_0(x)*L_1(y) + 2*L_1(x)*L_1(y)`` if axis=0 is ``x`` and axis=1 is
``y``.
Parameters
----------
c : array_like
Array of Legendre series coefficients. If c is multidimensional the
different axis correspond to different variables with the degree in
each axis given by the corresponding index.
m : int, optional
Number of derivatives taken, must be non-negative. (Default: 1)
scl : scalar, optional
Each differentiation is multiplied by `scl`. The end result is
multiplication by ``scl**m``. This is for use in a linear change of
variable. (Default: 1)
axis : int, optional
Axis over which the derivative is taken. (Default: 0).
.. versionadded:: 1.7.0
Returns
-------
der : ndarray
Legendre series of the derivative.
See Also
--------
legint
Notes
-----
In general, the result of differentiating a Legendre series does not
resemble the same operation on a power series. Thus the result of this
function may be "unintuitive," albeit correct; see Examples section
below.
Examples
--------
>>> from numpy.polynomial import legendre as L
>>> c = (1,2,3,4)
>>> L.legder(c)
array([ 6., 9., 20.])
>>> L.legder(c, 3)
array([60.])
>>> L.legder(c, scl=-1)
array([ -6., -9., -20.])
>>> L.legder(c, 2,-1)
array([ 9., 60.]) | Differentiate a Legendre series. | [
"Differentiate",
"a",
"Legendre",
"series",
"."
] | def legder(c, m=1, scl=1, axis=0):
"""
Differentiate a Legendre series.
Returns the Legendre series coefficients `c` differentiated `m` times
along `axis`. At each iteration the result is multiplied by `scl` (the
scaling factor is for use in a linear change of variable). The argument
`c` is an array of coefficients from low to high degree along each
axis, e.g., [1,2,3] represents the series ``1*L_0 + 2*L_1 + 3*L_2``
while [[1,2],[1,2]] represents ``1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) +
2*L_0(x)*L_1(y) + 2*L_1(x)*L_1(y)`` if axis=0 is ``x`` and axis=1 is
``y``.
Parameters
----------
c : array_like
Array of Legendre series coefficients. If c is multidimensional the
different axis correspond to different variables with the degree in
each axis given by the corresponding index.
m : int, optional
Number of derivatives taken, must be non-negative. (Default: 1)
scl : scalar, optional
Each differentiation is multiplied by `scl`. The end result is
multiplication by ``scl**m``. This is for use in a linear change of
variable. (Default: 1)
axis : int, optional
Axis over which the derivative is taken. (Default: 0).
.. versionadded:: 1.7.0
Returns
-------
der : ndarray
Legendre series of the derivative.
See Also
--------
legint
Notes
-----
In general, the result of differentiating a Legendre series does not
resemble the same operation on a power series. Thus the result of this
function may be "unintuitive," albeit correct; see Examples section
below.
Examples
--------
>>> from numpy.polynomial import legendre as L
>>> c = (1,2,3,4)
>>> L.legder(c)
array([ 6., 9., 20.])
>>> L.legder(c, 3)
array([60.])
>>> L.legder(c, scl=-1)
array([ -6., -9., -20.])
>>> L.legder(c, 2,-1)
array([ 9., 60.])
"""
c = np.array(c, ndmin=1, copy=True)
if c.dtype.char in '?bBhHiIlLqQpP':
c = c.astype(np.double)
cnt = pu._deprecate_as_int(m, "the order of derivation")
iaxis = pu._deprecate_as_int(axis, "the axis")
if cnt < 0:
raise ValueError("The order of derivation must be non-negative")
iaxis = normalize_axis_index(iaxis, c.ndim)
if cnt == 0:
return c
c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
else:
for i in range(cnt):
n = n - 1
c *= scl
der = np.empty((n,) + c.shape[1:], dtype=c.dtype)
for j in range(n, 2, -1):
der[j - 1] = (2*j - 1)*c[j]
c[j - 2] += c[j]
if n > 1:
der[1] = 3*c[2]
der[0] = c[1]
c = der
c = np.moveaxis(c, 0, iaxis)
return c | [
"def",
"legder",
"(",
"c",
",",
"m",
"=",
"1",
",",
"scl",
"=",
"1",
",",
"axis",
"=",
"0",
")",
":",
"c",
"=",
"np",
".",
"array",
"(",
"c",
",",
"ndmin",
"=",
"1",
",",
"copy",
"=",
"True",
")",
"if",
"c",
".",
"dtype",
".",
"char",
"in",
"'?bBhHiIlLqQpP'",
":",
"c",
"=",
"c",
".",
"astype",
"(",
"np",
".",
"double",
")",
"cnt",
"=",
"pu",
".",
"_deprecate_as_int",
"(",
"m",
",",
"\"the order of derivation\"",
")",
"iaxis",
"=",
"pu",
".",
"_deprecate_as_int",
"(",
"axis",
",",
"\"the axis\"",
")",
"if",
"cnt",
"<",
"0",
":",
"raise",
"ValueError",
"(",
"\"The order of derivation must be non-negative\"",
")",
"iaxis",
"=",
"normalize_axis_index",
"(",
"iaxis",
",",
"c",
".",
"ndim",
")",
"if",
"cnt",
"==",
"0",
":",
"return",
"c",
"c",
"=",
"np",
".",
"moveaxis",
"(",
"c",
",",
"iaxis",
",",
"0",
")",
"n",
"=",
"len",
"(",
"c",
")",
"if",
"cnt",
">=",
"n",
":",
"c",
"=",
"c",
"[",
":",
"1",
"]",
"*",
"0",
"else",
":",
"for",
"i",
"in",
"range",
"(",
"cnt",
")",
":",
"n",
"=",
"n",
"-",
"1",
"c",
"*=",
"scl",
"der",
"=",
"np",
".",
"empty",
"(",
"(",
"n",
",",
")",
"+",
"c",
".",
"shape",
"[",
"1",
":",
"]",
",",
"dtype",
"=",
"c",
".",
"dtype",
")",
"for",
"j",
"in",
"range",
"(",
"n",
",",
"2",
",",
"-",
"1",
")",
":",
"der",
"[",
"j",
"-",
"1",
"]",
"=",
"(",
"2",
"*",
"j",
"-",
"1",
")",
"*",
"c",
"[",
"j",
"]",
"c",
"[",
"j",
"-",
"2",
"]",
"+=",
"c",
"[",
"j",
"]",
"if",
"n",
">",
"1",
":",
"der",
"[",
"1",
"]",
"=",
"3",
"*",
"c",
"[",
"2",
"]",
"der",
"[",
"0",
"]",
"=",
"c",
"[",
"1",
"]",
"c",
"=",
"der",
"c",
"=",
"np",
".",
"moveaxis",
"(",
"c",
",",
"0",
",",
"iaxis",
")",
"return",
"c"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/polynomial/legendre.py#L612-L701 | |
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | native_client_sdk/src/tools/decode_dump.py | python | CoreDecoder._DecodeAddressSegment | (self, segments, address) | return ('(null)', address) | Convert an address to a segment relative one, plus filename.
Args:
segments: a list of phdr segments.
address: a process wide code address.
Returns:
A tuple of filename and segment relative address. | Convert an address to a segment relative one, plus filename. | [
"Convert",
"an",
"address",
"to",
"a",
"segment",
"relative",
"one",
"plus",
"filename",
"."
] | def _DecodeAddressSegment(self, segments, address):
"""Convert an address to a segment relative one, plus filename.
Args:
segments: a list of phdr segments.
address: a process wide code address.
Returns:
A tuple of filename and segment relative address.
"""
for segment in segments:
for phdr in segment['dlpi_phdr']:
start = segment['dlpi_addr'] + phdr['p_vaddr']
end = start + phdr['p_memsz']
if address >= start and address < end:
return (segment['dlpi_name'], address - segment['dlpi_addr'])
return ('(null)', address) | [
"def",
"_DecodeAddressSegment",
"(",
"self",
",",
"segments",
",",
"address",
")",
":",
"for",
"segment",
"in",
"segments",
":",
"for",
"phdr",
"in",
"segment",
"[",
"'dlpi_phdr'",
"]",
":",
"start",
"=",
"segment",
"[",
"'dlpi_addr'",
"]",
"+",
"phdr",
"[",
"'p_vaddr'",
"]",
"end",
"=",
"start",
"+",
"phdr",
"[",
"'p_memsz'",
"]",
"if",
"address",
">=",
"start",
"and",
"address",
"<",
"end",
":",
"return",
"(",
"segment",
"[",
"'dlpi_name'",
"]",
",",
"address",
"-",
"segment",
"[",
"'dlpi_addr'",
"]",
")",
"return",
"(",
"'(null)'",
",",
"address",
")"
] | https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/native_client_sdk/src/tools/decode_dump.py#L76-L91 | |
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | tools/git/move_source_file.py | python | MakeDestinationPath | (from_path, to_path) | return to_path | Given the from and to paths, return a correct destination path.
The initial destination path may either a full path or a directory.
Also does basic sanity checks. | Given the from and to paths, return a correct destination path. | [
"Given",
"the",
"from",
"and",
"to",
"paths",
"return",
"a",
"correct",
"destination",
"path",
"."
] | def MakeDestinationPath(from_path, to_path):
"""Given the from and to paths, return a correct destination path.
The initial destination path may either a full path or a directory.
Also does basic sanity checks.
"""
if not IsHandledFile(from_path):
raise Exception('Only intended to move individual source files '
'(%s does not have a recognized extension).' %
from_path)
# Remove '.', '..', etc.
to_path = os.path.normpath(to_path)
if os.path.isdir(to_path):
to_path = os.path.join(to_path, os.path.basename(from_path))
else:
dest_extension = os.path.splitext(to_path)[1]
if dest_extension not in HANDLED_EXTENSIONS:
raise Exception('Destination must be either a full path with '
'a recognized extension or a directory.')
return to_path | [
"def",
"MakeDestinationPath",
"(",
"from_path",
",",
"to_path",
")",
":",
"if",
"not",
"IsHandledFile",
"(",
"from_path",
")",
":",
"raise",
"Exception",
"(",
"'Only intended to move individual source files '",
"'(%s does not have a recognized extension).'",
"%",
"from_path",
")",
"# Remove '.', '..', etc.",
"to_path",
"=",
"os",
".",
"path",
".",
"normpath",
"(",
"to_path",
")",
"if",
"os",
".",
"path",
".",
"isdir",
"(",
"to_path",
")",
":",
"to_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"to_path",
",",
"os",
".",
"path",
".",
"basename",
"(",
"from_path",
")",
")",
"else",
":",
"dest_extension",
"=",
"os",
".",
"path",
".",
"splitext",
"(",
"to_path",
")",
"[",
"1",
"]",
"if",
"dest_extension",
"not",
"in",
"HANDLED_EXTENSIONS",
":",
"raise",
"Exception",
"(",
"'Destination must be either a full path with '",
"'a recognized extension or a directory.'",
")",
"return",
"to_path"
] | https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/git/move_source_file.py#L43-L64 | |
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/evergreen_task_tags.py | python | list_all_tags | (evg_config) | Print all task tags found in the evergreen configuration.
:param evg_config: evergreen configuration. | Print all task tags found in the evergreen configuration. | [
"Print",
"all",
"task",
"tags",
"found",
"in",
"the",
"evergreen",
"configuration",
"."
] | def list_all_tags(evg_config):
"""
Print all task tags found in the evergreen configuration.
:param evg_config: evergreen configuration.
"""
all_tags = get_all_task_tags(evg_config)
for tag in all_tags:
print(tag) | [
"def",
"list_all_tags",
"(",
"evg_config",
")",
":",
"all_tags",
"=",
"get_all_task_tags",
"(",
"evg_config",
")",
"for",
"tag",
"in",
"all_tags",
":",
"print",
"(",
"tag",
")"
] | https://github.com/mongodb/mongo/blob/d8ff665343ad29cf286ee2cf4a1960d29371937b/buildscripts/evergreen_task_tags.py#L48-L56 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/contextlib.py | python | _BaseExitStack.callback | (*args, **kwds) | return callback | Registers an arbitrary callback and arguments.
Cannot suppress exceptions. | Registers an arbitrary callback and arguments. | [
"Registers",
"an",
"arbitrary",
"callback",
"and",
"arguments",
"."
] | def callback(*args, **kwds):
"""Registers an arbitrary callback and arguments.
Cannot suppress exceptions.
"""
if len(args) >= 2:
self, callback, *args = args
elif not args:
raise TypeError("descriptor 'callback' of '_BaseExitStack' object "
"needs an argument")
elif 'callback' in kwds:
callback = kwds.pop('callback')
self, *args = args
else:
raise TypeError('callback expected at least 1 positional argument, '
'got %d' % (len(args)-1))
_exit_wrapper = self._create_cb_wrapper(callback, *args, **kwds)
# We changed the signature, so using @wraps is not appropriate, but
# setting __wrapped__ may still help with introspection.
_exit_wrapper.__wrapped__ = callback
self._push_exit_callback(_exit_wrapper)
return callback | [
"def",
"callback",
"(",
"*",
"args",
",",
"*",
"*",
"kwds",
")",
":",
"if",
"len",
"(",
"args",
")",
">=",
"2",
":",
"self",
",",
"callback",
",",
"",
"*",
"args",
"=",
"args",
"elif",
"not",
"args",
":",
"raise",
"TypeError",
"(",
"\"descriptor 'callback' of '_BaseExitStack' object \"",
"\"needs an argument\"",
")",
"elif",
"'callback'",
"in",
"kwds",
":",
"callback",
"=",
"kwds",
".",
"pop",
"(",
"'callback'",
")",
"self",
",",
"",
"*",
"args",
"=",
"args",
"else",
":",
"raise",
"TypeError",
"(",
"'callback expected at least 1 positional argument, '",
"'got %d'",
"%",
"(",
"len",
"(",
"args",
")",
"-",
"1",
")",
")",
"_exit_wrapper",
"=",
"self",
".",
"_create_cb_wrapper",
"(",
"callback",
",",
"*",
"args",
",",
"*",
"*",
"kwds",
")",
"# We changed the signature, so using @wraps is not appropriate, but",
"# setting __wrapped__ may still help with introspection.",
"_exit_wrapper",
".",
"__wrapped__",
"=",
"callback",
"self",
".",
"_push_exit_callback",
"(",
"_exit_wrapper",
")",
"return",
"callback"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/contextlib.py#L431-L454 | |
eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/python/bitstring/bitstring.py | python | Bits._converttobitstring | (cls, bs, offset=0, cache={}) | return cls(bs) | Convert bs to a bitstring and return it.
offset gives the suggested bit offset of first significant
bit, to optimise append etc. | Convert bs to a bitstring and return it. | [
"Convert",
"bs",
"to",
"a",
"bitstring",
"and",
"return",
"it",
"."
] | def _converttobitstring(cls, bs, offset=0, cache={}):
"""Convert bs to a bitstring and return it.
offset gives the suggested bit offset of first significant
bit, to optimise append etc.
"""
if isinstance(bs, Bits):
return bs
try:
return cache[(bs, offset)]
except KeyError:
if isinstance(bs, basestring):
b = cls()
try:
_, tokens = tokenparser(bs)
except ValueError as e:
raise CreationError(*e.args)
if tokens:
b._append(Bits._init_with_token(*tokens[0]))
b._datastore = offsetcopy(b._datastore, offset)
for token in tokens[1:]:
b._append(Bits._init_with_token(*token))
assert b._assertsanity()
assert b.len == 0 or b._offset == offset
if len(cache) < CACHE_SIZE:
cache[(bs, offset)] = b
return b
except TypeError:
# Unhashable type
pass
return cls(bs) | [
"def",
"_converttobitstring",
"(",
"cls",
",",
"bs",
",",
"offset",
"=",
"0",
",",
"cache",
"=",
"{",
"}",
")",
":",
"if",
"isinstance",
"(",
"bs",
",",
"Bits",
")",
":",
"return",
"bs",
"try",
":",
"return",
"cache",
"[",
"(",
"bs",
",",
"offset",
")",
"]",
"except",
"KeyError",
":",
"if",
"isinstance",
"(",
"bs",
",",
"basestring",
")",
":",
"b",
"=",
"cls",
"(",
")",
"try",
":",
"_",
",",
"tokens",
"=",
"tokenparser",
"(",
"bs",
")",
"except",
"ValueError",
"as",
"e",
":",
"raise",
"CreationError",
"(",
"*",
"e",
".",
"args",
")",
"if",
"tokens",
":",
"b",
".",
"_append",
"(",
"Bits",
".",
"_init_with_token",
"(",
"*",
"tokens",
"[",
"0",
"]",
")",
")",
"b",
".",
"_datastore",
"=",
"offsetcopy",
"(",
"b",
".",
"_datastore",
",",
"offset",
")",
"for",
"token",
"in",
"tokens",
"[",
"1",
":",
"]",
":",
"b",
".",
"_append",
"(",
"Bits",
".",
"_init_with_token",
"(",
"*",
"token",
")",
")",
"assert",
"b",
".",
"_assertsanity",
"(",
")",
"assert",
"b",
".",
"len",
"==",
"0",
"or",
"b",
".",
"_offset",
"==",
"offset",
"if",
"len",
"(",
"cache",
")",
"<",
"CACHE_SIZE",
":",
"cache",
"[",
"(",
"bs",
",",
"offset",
")",
"]",
"=",
"b",
"return",
"b",
"except",
"TypeError",
":",
"# Unhashable type",
"pass",
"return",
"cls",
"(",
"bs",
")"
] | https://github.com/eventql/eventql/blob/7ca0dbb2e683b525620ea30dc40540a22d5eb227/deps/3rdparty/spidermonkey/mozjs/python/bitstring/bitstring.py#L1947-L1978 | |
Smorodov/Multitarget-tracker | bee300e8bfd660c86cbeb6892c65a5b7195c9381 | thirdparty/pybind11/tools/clang/cindex.py | python | Type.get_class_type | (self) | return conf.lib.clang_Type_getClassType(self) | Retrieve the class type of the member pointer type. | Retrieve the class type of the member pointer type. | [
"Retrieve",
"the",
"class",
"type",
"of",
"the",
"member",
"pointer",
"type",
"."
] | def get_class_type(self):
"""
Retrieve the class type of the member pointer type.
"""
return conf.lib.clang_Type_getClassType(self) | [
"def",
"get_class_type",
"(",
"self",
")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_Type_getClassType",
"(",
"self",
")"
] | https://github.com/Smorodov/Multitarget-tracker/blob/bee300e8bfd660c86cbeb6892c65a5b7195c9381/thirdparty/pybind11/tools/clang/cindex.py#L2072-L2076 | |
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/applications/workbench/workbench/projectrecovery/projectrecoveryloader.py | python | ProjectRecoveryLoader._open_script_in_editor_call | (self, script) | Open script in editor method invokation to guarantee it occurring on the correct thread.
:param script: String; Path to the script
:return: | Open script in editor method invokation to guarantee it occurring on the correct thread.
:param script: String; Path to the script
:return: | [
"Open",
"script",
"in",
"editor",
"method",
"invokation",
"to",
"guarantee",
"it",
"occurring",
"on",
"the",
"correct",
"thread",
".",
":",
"param",
"script",
":",
"String",
";",
"Path",
"to",
"the",
"script",
":",
"return",
":"
] | def _open_script_in_editor_call(self, script):
"""
Open script in editor method invokation to guarantee it occurring on the correct thread.
:param script: String; Path to the script
:return:
"""
self.multi_file_interpreter.open_file_in_new_tab(script) | [
"def",
"_open_script_in_editor_call",
"(",
"self",
",",
"script",
")",
":",
"self",
".",
"multi_file_interpreter",
".",
"open_file_in_new_tab",
"(",
"script",
")"
] | https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/applications/workbench/workbench/projectrecovery/projectrecoveryloader.py#L126-L132 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/ResourceManager/lib/Crypto/Util/asn1.py | python | DerSequence.__init__ | (self, startSeq=None, implicit=None) | Initialize the DER object as a SEQUENCE.
:Parameters:
startSeq : Python sequence
A sequence whose element are either integers or
other DER objects.
implicit : integer
The IMPLICIT tag to use for the encoded object.
It overrides the universal tag for SEQUENCE (16). | Initialize the DER object as a SEQUENCE. | [
"Initialize",
"the",
"DER",
"object",
"as",
"a",
"SEQUENCE",
"."
] | def __init__(self, startSeq=None, implicit=None):
"""Initialize the DER object as a SEQUENCE.
:Parameters:
startSeq : Python sequence
A sequence whose element are either integers or
other DER objects.
implicit : integer
The IMPLICIT tag to use for the encoded object.
It overrides the universal tag for SEQUENCE (16).
"""
DerObject.__init__(self, 0x10, b'', implicit, True)
if startSeq is None:
self._seq = []
else:
self._seq = startSeq | [
"def",
"__init__",
"(",
"self",
",",
"startSeq",
"=",
"None",
",",
"implicit",
"=",
"None",
")",
":",
"DerObject",
".",
"__init__",
"(",
"self",
",",
"0x10",
",",
"b''",
",",
"implicit",
",",
"True",
")",
"if",
"startSeq",
"is",
"None",
":",
"self",
".",
"_seq",
"=",
"[",
"]",
"else",
":",
"self",
".",
"_seq",
"=",
"startSeq"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/ResourceManager/lib/Crypto/Util/asn1.py#L387-L404 | ||
vicaya/hypertable | e7386f799c238c109ae47973417c2a2c7f750825 | src/py/ThriftClient/gen-py/hyperthrift/gen/ClientService.py | python | Iface.open_mutator | (self, name, flags, flush_interval) | Open a table mutator
@param name - table name
@param flags - mutator flags
@param flush_interval - auto-flush interval in milliseconds; 0 disables it.
@return mutator id
Parameters:
- name
- flags
- flush_interval | Open a table mutator | [
"Open",
"a",
"table",
"mutator"
] | def open_mutator(self, name, flags, flush_interval):
"""
Open a table mutator
@param name - table name
@param flags - mutator flags
@param flush_interval - auto-flush interval in milliseconds; 0 disables it.
@return mutator id
Parameters:
- name
- flags
- flush_interval
"""
pass | [
"def",
"open_mutator",
"(",
"self",
",",
"name",
",",
"flags",
",",
"flush_interval",
")",
":",
"pass"
] | https://github.com/vicaya/hypertable/blob/e7386f799c238c109ae47973417c2a2c7f750825/src/py/ThriftClient/gen-py/hyperthrift/gen/ClientService.py#L176-L193 | ||
google/shaka-packager | e1b0c7c45431327fd3ce193514a5407d07b39b22 | packager/third_party/protobuf/python/google/protobuf/internal/well_known_types.py | python | Duration.FromTimedelta | (self, td) | Convertd timedelta to Duration. | Convertd timedelta to Duration. | [
"Convertd",
"timedelta",
"to",
"Duration",
"."
] | def FromTimedelta(self, td):
"""Convertd timedelta to Duration."""
self._NormalizeDuration(td.seconds + td.days * _SECONDS_PER_DAY,
td.microseconds * _NANOS_PER_MICROSECOND) | [
"def",
"FromTimedelta",
"(",
"self",
",",
"td",
")",
":",
"self",
".",
"_NormalizeDuration",
"(",
"td",
".",
"seconds",
"+",
"td",
".",
"days",
"*",
"_SECONDS_PER_DAY",
",",
"td",
".",
"microseconds",
"*",
"_NANOS_PER_MICROSECOND",
")"
] | https://github.com/google/shaka-packager/blob/e1b0c7c45431327fd3ce193514a5407d07b39b22/packager/third_party/protobuf/python/google/protobuf/internal/well_known_types.py#L352-L355 | ||
tangzhenyu/Scene-Text-Understanding | 0f7ffc7aea5971a50cdc03d33d0a41075285948b | SynthText_Chinese/colorize3_poisson.py | python | Colorize.border | (self, alpha, size, kernel_type='RECT') | return border | alpha : alpha layer of the text
size : size of the kernel
kernel_type : one of [rect,ellipse,cross]
@return : alpha layer of the border (color to be added externally). | alpha : alpha layer of the text
size : size of the kernel
kernel_type : one of [rect,ellipse,cross] | [
"alpha",
":",
"alpha",
"layer",
"of",
"the",
"text",
"size",
":",
"size",
"of",
"the",
"kernel",
"kernel_type",
":",
"one",
"of",
"[",
"rect",
"ellipse",
"cross",
"]"
] | def border(self, alpha, size, kernel_type='RECT'):
"""
alpha : alpha layer of the text
size : size of the kernel
kernel_type : one of [rect,ellipse,cross]
@return : alpha layer of the border (color to be added externally).
"""
kdict = {'RECT':cv.MORPH_RECT, 'ELLIPSE':cv.MORPH_ELLIPSE,
'CROSS':cv.MORPH_CROSS}
kernel = cv.getStructuringElement(kdict[kernel_type],(size,size))
border = cv.dilate(alpha,kernel,iterations=1) # - alpha
return border | [
"def",
"border",
"(",
"self",
",",
"alpha",
",",
"size",
",",
"kernel_type",
"=",
"'RECT'",
")",
":",
"kdict",
"=",
"{",
"'RECT'",
":",
"cv",
".",
"MORPH_RECT",
",",
"'ELLIPSE'",
":",
"cv",
".",
"MORPH_ELLIPSE",
",",
"'CROSS'",
":",
"cv",
".",
"MORPH_CROSS",
"}",
"kernel",
"=",
"cv",
".",
"getStructuringElement",
"(",
"kdict",
"[",
"kernel_type",
"]",
",",
"(",
"size",
",",
"size",
")",
")",
"border",
"=",
"cv",
".",
"dilate",
"(",
"alpha",
",",
"kernel",
",",
"iterations",
"=",
"1",
")",
"# - alpha",
"return",
"border"
] | https://github.com/tangzhenyu/Scene-Text-Understanding/blob/0f7ffc7aea5971a50cdc03d33d0a41075285948b/SynthText_Chinese/colorize3_poisson.py#L175-L187 | |
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/debug/lib/debug_data.py | python | DebugDumpDir.set_python_graph | (self, python_graph) | Provide Python `Graph` object to the wrapper.
Unlike the partition graphs, which are protobuf `GraphDef` objects, `Graph`
is a Python object and carries additional information such as the traceback
of the construction of the nodes in the graph.
Args:
python_graph: (ops.Graph) The Python Graph object. | Provide Python `Graph` object to the wrapper. | [
"Provide",
"Python",
"Graph",
"object",
"to",
"the",
"wrapper",
"."
] | def set_python_graph(self, python_graph):
"""Provide Python `Graph` object to the wrapper.
Unlike the partition graphs, which are protobuf `GraphDef` objects, `Graph`
is a Python object and carries additional information such as the traceback
of the construction of the nodes in the graph.
Args:
python_graph: (ops.Graph) The Python Graph object.
"""
self._python_graph = python_graph
self._node_traceback = {}
if self._python_graph:
for op in self._python_graph.get_operations():
self._node_traceback[op.name] = op.traceback | [
"def",
"set_python_graph",
"(",
"self",
",",
"python_graph",
")",
":",
"self",
".",
"_python_graph",
"=",
"python_graph",
"self",
".",
"_node_traceback",
"=",
"{",
"}",
"if",
"self",
".",
"_python_graph",
":",
"for",
"op",
"in",
"self",
".",
"_python_graph",
".",
"get_operations",
"(",
")",
":",
"self",
".",
"_node_traceback",
"[",
"op",
".",
"name",
"]",
"=",
"op",
".",
"traceback"
] | https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/debug/lib/debug_data.py#L853-L868 | ||
pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/_sources.py | python | get_source_lines_and_file | (
obj: Any,
error_msg: Optional[str] = None,
) | return sourcelines, file_lineno, filename | Wrapper around inspect.getsourcelines and inspect.getsourcefile.
Returns: (sourcelines, file_lino, filename) | Wrapper around inspect.getsourcelines and inspect.getsourcefile. | [
"Wrapper",
"around",
"inspect",
".",
"getsourcelines",
"and",
"inspect",
".",
"getsourcefile",
"."
] | def get_source_lines_and_file(
obj: Any,
error_msg: Optional[str] = None,
) -> Tuple[List[str], int, Optional[str]]:
"""
Wrapper around inspect.getsourcelines and inspect.getsourcefile.
Returns: (sourcelines, file_lino, filename)
"""
filename = None # in case getsourcefile throws
try:
filename = inspect.getsourcefile(obj)
sourcelines, file_lineno = inspect.getsourcelines(obj)
except OSError as e:
msg = (f"Can't get source for {obj}. TorchScript requires source access in "
"order to carry out compilation, make sure original .py files are "
"available.")
if error_msg:
msg += '\n' + error_msg
raise OSError(msg) from e
return sourcelines, file_lineno, filename | [
"def",
"get_source_lines_and_file",
"(",
"obj",
":",
"Any",
",",
"error_msg",
":",
"Optional",
"[",
"str",
"]",
"=",
"None",
",",
")",
"->",
"Tuple",
"[",
"List",
"[",
"str",
"]",
",",
"int",
",",
"Optional",
"[",
"str",
"]",
"]",
":",
"filename",
"=",
"None",
"# in case getsourcefile throws",
"try",
":",
"filename",
"=",
"inspect",
".",
"getsourcefile",
"(",
"obj",
")",
"sourcelines",
",",
"file_lineno",
"=",
"inspect",
".",
"getsourcelines",
"(",
"obj",
")",
"except",
"OSError",
"as",
"e",
":",
"msg",
"=",
"(",
"f\"Can't get source for {obj}. TorchScript requires source access in \"",
"\"order to carry out compilation, make sure original .py files are \"",
"\"available.\"",
")",
"if",
"error_msg",
":",
"msg",
"+=",
"'\\n'",
"+",
"error_msg",
"raise",
"OSError",
"(",
"msg",
")",
"from",
"e",
"return",
"sourcelines",
",",
"file_lineno",
",",
"filename"
] | https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/torch/_sources.py#L9-L30 | |
oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/MSVSSettings.py | python | _MovedAndRenamed | (
tool, msvs_settings_name, msbuild_tool_name, msbuild_settings_name, setting_type
) | Defines a setting that may have moved to a new section.
Args:
tool: a dictionary that gives the names of the tool for MSVS and MSBuild.
msvs_settings_name: the MSVS name of the setting.
msbuild_tool_name: the name of the MSBuild tool to place the setting under.
msbuild_settings_name: the MSBuild name of the setting.
setting_type: the type of this setting. | Defines a setting that may have moved to a new section. | [
"Defines",
"a",
"setting",
"that",
"may",
"have",
"moved",
"to",
"a",
"new",
"section",
"."
] | def _MovedAndRenamed(
tool, msvs_settings_name, msbuild_tool_name, msbuild_settings_name, setting_type
):
"""Defines a setting that may have moved to a new section.
Args:
tool: a dictionary that gives the names of the tool for MSVS and MSBuild.
msvs_settings_name: the MSVS name of the setting.
msbuild_tool_name: the name of the MSBuild tool to place the setting under.
msbuild_settings_name: the MSBuild name of the setting.
setting_type: the type of this setting.
"""
def _Translate(value, msbuild_settings):
tool_settings = msbuild_settings.setdefault(msbuild_tool_name, {})
tool_settings[msbuild_settings_name] = setting_type.ConvertToMSBuild(value)
_msvs_validators[tool.msvs_name][msvs_settings_name] = setting_type.ValidateMSVS
validator = setting_type.ValidateMSBuild
_msbuild_validators[msbuild_tool_name][msbuild_settings_name] = validator
_msvs_to_msbuild_converters[tool.msvs_name][msvs_settings_name] = _Translate | [
"def",
"_MovedAndRenamed",
"(",
"tool",
",",
"msvs_settings_name",
",",
"msbuild_tool_name",
",",
"msbuild_settings_name",
",",
"setting_type",
")",
":",
"def",
"_Translate",
"(",
"value",
",",
"msbuild_settings",
")",
":",
"tool_settings",
"=",
"msbuild_settings",
".",
"setdefault",
"(",
"msbuild_tool_name",
",",
"{",
"}",
")",
"tool_settings",
"[",
"msbuild_settings_name",
"]",
"=",
"setting_type",
".",
"ConvertToMSBuild",
"(",
"value",
")",
"_msvs_validators",
"[",
"tool",
".",
"msvs_name",
"]",
"[",
"msvs_settings_name",
"]",
"=",
"setting_type",
".",
"ValidateMSVS",
"validator",
"=",
"setting_type",
".",
"ValidateMSBuild",
"_msbuild_validators",
"[",
"msbuild_tool_name",
"]",
"[",
"msbuild_settings_name",
"]",
"=",
"validator",
"_msvs_to_msbuild_converters",
"[",
"tool",
".",
"msvs_name",
"]",
"[",
"msvs_settings_name",
"]",
"=",
"_Translate"
] | https://github.com/oracle/graaljs/blob/36a56e8e993d45fc40939a3a4d9c0c24990720f1/graal-nodejs/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/MSVSSettings.py#L270-L290 | ||
H-uru/Plasma | c2140ea046e82e9c199e257a7f2e7edb42602871 | Scripts/Python/plasma/Plasma.py | python | PtEnableMouseMovement | () | Enable avatar mouse movement input | Enable avatar mouse movement input | [
"Enable",
"avatar",
"mouse",
"movement",
"input"
] | def PtEnableMouseMovement():
"""Enable avatar mouse movement input"""
pass | [
"def",
"PtEnableMouseMovement",
"(",
")",
":",
"pass"
] | https://github.com/H-uru/Plasma/blob/c2140ea046e82e9c199e257a7f2e7edb42602871/Scripts/Python/plasma/Plasma.py#L254-L256 | ||
google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/server/wsgi/serve/snippets/util/dbroot_writer.py | python | _SetSnippets | (dbroot_proto, almost_snippet_values, log) | Writes the JSON snippet values into the dbroot_proto.
We write individual paths instead of the whole tree at once,
only because it's easier.
Args:
dbroot_proto: destination dbroot_proto
almost_snippet_values: list of tuples of dbroot path, value.
They're 'dense', ie the indexes of all repeated fields all
start at 0 and are contiguous.
log: logger object. | Writes the JSON snippet values into the dbroot_proto. | [
"Writes",
"the",
"JSON",
"snippet",
"values",
"into",
"the",
"dbroot_proto",
"."
] | def _SetSnippets(dbroot_proto, almost_snippet_values, log):
"""Writes the JSON snippet values into the dbroot_proto.
We write individual paths instead of the whole tree at once,
only because it's easier.
Args:
dbroot_proto: destination dbroot_proto
almost_snippet_values: list of tuples of dbroot path, value.
They're 'dense', ie the indexes of all repeated fields all
start at 0 and are contiguous.
log: logger object.
"""
log.debug(">_SetSnippets")
true_snippet_values = _MassageSpecialCases(almost_snippet_values, log)
true_snippet_values.sort()
log.debug("aiming to set in dbroot:")
for k, v in true_snippet_values:
assert isinstance(true_snippet_values, list)
assert isinstance(true_snippet_values[0], tuple)
log.debug("snippet name:[%s], val:[%s]" % (k, str(v)))
log.debug("debugged em all")
for path, value in true_snippet_values:
log.debug("path: %s value: %s" % (path, value))
log.debug("setting in binary...")
proto_reflection.WritePathValsToDbroot(
dbroot_proto, true_snippet_values, log)
log.debug("...wrote")
log.debug("<_SetSnippets") | [
"def",
"_SetSnippets",
"(",
"dbroot_proto",
",",
"almost_snippet_values",
",",
"log",
")",
":",
"log",
".",
"debug",
"(",
"\">_SetSnippets\"",
")",
"true_snippet_values",
"=",
"_MassageSpecialCases",
"(",
"almost_snippet_values",
",",
"log",
")",
"true_snippet_values",
".",
"sort",
"(",
")",
"log",
".",
"debug",
"(",
"\"aiming to set in dbroot:\"",
")",
"for",
"k",
",",
"v",
"in",
"true_snippet_values",
":",
"assert",
"isinstance",
"(",
"true_snippet_values",
",",
"list",
")",
"assert",
"isinstance",
"(",
"true_snippet_values",
"[",
"0",
"]",
",",
"tuple",
")",
"log",
".",
"debug",
"(",
"\"snippet name:[%s], val:[%s]\"",
"%",
"(",
"k",
",",
"str",
"(",
"v",
")",
")",
")",
"log",
".",
"debug",
"(",
"\"debugged em all\"",
")",
"for",
"path",
",",
"value",
"in",
"true_snippet_values",
":",
"log",
".",
"debug",
"(",
"\"path: %s value: %s\"",
"%",
"(",
"path",
",",
"value",
")",
")",
"log",
".",
"debug",
"(",
"\"setting in binary...\"",
")",
"proto_reflection",
".",
"WritePathValsToDbroot",
"(",
"dbroot_proto",
",",
"true_snippet_values",
",",
"log",
")",
"log",
".",
"debug",
"(",
"\"...wrote\"",
")",
"log",
".",
"debug",
"(",
"\"<_SetSnippets\"",
")"
] | https://github.com/google/earthenterprise/blob/0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9/earth_enterprise/src/server/wsgi/serve/snippets/util/dbroot_writer.py#L143-L174 | ||
facebookresearch/mvfst-rl | 778bc4259ae7277e67c2ead593a493845c93db83 | train/utils.py | python | delete_dir | (dir_path, max_tries=1, sleep_time=1) | Delete a directory (with potential retry mechanism) | Delete a directory (with potential retry mechanism) | [
"Delete",
"a",
"directory",
"(",
"with",
"potential",
"retry",
"mechanism",
")"
] | def delete_dir(dir_path, max_tries=1, sleep_time=1):
"""Delete a directory (with potential retry mechanism)"""
if not os.path.exists(dir_path):
return
for i in range(max_tries):
try:
shutil.rmtree(dir_path)
except Exception:
if i == max_tries - 1:
logging.warning("Failed to delete dir (giving up): %s", dir_path)
break
else:
logging.info("Failed to delete dir (will try again): %s", dir_path)
time.sleep(sleep_time)
else:
logging.info("Deleted dir: %s", dir_path)
break | [
"def",
"delete_dir",
"(",
"dir_path",
",",
"max_tries",
"=",
"1",
",",
"sleep_time",
"=",
"1",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"dir_path",
")",
":",
"return",
"for",
"i",
"in",
"range",
"(",
"max_tries",
")",
":",
"try",
":",
"shutil",
".",
"rmtree",
"(",
"dir_path",
")",
"except",
"Exception",
":",
"if",
"i",
"==",
"max_tries",
"-",
"1",
":",
"logging",
".",
"warning",
"(",
"\"Failed to delete dir (giving up): %s\"",
",",
"dir_path",
")",
"break",
"else",
":",
"logging",
".",
"info",
"(",
"\"Failed to delete dir (will try again): %s\"",
",",
"dir_path",
")",
"time",
".",
"sleep",
"(",
"sleep_time",
")",
"else",
":",
"logging",
".",
"info",
"(",
"\"Deleted dir: %s\"",
",",
"dir_path",
")",
"break"
] | https://github.com/facebookresearch/mvfst-rl/blob/778bc4259ae7277e67c2ead593a493845c93db83/train/utils.py#L239-L256 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py3/IPython/core/completerlib.py | python | reset_completer | (self, event) | return '-f -s in out array dhist'.split() | A completer for %reset magic | A completer for %reset magic | [
"A",
"completer",
"for",
"%reset",
"magic"
] | def reset_completer(self, event):
"A completer for %reset magic"
return '-f -s in out array dhist'.split() | [
"def",
"reset_completer",
"(",
"self",
",",
"event",
")",
":",
"return",
"'-f -s in out array dhist'",
".",
"split",
"(",
")"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/ipython/py3/IPython/core/completerlib.py#L400-L402 | |
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py2/numpy/ma/core.py | python | left_shift | (a, n) | Shift the bits of an integer to the left.
This is the masked array version of `numpy.left_shift`, for details
see that function.
See Also
--------
numpy.left_shift | Shift the bits of an integer to the left. | [
"Shift",
"the",
"bits",
"of",
"an",
"integer",
"to",
"the",
"left",
"."
] | def left_shift(a, n):
"""
Shift the bits of an integer to the left.
This is the masked array version of `numpy.left_shift`, for details
see that function.
See Also
--------
numpy.left_shift
"""
m = getmask(a)
if m is nomask:
d = umath.left_shift(filled(a), n)
return masked_array(d)
else:
d = umath.left_shift(filled(a, 0), n)
return masked_array(d, mask=m) | [
"def",
"left_shift",
"(",
"a",
",",
"n",
")",
":",
"m",
"=",
"getmask",
"(",
"a",
")",
"if",
"m",
"is",
"nomask",
":",
"d",
"=",
"umath",
".",
"left_shift",
"(",
"filled",
"(",
"a",
")",
",",
"n",
")",
"return",
"masked_array",
"(",
"d",
")",
"else",
":",
"d",
"=",
"umath",
".",
"left_shift",
"(",
"filled",
"(",
"a",
",",
"0",
")",
",",
"n",
")",
"return",
"masked_array",
"(",
"d",
",",
"mask",
"=",
"m",
")"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/numpy/py2/numpy/ma/core.py#L6812-L6830 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/command/easy_install.py | python | ScriptWriter.get_header | (cls, script_text="", executable=None) | return cmd.as_header() | Create a #! line, getting options (if any) from script_text | Create a #! line, getting options (if any) from script_text | [
"Create",
"a",
"#!",
"line",
"getting",
"options",
"(",
"if",
"any",
")",
"from",
"script_text"
] | def get_header(cls, script_text="", executable=None):
"""Create a #! line, getting options (if any) from script_text"""
cmd = cls.command_spec_class.best().from_param(executable)
cmd.install_options(script_text)
return cmd.as_header() | [
"def",
"get_header",
"(",
"cls",
",",
"script_text",
"=",
"\"\"",
",",
"executable",
"=",
"None",
")",
":",
"cmd",
"=",
"cls",
".",
"command_spec_class",
".",
"best",
"(",
")",
".",
"from_param",
"(",
"executable",
")",
"cmd",
".",
"install_options",
"(",
"script_text",
")",
"return",
"cmd",
".",
"as_header",
"(",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/command/easy_install.py#L2155-L2159 | |
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/prompt-toolkit/py2/prompt_toolkit/output.py | python | Output.cursor_down | (self, amount) | Move cursor `amount` place down. | Move cursor `amount` place down. | [
"Move",
"cursor",
"amount",
"place",
"down",
"."
] | def cursor_down(self, amount):
" Move cursor `amount` place down. " | [
"def",
"cursor_down",
"(",
"self",
",",
"amount",
")",
":"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/prompt-toolkit/py2/prompt_toolkit/output.py#L117-L118 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/tseries/holiday.py | python | AbstractHolidayCalendar.holidays | (self, start=None, end=None, return_name=False) | Returns a curve with holidays between start_date and end_date
Parameters
----------
start : starting date, datetime-like, optional
end : ending date, datetime-like, optional
return_name : bool, optional
If True, return a series that has dates and holiday names.
False will only return a DatetimeIndex of dates.
Returns
-------
DatetimeIndex of holidays | Returns a curve with holidays between start_date and end_date | [
"Returns",
"a",
"curve",
"with",
"holidays",
"between",
"start_date",
"and",
"end_date"
] | def holidays(self, start=None, end=None, return_name=False):
"""
Returns a curve with holidays between start_date and end_date
Parameters
----------
start : starting date, datetime-like, optional
end : ending date, datetime-like, optional
return_name : bool, optional
If True, return a series that has dates and holiday names.
False will only return a DatetimeIndex of dates.
Returns
-------
DatetimeIndex of holidays
"""
if self.rules is None:
raise Exception(
f"Holiday Calendar {self.name} does not have any rules specified"
)
if start is None:
start = AbstractHolidayCalendar.start_date
if end is None:
end = AbstractHolidayCalendar.end_date
start = Timestamp(start)
end = Timestamp(end)
# If we don't have a cache or the dates are outside the prior cache, we
# get them again
if self._cache is None or start < self._cache[0] or end > self._cache[1]:
pre_holidays = [
rule.dates(start, end, return_name=True) for rule in self.rules
]
if pre_holidays:
holidays = concat(pre_holidays)
else:
holidays = Series(index=DatetimeIndex([]), dtype=object)
self._cache = (start, end, holidays.sort_index())
holidays = self._cache[2]
holidays = holidays[start:end]
if return_name:
return holidays
else:
return holidays.index | [
"def",
"holidays",
"(",
"self",
",",
"start",
"=",
"None",
",",
"end",
"=",
"None",
",",
"return_name",
"=",
"False",
")",
":",
"if",
"self",
".",
"rules",
"is",
"None",
":",
"raise",
"Exception",
"(",
"f\"Holiday Calendar {self.name} does not have any rules specified\"",
")",
"if",
"start",
"is",
"None",
":",
"start",
"=",
"AbstractHolidayCalendar",
".",
"start_date",
"if",
"end",
"is",
"None",
":",
"end",
"=",
"AbstractHolidayCalendar",
".",
"end_date",
"start",
"=",
"Timestamp",
"(",
"start",
")",
"end",
"=",
"Timestamp",
"(",
"end",
")",
"# If we don't have a cache or the dates are outside the prior cache, we",
"# get them again",
"if",
"self",
".",
"_cache",
"is",
"None",
"or",
"start",
"<",
"self",
".",
"_cache",
"[",
"0",
"]",
"or",
"end",
">",
"self",
".",
"_cache",
"[",
"1",
"]",
":",
"pre_holidays",
"=",
"[",
"rule",
".",
"dates",
"(",
"start",
",",
"end",
",",
"return_name",
"=",
"True",
")",
"for",
"rule",
"in",
"self",
".",
"rules",
"]",
"if",
"pre_holidays",
":",
"holidays",
"=",
"concat",
"(",
"pre_holidays",
")",
"else",
":",
"holidays",
"=",
"Series",
"(",
"index",
"=",
"DatetimeIndex",
"(",
"[",
"]",
")",
",",
"dtype",
"=",
"object",
")",
"self",
".",
"_cache",
"=",
"(",
"start",
",",
"end",
",",
"holidays",
".",
"sort_index",
"(",
")",
")",
"holidays",
"=",
"self",
".",
"_cache",
"[",
"2",
"]",
"holidays",
"=",
"holidays",
"[",
"start",
":",
"end",
"]",
"if",
"return_name",
":",
"return",
"holidays",
"else",
":",
"return",
"holidays",
".",
"index"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/tseries/holiday.py#L420-L469 | ||
dicecco1/fpga_caffe | 7a191704efd7873071cfef35772d7e7bf3e3cfd6 | python/caffe/pycaffe.py | python | _Net_params | (self) | return self._params_dict | An OrderedDict (bottom to top, i.e., input to output) of network
parameters indexed by name; each is a list of multiple blobs (e.g.,
weights and biases) | An OrderedDict (bottom to top, i.e., input to output) of network
parameters indexed by name; each is a list of multiple blobs (e.g.,
weights and biases) | [
"An",
"OrderedDict",
"(",
"bottom",
"to",
"top",
"i",
".",
"e",
".",
"input",
"to",
"output",
")",
"of",
"network",
"parameters",
"indexed",
"by",
"name",
";",
"each",
"is",
"a",
"list",
"of",
"multiple",
"blobs",
"(",
"e",
".",
"g",
".",
"weights",
"and",
"biases",
")"
] | def _Net_params(self):
"""
An OrderedDict (bottom to top, i.e., input to output) of network
parameters indexed by name; each is a list of multiple blobs (e.g.,
weights and biases)
"""
if not hasattr(self, '_params_dict'):
self._params_dict = OrderedDict([(name, lr.blobs)
for name, lr in zip(
self._layer_names, self.layers)
if len(lr.blobs) > 0])
return self._params_dict | [
"def",
"_Net_params",
"(",
"self",
")",
":",
"if",
"not",
"hasattr",
"(",
"self",
",",
"'_params_dict'",
")",
":",
"self",
".",
"_params_dict",
"=",
"OrderedDict",
"(",
"[",
"(",
"name",
",",
"lr",
".",
"blobs",
")",
"for",
"name",
",",
"lr",
"in",
"zip",
"(",
"self",
".",
"_layer_names",
",",
"self",
".",
"layers",
")",
"if",
"len",
"(",
"lr",
".",
"blobs",
")",
">",
"0",
"]",
")",
"return",
"self",
".",
"_params_dict"
] | https://github.com/dicecco1/fpga_caffe/blob/7a191704efd7873071cfef35772d7e7bf3e3cfd6/python/caffe/pycaffe.py#L58-L69 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/config_key.py | python | GetKeysDialog.keys_ok | (self, keys) | return False | Validity check on user's 'basic' keybinding selection.
Doesn't check the string produced by the advanced dialog because
'modifiers' isn't set. | Validity check on user's 'basic' keybinding selection. | [
"Validity",
"check",
"on",
"user",
"s",
"basic",
"keybinding",
"selection",
"."
] | def keys_ok(self, keys):
"""Validity check on user's 'basic' keybinding selection.
Doesn't check the string produced by the advanced dialog because
'modifiers' isn't set.
"""
final_key = self.list_keys_final.get('anchor')
modifiers = self.get_modifiers()
title = self.keyerror_title
key_sequences = [key for keylist in self.current_key_sequences
for key in keylist]
if not keys.endswith('>'):
self.showerror(title, parent=self,
message='Missing the final Key')
elif (not modifiers
and final_key not in FUNCTION_KEYS + MOVE_KEYS):
self.showerror(title=title, parent=self,
message='No modifier key(s) specified.')
elif (modifiers == ['Shift']) \
and (final_key not in
FUNCTION_KEYS + MOVE_KEYS + ('Tab', 'Space')):
msg = 'The shift modifier by itself may not be used with'\
' this key symbol.'
self.showerror(title=title, parent=self, message=msg)
elif keys in key_sequences:
msg = 'This key combination is already in use.'
self.showerror(title=title, parent=self, message=msg)
else:
return True
return False | [
"def",
"keys_ok",
"(",
"self",
",",
"keys",
")",
":",
"final_key",
"=",
"self",
".",
"list_keys_final",
".",
"get",
"(",
"'anchor'",
")",
"modifiers",
"=",
"self",
".",
"get_modifiers",
"(",
")",
"title",
"=",
"self",
".",
"keyerror_title",
"key_sequences",
"=",
"[",
"key",
"for",
"keylist",
"in",
"self",
".",
"current_key_sequences",
"for",
"key",
"in",
"keylist",
"]",
"if",
"not",
"keys",
".",
"endswith",
"(",
"'>'",
")",
":",
"self",
".",
"showerror",
"(",
"title",
",",
"parent",
"=",
"self",
",",
"message",
"=",
"'Missing the final Key'",
")",
"elif",
"(",
"not",
"modifiers",
"and",
"final_key",
"not",
"in",
"FUNCTION_KEYS",
"+",
"MOVE_KEYS",
")",
":",
"self",
".",
"showerror",
"(",
"title",
"=",
"title",
",",
"parent",
"=",
"self",
",",
"message",
"=",
"'No modifier key(s) specified.'",
")",
"elif",
"(",
"modifiers",
"==",
"[",
"'Shift'",
"]",
")",
"and",
"(",
"final_key",
"not",
"in",
"FUNCTION_KEYS",
"+",
"MOVE_KEYS",
"+",
"(",
"'Tab'",
",",
"'Space'",
")",
")",
":",
"msg",
"=",
"'The shift modifier by itself may not be used with'",
"' this key symbol.'",
"self",
".",
"showerror",
"(",
"title",
"=",
"title",
",",
"parent",
"=",
"self",
",",
"message",
"=",
"msg",
")",
"elif",
"keys",
"in",
"key_sequences",
":",
"msg",
"=",
"'This key combination is already in use.'",
"self",
".",
"showerror",
"(",
"title",
"=",
"title",
",",
"parent",
"=",
"self",
",",
"message",
"=",
"msg",
")",
"else",
":",
"return",
"True",
"return",
"False"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/config_key.py#L274-L303 | |
Z3Prover/z3 | d745d03afdfdf638d66093e2bfbacaf87187f35b | src/api/python/z3/z3num.py | python | Numeral.power | (self, k) | return Numeral(Z3_algebraic_power(self.ctx_ref(), self.ast, k), self.ctx) | Return the numeral `self^k`.
>>> sqrt3 = Numeral(3).root(2)
>>> sqrt3
1.7320508075?
>>> sqrt3.power(2)
3 | Return the numeral `self^k`. | [
"Return",
"the",
"numeral",
"self^k",
"."
] | def power(self, k):
""" Return the numeral `self^k`.
>>> sqrt3 = Numeral(3).root(2)
>>> sqrt3
1.7320508075?
>>> sqrt3.power(2)
3
"""
return Numeral(Z3_algebraic_power(self.ctx_ref(), self.ast, k), self.ctx) | [
"def",
"power",
"(",
"self",
",",
"k",
")",
":",
"return",
"Numeral",
"(",
"Z3_algebraic_power",
"(",
"self",
".",
"ctx_ref",
"(",
")",
",",
"self",
".",
"ast",
",",
"k",
")",
",",
"self",
".",
"ctx",
")"
] | https://github.com/Z3Prover/z3/blob/d745d03afdfdf638d66093e2bfbacaf87187f35b/src/api/python/z3/z3num.py#L383-L392 | |
opengauss-mirror/openGauss-server | e383f1b77720a00ddbe4c0655bc85914d9b02a2b | src/gausskernel/dbmind/tools/ai_manager/module/anomaly_detection/install.py | python | Installer.try_to_kill_process_exist | (self) | Try to kill process, if already exist | Try to kill process, if already exist | [
"Try",
"to",
"kill",
"process",
"if",
"already",
"exist"
] | def try_to_kill_process_exist(self):
"""
Try to kill process, if already exist
"""
script_path = os.path.realpath(
os.path.join(self.install_path, Constant.ANORMALY_MAIN_SCRIPT))
process_list = [(cmd % (Constant.CMD_PREFIX, os.path.dirname(script_path), script_path)
).split(self.version)[-1] for cmd in self.service_list]
for process in process_list:
process_num = CommonTools.check_process(process)
if process_num:
CommonTools.grep_process_and_kill(process)
g.logger.info('Killed process of [%s]' % process) | [
"def",
"try_to_kill_process_exist",
"(",
"self",
")",
":",
"script_path",
"=",
"os",
".",
"path",
".",
"realpath",
"(",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"install_path",
",",
"Constant",
".",
"ANORMALY_MAIN_SCRIPT",
")",
")",
"process_list",
"=",
"[",
"(",
"cmd",
"%",
"(",
"Constant",
".",
"CMD_PREFIX",
",",
"os",
".",
"path",
".",
"dirname",
"(",
"script_path",
")",
",",
"script_path",
")",
")",
".",
"split",
"(",
"self",
".",
"version",
")",
"[",
"-",
"1",
"]",
"for",
"cmd",
"in",
"self",
".",
"service_list",
"]",
"for",
"process",
"in",
"process_list",
":",
"process_num",
"=",
"CommonTools",
".",
"check_process",
"(",
"process",
")",
"if",
"process_num",
":",
"CommonTools",
".",
"grep_process_and_kill",
"(",
"process",
")",
"g",
".",
"logger",
".",
"info",
"(",
"'Killed process of [%s]'",
"%",
"process",
")"
] | https://github.com/opengauss-mirror/openGauss-server/blob/e383f1b77720a00ddbe4c0655bc85914d9b02a2b/src/gausskernel/dbmind/tools/ai_manager/module/anomaly_detection/install.py#L159-L171 | ||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/docview.py | python | Document.GetWriteable | (self) | Returns true if the document can be written to its accociated file path.
This method has been added to wxPython and is not in wxWindows. | Returns true if the document can be written to its accociated file path.
This method has been added to wxPython and is not in wxWindows. | [
"Returns",
"true",
"if",
"the",
"document",
"can",
"be",
"written",
"to",
"its",
"accociated",
"file",
"path",
".",
"This",
"method",
"has",
"been",
"added",
"to",
"wxPython",
"and",
"is",
"not",
"in",
"wxWindows",
"."
] | def GetWriteable(self):
"""
Returns true if the document can be written to its accociated file path.
This method has been added to wxPython and is not in wxWindows.
"""
if not self._writeable:
return False
if not self._documentFile: # Doesn't exist, do a save as
return True
else:
return os.access(self._documentFile, os.W_OK) | [
"def",
"GetWriteable",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"_writeable",
":",
"return",
"False",
"if",
"not",
"self",
".",
"_documentFile",
":",
"# Doesn't exist, do a save as",
"return",
"True",
"else",
":",
"return",
"os",
".",
"access",
"(",
"self",
".",
"_documentFile",
",",
"os",
".",
"W_OK",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/docview.py#L747-L757 | ||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | TextAttr.HasFontSize | (*args, **kwargs) | return _controls_.TextAttr_HasFontSize(*args, **kwargs) | HasFontSize(self) -> bool | HasFontSize(self) -> bool | [
"HasFontSize",
"(",
"self",
")",
"-",
">",
"bool"
] | def HasFontSize(*args, **kwargs):
"""HasFontSize(self) -> bool"""
return _controls_.TextAttr_HasFontSize(*args, **kwargs) | [
"def",
"HasFontSize",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_controls_",
".",
"TextAttr_HasFontSize",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_controls.py#L1796-L1798 | |
google/skia | 82d65d0487bd72f5f7332d002429ec2dc61d2463 | infra/bots/assets/chromebook_x86_64_gles/create.py | python | create_asset | (target_dir, gl_path) | Create the asset. | Create the asset. | [
"Create",
"the",
"asset",
"."
] | def create_asset(target_dir, gl_path):
"""Create the asset."""
cmd = [
'sudo','apt-get','install',
'libgles2-mesa-dev',
'libegl1-mesa-dev'
]
subprocess.check_call(cmd)
lib_dir = os.path.join(target_dir, 'lib')
os.mkdir(lib_dir)
to_copy = glob.glob(os.path.join(gl_path,'libGL*'))
to_copy.extend(glob.glob(os.path.join(gl_path,'libEGL*')))
to_copy.extend(glob.glob(os.path.join(gl_path,'libdrm*')))
for f in to_copy:
shutil.copy(f, lib_dir)
include_dir = os.path.join(target_dir, 'include')
os.mkdir(include_dir)
shutil.copytree('/usr/include/EGL', os.path.join(include_dir, 'EGL'))
shutil.copytree('/usr/include/KHR', os.path.join(include_dir, 'KHR'))
shutil.copytree('/usr/include/GLES2', os.path.join(include_dir, 'GLES2'))
shutil.copytree('/usr/include/GLES3', os.path.join(include_dir, 'GLES3')) | [
"def",
"create_asset",
"(",
"target_dir",
",",
"gl_path",
")",
":",
"cmd",
"=",
"[",
"'sudo'",
",",
"'apt-get'",
",",
"'install'",
",",
"'libgles2-mesa-dev'",
",",
"'libegl1-mesa-dev'",
"]",
"subprocess",
".",
"check_call",
"(",
"cmd",
")",
"lib_dir",
"=",
"os",
".",
"path",
".",
"join",
"(",
"target_dir",
",",
"'lib'",
")",
"os",
".",
"mkdir",
"(",
"lib_dir",
")",
"to_copy",
"=",
"glob",
".",
"glob",
"(",
"os",
".",
"path",
".",
"join",
"(",
"gl_path",
",",
"'libGL*'",
")",
")",
"to_copy",
".",
"extend",
"(",
"glob",
".",
"glob",
"(",
"os",
".",
"path",
".",
"join",
"(",
"gl_path",
",",
"'libEGL*'",
")",
")",
")",
"to_copy",
".",
"extend",
"(",
"glob",
".",
"glob",
"(",
"os",
".",
"path",
".",
"join",
"(",
"gl_path",
",",
"'libdrm*'",
")",
")",
")",
"for",
"f",
"in",
"to_copy",
":",
"shutil",
".",
"copy",
"(",
"f",
",",
"lib_dir",
")",
"include_dir",
"=",
"os",
".",
"path",
".",
"join",
"(",
"target_dir",
",",
"'include'",
")",
"os",
".",
"mkdir",
"(",
"include_dir",
")",
"shutil",
".",
"copytree",
"(",
"'/usr/include/EGL'",
",",
"os",
".",
"path",
".",
"join",
"(",
"include_dir",
",",
"'EGL'",
")",
")",
"shutil",
".",
"copytree",
"(",
"'/usr/include/KHR'",
",",
"os",
".",
"path",
".",
"join",
"(",
"include_dir",
",",
"'KHR'",
")",
")",
"shutil",
".",
"copytree",
"(",
"'/usr/include/GLES2'",
",",
"os",
".",
"path",
".",
"join",
"(",
"include_dir",
",",
"'GLES2'",
")",
")",
"shutil",
".",
"copytree",
"(",
"'/usr/include/GLES3'",
",",
"os",
".",
"path",
".",
"join",
"(",
"include_dir",
",",
"'GLES3'",
")",
")"
] | https://github.com/google/skia/blob/82d65d0487bd72f5f7332d002429ec2dc61d2463/infra/bots/assets/chromebook_x86_64_gles/create.py#L33-L58 | ||
deeplearningais/CUV | 4e920ad1304af9de3e5f755cc2e9c5c96e06c324 | examples/rbm/base.py | python | RBMStack.run | (self, iterstart, itermax, mbatch_provider) | Trains all levels of the RBM stack for itermax epochs. Lowest-level data comes from mbatch_provider. | Trains all levels of the RBM stack for itermax epochs. Lowest-level data comes from mbatch_provider. | [
"Trains",
"all",
"levels",
"of",
"the",
"RBM",
"stack",
"for",
"itermax",
"epochs",
".",
"Lowest",
"-",
"level",
"data",
"comes",
"from",
"mbatch_provider",
"."
] | def run(self, iterstart, itermax, mbatch_provider):
""" Trains all levels of the RBM stack for itermax epochs. Lowest-level data comes from mbatch_provider. """
self.mbp = mbatch_provider
self.err = []
for layer in xrange( self.cfg.num_layers-1 ):
if layer >= self.cfg.continue_learning-1:
try:
self.trainLayer(mbatch_provider, iterstart, itermax, layer)
print "Finished Layer ", layer
except KeyboardInterrupt:
mbatch_provider.forgetOriginalData()
print "Stopping training of layer %d" % layer
finally:
self.saveLayer(layer, self.cfg.workdir, "-pretrain")
if layer < self.cfg.num_layers-2:
mbatch_provider = self.getHiddenRep(layer, mbatch_provider)
print "Got ", len(mbatch_provider.dataset), "batches" | [
"def",
"run",
"(",
"self",
",",
"iterstart",
",",
"itermax",
",",
"mbatch_provider",
")",
":",
"self",
".",
"mbp",
"=",
"mbatch_provider",
"self",
".",
"err",
"=",
"[",
"]",
"for",
"layer",
"in",
"xrange",
"(",
"self",
".",
"cfg",
".",
"num_layers",
"-",
"1",
")",
":",
"if",
"layer",
">=",
"self",
".",
"cfg",
".",
"continue_learning",
"-",
"1",
":",
"try",
":",
"self",
".",
"trainLayer",
"(",
"mbatch_provider",
",",
"iterstart",
",",
"itermax",
",",
"layer",
")",
"print",
"\"Finished Layer \"",
",",
"layer",
"except",
"KeyboardInterrupt",
":",
"mbatch_provider",
".",
"forgetOriginalData",
"(",
")",
"print",
"\"Stopping training of layer %d\"",
"%",
"layer",
"finally",
":",
"self",
".",
"saveLayer",
"(",
"layer",
",",
"self",
".",
"cfg",
".",
"workdir",
",",
"\"-pretrain\"",
")",
"if",
"layer",
"<",
"self",
".",
"cfg",
".",
"num_layers",
"-",
"2",
":",
"mbatch_provider",
"=",
"self",
".",
"getHiddenRep",
"(",
"layer",
",",
"mbatch_provider",
")",
"print",
"\"Got \"",
",",
"len",
"(",
"mbatch_provider",
".",
"dataset",
")",
",",
"\"batches\""
] | https://github.com/deeplearningais/CUV/blob/4e920ad1304af9de3e5f755cc2e9c5c96e06c324/examples/rbm/base.py#L317-L333 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/requests/models.py | python | Response.iter_lines | (self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=False, delimiter=None) | Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses.
.. note:: This method is not reentrant safe. | Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses. | [
"Iterates",
"over",
"the",
"response",
"data",
"one",
"line",
"at",
"a",
"time",
".",
"When",
"stream",
"=",
"True",
"is",
"set",
"on",
"the",
"request",
"this",
"avoids",
"reading",
"the",
"content",
"at",
"once",
"into",
"memory",
"for",
"large",
"responses",
"."
] | def iter_lines(self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=False, delimiter=None):
"""Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses.
.. note:: This method is not reentrant safe.
"""
pending = None
for chunk in self.iter_content(chunk_size=chunk_size, decode_unicode=decode_unicode):
if pending is not None:
chunk = pending + chunk
if delimiter:
lines = chunk.split(delimiter)
else:
lines = chunk.splitlines()
if lines and lines[-1] and chunk and lines[-1][-1] == chunk[-1]:
pending = lines.pop()
else:
pending = None
for line in lines:
yield line
if pending is not None:
yield pending | [
"def",
"iter_lines",
"(",
"self",
",",
"chunk_size",
"=",
"ITER_CHUNK_SIZE",
",",
"decode_unicode",
"=",
"False",
",",
"delimiter",
"=",
"None",
")",
":",
"pending",
"=",
"None",
"for",
"chunk",
"in",
"self",
".",
"iter_content",
"(",
"chunk_size",
"=",
"chunk_size",
",",
"decode_unicode",
"=",
"decode_unicode",
")",
":",
"if",
"pending",
"is",
"not",
"None",
":",
"chunk",
"=",
"pending",
"+",
"chunk",
"if",
"delimiter",
":",
"lines",
"=",
"chunk",
".",
"split",
"(",
"delimiter",
")",
"else",
":",
"lines",
"=",
"chunk",
".",
"splitlines",
"(",
")",
"if",
"lines",
"and",
"lines",
"[",
"-",
"1",
"]",
"and",
"chunk",
"and",
"lines",
"[",
"-",
"1",
"]",
"[",
"-",
"1",
"]",
"==",
"chunk",
"[",
"-",
"1",
"]",
":",
"pending",
"=",
"lines",
".",
"pop",
"(",
")",
"else",
":",
"pending",
"=",
"None",
"for",
"line",
"in",
"lines",
":",
"yield",
"line",
"if",
"pending",
"is",
"not",
"None",
":",
"yield",
"pending"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/requests/models.py#L785-L814 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pyparsing/py2/pyparsing.py | python | ParserElement.enablePackrat | (cache_size_limit=128) | Enables "packrat" parsing, which adds memoizing to the parsing logic.
Repeated parse attempts at the same string location (which happens
often in many complex grammars) can immediately return a cached value,
instead of re-executing parsing/validating code. Memoizing is done of
both valid results and parsing exceptions.
Parameters:
- cache_size_limit - (default= ``128``) - if an integer value is provided
will limit the size of the packrat cache; if None is passed, then
the cache size will be unbounded; if 0 is passed, the cache will
be effectively disabled.
This speedup may break existing programs that use parse actions that
have side-effects. For this reason, packrat parsing is disabled when
you first import pyparsing. To activate the packrat feature, your
program must call the class method :class:`ParserElement.enablePackrat`.
For best results, call ``enablePackrat()`` immediately after
importing pyparsing.
Example::
import pyparsing
pyparsing.ParserElement.enablePackrat() | Enables "packrat" parsing, which adds memoizing to the parsing logic.
Repeated parse attempts at the same string location (which happens
often in many complex grammars) can immediately return a cached value,
instead of re-executing parsing/validating code. Memoizing is done of
both valid results and parsing exceptions. | [
"Enables",
"packrat",
"parsing",
"which",
"adds",
"memoizing",
"to",
"the",
"parsing",
"logic",
".",
"Repeated",
"parse",
"attempts",
"at",
"the",
"same",
"string",
"location",
"(",
"which",
"happens",
"often",
"in",
"many",
"complex",
"grammars",
")",
"can",
"immediately",
"return",
"a",
"cached",
"value",
"instead",
"of",
"re",
"-",
"executing",
"parsing",
"/",
"validating",
"code",
".",
"Memoizing",
"is",
"done",
"of",
"both",
"valid",
"results",
"and",
"parsing",
"exceptions",
"."
] | def enablePackrat(cache_size_limit=128):
"""Enables "packrat" parsing, which adds memoizing to the parsing logic.
Repeated parse attempts at the same string location (which happens
often in many complex grammars) can immediately return a cached value,
instead of re-executing parsing/validating code. Memoizing is done of
both valid results and parsing exceptions.
Parameters:
- cache_size_limit - (default= ``128``) - if an integer value is provided
will limit the size of the packrat cache; if None is passed, then
the cache size will be unbounded; if 0 is passed, the cache will
be effectively disabled.
This speedup may break existing programs that use parse actions that
have side-effects. For this reason, packrat parsing is disabled when
you first import pyparsing. To activate the packrat feature, your
program must call the class method :class:`ParserElement.enablePackrat`.
For best results, call ``enablePackrat()`` immediately after
importing pyparsing.
Example::
import pyparsing
pyparsing.ParserElement.enablePackrat()
"""
if not ParserElement._packratEnabled:
ParserElement._packratEnabled = True
if cache_size_limit is None:
ParserElement.packrat_cache = ParserElement._UnboundedCache()
else:
ParserElement.packrat_cache = ParserElement._FifoCache(cache_size_limit)
ParserElement._parse = ParserElement._parseCache | [
"def",
"enablePackrat",
"(",
"cache_size_limit",
"=",
"128",
")",
":",
"if",
"not",
"ParserElement",
".",
"_packratEnabled",
":",
"ParserElement",
".",
"_packratEnabled",
"=",
"True",
"if",
"cache_size_limit",
"is",
"None",
":",
"ParserElement",
".",
"packrat_cache",
"=",
"ParserElement",
".",
"_UnboundedCache",
"(",
")",
"else",
":",
"ParserElement",
".",
"packrat_cache",
"=",
"ParserElement",
".",
"_FifoCache",
"(",
"cache_size_limit",
")",
"ParserElement",
".",
"_parse",
"=",
"ParserElement",
".",
"_parseCache"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pyparsing/py2/pyparsing.py#L1867-L1899 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/docutils/parsers/rst/tableparser.py | python | SimpleTableParser.parse_table | (self) | First determine the column boundaries from the top border, then
process rows. Each row may consist of multiple lines; accumulate
lines until a row is complete. Call `self.parse_row` to finish the
job. | First determine the column boundaries from the top border, then
process rows. Each row may consist of multiple lines; accumulate
lines until a row is complete. Call `self.parse_row` to finish the
job. | [
"First",
"determine",
"the",
"column",
"boundaries",
"from",
"the",
"top",
"border",
"then",
"process",
"rows",
".",
"Each",
"row",
"may",
"consist",
"of",
"multiple",
"lines",
";",
"accumulate",
"lines",
"until",
"a",
"row",
"is",
"complete",
".",
"Call",
"self",
".",
"parse_row",
"to",
"finish",
"the",
"job",
"."
] | def parse_table(self):
"""
First determine the column boundaries from the top border, then
process rows. Each row may consist of multiple lines; accumulate
lines until a row is complete. Call `self.parse_row` to finish the
job.
"""
# Top border must fully describe all table columns.
self.columns = self.parse_columns(self.block[0], 0)
self.border_end = self.columns[-1][1]
firststart, firstend = self.columns[0]
offset = 1 # skip top border
start = 1
text_found = None
while offset < len(self.block):
line = self.block[offset]
if self.span_pat.match(line):
# Column span underline or border; row is complete.
self.parse_row(self.block[start:offset], start,
(line.rstrip(), offset))
start = offset + 1
text_found = None
elif line[firststart:firstend].strip():
# First column not blank, therefore it's a new row.
if text_found and offset != start:
self.parse_row(self.block[start:offset], start)
start = offset
text_found = 1
elif not text_found:
start = offset + 1
offset += 1 | [
"def",
"parse_table",
"(",
"self",
")",
":",
"# Top border must fully describe all table columns.",
"self",
".",
"columns",
"=",
"self",
".",
"parse_columns",
"(",
"self",
".",
"block",
"[",
"0",
"]",
",",
"0",
")",
"self",
".",
"border_end",
"=",
"self",
".",
"columns",
"[",
"-",
"1",
"]",
"[",
"1",
"]",
"firststart",
",",
"firstend",
"=",
"self",
".",
"columns",
"[",
"0",
"]",
"offset",
"=",
"1",
"# skip top border",
"start",
"=",
"1",
"text_found",
"=",
"None",
"while",
"offset",
"<",
"len",
"(",
"self",
".",
"block",
")",
":",
"line",
"=",
"self",
".",
"block",
"[",
"offset",
"]",
"if",
"self",
".",
"span_pat",
".",
"match",
"(",
"line",
")",
":",
"# Column span underline or border; row is complete.",
"self",
".",
"parse_row",
"(",
"self",
".",
"block",
"[",
"start",
":",
"offset",
"]",
",",
"start",
",",
"(",
"line",
".",
"rstrip",
"(",
")",
",",
"offset",
")",
")",
"start",
"=",
"offset",
"+",
"1",
"text_found",
"=",
"None",
"elif",
"line",
"[",
"firststart",
":",
"firstend",
"]",
".",
"strip",
"(",
")",
":",
"# First column not blank, therefore it's a new row.",
"if",
"text_found",
"and",
"offset",
"!=",
"start",
":",
"self",
".",
"parse_row",
"(",
"self",
".",
"block",
"[",
"start",
":",
"offset",
"]",
",",
"start",
")",
"start",
"=",
"offset",
"text_found",
"=",
"1",
"elif",
"not",
"text_found",
":",
"start",
"=",
"offset",
"+",
"1",
"offset",
"+=",
"1"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/docutils/parsers/rst/tableparser.py#L392-L422 | ||
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/ReflectometryISISLoadAndProcess.py | python | ReflectometryISISLoadAndProcess.validateInputs | (self) | return issues | Return a dictionary containing issues found in properties. | Return a dictionary containing issues found in properties. | [
"Return",
"a",
"dictionary",
"containing",
"issues",
"found",
"in",
"properties",
"."
] | def validateInputs(self):
"""Return a dictionary containing issues found in properties."""
issues = dict()
if len(self.getProperty(Prop.RUNS).value) > 1 and self.getProperty(Prop.SLICE).value:
issues[Prop.SLICE] = "Cannot perform slicing when summing multiple input runs"
return issues | [
"def",
"validateInputs",
"(",
"self",
")",
":",
"issues",
"=",
"dict",
"(",
")",
"if",
"len",
"(",
"self",
".",
"getProperty",
"(",
"Prop",
".",
"RUNS",
")",
".",
"value",
")",
">",
"1",
"and",
"self",
".",
"getProperty",
"(",
"Prop",
".",
"SLICE",
")",
".",
"value",
":",
"issues",
"[",
"Prop",
".",
"SLICE",
"]",
"=",
"\"Cannot perform slicing when summing multiple input runs\"",
"return",
"issues"
] | https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/ReflectometryISISLoadAndProcess.py#L111-L116 | |
apache/mesos | 97d9a4063332aae3825d78de71611657e05cf5e2 | support/cpplint.py | python | _CppLintState.SetVerboseLevel | (self, level) | return last_verbose_level | Sets the module's verbosity, and returns the previous setting. | Sets the module's verbosity, and returns the previous setting. | [
"Sets",
"the",
"module",
"s",
"verbosity",
"and",
"returns",
"the",
"previous",
"setting",
"."
] | def SetVerboseLevel(self, level):
"""Sets the module's verbosity, and returns the previous setting."""
last_verbose_level = self.verbose_level
self.verbose_level = level
return last_verbose_level | [
"def",
"SetVerboseLevel",
"(",
"self",
",",
"level",
")",
":",
"last_verbose_level",
"=",
"self",
".",
"verbose_level",
"self",
".",
"verbose_level",
"=",
"level",
"return",
"last_verbose_level"
] | https://github.com/apache/mesos/blob/97d9a4063332aae3825d78de71611657e05cf5e2/support/cpplint.py#L896-L900 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/kernels/reduction.py | python | Reduce.__init__ | (self, functor) | Create a reduction object that reduces values using a given binary
function. The binary function is compiled once and cached inside this
object. Keeping this object alive will prevent re-compilation.
:param binop: A function to be compiled as a CUDA device function that
will be used as the binary operation for reduction on a
CUDA device. Internally, it is compiled using
``cuda.jit(device=True)``. | Create a reduction object that reduces values using a given binary
function. The binary function is compiled once and cached inside this
object. Keeping this object alive will prevent re-compilation. | [
"Create",
"a",
"reduction",
"object",
"that",
"reduces",
"values",
"using",
"a",
"given",
"binary",
"function",
".",
"The",
"binary",
"function",
"is",
"compiled",
"once",
"and",
"cached",
"inside",
"this",
"object",
".",
"Keeping",
"this",
"object",
"alive",
"will",
"prevent",
"re",
"-",
"compilation",
"."
] | def __init__(self, functor):
"""Create a reduction object that reduces values using a given binary
function. The binary function is compiled once and cached inside this
object. Keeping this object alive will prevent re-compilation.
:param binop: A function to be compiled as a CUDA device function that
will be used as the binary operation for reduction on a
CUDA device. Internally, it is compiled using
``cuda.jit(device=True)``.
"""
self._functor = functor | [
"def",
"__init__",
"(",
"self",
",",
"functor",
")",
":",
"self",
".",
"_functor",
"=",
"functor"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/kernels/reduction.py#L166-L176 | ||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/richtext.py | python | TextAttrBorder.HasWidth | (*args, **kwargs) | return _richtext.TextAttrBorder_HasWidth(*args, **kwargs) | HasWidth(self) -> bool | HasWidth(self) -> bool | [
"HasWidth",
"(",
"self",
")",
"-",
">",
"bool"
] | def HasWidth(*args, **kwargs):
"""HasWidth(self) -> bool"""
return _richtext.TextAttrBorder_HasWidth(*args, **kwargs) | [
"def",
"HasWidth",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_richtext",
".",
"TextAttrBorder_HasWidth",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/richtext.py#L394-L396 | |
PaddlePaddle/PaddleOCR | b756bf5f8c90142e0d89d3db0163965c686b6ffe | ppocr/utils/e2e_utils/visual.py | python | expand_poly_along_width | (poly, shrink_ratio_of_width=0.3) | return poly | expand poly along width. | expand poly along width. | [
"expand",
"poly",
"along",
"width",
"."
] | def expand_poly_along_width(poly, shrink_ratio_of_width=0.3):
"""
expand poly along width.
"""
point_num = poly.shape[0]
left_quad = np.array(
[poly[0], poly[1], poly[-2], poly[-1]], dtype=np.float32)
left_ratio = -shrink_ratio_of_width * np.linalg.norm(left_quad[0] - left_quad[3]) / \
(np.linalg.norm(left_quad[0] - left_quad[1]) + 1e-6)
left_quad_expand = shrink_quad_along_width(left_quad, left_ratio, 1.0)
right_quad = np.array(
[
poly[point_num // 2 - 2], poly[point_num // 2 - 1],
poly[point_num // 2], poly[point_num // 2 + 1]
],
dtype=np.float32)
right_ratio = 1.0 + \
shrink_ratio_of_width * np.linalg.norm(right_quad[0] - right_quad[3]) / \
(np.linalg.norm(right_quad[0] - right_quad[1]) + 1e-6)
right_quad_expand = shrink_quad_along_width(right_quad, 0.0, right_ratio)
poly[0] = left_quad_expand[0]
poly[-1] = left_quad_expand[-1]
poly[point_num // 2 - 1] = right_quad_expand[1]
poly[point_num // 2] = right_quad_expand[2]
return poly | [
"def",
"expand_poly_along_width",
"(",
"poly",
",",
"shrink_ratio_of_width",
"=",
"0.3",
")",
":",
"point_num",
"=",
"poly",
".",
"shape",
"[",
"0",
"]",
"left_quad",
"=",
"np",
".",
"array",
"(",
"[",
"poly",
"[",
"0",
"]",
",",
"poly",
"[",
"1",
"]",
",",
"poly",
"[",
"-",
"2",
"]",
",",
"poly",
"[",
"-",
"1",
"]",
"]",
",",
"dtype",
"=",
"np",
".",
"float32",
")",
"left_ratio",
"=",
"-",
"shrink_ratio_of_width",
"*",
"np",
".",
"linalg",
".",
"norm",
"(",
"left_quad",
"[",
"0",
"]",
"-",
"left_quad",
"[",
"3",
"]",
")",
"/",
"(",
"np",
".",
"linalg",
".",
"norm",
"(",
"left_quad",
"[",
"0",
"]",
"-",
"left_quad",
"[",
"1",
"]",
")",
"+",
"1e-6",
")",
"left_quad_expand",
"=",
"shrink_quad_along_width",
"(",
"left_quad",
",",
"left_ratio",
",",
"1.0",
")",
"right_quad",
"=",
"np",
".",
"array",
"(",
"[",
"poly",
"[",
"point_num",
"//",
"2",
"-",
"2",
"]",
",",
"poly",
"[",
"point_num",
"//",
"2",
"-",
"1",
"]",
",",
"poly",
"[",
"point_num",
"//",
"2",
"]",
",",
"poly",
"[",
"point_num",
"//",
"2",
"+",
"1",
"]",
"]",
",",
"dtype",
"=",
"np",
".",
"float32",
")",
"right_ratio",
"=",
"1.0",
"+",
"shrink_ratio_of_width",
"*",
"np",
".",
"linalg",
".",
"norm",
"(",
"right_quad",
"[",
"0",
"]",
"-",
"right_quad",
"[",
"3",
"]",
")",
"/",
"(",
"np",
".",
"linalg",
".",
"norm",
"(",
"right_quad",
"[",
"0",
"]",
"-",
"right_quad",
"[",
"1",
"]",
")",
"+",
"1e-6",
")",
"right_quad_expand",
"=",
"shrink_quad_along_width",
"(",
"right_quad",
",",
"0.0",
",",
"right_ratio",
")",
"poly",
"[",
"0",
"]",
"=",
"left_quad_expand",
"[",
"0",
"]",
"poly",
"[",
"-",
"1",
"]",
"=",
"left_quad_expand",
"[",
"-",
"1",
"]",
"poly",
"[",
"point_num",
"//",
"2",
"-",
"1",
"]",
"=",
"right_quad_expand",
"[",
"1",
"]",
"poly",
"[",
"point_num",
"//",
"2",
"]",
"=",
"right_quad_expand",
"[",
"2",
"]",
"return",
"poly"
] | https://github.com/PaddlePaddle/PaddleOCR/blob/b756bf5f8c90142e0d89d3db0163965c686b6ffe/ppocr/utils/e2e_utils/visual.py#L128-L152 | |
sphinxsearch/sphinx | 409f2c2b5b2ff70b04e38f92b6b1a890326bad65 | api/sphinxapi.py | python | SphinxClient.Status | ( self, session=False ) | return res | Get the status | Get the status | [
"Get",
"the",
"status"
] | def Status ( self, session=False ):
"""
Get the status
"""
# connect, send query, get response
sock = self._Connect()
if not sock:
return None
sess = 1
if session:
sess = 0
req = pack ( '>2HLL', SEARCHD_COMMAND_STATUS, VER_COMMAND_STATUS, 4, sess )
self._Send ( sock, req )
response = self._GetResponse ( sock, VER_COMMAND_STATUS )
if not response:
return None
# parse response
res = []
p = 8
max_ = len(response)
while p<max_:
length = unpack ( '>L', response[p:p+4] )[0]
k = response[p+4:p+length+4]
p += 4+length
length = unpack ( '>L', response[p:p+4] )[0]
v = response[p+4:p+length+4]
p += 4+length
res += [[bytes_str(k), bytes_str(v)]]
return res | [
"def",
"Status",
"(",
"self",
",",
"session",
"=",
"False",
")",
":",
"# connect, send query, get response",
"sock",
"=",
"self",
".",
"_Connect",
"(",
")",
"if",
"not",
"sock",
":",
"return",
"None",
"sess",
"=",
"1",
"if",
"session",
":",
"sess",
"=",
"0",
"req",
"=",
"pack",
"(",
"'>2HLL'",
",",
"SEARCHD_COMMAND_STATUS",
",",
"VER_COMMAND_STATUS",
",",
"4",
",",
"sess",
")",
"self",
".",
"_Send",
"(",
"sock",
",",
"req",
")",
"response",
"=",
"self",
".",
"_GetResponse",
"(",
"sock",
",",
"VER_COMMAND_STATUS",
")",
"if",
"not",
"response",
":",
"return",
"None",
"# parse response",
"res",
"=",
"[",
"]",
"p",
"=",
"8",
"max_",
"=",
"len",
"(",
"response",
")",
"while",
"p",
"<",
"max_",
":",
"length",
"=",
"unpack",
"(",
"'>L'",
",",
"response",
"[",
"p",
":",
"p",
"+",
"4",
"]",
")",
"[",
"0",
"]",
"k",
"=",
"response",
"[",
"p",
"+",
"4",
":",
"p",
"+",
"length",
"+",
"4",
"]",
"p",
"+=",
"4",
"+",
"length",
"length",
"=",
"unpack",
"(",
"'>L'",
",",
"response",
"[",
"p",
":",
"p",
"+",
"4",
"]",
")",
"[",
"0",
"]",
"v",
"=",
"response",
"[",
"p",
"+",
"4",
":",
"p",
"+",
"length",
"+",
"4",
"]",
"p",
"+=",
"4",
"+",
"length",
"res",
"+=",
"[",
"[",
"bytes_str",
"(",
"k",
")",
",",
"bytes_str",
"(",
"v",
")",
"]",
"]",
"return",
"res"
] | https://github.com/sphinxsearch/sphinx/blob/409f2c2b5b2ff70b04e38f92b6b1a890326bad65/api/sphinxapi.py#L1199-L1235 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/lmbr_aws/cleanup_utils/cleanup_s3_utils.py | python | _clean_s3_bucket | (cleaner, bucket_name) | Deletes all object dependencies in a bucket. The delete function is unique in that it deletes objects in
batches.
:param cleaner: A Cleaner object from the main cleanup.py script
:param bucket_name: The name of the s3 bucket to clean.
:return: | Deletes all object dependencies in a bucket. The delete function is unique in that it deletes objects in
batches.
:param cleaner: A Cleaner object from the main cleanup.py script
:param bucket_name: The name of the s3 bucket to clean.
:return: | [
"Deletes",
"all",
"object",
"dependencies",
"in",
"a",
"bucket",
".",
"The",
"delete",
"function",
"is",
"unique",
"in",
"that",
"it",
"deletes",
"objects",
"in",
"batches",
".",
":",
"param",
"cleaner",
":",
"A",
"Cleaner",
"object",
"from",
"the",
"main",
"cleanup",
".",
"py",
"script",
":",
"param",
"bucket_name",
":",
"The",
"name",
"of",
"the",
"s3",
"bucket",
"to",
"clean",
".",
":",
"return",
":"
] | def _clean_s3_bucket(cleaner, bucket_name):
"""
Deletes all object dependencies in a bucket. The delete function is unique in that it deletes objects in
batches.
:param cleaner: A Cleaner object from the main cleanup.py script
:param bucket_name: The name of the s3 bucket to clean.
:return:
"""
print(' cleaning bucket {}'.format(bucket_name))
# Get the first batch
try:
response = cleaner.s3.list_object_versions(Bucket=bucket_name, MaxKeys=1000)
except ClientError as e:
print(' ERROR: Unexpected error while trying to gather s3 object versions. {}'.format(e))
code = e.response['Error']['Code']
if code != "NoSuchBucket":
cleaner.add_to_failed_resources('s3', bucket_name)
return
# Deleting objects in batches is capped at 1000 objects, therefore we can't construct the entire list beforehand
delete_verification_list = []
while True:
delete_list = []
for version in response.get('Versions', []):
delete_list.append({'Key': version['Key'], 'VersionId': version['VersionId']})
for marker in response.get('DeleteMarkers', []):
delete_list.append({'Key': marker['Key'], 'VersionId': marker['VersionId']})
delete_verification_list.extend(delete_list)
try:
cleaner.s3.delete_objects(Bucket=bucket_name, Delete={'Objects': delete_list, 'Quiet': True})
except ClientError as e:
print(' ERROR: Failed to delete objects {0} from bucket {1}. {2}'
.format(delete_list, bucket_name, exception_utils.message(e)))
code = e.response['Error']['Code']
if code != "NoSuchBucket":
cleaner.add_to_failed_resources('s3', delete_list)
next_key = response.get('NextKeyMarker', None)
if next_key:
response = cleaner.s3.list_object_versions(Bucket=bucket_name, MaxKeys=1000, KeyMarker=next_key)
else:
break
# Wait for all objects to be deleted
waiter = cleaner.s3.get_waiter('object_not_exists')
for deleting_object in delete_verification_list:
try:
waiter.wait(Bucket=bucket_name, Key=deleting_object['Key'], VersionId=deleting_object['VersionId'],
WaiterConfig={'Delay': cleaner.wait_interval, 'MaxAttempts': cleaner.wait_attempts})
print(' Finished deleting s3 object with key {}'.format(deleting_object['Key']))
except botocore.exceptions.WaiterError as e:
if cleanup_utils.WAITER_ERROR_MESSAGE in exception_utils.message(e):
print("ERROR: Timed out waiting for s3 object with key {} to delete".format(deleting_object['Key']))
else:
print("ERROR: Unexpected error occurred waiting for s3 object with key {0} to delete due to {1}"
.format(deleting_object['Key'], exception_utils.message(e)))
cleaner.add_to_failed_resources('s3', deleting_object['Key']) | [
"def",
"_clean_s3_bucket",
"(",
"cleaner",
",",
"bucket_name",
")",
":",
"print",
"(",
"' cleaning bucket {}'",
".",
"format",
"(",
"bucket_name",
")",
")",
"# Get the first batch",
"try",
":",
"response",
"=",
"cleaner",
".",
"s3",
".",
"list_object_versions",
"(",
"Bucket",
"=",
"bucket_name",
",",
"MaxKeys",
"=",
"1000",
")",
"except",
"ClientError",
"as",
"e",
":",
"print",
"(",
"' ERROR: Unexpected error while trying to gather s3 object versions. {}'",
".",
"format",
"(",
"e",
")",
")",
"code",
"=",
"e",
".",
"response",
"[",
"'Error'",
"]",
"[",
"'Code'",
"]",
"if",
"code",
"!=",
"\"NoSuchBucket\"",
":",
"cleaner",
".",
"add_to_failed_resources",
"(",
"'s3'",
",",
"bucket_name",
")",
"return",
"# Deleting objects in batches is capped at 1000 objects, therefore we can't construct the entire list beforehand",
"delete_verification_list",
"=",
"[",
"]",
"while",
"True",
":",
"delete_list",
"=",
"[",
"]",
"for",
"version",
"in",
"response",
".",
"get",
"(",
"'Versions'",
",",
"[",
"]",
")",
":",
"delete_list",
".",
"append",
"(",
"{",
"'Key'",
":",
"version",
"[",
"'Key'",
"]",
",",
"'VersionId'",
":",
"version",
"[",
"'VersionId'",
"]",
"}",
")",
"for",
"marker",
"in",
"response",
".",
"get",
"(",
"'DeleteMarkers'",
",",
"[",
"]",
")",
":",
"delete_list",
".",
"append",
"(",
"{",
"'Key'",
":",
"marker",
"[",
"'Key'",
"]",
",",
"'VersionId'",
":",
"marker",
"[",
"'VersionId'",
"]",
"}",
")",
"delete_verification_list",
".",
"extend",
"(",
"delete_list",
")",
"try",
":",
"cleaner",
".",
"s3",
".",
"delete_objects",
"(",
"Bucket",
"=",
"bucket_name",
",",
"Delete",
"=",
"{",
"'Objects'",
":",
"delete_list",
",",
"'Quiet'",
":",
"True",
"}",
")",
"except",
"ClientError",
"as",
"e",
":",
"print",
"(",
"' ERROR: Failed to delete objects {0} from bucket {1}. {2}'",
".",
"format",
"(",
"delete_list",
",",
"bucket_name",
",",
"exception_utils",
".",
"message",
"(",
"e",
")",
")",
")",
"code",
"=",
"e",
".",
"response",
"[",
"'Error'",
"]",
"[",
"'Code'",
"]",
"if",
"code",
"!=",
"\"NoSuchBucket\"",
":",
"cleaner",
".",
"add_to_failed_resources",
"(",
"'s3'",
",",
"delete_list",
")",
"next_key",
"=",
"response",
".",
"get",
"(",
"'NextKeyMarker'",
",",
"None",
")",
"if",
"next_key",
":",
"response",
"=",
"cleaner",
".",
"s3",
".",
"list_object_versions",
"(",
"Bucket",
"=",
"bucket_name",
",",
"MaxKeys",
"=",
"1000",
",",
"KeyMarker",
"=",
"next_key",
")",
"else",
":",
"break",
"# Wait for all objects to be deleted",
"waiter",
"=",
"cleaner",
".",
"s3",
".",
"get_waiter",
"(",
"'object_not_exists'",
")",
"for",
"deleting_object",
"in",
"delete_verification_list",
":",
"try",
":",
"waiter",
".",
"wait",
"(",
"Bucket",
"=",
"bucket_name",
",",
"Key",
"=",
"deleting_object",
"[",
"'Key'",
"]",
",",
"VersionId",
"=",
"deleting_object",
"[",
"'VersionId'",
"]",
",",
"WaiterConfig",
"=",
"{",
"'Delay'",
":",
"cleaner",
".",
"wait_interval",
",",
"'MaxAttempts'",
":",
"cleaner",
".",
"wait_attempts",
"}",
")",
"print",
"(",
"' Finished deleting s3 object with key {}'",
".",
"format",
"(",
"deleting_object",
"[",
"'Key'",
"]",
")",
")",
"except",
"botocore",
".",
"exceptions",
".",
"WaiterError",
"as",
"e",
":",
"if",
"cleanup_utils",
".",
"WAITER_ERROR_MESSAGE",
"in",
"exception_utils",
".",
"message",
"(",
"e",
")",
":",
"print",
"(",
"\"ERROR: Timed out waiting for s3 object with key {} to delete\"",
".",
"format",
"(",
"deleting_object",
"[",
"'Key'",
"]",
")",
")",
"else",
":",
"print",
"(",
"\"ERROR: Unexpected error occurred waiting for s3 object with key {0} to delete due to {1}\"",
".",
"format",
"(",
"deleting_object",
"[",
"'Key'",
"]",
",",
"exception_utils",
".",
"message",
"(",
"e",
")",
")",
")",
"cleaner",
".",
"add_to_failed_resources",
"(",
"'s3'",
",",
"deleting_object",
"[",
"'Key'",
"]",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/lmbr_aws/cleanup_utils/cleanup_s3_utils.py#L88-L143 | ||
RamadhanAmizudin/malware | 2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1 | GMBot/gmbot/apps/smsg_r/smsapp/remote_api.py | python | listen_status_change | (rec, data) | Signals that the phone has changed its listen status in reply to #listen_sms_start & #listen_sms_stop
data."listening status" contains either "started" or "stopped"
@param rec: Phone data record
@type rec: models.PhoneData
@param data: Phone data
@type data: dict
@rtype: None | Signals that the phone has changed its listen status in reply to #listen_sms_start & #listen_sms_stop
data."listening status" contains either "started" or "stopped" | [
"Signals",
"that",
"the",
"phone",
"has",
"changed",
"its",
"listen",
"status",
"in",
"reply",
"to",
"#listen_sms_start",
"&",
"#listen_sms_stop",
"data",
".",
"listening",
"status",
"contains",
"either",
"started",
"or",
"stopped"
] | def listen_status_change(rec, data):
"""
Signals that the phone has changed its listen status in reply to #listen_sms_start & #listen_sms_stop
data."listening status" contains either "started" or "stopped"
@param rec: Phone data record
@type rec: models.PhoneData
@param data: Phone data
@type data: dict
@rtype: None
"""
new_status = data.get('listening status')
owner = rec.owner
if new_status == "started":
rec.sms_status = models.PhoneData.SMS_LISTEN
rec.save()
elif new_status == "stopped":
rec.owner = None
rec.sms_status = models.PhoneData.SMS_INITIAL
rec.save()
msg = {
'info': "Phone {0} SMS listening {1}".format(rec, new_status),
'imei': rec.imei
}
sys_messages.add_message(rec.uniq_id, msg) | [
"def",
"listen_status_change",
"(",
"rec",
",",
"data",
")",
":",
"new_status",
"=",
"data",
".",
"get",
"(",
"'listening status'",
")",
"owner",
"=",
"rec",
".",
"owner",
"if",
"new_status",
"==",
"\"started\"",
":",
"rec",
".",
"sms_status",
"=",
"models",
".",
"PhoneData",
".",
"SMS_LISTEN",
"rec",
".",
"save",
"(",
")",
"elif",
"new_status",
"==",
"\"stopped\"",
":",
"rec",
".",
"owner",
"=",
"None",
"rec",
".",
"sms_status",
"=",
"models",
".",
"PhoneData",
".",
"SMS_INITIAL",
"rec",
".",
"save",
"(",
")",
"msg",
"=",
"{",
"'info'",
":",
"\"Phone {0} SMS listening {1}\"",
".",
"format",
"(",
"rec",
",",
"new_status",
")",
",",
"'imei'",
":",
"rec",
".",
"imei",
"}",
"sys_messages",
".",
"add_message",
"(",
"rec",
".",
"uniq_id",
",",
"msg",
")"
] | https://github.com/RamadhanAmizudin/malware/blob/2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1/GMBot/gmbot/apps/smsg_r/smsapp/remote_api.py#L288-L311 | ||
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/control_flow_ops.py | python | switch | (data, pred, dtype=None, name=None) | Forwards `data` to an output determined by `pred`.
If `pred` is false, the `data` input is forwarded to the first output.
Otherwise, the data goes to the second output.
This op handles `Tensor`s and `IndexedSlices`.
Args:
data: The tensor to be forwarded to the appropriate output.
pred: A scalar that specifies which output port will receive data.
dtype: Optional element type for the returned tensor. If missing,
the type is inferred from the type of `value`.
name: A name for this operation (optional).
Returns:
`(output_false, output_true)`: If `pred` is true, data will be forwarded
to `output_true`, otherwise it goes to `output_false`. | Forwards `data` to an output determined by `pred`. | [
"Forwards",
"data",
"to",
"an",
"output",
"determined",
"by",
"pred",
"."
] | def switch(data, pred, dtype=None, name=None):
"""Forwards `data` to an output determined by `pred`.
If `pred` is false, the `data` input is forwarded to the first output.
Otherwise, the data goes to the second output.
This op handles `Tensor`s and `IndexedSlices`.
Args:
data: The tensor to be forwarded to the appropriate output.
pred: A scalar that specifies which output port will receive data.
dtype: Optional element type for the returned tensor. If missing,
the type is inferred from the type of `value`.
name: A name for this operation (optional).
Returns:
`(output_false, output_true)`: If `pred` is true, data will be forwarded
to `output_true`, otherwise it goes to `output_false`.
"""
with ops.name_scope(name, "Switch", [data, pred]) as name:
data = ops.internal_convert_to_tensor_or_indexed_slices(
data, dtype=dtype, name="data", as_ref=True)
pred = ops.convert_to_tensor(pred, name="pred")
if isinstance(data, ops.Tensor):
return gen_control_flow_ops._switch(data, pred, name=name)
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
val, ind = data.values, data.indices
val_f, val_t = gen_control_flow_ops._switch(val, pred, name=name)
ind_f, ind_t = gen_control_flow_ops._switch(ind, pred, name="indices")
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape_f, dense_shape_t = gen_control_flow_ops._switch(
dense_shape, pred, name="dense_shape")
else:
dense_shape_f, dense_shape_t = None, None
return (ops.IndexedSlices(val_f, ind_f, dense_shape_f),
ops.IndexedSlices(val_t, ind_t, dense_shape_t))
else:
dense_shape = data.dense_shape
dense_shape_f, dense_shape_t = gen_control_flow_ops._switch(
data.dense_shape, pred, name="dense_shape")
return (sparse_tensor.SparseTensor(ind_f, val_f, dense_shape_f),
sparse_tensor.SparseTensor(ind_t, val_t, dense_shape_t)) | [
"def",
"switch",
"(",
"data",
",",
"pred",
",",
"dtype",
"=",
"None",
",",
"name",
"=",
"None",
")",
":",
"with",
"ops",
".",
"name_scope",
"(",
"name",
",",
"\"Switch\"",
",",
"[",
"data",
",",
"pred",
"]",
")",
"as",
"name",
":",
"data",
"=",
"ops",
".",
"internal_convert_to_tensor_or_indexed_slices",
"(",
"data",
",",
"dtype",
"=",
"dtype",
",",
"name",
"=",
"\"data\"",
",",
"as_ref",
"=",
"True",
")",
"pred",
"=",
"ops",
".",
"convert_to_tensor",
"(",
"pred",
",",
"name",
"=",
"\"pred\"",
")",
"if",
"isinstance",
"(",
"data",
",",
"ops",
".",
"Tensor",
")",
":",
"return",
"gen_control_flow_ops",
".",
"_switch",
"(",
"data",
",",
"pred",
",",
"name",
"=",
"name",
")",
"else",
":",
"if",
"not",
"isinstance",
"(",
"data",
",",
"(",
"ops",
".",
"IndexedSlices",
",",
"sparse_tensor",
".",
"SparseTensor",
")",
")",
":",
"raise",
"TypeError",
"(",
"\"Type %s not supported\"",
"%",
"type",
"(",
"data",
")",
")",
"val",
",",
"ind",
"=",
"data",
".",
"values",
",",
"data",
".",
"indices",
"val_f",
",",
"val_t",
"=",
"gen_control_flow_ops",
".",
"_switch",
"(",
"val",
",",
"pred",
",",
"name",
"=",
"name",
")",
"ind_f",
",",
"ind_t",
"=",
"gen_control_flow_ops",
".",
"_switch",
"(",
"ind",
",",
"pred",
",",
"name",
"=",
"\"indices\"",
")",
"if",
"isinstance",
"(",
"data",
",",
"ops",
".",
"IndexedSlices",
")",
":",
"dense_shape",
"=",
"data",
".",
"dense_shape",
"if",
"dense_shape",
"is",
"not",
"None",
":",
"dense_shape_f",
",",
"dense_shape_t",
"=",
"gen_control_flow_ops",
".",
"_switch",
"(",
"dense_shape",
",",
"pred",
",",
"name",
"=",
"\"dense_shape\"",
")",
"else",
":",
"dense_shape_f",
",",
"dense_shape_t",
"=",
"None",
",",
"None",
"return",
"(",
"ops",
".",
"IndexedSlices",
"(",
"val_f",
",",
"ind_f",
",",
"dense_shape_f",
")",
",",
"ops",
".",
"IndexedSlices",
"(",
"val_t",
",",
"ind_t",
",",
"dense_shape_t",
")",
")",
"else",
":",
"dense_shape",
"=",
"data",
".",
"dense_shape",
"dense_shape_f",
",",
"dense_shape_t",
"=",
"gen_control_flow_ops",
".",
"_switch",
"(",
"data",
".",
"dense_shape",
",",
"pred",
",",
"name",
"=",
"\"dense_shape\"",
")",
"return",
"(",
"sparse_tensor",
".",
"SparseTensor",
"(",
"ind_f",
",",
"val_f",
",",
"dense_shape_f",
")",
",",
"sparse_tensor",
".",
"SparseTensor",
"(",
"ind_t",
",",
"val_t",
",",
"dense_shape_t",
")",
")"
] | https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/ops/control_flow_ops.py#L284-L329 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/pkg_resources/__init__.py | python | WorkingSet.run_script | (self, requires, script_name) | Locate distribution for `requires` and run `script_name` script | Locate distribution for `requires` and run `script_name` script | [
"Locate",
"distribution",
"for",
"requires",
"and",
"run",
"script_name",
"script"
] | def run_script(self, requires, script_name):
"""Locate distribution for `requires` and run `script_name` script"""
ns = sys._getframe(1).f_globals
name = ns['__name__']
ns.clear()
ns['__name__'] = name
self.require(requires)[0].run_script(script_name, ns) | [
"def",
"run_script",
"(",
"self",
",",
"requires",
",",
"script_name",
")",
":",
"ns",
"=",
"sys",
".",
"_getframe",
"(",
"1",
")",
".",
"f_globals",
"name",
"=",
"ns",
"[",
"'__name__'",
"]",
"ns",
".",
"clear",
"(",
")",
"ns",
"[",
"'__name__'",
"]",
"=",
"name",
"self",
".",
"require",
"(",
"requires",
")",
"[",
"0",
"]",
".",
"run_script",
"(",
"script_name",
",",
"ns",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/pkg_resources/__init__.py#L660-L666 | ||
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/keras/_impl/keras/callbacks.py | python | CallbackList.on_batch_begin | (self, batch, logs=None) | Called right before processing a batch.
Arguments:
batch: integer, index of batch within the current epoch.
logs: dictionary of logs. | Called right before processing a batch. | [
"Called",
"right",
"before",
"processing",
"a",
"batch",
"."
] | def on_batch_begin(self, batch, logs=None):
"""Called right before processing a batch.
Arguments:
batch: integer, index of batch within the current epoch.
logs: dictionary of logs.
"""
logs = logs or {}
t_before_callbacks = time.time()
for callback in self.callbacks:
callback.on_batch_begin(batch, logs)
self._delta_ts_batch_begin.append(time.time() - t_before_callbacks)
delta_t_median = np.median(self._delta_ts_batch_begin)
if (self._delta_t_batch > 0. and
delta_t_median > 0.95 * self._delta_t_batch and delta_t_median > 0.1):
logging.warning(
'Method on_batch_begin() is slow compared '
'to the batch update (%f). Check your callbacks.' % delta_t_median)
self._t_enter_batch = time.time() | [
"def",
"on_batch_begin",
"(",
"self",
",",
"batch",
",",
"logs",
"=",
"None",
")",
":",
"logs",
"=",
"logs",
"or",
"{",
"}",
"t_before_callbacks",
"=",
"time",
".",
"time",
"(",
")",
"for",
"callback",
"in",
"self",
".",
"callbacks",
":",
"callback",
".",
"on_batch_begin",
"(",
"batch",
",",
"logs",
")",
"self",
".",
"_delta_ts_batch_begin",
".",
"append",
"(",
"time",
".",
"time",
"(",
")",
"-",
"t_before_callbacks",
")",
"delta_t_median",
"=",
"np",
".",
"median",
"(",
"self",
".",
"_delta_ts_batch_begin",
")",
"if",
"(",
"self",
".",
"_delta_t_batch",
">",
"0.",
"and",
"delta_t_median",
">",
"0.95",
"*",
"self",
".",
"_delta_t_batch",
"and",
"delta_t_median",
">",
"0.1",
")",
":",
"logging",
".",
"warning",
"(",
"'Method on_batch_begin() is slow compared '",
"'to the batch update (%f). Check your callbacks.'",
"%",
"delta_t_median",
")",
"self",
".",
"_t_enter_batch",
"=",
"time",
".",
"time",
"(",
")"
] | https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/keras/_impl/keras/callbacks.py#L97-L115 | ||
mapnik/mapnik | f3da900c355e1d15059c4a91b00203dcc9d9f0ef | scons/scons-local-4.1.0/SCons/Platform/virtualenv.py | python | ImportVirtualenv | (env) | Copies virtualenv-related environment variables from OS environment
to ``env['ENV']`` and prepends virtualenv's PATH to ``env['ENV']['PATH']``. | Copies virtualenv-related environment variables from OS environment
to ``env['ENV']`` and prepends virtualenv's PATH to ``env['ENV']['PATH']``. | [
"Copies",
"virtualenv",
"-",
"related",
"environment",
"variables",
"from",
"OS",
"environment",
"to",
"env",
"[",
"ENV",
"]",
"and",
"prepends",
"virtualenv",
"s",
"PATH",
"to",
"env",
"[",
"ENV",
"]",
"[",
"PATH",
"]",
"."
] | def ImportVirtualenv(env):
"""Copies virtualenv-related environment variables from OS environment
to ``env['ENV']`` and prepends virtualenv's PATH to ``env['ENV']['PATH']``.
"""
_inject_venv_variables(env)
_inject_venv_path(env) | [
"def",
"ImportVirtualenv",
"(",
"env",
")",
":",
"_inject_venv_variables",
"(",
"env",
")",
"_inject_venv_path",
"(",
"env",
")"
] | https://github.com/mapnik/mapnik/blob/f3da900c355e1d15059c4a91b00203dcc9d9f0ef/scons/scons-local-4.1.0/SCons/Platform/virtualenv.py#L89-L94 | ||
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/profiler/parser/memory_usage_parser.py | python | GraphMemoryParser._calc_node_memory | (self, tensor_ids) | return node_mem | Calculate the allocated memory for the node. | Calculate the allocated memory for the node. | [
"Calculate",
"the",
"allocated",
"memory",
"for",
"the",
"node",
"."
] | def _calc_node_memory(self, tensor_ids):
"""Calculate the allocated memory for the node."""
node_mem = 0
for t_id in tensor_ids:
tensor = self.tensors[t_id]
size = tensor.size
node_mem += size
return node_mem | [
"def",
"_calc_node_memory",
"(",
"self",
",",
"tensor_ids",
")",
":",
"node_mem",
"=",
"0",
"for",
"t_id",
"in",
"tensor_ids",
":",
"tensor",
"=",
"self",
".",
"tensors",
"[",
"t_id",
"]",
"size",
"=",
"tensor",
".",
"size",
"node_mem",
"+=",
"size",
"return",
"node_mem"
] | https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/profiler/parser/memory_usage_parser.py#L294-L302 | |
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqt/mantidqt/widgets/plotconfigdialog/legendtabwidget/presenter.py | python | LegendTabWidgetPresenter.hide_box_ticked | (self, enable) | Disables or enables all options related to the legend box when hide box is ticked or unticked. | Disables or enables all options related to the legend box when hide box is ticked or unticked. | [
"Disables",
"or",
"enables",
"all",
"options",
"related",
"to",
"the",
"legend",
"box",
"when",
"hide",
"box",
"is",
"ticked",
"or",
"unticked",
"."
] | def hide_box_ticked(self, enable):
"""Disables or enables all options related to the legend box when hide box is ticked or unticked."""
self.view.background_color_selector_widget.setEnabled(enable)
self.view.edge_color_selector_widget.setEnabled(enable)
self.view.transparency_slider.setEnabled(enable)
self.view.transparency_spin_box.setEnabled(enable)
self.view.advanced_options.shadow_check_box.setEnabled(enable)
self.view.advanced_options.round_edges_check_box.setEnabled(enable) | [
"def",
"hide_box_ticked",
"(",
"self",
",",
"enable",
")",
":",
"self",
".",
"view",
".",
"background_color_selector_widget",
".",
"setEnabled",
"(",
"enable",
")",
"self",
".",
"view",
".",
"edge_color_selector_widget",
".",
"setEnabled",
"(",
"enable",
")",
"self",
".",
"view",
".",
"transparency_slider",
".",
"setEnabled",
"(",
"enable",
")",
"self",
".",
"view",
".",
"transparency_spin_box",
".",
"setEnabled",
"(",
"enable",
")",
"self",
".",
"view",
".",
"advanced_options",
".",
"shadow_check_box",
".",
"setEnabled",
"(",
"enable",
")",
"self",
".",
"view",
".",
"advanced_options",
".",
"round_edges_check_box",
".",
"setEnabled",
"(",
"enable",
")"
] | https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqt/mantidqt/widgets/plotconfigdialog/legendtabwidget/presenter.py#L149-L156 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/spatial/kdtree.py | python | Rectangle.max_distance_rectangle | (self, other, p=2.) | return minkowski_distance(0, np.maximum(self.maxes-other.mins,other.maxes-self.mins),p) | Compute the maximum distance between points in the two hyperrectangles.
Parameters
----------
other : hyperrectangle
Input.
p : float, optional
Input. | Compute the maximum distance between points in the two hyperrectangles. | [
"Compute",
"the",
"maximum",
"distance",
"between",
"points",
"in",
"the",
"two",
"hyperrectangles",
"."
] | def max_distance_rectangle(self, other, p=2.):
"""
Compute the maximum distance between points in the two hyperrectangles.
Parameters
----------
other : hyperrectangle
Input.
p : float, optional
Input.
"""
return minkowski_distance(0, np.maximum(self.maxes-other.mins,other.maxes-self.mins),p) | [
"def",
"max_distance_rectangle",
"(",
"self",
",",
"other",
",",
"p",
"=",
"2.",
")",
":",
"return",
"minkowski_distance",
"(",
"0",
",",
"np",
".",
"maximum",
"(",
"self",
".",
"maxes",
"-",
"other",
".",
"mins",
",",
"other",
".",
"maxes",
"-",
"self",
".",
"mins",
")",
",",
"p",
")"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py2/scipy/spatial/kdtree.py#L161-L173 | |
SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/convert/entity_object/conversion/converter_object.py | python | ConverterObjectGroup.create_nyan_objects | (self) | Creates nyan objects from the existing raw API objects. | Creates nyan objects from the existing raw API objects. | [
"Creates",
"nyan",
"objects",
"from",
"the",
"existing",
"raw",
"API",
"objects",
"."
] | def create_nyan_objects(self):
"""
Creates nyan objects from the existing raw API objects.
"""
patch_objects = []
for raw_api_object in self.raw_api_objects.values():
raw_api_object.create_nyan_object()
if raw_api_object.is_patch():
patch_objects.append(raw_api_object)
for patch_object in patch_objects:
patch_object.link_patch_target() | [
"def",
"create_nyan_objects",
"(",
"self",
")",
":",
"patch_objects",
"=",
"[",
"]",
"for",
"raw_api_object",
"in",
"self",
".",
"raw_api_objects",
".",
"values",
"(",
")",
":",
"raw_api_object",
".",
"create_nyan_object",
"(",
")",
"if",
"raw_api_object",
".",
"is_patch",
"(",
")",
":",
"patch_objects",
".",
"append",
"(",
"raw_api_object",
")",
"for",
"patch_object",
"in",
"patch_objects",
":",
"patch_object",
".",
"link_patch_target",
"(",
")"
] | https://github.com/SFTtech/openage/blob/d6a08c53c48dc1e157807471df92197f6ca9e04d/openage/convert/entity_object/conversion/converter_object.py#L191-L203 | ||
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/protorpc/protorpc/generate_python.py | python | _write_services | (service_descriptors, out) | Write Service types.
Args:
service_descriptors: List of ServiceDescriptor instances from which to
generate services.
out: Indent writer used for generating text. | Write Service types. | [
"Write",
"Service",
"types",
"."
] | def _write_services(service_descriptors, out):
"""Write Service types.
Args:
service_descriptors: List of ServiceDescriptor instances from which to
generate services.
out: Indent writer used for generating text.
"""
for service in service_descriptors or []:
out << ''
out << ''
out << 'class %s(remote.Service):' % service.name
with out.indent():
if service.methods:
_write_methods(service.methods, out)
else:
out << ''
out << 'pass' | [
"def",
"_write_services",
"(",
"service_descriptors",
",",
"out",
")",
":",
"for",
"service",
"in",
"service_descriptors",
"or",
"[",
"]",
":",
"out",
"<<",
"''",
"out",
"<<",
"''",
"out",
"<<",
"'class %s(remote.Service):'",
"%",
"service",
".",
"name",
"with",
"out",
".",
"indent",
"(",
")",
":",
"if",
"service",
".",
"methods",
":",
"_write_methods",
"(",
"service",
".",
"methods",
",",
"out",
")",
"else",
":",
"out",
"<<",
"''",
"out",
"<<",
"'pass'"
] | https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/protorpc/protorpc/generate_python.py#L164-L182 | ||
nsnam/ns-3-dev-git | efdb2e21f45c0a87a60b47c547b68fa140a7b686 | bindings/python/rad_util.py | python | uniquify | (seq, preserve_order=False) | Return sequence with duplicate items in sequence seq removed.
The code is based on usenet post by Tim Peters.
This code is O(N) if the sequence items are hashable, O(N**2) if not.
Peter Bengtsson has a blog post with an empirical comparison of other
approaches:
http://www.peterbe.com/plog/uniqifiers-benchmark
If order is not important and the sequence items are hashable then
list(set(seq)) is readable and efficient.
If order is important and the sequence items are hashable generator
expressions can be used (in py >= 2.4) (useful for large sequences):
seen = set()
do_something(x for x in seq if x not in seen or seen.add(x))
Arguments:
seq -- sequence
preserve_order -- if not set the order will be arbitrary
Using this option will incur a speed penalty.
(default: False)
Example showing order preservation:
>>> uniquify(['a', 'aa', 'b', 'b', 'ccc', 'ccc', 'd'], preserve_order=True)
['a', 'aa', 'b', 'ccc', 'd']
Example using a sequence of un-hashable items:
>>> uniquify([['z'], ['x'], ['y'], ['z']], preserve_order=True)
[['z'], ['x'], ['y']]
The sorted output or the non-order-preserving approach should equal
that of the sorted order-preserving approach output:
>>> unordered = uniquify([3, 3, 1, 2], preserve_order=False)
>>> unordered.sort()
>>> ordered = uniquify([3, 3, 1, 2], preserve_order=True)
>>> ordered.sort()
>>> ordered
[1, 2, 3]
>>> int(ordered == unordered)
1 | Return sequence with duplicate items in sequence seq removed. | [
"Return",
"sequence",
"with",
"duplicate",
"items",
"in",
"sequence",
"seq",
"removed",
"."
] | def uniquify(seq, preserve_order=False):
"""Return sequence with duplicate items in sequence seq removed.
The code is based on usenet post by Tim Peters.
This code is O(N) if the sequence items are hashable, O(N**2) if not.
Peter Bengtsson has a blog post with an empirical comparison of other
approaches:
http://www.peterbe.com/plog/uniqifiers-benchmark
If order is not important and the sequence items are hashable then
list(set(seq)) is readable and efficient.
If order is important and the sequence items are hashable generator
expressions can be used (in py >= 2.4) (useful for large sequences):
seen = set()
do_something(x for x in seq if x not in seen or seen.add(x))
Arguments:
seq -- sequence
preserve_order -- if not set the order will be arbitrary
Using this option will incur a speed penalty.
(default: False)
Example showing order preservation:
>>> uniquify(['a', 'aa', 'b', 'b', 'ccc', 'ccc', 'd'], preserve_order=True)
['a', 'aa', 'b', 'ccc', 'd']
Example using a sequence of un-hashable items:
>>> uniquify([['z'], ['x'], ['y'], ['z']], preserve_order=True)
[['z'], ['x'], ['y']]
The sorted output or the non-order-preserving approach should equal
that of the sorted order-preserving approach output:
>>> unordered = uniquify([3, 3, 1, 2], preserve_order=False)
>>> unordered.sort()
>>> ordered = uniquify([3, 3, 1, 2], preserve_order=True)
>>> ordered.sort()
>>> ordered
[1, 2, 3]
>>> int(ordered == unordered)
1
"""
try:
# Attempt fast algorithm.
d = {}
if preserve_order:
# This is based on Dave Kirby's method (f8) noted in the post:
# http://www.peterbe.com/plog/uniqifiers-benchmark
return [x for x in seq if (x not in d) and not d.__setitem__(x, 0)]
else:
for x in seq:
d[x] = 0
return d.keys()
except TypeError:
# Have an unhashable object, so use slow algorithm.
result = []
app = result.append
for x in seq:
if x not in result:
app(x)
return result | [
"def",
"uniquify",
"(",
"seq",
",",
"preserve_order",
"=",
"False",
")",
":",
"try",
":",
"# Attempt fast algorithm.",
"d",
"=",
"{",
"}",
"if",
"preserve_order",
":",
"# This is based on Dave Kirby's method (f8) noted in the post:",
"# http://www.peterbe.com/plog/uniqifiers-benchmark",
"return",
"[",
"x",
"for",
"x",
"in",
"seq",
"if",
"(",
"x",
"not",
"in",
"d",
")",
"and",
"not",
"d",
".",
"__setitem__",
"(",
"x",
",",
"0",
")",
"]",
"else",
":",
"for",
"x",
"in",
"seq",
":",
"d",
"[",
"x",
"]",
"=",
"0",
"return",
"d",
".",
"keys",
"(",
")",
"except",
"TypeError",
":",
"# Have an unhashable object, so use slow algorithm.",
"result",
"=",
"[",
"]",
"app",
"=",
"result",
".",
"append",
"for",
"x",
"in",
"seq",
":",
"if",
"x",
"not",
"in",
"result",
":",
"app",
"(",
"x",
")",
"return",
"result"
] | https://github.com/nsnam/ns-3-dev-git/blob/efdb2e21f45c0a87a60b47c547b68fa140a7b686/bindings/python/rad_util.py#L512-L578 | ||
feelpp/feelpp | 2d547ed701cc5adb01639185b4a8eb47940367c7 | toolboxes/pyfeelpp-toolboxes/feelpp/toolboxes/multifluid/__init__.py | python | thermoelectric | ( dim=2, orderPotential=1, buildMesh=True, worldComm=core.Environment.worldCommPtr() ) | return _thermoelectrics[key]( "thermoelectric", buildMesh, worldComm ) | create a thermoelectric toolbox solver
Keyword arguments:
dim -- the dimension (default: 2)
orderPotential -- the polynomial order for the potential (default: 1)
worldComm -- the parallel communicator for the mesh (default: core.Environment::worldCommPtr()) | create a thermoelectric toolbox solver
Keyword arguments:
dim -- the dimension (default: 2)
orderPotential -- the polynomial order for the potential (default: 1)
worldComm -- the parallel communicator for the mesh (default: core.Environment::worldCommPtr()) | [
"create",
"a",
"thermoelectric",
"toolbox",
"solver",
"Keyword",
"arguments",
":",
"dim",
"--",
"the",
"dimension",
"(",
"default",
":",
"2",
")",
"orderPotential",
"--",
"the",
"polynomial",
"order",
"for",
"the",
"potential",
"(",
"default",
":",
"1",
")",
"worldComm",
"--",
"the",
"parallel",
"communicator",
"for",
"the",
"mesh",
"(",
"default",
":",
"core",
".",
"Environment",
"::",
"worldCommPtr",
"()",
")"
] | def thermoelectric( dim=2, orderPotential=1, buildMesh=True, worldComm=core.Environment.worldCommPtr() ):
"""create a thermoelectric toolbox solver
Keyword arguments:
dim -- the dimension (default: 2)
orderPotential -- the polynomial order for the potential (default: 1)
worldComm -- the parallel communicator for the mesh (default: core.Environment::worldCommPtr())
"""
key='thermoelectric('+str(dim)+','+str(orderPotential)+')'
if worldComm.isMasterRank():
print(key)
if key not in _thermoelectrics:
raise RuntimeError('Thermoelectric solver '+key+' not existing')
return _thermoelectrics[key]( "thermoelectric", buildMesh, worldComm ) | [
"def",
"thermoelectric",
"(",
"dim",
"=",
"2",
",",
"orderPotential",
"=",
"1",
",",
"buildMesh",
"=",
"True",
",",
"worldComm",
"=",
"core",
".",
"Environment",
".",
"worldCommPtr",
"(",
")",
")",
":",
"key",
"=",
"'thermoelectric('",
"+",
"str",
"(",
"dim",
")",
"+",
"','",
"+",
"str",
"(",
"orderPotential",
")",
"+",
"')'",
"if",
"worldComm",
".",
"isMasterRank",
"(",
")",
":",
"print",
"(",
"key",
")",
"if",
"key",
"not",
"in",
"_thermoelectrics",
":",
"raise",
"RuntimeError",
"(",
"'Thermoelectric solver '",
"+",
"key",
"+",
"' not existing'",
")",
"return",
"_thermoelectrics",
"[",
"key",
"]",
"(",
"\"thermoelectric\"",
",",
"buildMesh",
",",
"worldComm",
")"
] | https://github.com/feelpp/feelpp/blob/2d547ed701cc5adb01639185b4a8eb47940367c7/toolboxes/pyfeelpp-toolboxes/feelpp/toolboxes/multifluid/__init__.py#L12-L24 | |
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/gslib/gcs_json_media.py | python | DownloadCallbackConnectionClassFactory.GetConnectionClass | (self) | return DownloadCallbackConnection | Returns a connection class that overrides getresponse. | Returns a connection class that overrides getresponse. | [
"Returns",
"a",
"connection",
"class",
"that",
"overrides",
"getresponse",
"."
] | def GetConnectionClass(self):
"""Returns a connection class that overrides getresponse."""
class DownloadCallbackConnection(httplib2.HTTPSConnectionWithTimeout):
"""Connection class override for downloads."""
outer_total_size = self.total_size
outer_digesters = self.digesters
outer_progress_callback = self.progress_callback
outer_bytes_downloaded_container = self.bytes_downloaded_container
processed_initial_bytes = False
callback_processor = None
def __init__(self, *args, **kwargs):
kwargs['timeout'] = SSL_TIMEOUT
httplib2.HTTPSConnectionWithTimeout.__init__(self, *args, **kwargs)
def getresponse(self, buffering=False):
"""Wraps an HTTPResponse to perform callbacks and hashing.
In this function, self is a DownloadCallbackConnection.
Args:
buffering: Unused. This function uses a local buffer.
Returns:
HTTPResponse object with wrapped read function.
"""
orig_response = httplib.HTTPConnection.getresponse(self)
if orig_response.status not in (httplib.OK, httplib.PARTIAL_CONTENT):
return orig_response
orig_read_func = orig_response.read
def read(amt=None): # pylint: disable=invalid-name
"""Overrides HTTPConnection.getresponse.read.
This function only supports reads of TRANSFER_BUFFER_SIZE or smaller.
Args:
amt: Integer n where 0 < n <= TRANSFER_BUFFER_SIZE. This is a
keyword argument to match the read function it overrides,
but it is required.
Returns:
Data read from HTTPConnection.
"""
if not amt or amt > TRANSFER_BUFFER_SIZE:
raise BadRequestException(
'Invalid HTTP read size %s during download, expected %s.' %
(amt, TRANSFER_BUFFER_SIZE))
else:
amt = amt or TRANSFER_BUFFER_SIZE
if not self.processed_initial_bytes:
self.processed_initial_bytes = True
if self.outer_progress_callback:
self.callback_processor = ProgressCallbackWithBackoff(
self.outer_total_size, self.outer_progress_callback)
self.callback_processor.Progress(
self.outer_bytes_downloaded_container.bytes_transferred)
data = orig_read_func(amt)
read_length = len(data)
if self.callback_processor:
self.callback_processor.Progress(read_length)
if self.outer_digesters:
for alg in self.outer_digesters:
self.outer_digesters[alg].update(data)
return data
orig_response.read = read
return orig_response
return DownloadCallbackConnection | [
"def",
"GetConnectionClass",
"(",
"self",
")",
":",
"class",
"DownloadCallbackConnection",
"(",
"httplib2",
".",
"HTTPSConnectionWithTimeout",
")",
":",
"\"\"\"Connection class override for downloads.\"\"\"",
"outer_total_size",
"=",
"self",
".",
"total_size",
"outer_digesters",
"=",
"self",
".",
"digesters",
"outer_progress_callback",
"=",
"self",
".",
"progress_callback",
"outer_bytes_downloaded_container",
"=",
"self",
".",
"bytes_downloaded_container",
"processed_initial_bytes",
"=",
"False",
"callback_processor",
"=",
"None",
"def",
"__init__",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"kwargs",
"[",
"'timeout'",
"]",
"=",
"SSL_TIMEOUT",
"httplib2",
".",
"HTTPSConnectionWithTimeout",
".",
"__init__",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"def",
"getresponse",
"(",
"self",
",",
"buffering",
"=",
"False",
")",
":",
"\"\"\"Wraps an HTTPResponse to perform callbacks and hashing.\n\n In this function, self is a DownloadCallbackConnection.\n\n Args:\n buffering: Unused. This function uses a local buffer.\n\n Returns:\n HTTPResponse object with wrapped read function.\n \"\"\"",
"orig_response",
"=",
"httplib",
".",
"HTTPConnection",
".",
"getresponse",
"(",
"self",
")",
"if",
"orig_response",
".",
"status",
"not",
"in",
"(",
"httplib",
".",
"OK",
",",
"httplib",
".",
"PARTIAL_CONTENT",
")",
":",
"return",
"orig_response",
"orig_read_func",
"=",
"orig_response",
".",
"read",
"def",
"read",
"(",
"amt",
"=",
"None",
")",
":",
"# pylint: disable=invalid-name",
"\"\"\"Overrides HTTPConnection.getresponse.read.\n\n This function only supports reads of TRANSFER_BUFFER_SIZE or smaller.\n\n Args:\n amt: Integer n where 0 < n <= TRANSFER_BUFFER_SIZE. This is a\n keyword argument to match the read function it overrides,\n but it is required.\n\n Returns:\n Data read from HTTPConnection.\n \"\"\"",
"if",
"not",
"amt",
"or",
"amt",
">",
"TRANSFER_BUFFER_SIZE",
":",
"raise",
"BadRequestException",
"(",
"'Invalid HTTP read size %s during download, expected %s.'",
"%",
"(",
"amt",
",",
"TRANSFER_BUFFER_SIZE",
")",
")",
"else",
":",
"amt",
"=",
"amt",
"or",
"TRANSFER_BUFFER_SIZE",
"if",
"not",
"self",
".",
"processed_initial_bytes",
":",
"self",
".",
"processed_initial_bytes",
"=",
"True",
"if",
"self",
".",
"outer_progress_callback",
":",
"self",
".",
"callback_processor",
"=",
"ProgressCallbackWithBackoff",
"(",
"self",
".",
"outer_total_size",
",",
"self",
".",
"outer_progress_callback",
")",
"self",
".",
"callback_processor",
".",
"Progress",
"(",
"self",
".",
"outer_bytes_downloaded_container",
".",
"bytes_transferred",
")",
"data",
"=",
"orig_read_func",
"(",
"amt",
")",
"read_length",
"=",
"len",
"(",
"data",
")",
"if",
"self",
".",
"callback_processor",
":",
"self",
".",
"callback_processor",
".",
"Progress",
"(",
"read_length",
")",
"if",
"self",
".",
"outer_digesters",
":",
"for",
"alg",
"in",
"self",
".",
"outer_digesters",
":",
"self",
".",
"outer_digesters",
"[",
"alg",
"]",
".",
"update",
"(",
"data",
")",
"return",
"data",
"orig_response",
".",
"read",
"=",
"read",
"return",
"orig_response",
"return",
"DownloadCallbackConnection"
] | https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/gslib/gcs_json_media.py#L179-L250 | |
microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPMT_TK_AUTH.__init__ | (self, tag = 0, hierarchy = TPM_HANDLE(), digest = None) | This ticket is produced by TPM2_PolicySigned() and
TPM2_PolicySecret() when the authorization has an expiration time. If
nonceTPM was provided in the policy command, the ticket is computed by
Attributes:
tag (TPM_ST): Ticket structure tag
hierarchy (TPM_HANDLE): The hierarchy of the object used to produce
the ticket
digest (bytes): This shall be the HMAC produced using a proof value
of hierarchy. | This ticket is produced by TPM2_PolicySigned() and
TPM2_PolicySecret() when the authorization has an expiration time. If
nonceTPM was provided in the policy command, the ticket is computed by | [
"This",
"ticket",
"is",
"produced",
"by",
"TPM2_PolicySigned",
"()",
"and",
"TPM2_PolicySecret",
"()",
"when",
"the",
"authorization",
"has",
"an",
"expiration",
"time",
".",
"If",
"nonceTPM",
"was",
"provided",
"in",
"the",
"policy",
"command",
"the",
"ticket",
"is",
"computed",
"by"
] | def __init__(self, tag = 0, hierarchy = TPM_HANDLE(), digest = None):
""" This ticket is produced by TPM2_PolicySigned() and
TPM2_PolicySecret() when the authorization has an expiration time. If
nonceTPM was provided in the policy command, the ticket is computed by
Attributes:
tag (TPM_ST): Ticket structure tag
hierarchy (TPM_HANDLE): The hierarchy of the object used to produce
the ticket
digest (bytes): This shall be the HMAC produced using a proof value
of hierarchy.
"""
self.tag = tag
self.hierarchy = hierarchy
self.digest = digest | [
"def",
"__init__",
"(",
"self",
",",
"tag",
"=",
"0",
",",
"hierarchy",
"=",
"TPM_HANDLE",
"(",
")",
",",
"digest",
"=",
"None",
")",
":",
"self",
".",
"tag",
"=",
"tag",
"self",
".",
"hierarchy",
"=",
"hierarchy",
"self",
".",
"digest",
"=",
"digest"
] | https://github.com/microsoft/TSS.MSR/blob/0f2516fca2cd9929c31d5450e39301c9bde43688/TSS.Py/src/TpmTypes.py#L4171-L4185 | ||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/lib/arraysetops.py | python | isin | (element, test_elements, assume_unique=False, invert=False) | return in1d(element, test_elements, assume_unique=assume_unique,
invert=invert).reshape(element.shape) | Calculates `element in test_elements`, broadcasting over `element` only.
Returns a boolean array of the same shape as `element` that is True
where an element of `element` is in `test_elements` and False otherwise.
Parameters
----------
element : array_like
Input array.
test_elements : array_like
The values against which to test each value of `element`.
This argument is flattened if it is an array or array_like.
See notes for behavior with non-array-like parameters.
assume_unique : bool, optional
If True, the input arrays are both assumed to be unique, which
can speed up the calculation. Default is False.
invert : bool, optional
If True, the values in the returned array are inverted, as if
calculating `element not in test_elements`. Default is False.
``np.isin(a, b, invert=True)`` is equivalent to (but faster
than) ``np.invert(np.isin(a, b))``.
Returns
-------
isin : ndarray, bool
Has the same shape as `element`. The values `element[isin]`
are in `test_elements`.
See Also
--------
in1d : Flattened version of this function.
numpy.lib.arraysetops : Module with a number of other functions for
performing set operations on arrays.
Notes
-----
`isin` is an element-wise function version of the python keyword `in`.
``isin(a, b)`` is roughly equivalent to
``np.array([item in b for item in a])`` if `a` and `b` are 1-D sequences.
`element` and `test_elements` are converted to arrays if they are not
already. If `test_elements` is a set (or other non-sequence collection)
it will be converted to an object array with one element, rather than an
array of the values contained in `test_elements`. This is a consequence
of the `array` constructor's way of handling non-sequence collections.
Converting the set to a list usually gives the desired behavior.
.. versionadded:: 1.13.0
Examples
--------
>>> element = 2*np.arange(4).reshape((2, 2))
>>> element
array([[0, 2],
[4, 6]])
>>> test_elements = [1, 2, 4, 8]
>>> mask = np.isin(element, test_elements)
>>> mask
array([[False, True],
[ True, False]])
>>> element[mask]
array([2, 4])
The indices of the matched values can be obtained with `nonzero`:
>>> np.nonzero(mask)
(array([0, 1]), array([1, 0]))
The test can also be inverted:
>>> mask = np.isin(element, test_elements, invert=True)
>>> mask
array([[ True, False],
[False, True]])
>>> element[mask]
array([0, 6])
Because of how `array` handles sets, the following does not
work as expected:
>>> test_set = {1, 2, 4, 8}
>>> np.isin(element, test_set)
array([[False, False],
[False, False]])
Casting the set to a list gives the expected result:
>>> np.isin(element, list(test_set))
array([[False, True],
[ True, False]]) | Calculates `element in test_elements`, broadcasting over `element` only.
Returns a boolean array of the same shape as `element` that is True
where an element of `element` is in `test_elements` and False otherwise. | [
"Calculates",
"element",
"in",
"test_elements",
"broadcasting",
"over",
"element",
"only",
".",
"Returns",
"a",
"boolean",
"array",
"of",
"the",
"same",
"shape",
"as",
"element",
"that",
"is",
"True",
"where",
"an",
"element",
"of",
"element",
"is",
"in",
"test_elements",
"and",
"False",
"otherwise",
"."
] | def isin(element, test_elements, assume_unique=False, invert=False):
"""
Calculates `element in test_elements`, broadcasting over `element` only.
Returns a boolean array of the same shape as `element` that is True
where an element of `element` is in `test_elements` and False otherwise.
Parameters
----------
element : array_like
Input array.
test_elements : array_like
The values against which to test each value of `element`.
This argument is flattened if it is an array or array_like.
See notes for behavior with non-array-like parameters.
assume_unique : bool, optional
If True, the input arrays are both assumed to be unique, which
can speed up the calculation. Default is False.
invert : bool, optional
If True, the values in the returned array are inverted, as if
calculating `element not in test_elements`. Default is False.
``np.isin(a, b, invert=True)`` is equivalent to (but faster
than) ``np.invert(np.isin(a, b))``.
Returns
-------
isin : ndarray, bool
Has the same shape as `element`. The values `element[isin]`
are in `test_elements`.
See Also
--------
in1d : Flattened version of this function.
numpy.lib.arraysetops : Module with a number of other functions for
performing set operations on arrays.
Notes
-----
`isin` is an element-wise function version of the python keyword `in`.
``isin(a, b)`` is roughly equivalent to
``np.array([item in b for item in a])`` if `a` and `b` are 1-D sequences.
`element` and `test_elements` are converted to arrays if they are not
already. If `test_elements` is a set (or other non-sequence collection)
it will be converted to an object array with one element, rather than an
array of the values contained in `test_elements`. This is a consequence
of the `array` constructor's way of handling non-sequence collections.
Converting the set to a list usually gives the desired behavior.
.. versionadded:: 1.13.0
Examples
--------
>>> element = 2*np.arange(4).reshape((2, 2))
>>> element
array([[0, 2],
[4, 6]])
>>> test_elements = [1, 2, 4, 8]
>>> mask = np.isin(element, test_elements)
>>> mask
array([[False, True],
[ True, False]])
>>> element[mask]
array([2, 4])
The indices of the matched values can be obtained with `nonzero`:
>>> np.nonzero(mask)
(array([0, 1]), array([1, 0]))
The test can also be inverted:
>>> mask = np.isin(element, test_elements, invert=True)
>>> mask
array([[ True, False],
[False, True]])
>>> element[mask]
array([0, 6])
Because of how `array` handles sets, the following does not
work as expected:
>>> test_set = {1, 2, 4, 8}
>>> np.isin(element, test_set)
array([[False, False],
[False, False]])
Casting the set to a list gives the expected result:
>>> np.isin(element, list(test_set))
array([[False, True],
[ True, False]])
"""
element = np.asarray(element)
return in1d(element, test_elements, assume_unique=assume_unique,
invert=invert).reshape(element.shape) | [
"def",
"isin",
"(",
"element",
",",
"test_elements",
",",
"assume_unique",
"=",
"False",
",",
"invert",
"=",
"False",
")",
":",
"element",
"=",
"np",
".",
"asarray",
"(",
"element",
")",
"return",
"in1d",
"(",
"element",
",",
"test_elements",
",",
"assume_unique",
"=",
"assume_unique",
",",
"invert",
"=",
"invert",
")",
".",
"reshape",
"(",
"element",
".",
"shape",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/lib/arraysetops.py#L602-L697 | |
thalium/icebox | 99d147d5b9269222225443ce171b4fd46d8985d4 | third_party/benchmark/tools/gbench/report.py | python | intersect | (list1, list2) | return [x for x in list1 if x in list2] | Given two lists, get a new list consisting of the elements only contained
in *both of the input lists*, while preserving the ordering. | Given two lists, get a new list consisting of the elements only contained
in *both of the input lists*, while preserving the ordering. | [
"Given",
"two",
"lists",
"get",
"a",
"new",
"list",
"consisting",
"of",
"the",
"elements",
"only",
"contained",
"in",
"*",
"both",
"of",
"the",
"input",
"lists",
"*",
"while",
"preserving",
"the",
"ordering",
"."
] | def intersect(list1, list2):
"""
Given two lists, get a new list consisting of the elements only contained
in *both of the input lists*, while preserving the ordering.
"""
return [x for x in list1 if x in list2] | [
"def",
"intersect",
"(",
"list1",
",",
"list2",
")",
":",
"return",
"[",
"x",
"for",
"x",
"in",
"list1",
"if",
"x",
"in",
"list2",
"]"
] | https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/benchmark/tools/gbench/report.py#L109-L114 | |
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | tools/json_schema_compiler/model.py | python | _GetModelHierarchy | (entity) | return hierarchy | Returns the hierarchy of the given model entity. | Returns the hierarchy of the given model entity. | [
"Returns",
"the",
"hierarchy",
"of",
"the",
"given",
"model",
"entity",
"."
] | def _GetModelHierarchy(entity):
"""Returns the hierarchy of the given model entity."""
hierarchy = []
while entity is not None:
hierarchy.append(getattr(entity, 'name', repr(entity)))
if isinstance(entity, Namespace):
hierarchy.insert(0, ' in %s' % entity.source_file)
entity = getattr(entity, 'parent', None)
hierarchy.reverse()
return hierarchy | [
"def",
"_GetModelHierarchy",
"(",
"entity",
")",
":",
"hierarchy",
"=",
"[",
"]",
"while",
"entity",
"is",
"not",
"None",
":",
"hierarchy",
".",
"append",
"(",
"getattr",
"(",
"entity",
",",
"'name'",
",",
"repr",
"(",
"entity",
")",
")",
")",
"if",
"isinstance",
"(",
"entity",
",",
"Namespace",
")",
":",
"hierarchy",
".",
"insert",
"(",
"0",
",",
"' in %s'",
"%",
"entity",
".",
"source_file",
")",
"entity",
"=",
"getattr",
"(",
"entity",
",",
"'parent'",
",",
"None",
")",
"hierarchy",
".",
"reverse",
"(",
")",
"return",
"hierarchy"
] | https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/json_schema_compiler/model.py#L531-L540 | |
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/distributions/bijector_impl.py | python | Bijector.forward_min_event_ndims | (self) | return self._forward_min_event_ndims | Returns the minimal number of dimensions bijector.forward operates on. | Returns the minimal number of dimensions bijector.forward operates on. | [
"Returns",
"the",
"minimal",
"number",
"of",
"dimensions",
"bijector",
".",
"forward",
"operates",
"on",
"."
] | def forward_min_event_ndims(self):
"""Returns the minimal number of dimensions bijector.forward operates on."""
return self._forward_min_event_ndims | [
"def",
"forward_min_event_ndims",
"(",
"self",
")",
":",
"return",
"self",
".",
"_forward_min_event_ndims"
] | https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/distributions/bijector_impl.py#L590-L592 | |
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_windows.py | python | TaskBarIcon.__init__ | (self, *args, **kwargs) | __init__(self, int iconType=TBI_DEFAULT_TYPE) -> TaskBarIcon | __init__(self, int iconType=TBI_DEFAULT_TYPE) -> TaskBarIcon | [
"__init__",
"(",
"self",
"int",
"iconType",
"=",
"TBI_DEFAULT_TYPE",
")",
"-",
">",
"TaskBarIcon"
] | def __init__(self, *args, **kwargs):
"""__init__(self, int iconType=TBI_DEFAULT_TYPE) -> TaskBarIcon"""
_windows_.TaskBarIcon_swiginit(self,_windows_.new_TaskBarIcon(*args, **kwargs))
self._setOORInfo(self);TaskBarIcon._setCallbackInfo(self, self, TaskBarIcon) | [
"def",
"__init__",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"_windows_",
".",
"TaskBarIcon_swiginit",
"(",
"self",
",",
"_windows_",
".",
"new_TaskBarIcon",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
")",
"self",
".",
"_setOORInfo",
"(",
"self",
")",
"TaskBarIcon",
".",
"_setCallbackInfo",
"(",
"self",
",",
"self",
",",
"TaskBarIcon",
")"
] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_windows.py#L2810-L2813 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/prompt-toolkit/py2/prompt_toolkit/document.py | python | Document.get_end_of_line_position | (self) | return len(self.current_line_after_cursor) | Relative position for the end of this line. | Relative position for the end of this line. | [
"Relative",
"position",
"for",
"the",
"end",
"of",
"this",
"line",
"."
] | def get_end_of_line_position(self):
""" Relative position for the end of this line. """
return len(self.current_line_after_cursor) | [
"def",
"get_end_of_line_position",
"(",
"self",
")",
":",
"return",
"len",
"(",
"self",
".",
"current_line_after_cursor",
")"
] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/prompt-toolkit/py2/prompt_toolkit/document.py#L741-L743 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/share/doc/python3.7/examples/Tools/iobench/iobench.py | python | read_seek_blockwise | (f) | alternate read & seek 1000 units | alternate read & seek 1000 units | [
"alternate",
"read",
"&",
"seek",
"1000",
"units"
] | def read_seek_blockwise(f):
""" alternate read & seek 1000 units """
f.seek(0)
while f.read(1000):
f.seek(1000, 1) | [
"def",
"read_seek_blockwise",
"(",
"f",
")",
":",
"f",
".",
"seek",
"(",
"0",
")",
"while",
"f",
".",
"read",
"(",
"1000",
")",
":",
"f",
".",
"seek",
"(",
"1000",
",",
"1",
")"
] | https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/share/doc/python3.7/examples/Tools/iobench/iobench.py#L129-L133 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.