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FSecureLABS/Jandroid | e31d0dab58a2bfd6ed8e0a387172b8bd7c893436 | libs/platform-tools/platform-tools_linux/systrace/catapult/systrace/systrace/tracing_agents/__init__.py | python | TracingAgent.SupportsExplicitClockSync | (self) | Find out if this agent supports recording of clock sync markers.
Returns:
Boolean value indicating whether this agent supports recording
of clock sync markers. | Find out if this agent supports recording of clock sync markers. | [
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"if",
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"agent",
"supports",
"recording",
"of",
"clock",
"sync",
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] | def SupportsExplicitClockSync(self):
'''Find out if this agent supports recording of clock sync markers.
Returns:
Boolean value indicating whether this agent supports recording
of clock sync markers.
'''
raise NotImplementedError | [
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gammapy/gammapy | 735b25cd5bbed35e2004d633621896dcd5295e8b | gammapy/maps/wcs/geom.py | python | WcsGeom.axes_names | (self) | return ["lon", "lat"] + self.axes.names | All axes names | All axes names | [
"All",
"axes",
"names"
] | def axes_names(self):
"""All axes names"""
return ["lon", "lat"] + self.axes.names | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/physics/quantum/spin.py | python | Rotation._represent_default_basis | (self, **options) | return self._represent_JzOp(None, **options) | [] | def _represent_default_basis(self, **options):
return self._represent_JzOp(None, **options) | [
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dot-osk/monitor_ctrl | 5e5a6d151478e5dd5b0361ff401a96b609b98c84 | monitor_ctrl.py | python | parse_arg | () | Parse command line arguments.
:return: | Parse command line arguments.
:return: | [
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"line",
"arguments",
".",
":",
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] | def parse_arg():
"""
Parse command line arguments.
:return:
"""
parser = argparse.ArgumentParser(description='通过DDC/CI设置显示器参数.')
parser.add_argument('-m', action='store', type=str, default='*', help='指定要应用到的Monitor Model，'
'不指定则应用到所有可操作的显示器')
parser.add_argument('-s', action='store', type=str, help='property1=value1{}property2="value 2" 应用多项设置'
.format(ARG_SPLITTER))
parser.add_argument('-r', action='store_true', default=False, help='将显示器恢复出厂设置')
parser.add_argument('-t', action='store_true', default=False, help='对输入执行自动调整（仅VGA输入需要）')
parser.add_argument('-c', action='store_true', default=False, help='不启用GUI')
parser.add_argument('-l', action='store_true', help='显示可操作的显示器model')
parser.add_argument('-v', action='store_true', help='Verbose logging')
opts = parser.parse_args()
global APP_OPTIONS
APP_OPTIONS['apply_to_model'] = opts.m
APP_OPTIONS['list_monitors'] = opts.l
APP_OPTIONS['setting_value_string'] = opts.s
APP_OPTIONS['restore_factory'] = opts.r
APP_OPTIONS['perform_auto_setup'] = opts.t
# if specified -c argument or tkinter not imported
if opts.c or (not TK_IMPORTED):
APP_OPTIONS['console'] = True
# log to console
APP_OPTIONS['log_file'] = None
else:
APP_OPTIONS['console'] = False
# log to file
APP_OPTIONS['log_file'] = DEFAULT_LOGFILE_PATH
# logging level
if opts.v:
APP_OPTIONS['log_level'] = logging.DEBUG
else:
APP_OPTIONS['log_level'] = logging.INFO | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/crypto/mq/rijndael_gf.py | python | RijndaelGF.key_length | (self) | return self._Nk | r"""
Return the key length of this instantiation of Rijndael-GF.
EXAMPLES::
sage: from sage.crypto.mq.rijndael_gf import RijndaelGF
sage: rgf = RijndaelGF(4, 8)
sage: rgf.key_length()
8 | r"""
Return the key length of this instantiation of Rijndael-GF. | [
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] | def key_length(self):
r"""
Return the key length of this instantiation of Rijndael-GF.
EXAMPLES::
sage: from sage.crypto.mq.rijndael_gf import RijndaelGF
sage: rgf = RijndaelGF(4, 8)
sage: rgf.key_length()
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"""
return self._Nk | [
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apache/tvm | 6eb4ed813ebcdcd9558f0906a1870db8302ff1e0 | python/tvm/script/tir/scope_handler.py | python | ForScopeHandler.create_loop_info | (
self,
begin: PrimExpr,
end: PrimExpr,
kind: ForKind,
thread_binding: Optional[str] = None,
annotations: Optional[Mapping[str, Object]] = None,
) | Helper function for creating For in TVM Script parser.
Parameters
----------
begin : PrimExpr
The beginning value.
end : PrimExpr
The endding value.
kind : ForKind
The type of the for.
thread_binding: Optional[str]
The thread this loop binds to.
annotations : Optional[Mapping[str, Object]]
Additional annotation hints.
span : Optional[Span]
The location of this for in the source code.
Returns
-------
for : For
The constructed For. | Helper function for creating For in TVM Script parser. | [
"Helper",
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"parser",
"."
] | def create_loop_info(
self,
begin: PrimExpr,
end: PrimExpr,
kind: ForKind,
thread_binding: Optional[str] = None,
annotations: Optional[Mapping[str, Object]] = None,
) -> None:
"""
Helper function for creating For in TVM Script parser.
Parameters
----------
begin : PrimExpr
The beginning value.
end : PrimExpr
The endding value.
kind : ForKind
The type of the for.
thread_binding: Optional[str]
The thread this loop binds to.
annotations : Optional[Mapping[str, Object]]
Additional annotation hints.
span : Optional[Span]
The location of this for in the source code.
Returns
-------
for : For
The constructed For.
"""
assert self.context and self.node, "call 'exit_scope' before 'enter_scope'"
extent = end if begin == 0 else self.context.analyzer.simplify(end - begin)
self.annotations = annotations
self.loop_info.append(LoopInfo(begin, extent, kind, thread_binding, self.annotations)) | [
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OpenCobolIDE/OpenCobolIDE | c78d0d335378e5fe0a5e74f53c19b68b55e85388 | open_cobol_ide/extlibs/pyqode/core/modes/caret_line_highlight.py | python | CaretLineHighlighterMode.background | (self) | Background color of the caret line. Default is to use a color slightly
darker/lighter than the background color. You can override the
automatic color by setting up this property | Background color of the caret line. Default is to use a color slightly
darker/lighter than the background color. You can override the
automatic color by setting up this property | [
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"""
Background color of the caret line. Default is to use a color slightly
darker/lighter than the background color. You can override the
automatic color by setting up this property
"""
if self._color or not self.editor:
return self._color
else:
return drift_color(self.editor.background, 110) | [
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Komodo/KomodoEdit | 61edab75dce2bdb03943b387b0608ea36f548e8e | src/udl/luddite.py | python | Shell.do_lexhtml | (self, subcmd, opts, lang, path) | ${cmd_name}: lex the given file to styled HTML (for debugging)
${cmd_usage}
${cmd_option_list} | ${cmd_name}: lex the given file to styled HTML (for debugging) | [
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] | def do_lexhtml(self, subcmd, opts, lang, path):
"""${cmd_name}: lex the given file to styled HTML (for debugging)
${cmd_usage}
${cmd_option_list}
"""
from ludditelib.debug import lex_to_html
content = open(path, 'r').read()
html = lex_to_html(content, lang)
if opts.output == '-':
output_path = None
output_file = sys.stdout
else:
if opts.output:
output_path = opts.output
else:
output_path = path+".html"
if exists(output_path):
os.remove(output_path)
output_file = open(output_path, 'w')
if output_file:
output_file.write(html)
if output_path:
output_file.close()
if opts.browse:
if not output_path:
raise LudditeError("cannot open in browser if stdout used "
"for output")
import webbrowser
url = _url_from_local_path(output_path)
webbrowser.open_new(url) | [
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SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/bdf/cards/aero/aero.py | python | CAERO2._update_field_helper | (self, n, value) | Updates complicated parameters on the CAERO2 card
Parameters
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n : int
The field number to update
value : int, float, None
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"""
Updates complicated parameters on the CAERO2 card
Parameters
----------
n : int
The field number to update
value : int, float, None
The value for the appropriate field
"""
if n == 9:
self.p1[0] = value
elif n == 10:
self.p1[1] = value
elif n == 11:
self.p1[2] = value
else:
raise KeyError('Field %r=%r is an invalid CAERO2 entry.' % (n, value)) | [
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arthurdejong/python-stdnum | 02dec52602ae0709b940b781fc1fcebfde7340b7 | update/isbn.py | python | ranges | (group) | Provide the ranges for the group. | Provide the ranges for the group. | [
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"""Provide the ranges for the group."""
for rule in group.findall('./Rules/Rule'):
length = int(rule.find('./Length').text.strip())
if length:
yield '-'.join(
x[:length]
for x in rule.find('./Range').text.strip().split('-')) | [
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Tencent/QT4A | cc99ce12bd10f864c95b7bf0675fd1b757bce4bb | qt4a/andrcontrols.py | python | ListItem.__getattr__ | (self, attr) | return getattr(self._view, attr) | 委托self._view实现 | 委托self._view实现 | [
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'''委托self._view实现
'''
return getattr(self._view, attr) | [
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nerdvegas/rez | d392c65bf63b4bca8106f938cec49144ba54e770 | src/rez/utils/memcached.py | python | Client.flush | (self, hard=False) | Drop existing entries from the cache.
Args:
hard (bool): If True, all current entries are flushed from the
server(s), which affects all users. If False, only the local
process is affected. | Drop existing entries from the cache. | [
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"""Drop existing entries from the cache.
Args:
hard (bool): If True, all current entries are flushed from the
server(s), which affects all users. If False, only the local
process is affected.
"""
if not self.servers:
return
if hard:
self.client.flush_all()
self.reset_stats()
else:
from uuid import uuid4
tag = uuid4().hex
if self.debug:
tag = "flushed" + tag
self.current = tag | [
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out0fmemory/GoAgent-Always-Available | c4254984fea633ce3d1893fe5901debd9f22c2a9 | server/lib/six/__init__.py | python | _SixMetaPathImporter.get_code | (self, fullname) | return None | Return None
Required, if is_package is implemented | Return None | [
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] | def get_code(self, fullname):
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Required, if is_package is implemented"""
self.__get_module(fullname) # eventually raises ImportError
return None | [
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Jenyay/outwiker | 50530cf7b3f71480bb075b2829bc0669773b835b | plugins/updatenotifier/updatenotifier/updatecontroller.py | python | UpdateController.__init__ | (self, application, plugin) | application - instance of the ApplicationParams class.
pluginPath - path to UpdateNotifier plugin. | application - instance of the ApplicationParams class.
pluginPath - path to UpdateNotifier plugin. | [
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'''
application - instance of the ApplicationParams class.
pluginPath - path to UpdateNotifier plugin.
'''
global _
_ = get_()
join = os.path.join
self._application = application
self._plugin = plugin
self._config = UpdatesConfig(self._application.config)
self._dataPath = join(plugin.pluginPath, u'data')
self._updateTemplatePath = join(self._dataPath, u'update.html')
self.__deletedPlugins = {}
self.vl = VersionList() # to load app info from the internet.
# Special string id for stable and unstable OutWiker URL
self._OUTWIKER_STABLE_KEY = u'OUTWIKER_STABLE'
self._OUTWIKER_UNSTABLE_KEY = u'OUTWIKER_UNSTABLE'
# Dictionary. Key - plugin name or special string id,
# Value - URL to XML file with versions information.
self._updateUrls = {}
self._updateUrls[self._OUTWIKER_STABLE_KEY] = u'https://jenyay.net/uploads/Soft/Outwiker/versions.xml'
self._updateUrls[self._OUTWIKER_UNSTABLE_KEY] = u'https://jenyay.net/uploads/Outwiker/Unstable/versions.xml'
# update dialog instance
self._dialog = None
# The thread to check updates in the silence mode (after program start)
self._silenceThread = None
if self._application.mainWindow is not None:
self._application.mainWindow.Bind(
EVT_UPDATE_VERSIONS,
handler=self._onVersionUpdate) | [
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NVlabs/Deep_Object_Pose | c50e5fcd3741802484bf59c0f7bcf507b918e417 | scripts/train2/inference/cuboid.py | python | Cuboid3d.get_vertex | (self, vertex_type) | return self._vertices[vertex_type] | Returns the location of a vertex.
Args:
vertex_type: enum of type CuboidVertexType
Returns:
Numpy array(3) - Location of the vertex type in the cuboid | Returns the location of a vertex. | [
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"""Returns the location of a vertex.
Args:
vertex_type: enum of type CuboidVertexType
Returns:
Numpy array(3) - Location of the vertex type in the cuboid
"""
return self._vertices[vertex_type] | [
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minio/minio-py | b3ba3bf99fe6b9ff2b28855550d6ab5345c134e3 | minio/credentials/providers.py | python | WebIdentityClientGrantsProvider.retrieve | (self) | return self._credentials | Retrieve credentials. | Retrieve credentials. | [
"Retrieve",
"credentials",
"."
] | def retrieve(self):
"""Retrieve credentials."""
if self._credentials and not self._credentials.is_expired():
return self._credentials
jwt = self._jwt_provider_func()
query_params = {"Version": "2011-06-15"}
duration_seconds = self._get_duration_seconds(
int(jwt.get("expires_in", "0")),
)
if duration_seconds:
query_params["DurationSeconds"] = str(duration_seconds)
if self._policy:
query_params["Policy"] = self._policy
if self._is_web_identity():
query_params["Action"] = "AssumeRoleWithWebIdentity"
query_params["WebIdentityToken"] = jwt.get("access_token")
if self._role_arn:
query_params["RoleArn"] = self._role_arn
query_params["RoleSessionName"] = (
self._role_session_name
if self._role_session_name
else str(time.time()).replace(".", "")
)
else:
query_params["Action"] = "AssumeRoleWithClientGrants"
query_params["Token"] = jwt.get("access_token")
url = self._sts_endpoint + "?" + urlencode(query_params)
res = _urlopen(self._http_client, "POST", url)
self._credentials = _parse_credentials(
res.data.decode(),
(
"AssumeRoleWithWebIdentityResult"
if self._is_web_identity()
else "AssumeRoleWithClientGrantsResult"
),
)
return self._credentials | [
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XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | python3.8.2/Lib/mailbox.py | python | Babyl.remove | (self, key) | Remove the keyed message; raise KeyError if it doesn't exist. | Remove the keyed message; raise KeyError if it doesn't exist. | [
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] | def remove(self, key):
"""Remove the keyed message; raise KeyError if it doesn't exist."""
_singlefileMailbox.remove(self, key)
if key in self._labels:
del self._labels[key] | [
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pympler/pympler | 8019a883eec547d91ecda6ba12669d4f4504c625 | pympler/asizeof.py | python | _len_int | (obj) | return n | Length of multi-precision int (aka long) in digits. | Length of multi-precision int (aka long) in digits. | [
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] | def _len_int(obj):
'''Length of multi-precision int (aka long) in digits.
'''
if obj:
n, i = 1, abs(obj)
if i > _digitmax:
# no log(x[, base]) in Python 2.2
n += int(log(i) * _digitlog)
else: # zero
n = 0
return n | [
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cagbal/ros_people_object_detection_tensorflow | 982ffd4a54b8059638f5cd4aa167299c7fc9e61f | src/object_detection/core/box_predictor.py | python | RfcnBoxPredictor.num_classes | (self) | return self._num_classes | [] | def num_classes(self):
return self._num_classes | [
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wmayner/pyphi | 299fccd4a8152dcfa4bb989d7d739e245343b0a5 | pyphi/models/mechanism.py | python | Concept.to_json | (self) | return {attr: getattr(self, attr) for attr in _concept_attributes + ["time"]} | Return a JSON-serializable representation. | Return a JSON-serializable representation. | [
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"-",
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] | def to_json(self):
"""Return a JSON-serializable representation."""
return {attr: getattr(self, attr) for attr in _concept_attributes + ["time"]} | [
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wikimedia/pywikibot | 81a01ffaec7271bf5b4b170f85a80388420a4e78 | pywikibot/site/_apisite.py | python | APISite.is_uploaddisabled | (self) | Return True if upload is disabled on site.
When the version is at least 1.27wmf9, uses general siteinfo.
If not called directly, it is cached by the first attempted
upload action. | Return True if upload is disabled on site. | [
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] | def is_uploaddisabled(self):
"""Return True if upload is disabled on site.
When the version is at least 1.27wmf9, uses general siteinfo.
If not called directly, it is cached by the first attempted
upload action.
"""
if self.mw_version >= '1.27wmf9':
return not self._siteinfo.get('general')['uploadsenabled']
if hasattr(self, '_uploaddisabled'):
return self._uploaddisabled
# attempt a fake upload; on enabled sites will fail for:
# missingparam: One of the parameters
# filekey, file, url, statuskey is required
# TODO: is there another way?
try:
req = self._request(throttle=False,
parameters={'action': 'upload',
'token': self.tokens['edit']})
req.submit()
except APIError as error:
if error.code == 'uploaddisabled':
self._uploaddisabled = True
elif error.code == 'missingparam':
# If the upload module is enabled, the above dummy request
# does not have sufficient parameters and will cause a
# 'missingparam' error.
self._uploaddisabled = False
else:
# Unexpected error
raise
return self._uploaddisabled
raise RuntimeError(
'Unexpected success of upload action without parameters.') | [
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SekoiaLab/Fastir_Collector | 7586e1fb30b97714a40bebdcc845027e1a5ec257 | registry/reg.py | python | _Reg.__get_user_assist | (self, is_win7_or_further) | return to_csv_list | Extracts information from UserAssist registry key which contains information about executed programs
The count offset is for Windows versions before 7, where it would start at 6 | Extracts information from UserAssist registry key which contains information about executed programs
The count offset is for Windows versions before 7, where it would start at 6 | [
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] | def __get_user_assist(self, is_win7_or_further):
"""
Extracts information from UserAssist registry key which contains information about executed programs
The count offset is for Windows versions before 7, where it would start at 6
"""
self.logger.info("Extracting user assist")
path = r"Software\Microsoft\Windows\CurrentVersion\Explorer\\UserAssist"
count = "\Count"
# logged on users
users = registry_obj.RegistryKey(registry_obj.HKEY_USERS)
hive_list = []
for i in xrange(users.get_number_of_sub_keys()):
user = users.get_sub_key(i)
user_assist_key = user.get_sub_key_by_path(path)
if user_assist_key:
for j in xrange(user_assist_key.get_number_of_sub_keys()):
# getting Software\Microsoft\Windows\CurrentVersion\Explorer\UserAssist\*\Count
path_no_sid = "\\".join(user_assist_key.get_sub_key(j).get_path().split("\\")[1:])
hive_list += self._get_list_from_registry_key(registry_obj.HKEY_USERS, path_no_sid + count)
if is_win7_or_further:
to_csv_list = [("COMPUTER_NAME", "TYPE", "LAST_WRITE_TIME", "HIVE", "KEY_PATH", "ATTR_NAME", "REG_TYPE",
"ATTR_TYPE", "ATTR_DATA", "DATA_SESSION", "DATA_COUNT", "DATA_FOCUS", "DATA_LAST_EXEC")]
else:
to_csv_list = [("COMPUTER_NAME", "TYPE", "LAST_WRITE_TIME", "HIVE", "KEY_PATH", "ATTR_NAME", "REG_TYPE",
"ATTR_TYPE", "ATTR_DATA", "DATA_SESSION", "DATA_COUNT", "DATA_LAST_EXEC")]
for item in hive_list:
if item[KEY_VALUE_STR] == "VALUE":
str_value_name = codecs.decode(item[VALUE_NAME], "rot_13")
str_value_datatmp = item[VALUE_DATA]
# some data are less than 16 bytes for some reason...
if len(str_value_datatmp) < 16:
to_csv_list.append((self.computer_name,
"userassist",
item[VALUE_LAST_WRITE_TIME],
"HKEY_USERS",
item[VALUE_PATH],
item[VALUE_NAME],
item[KEY_VALUE_STR],
registry_obj.get_str_type(item[VALUE_TYPE]),
str_value_name))
else:
if is_win7_or_further:
data = csv_user_assist_value_decode_win7_and_after(str_value_datatmp)
else:
data = csv_user_assist_value_decode_before_win7(str_value_datatmp)
to_csv_list.append((self.computer_name,
"user_assist",
item[VALUE_LAST_WRITE_TIME],
"HKEY_USERS",
item[VALUE_PATH],
item[VALUE_NAME],
item[KEY_VALUE_STR],
registry_obj.get_str_type(item[VALUE_TYPE]),
str_value_name) + tuple(data))
return to_csv_list | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/sqlalchemy/sql/elements.py | python | Grouping.__getattr__ | (self, attr) | return getattr(self.element, attr) | [] | def __getattr__(self, attr):
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hunkim/DeepLearningStars | 8672d23c23fc9ebe6113f1808a09aa1ae5b9cd99 | list2md.multiprocess.py | python | dict2md | (dict_) | return "| [{name}]({url}) | {stars} | {description} |".format(**dict_) | Convert a dictionary to a markdown format | Convert a dictionary to a markdown format | [
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] | def dict2md(dict_):
"""Convert a dictionary to a markdown format"""
return "| [{name}]({url}) | {stars} | {description} |".format(**dict_) | [
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shiba24/3d-unet | 57e0ca31b371a833d7e60f14ca857844dc8bcc02 | tensorflow/model.py | python | error_rate | (predictions, labels) | return 100.0 - (
100.0 *
np.sum(np.argmax(predictions, 3) == np.argmax(labels, 3)) /
(predictions.shape[0]*predictions.shape[1]*predictions.shape[2])) | Return the error rate based on dense predictions and 1-hot labels. | Return the error rate based on dense predictions and 1-hot labels. | [
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] | def error_rate(predictions, labels):
"""
Return the error rate based on dense predictions and 1-hot labels.
"""
return 100.0 - (
100.0 *
np.sum(np.argmax(predictions, 3) == np.argmax(labels, 3)) /
(predictions.shape[0]*predictions.shape[1]*predictions.shape[2])) | [
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brython-dev/brython | 9cba5fb7f43a9b52fff13e89b403e02a1dfaa5f3 | www/src/Lib/shutil.py | python | _copyfileobj_readinto | (fsrc, fdst, length=COPY_BUFSIZE) | readinto()/memoryview() based variant of copyfileobj().
*fsrc* must support readinto() method and both files must be
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*fsrc* must support readinto() method and both files must be
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*fsrc* must support readinto() method and both files must be
open in binary mode.
"""
# Localize variable access to minimize overhead.
fsrc_readinto = fsrc.readinto
fdst_write = fdst.write
with memoryview(bytearray(length)) as mv:
while True:
n = fsrc_readinto(mv)
if not n:
break
elif n < length:
with mv[:n] as smv:
fdst.write(smv)
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fdst_write(mv) | [
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CGATOxford/cgat | 326aad4694bdfae8ddc194171bb5d73911243947 | obsolete/pipeline_proj007.py | python | annotateLiverTestesMergedTranscriptTSSDistance | ( infile, outfile ) | Compute distance from CAPseq intervals to nearest transcript TSS | Compute distance from CAPseq intervals to nearest transcript TSS | [
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] | def annotateLiverTestesMergedTranscriptTSSDistance( infile, outfile ):
'''Compute distance from CAPseq intervals to nearest transcript TSS'''
to_cluster = True
annotation_file = os.path.join( PARAMS["geneset_dir"],PARAMS["geneset_transcript_tss"] )
statement = """cat < %(infile)s
| python %(scriptsdir)s/bed2gff.py --as-gtf
| python %(scriptsdir)s/gtf2table.py
--counter=distance-tss
--log=%(outfile)s.log
--filename-gff=%(annotation_file)s
--filename-format="bed"
> %(outfile)s"""
P.run() | [
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akfamily/akshare | 590e50eece9ec067da3538c7059fd660b71f1339 | akshare/fortune/fortune_xincaifu_500.py | python | xincaifu_rank | (year: str = "2020") | return temp_df | 新财富 500 人富豪榜
http://www.xcf.cn/zhuanti/ztzz/hdzt1/500frb/index.html
:param year: 具体排名年份, 数据从 2003-至今
:type year: str
:return: 排行榜
:rtype: pandas.DataFrame | 新财富 500 人富豪榜
http://www.xcf.cn/zhuanti/ztzz/hdzt1/500frb/index.html
:param year: 具体排名年份, 数据从 2003-至今
:type year: str
:return: 排行榜
:rtype: pandas.DataFrame | [
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"""
新财富 500 人富豪榜
http://www.xcf.cn/zhuanti/ztzz/hdzt1/500frb/index.html
:param year: 具体排名年份, 数据从 2003-至今
:type year: str
:return: 排行榜
:rtype: pandas.DataFrame
"""
url = "http://service.ikuyu.cn/XinCaiFu2/pcremoting/bdListAction.do"
params = {
"method": "getPage",
"callback": "jsonpCallback",
"sortBy": "",
"order": "",
"type": "4",
"keyword": "",
"pageSize": "1000",
"year": year,
"pageNo": "1",
"from": "jsonp",
"_": "1604722171732",
}
r = requests.get(url, params=params)
data_text = r.text
data_json = json.loads(data_text[data_text.find("{") : -1])
temp_df = pd.DataFrame(data_json["data"]["rows"])
temp_df.columns = [
"_",
"财富",
"性别",
"排名",
"年龄",
"主要公司",
"姓名",
"公司总部",
"年份",
"_",
"相关行业",
]
temp_df = temp_df[
[
"排名",
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"姓名",
"主要公司",
"相关行业",
"公司总部",
"性别",
"年龄",
"年份",
]
]
return temp_df | [
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... | https://github.com/akfamily/akshare/blob/590e50eece9ec067da3538c7059fd660b71f1339/akshare/fortune/fortune_xincaifu_500.py#L14-L67 | |
seppius-xbmc-repo/ru | d0879d56ec8243b2c7af44fda5cf3d1ff77fd2e2 | plugin.video.stepashka.com/resources/lib/BeautifulSoup.py | python | Tag.get | (self, key, default=None) | return self._getAttrMap().get(key, default) | Returns the value of the 'key' attribute for the tag, or
the value given for 'default' if it doesn't have that
attribute. | Returns the value of the 'key' attribute for the tag, or
the value given for 'default' if it doesn't have that
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_vendored_deps/library/oc_obj.py | python | Yedit.yaml_dict | (self) | return self.__yaml_dict | getter method for yaml_dict | getter method for yaml_dict | [
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''' getter method for yaml_dict '''
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conansherry/detectron2 | 72c935d9aad8935406b1038af408aa06077d950a | detectron2/modeling/backbone/resnet.py | python | BottleneckBlock.__init__ | (
self,
in_channels,
out_channels,
*,
bottleneck_channels,
stride=1,
num_groups=1,
norm="BN",
stride_in_1x1=False,
dilation=1,
) | Args:
norm (str or callable): a callable that takes the number of
channels and return a `nn.Module`, or a pre-defined string
(one of {"FrozenBN", "BN", "GN"}).
stride_in_1x1 (bool): when stride==2, whether to put stride in the
first 1x1 convolution or the bottleneck 3x3 convolution. | Args:
norm (str or callable): a callable that takes the number of
channels and return a `nn.Module`, or a pre-defined string
(one of {"FrozenBN", "BN", "GN"}).
stride_in_1x1 (bool): when stride==2, whether to put stride in the
first 1x1 convolution or the bottleneck 3x3 convolution. | [
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self,
in_channels,
out_channels,
*,
bottleneck_channels,
stride=1,
num_groups=1,
norm="BN",
stride_in_1x1=False,
dilation=1,
):
"""
Args:
norm (str or callable): a callable that takes the number of
channels and return a `nn.Module`, or a pre-defined string
(one of {"FrozenBN", "BN", "GN"}).
stride_in_1x1 (bool): when stride==2, whether to put stride in the
first 1x1 convolution or the bottleneck 3x3 convolution.
"""
super().__init__(in_channels, out_channels, stride)
if in_channels != out_channels:
self.shortcut = Conv2d(
in_channels,
out_channels,
kernel_size=1,
stride=stride,
bias=False,
norm=get_norm(norm, out_channels),
)
else:
self.shortcut = None
# The original MSRA ResNet models have stride in the first 1x1 conv
# The subsequent fb.torch.resnet and Caffe2 ResNe[X]t implementations have
# stride in the 3x3 conv
stride_1x1, stride_3x3 = (stride, 1) if stride_in_1x1 else (1, stride)
self.conv1 = Conv2d(
in_channels,
bottleneck_channels,
kernel_size=1,
stride=stride_1x1,
bias=False,
norm=get_norm(norm, bottleneck_channels),
)
self.conv2 = Conv2d(
bottleneck_channels,
bottleneck_channels,
kernel_size=3,
stride=stride_3x3,
padding=1 * dilation,
bias=False,
groups=num_groups,
dilation=dilation,
norm=get_norm(norm, bottleneck_channels),
)
self.conv3 = Conv2d(
bottleneck_channels,
out_channels,
kernel_size=1,
bias=False,
norm=get_norm(norm, out_channels),
)
for layer in [self.conv1, self.conv2, self.conv3, self.shortcut]:
if layer is not None: # shortcut can be None
weight_init.c2_msra_fill(layer) | [
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/api/storage_v1_api.py | python | StorageV1Api.read_volume_attachment | (self, name, **kwargs) | return self.read_volume_attachment_with_http_info(name, **kwargs) | read_volume_attachment # noqa: E501
read the specified VolumeAttachment # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.read_volume_attachment(name, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str name: name of the VolumeAttachment (required)
:param str pretty: If 'true', then the output is pretty printed.
:param bool exact: Should the export be exact. Exact export maintains cluster-specific fields like 'Namespace'. Deprecated. Planned for removal in 1.18.
:param bool export: Should this value be exported. Export strips fields that a user can not specify. Deprecated. Planned for removal in 1.18.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: V1VolumeAttachment
If the method is called asynchronously,
returns the request thread. | read_volume_attachment # noqa: E501 | [
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"noqa",
":",
"E501"
] | def read_volume_attachment(self, name, **kwargs): # noqa: E501
"""read_volume_attachment # noqa: E501
read the specified VolumeAttachment # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.read_volume_attachment(name, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str name: name of the VolumeAttachment (required)
:param str pretty: If 'true', then the output is pretty printed.
:param bool exact: Should the export be exact. Exact export maintains cluster-specific fields like 'Namespace'. Deprecated. Planned for removal in 1.18.
:param bool export: Should this value be exported. Export strips fields that a user can not specify. Deprecated. Planned for removal in 1.18.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: V1VolumeAttachment
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.read_volume_attachment_with_http_info(name, **kwargs) | [
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pantsbuild/pex | 473c6ac732ed4bc338b4b20a9ec930d1d722c9b4 | pex/vendor/_vendored/packaging/packaging/_structures.py | python | NegativeInfinityType.__lt__ | (self, other) | return True | [] | def __lt__(self, other):
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CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/urllib/parse.py | python | clear_cache | () | Clear the parse cache and the quoters cache. | Clear the parse cache and the quoters cache. | [
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"""Clear the parse cache and the quoters cache."""
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libtcod/python-tcod | e12c4172baa9efdfd74aff6ee9bab8454a835248 | tcod/context.py | python | Context.__init__ | (self, context_p: Any) | Creates a context from a cffi pointer. | Creates a context from a cffi pointer. | [
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"""Creates a context from a cffi pointer."""
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omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib/site-packages/mechanize/_clientcookie.py | python | eff_request_host | (request) | return req_host, erhn | Return a tuple (request-host, effective request-host name). | Return a tuple (request-host, effective request-host name). | [
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erhn = req_host = request_host(request)
if req_host.find(".") == -1 and not IPV4_RE.search(req_host):
erhn = req_host + ".local"
return req_host, erhn | [
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SigmaHQ/sigma | 6f7d28b52a6468b2430e8d7dfefb79dc01e2f1af | tools/sigma/backends/splunk.py | python | SplunkXMLBackend.finalize | (self) | return self.queries | [] | def finalize(self):
self.queries += self.dash_suf
return self.queries | [
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vmware/vcd-cli | 648dced8c2f6b14493b69b7c3f67344a1b5dbcc5 | vcd_cli/service_certificates.py | python | get_service_certificate | (ctx, gateway_name, id) | return certificate | Get the sdk's certificate object.
It will restore sessions if expired. It will read the client. | Get the sdk's certificate object. | [
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] | def get_service_certificate(ctx, gateway_name, id):
"""Get the sdk's certificate object.
It will restore sessions if expired. It will read the client.
"""
restore_session(ctx, vdc_required=True)
client = ctx.obj['client']
certificate = Certificate(client=client,
gateway_name=gateway_name,
resource_id=id)
return certificate | [
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encode/django-rest-framework | c5be86a6dbf3d21b00a296af5994fa075826bf0b | rest_framework/request.py | python | clone_request | (request, method) | return ret | Internal helper method to clone a request, replacing with a different
HTTP method. Used for checking permissions against other methods. | Internal helper method to clone a request, replacing with a different
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"""
Internal helper method to clone a request, replacing with a different
HTTP method. Used for checking permissions against other methods.
"""
ret = Request(request=request._request,
parsers=request.parsers,
authenticators=request.authenticators,
negotiator=request.negotiator,
parser_context=request.parser_context)
ret._data = request._data
ret._files = request._files
ret._full_data = request._full_data
ret._content_type = request._content_type
ret._stream = request._stream
ret.method = method
if hasattr(request, '_user'):
ret._user = request._user
if hasattr(request, '_auth'):
ret._auth = request._auth
if hasattr(request, '_authenticator'):
ret._authenticator = request._authenticator
if hasattr(request, 'accepted_renderer'):
ret.accepted_renderer = request.accepted_renderer
if hasattr(request, 'accepted_media_type'):
ret.accepted_media_type = request.accepted_media_type
if hasattr(request, 'version'):
ret.version = request.version
if hasattr(request, 'versioning_scheme'):
ret.versioning_scheme = request.versioning_scheme
return ret | [
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ansible/ansible | 4676c08f188fb5dca98df61630c76dba1f0d2d77 | lib/ansible/module_utils/compat/_selectors2.py | python | BaseSelector.get_key | (self, fileobj) | Return the key associated with a registered file object. | Return the key associated with a registered file object. | [
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WikidPad/WikidPad | 558109638807bc76b4672922686e416ab2d5f79c | WikidPad/lib/aui/framemanager.py | python | AuiPaneInfo.HasMaximizeButton | (self) | return self.HasFlag(self.buttonMaximize) | Returns ``True`` if the pane displays a button to maximize the pane. | Returns ``True`` if the pane displays a button to maximize the pane. | [
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jparkhill/TensorMol | d52104dc7ee46eec8301d332a95d672270ac0bd1 | TensorMol/TFNetworks/TFMolInstance.py | python | MolInstance_fc_sqdiff_BP_Update.train_step | (self, step) | return | Perform a single training step (complete processing of all input), using minibatches of size self.batch_size
Args:
step: the index of this step. | Perform a single training step (complete processing of all input), using minibatches of size self.batch_size | [
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"""
Perform a single training step (complete processing of all input), using minibatches of size self.batch_size
Args:
step: the index of this step.
"""
Ncase_train = self.TData.NTrain
start_time = time.time()
train_loss = 0.0
num_of_mols = 0
pre_output = np.zeros((self.batch_size_output),dtype=np.float64)
for ministep in range (0, int(Ncase_train/self.batch_size)):
#print ("ministep: ", ministep, " Ncase_train:", Ncase_train, " self.batch_size", self.batch_size)
batch_data = self.TData.GetTrainBatch(self.batch_size,self.batch_size_output)
actual_mols = np.count_nonzero(batch_data[2])
#print ("index:", batch_data[1][0][:40], batch_data[1][1][:20])
dump_, dump_2, total_loss_value, loss_value, mol_output, atom_outputs = self.sess.run([self.check, self.train_op, self.total_loss, self.loss, self.output, self.atom_outputs], feed_dict=self.fill_feed_dict(batch_data))
#np.set_printoptions(threshold=np.nan)
#print ("self.atom_outputs", atom_outputs[0][0][:40], "\n", atom_outputs[1][0][:20], atom_outputs[1].shape, "\n mol_outputs:", mol_output[:20], mol_output.shape)
#print ("self.gradient:", gradient)
train_loss = train_loss + loss_value
duration = time.time() - start_time
num_of_mols += actual_mols
#print ("atom_outputs:", atom_outputs, " mol outputs:", mol_output)
#print ("atom_outputs shape:", atom_outputs[0].shape, " mol outputs", mol_output.shape)
#print("train diff:", (mol_output[0]-batch_data[2])[:actual_mols], np.sum(np.square((mol_output[0]-batch_data[2])[:actual_mols])))
#print ("train_loss:", train_loss, " Ncase_train:", Ncase_train, train_loss/num_of_mols)
#print ("diff:", mol_output - batch_data[2], " shape:", mol_output.shape)
self.print_training(step, train_loss, num_of_mols, duration)
return | [
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rembo10/headphones | b3199605be1ebc83a7a8feab6b1e99b64014187c | lib/cherrypy/process/wspbus.py | python | Bus.wait | (self, state, interval=0.1, channel=None) | Poll for the given state(s) at intervals; publish to channel. | Poll for the given state(s) at intervals; publish to channel. | [
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states = state
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states = [state]
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joxeankoret/diaphora | dcb5a25ac9fe23a285b657e5389cf770de7ac928 | jkutils/factor.py | python | _difference | (num1, num2) | return diffs, s | [] | def _difference(num1, num2):
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diffs[x] = max(s[0][x], s[1][x]) - min(s[0][x], s[1][x])
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diffs[x] = s[1][x]
return diffs, s | [
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scikit-image/scikit-image | ed642e2bc822f362504d24379dee94978d6fa9de | skimage/draw/_random_shapes.py | python | _generate_rectangle_mask | (point, image, shape, random) | return rectangle, label | Generate a mask for a filled rectangle shape.
The height and width of the rectangle are generated randomly.
Parameters
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point : tuple
The row and column of the top left corner of the rectangle.
image : tuple
The height, width and depth of the image into which the shape
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The minimum and maximum size of the shape to fit.
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The random state to use for random sampling.
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label : tuple
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indices : 2-D array
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"""Generate a mask for a filled rectangle shape.
The height and width of the rectangle are generated randomly.
Parameters
----------
point : tuple
The row and column of the top left corner of the rectangle.
image : tuple
The height, width and depth of the image into which the shape
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shape : tuple
The minimum and maximum size of the shape to fit.
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available_width = min(image[1] - point[1], shape[1]) - shape[0]
available_height = min(image[0] - point[0], shape[1]) - shape[0]
# Pick random widths and heights.
r = shape[0] + random.integers(max(1, available_height)) - 1
c = shape[0] + random.integers(max(1, available_width)) - 1
rectangle = draw_polygon([
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label = ('rectangle', ((point[0], point[0] + r + 1),
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phoenix2/phoenix | 2c83ee6e7c509d2a9378bcd15634a3740adf7666 | phoenix2/backend/MMPProtocol.py | python | MMPProtocolBase.handleCommand | (self, cmd, args) | Handle a parsed command.
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function = getattr(self, 'cmd_' + cmd, None)
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jython/jython3 | def4f8ec47cb7a9c799ea4c745f12badf92c5769 | lib-python/3.5.1/http/cookiejar.py | python | request_host | (request) | return host.lower() | Return request-host, as defined by RFC 2965.
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"""Return request-host, as defined by RFC 2965.
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"""
url = request.get_full_url()
host = urllib.parse.urlparse(url)[1]
if host == "":
host = request.get_header("Host", "")
# remove port, if present
host = cut_port_re.sub("", host, 1)
return host.lower() | [
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home-assistant-libs/netdisco | 477db5a1dc93919a6c5bd61b4b1d3c80e75785bd | netdisco/mdns.py | python | MDNS.entries | (self) | return list(
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quantumlib/OpenFermion | 6187085f2a7707012b68370b625acaeed547e62b | src/openfermion/hamiltonians/special_operators.py | python | sz_operator | (n_spatial_orbitals: int) | return operator | r"""Return the sz operator.
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r"""Return the sz operator.
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$$
Args:
n_spatial_orbitals: number of spatial orbitals (n_qubits // 2).
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Note:
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"""
if not isinstance(n_spatial_orbitals, int):
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operator += (number_operator(n_spinless_orbitals, up_index(ni), 0.5) +
number_operator(n_spinless_orbitals, down_index(ni), -0.5))
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/data/oweditdomain.py | python | DiscreteVariableEditor.__categories_mapping | (self) | return res | Encode and return the current state as a CategoriesMappingType | Encode and return the current state as a CategoriesMappingType | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/qtconsole/console_widget.py | python | ConsoleWidget._get_line_end_pos | (self) | return self._get_line_end_cursor().position() | Get the position of the last character of the current line. | Get the position of the last character of the current line. | [
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Qirky/FoxDot | 76318f9630bede48ff3994146ed644affa27bfa4 | FoxDot/lib/Workspace/Simple/SimpleEditor.py | python | workspace.__init__ | (self, CodeClass) | [] | def __init__(self, CodeClass):
self.app = wx.App(False)
self.root = Editor(None, 'FoxDot - Live Coding with Python and SuperCollider') | [
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duo-labs/isthislegit | 5d51fd2e0fe070cacd1ee169ca8a371a72e005ef | dashboard/lib/flanker/mime/message/utils.py | python | _guess_and_convert_with | (value, detector=chardet) | Try to guess the encoding of the passed value with the provided detector
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debian-calibre/calibre | 020fc81d3936a64b2ac51459ecb796666ab6a051 | src/calibre/ebooks/lrf/html/table.py | python | Table.get_widths | (self, maxwidth) | return [i+self.colpad for i in widths] | Return widths of columns + self.colpad | Return widths of columns + self.colpad | [
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widths = list(range(cols))
for c in range(cols):
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RasaHQ/rasa | 54823b68c1297849ba7ae841a4246193cd1223a1 | rasa/core/training/interactive.py | python | _split_conversation_at_restarts | (
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Returns an array of event lists, without the restart events."""
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/gui/display.py | python | display_help | (webpage='', section='') | Display the specified webpage and section from the Gramps wiki. | Display the specified webpage and section from the Gramps wiki. | [
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Display the specified webpage and section from the Gramps wiki.
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if not webpage:
link = URL_WIKISTRING + URL_MANUAL_PAGE + EXTENSION
else:
link = URL_WIKISTRING + quote(webpage) + EXTENSION
if section:
link += '#' + quote(section.replace(' ', '_')).replace('%', '.')
display_url(link) | [
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gammapy/gammapy | 735b25cd5bbed35e2004d633621896dcd5295e8b | gammapy/maps/geom.py | python | Geom.data_shape | (self) | Shape of the Numpy data array matching this geometry. | Shape of the Numpy data array matching this geometry. | [
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] | def data_shape(self):
"""Shape of the Numpy data array matching this geometry."""
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/lib2to3/fixer_util.py | python | String | (string, prefix=None) | return Leaf(token.STRING, string, prefix=prefix) | A string leaf | A string leaf | [
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"leaf"
] | def String(string, prefix=None):
"""A string leaf"""
return Leaf(token.STRING, string, prefix=prefix) | [
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LabPy/lantz | 3e878e3f765a4295b0089d04e241d4beb7b8a65b | lantz/drivers/legacy/ni/daqmx/base.py | python | Task.unreserve | (self) | Release all reserved resources. | Release all reserved resources. | [
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] | def unreserve(self):
"""Release all reserved resources.
"""
self.alter_state('unreserve') | [
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apkudo/adbusbini | a5493afa4339e3b5f3645ae6052636fbf70a6fbc | adbusbini_scrape.py | python | handle_vendor | (vendor_id, vendor_name) | [] | def handle_vendor(vendor_id, vendor_name):
if not vendor_exists_file(vendor_id, adb_usb_ini):
vendor_add_adb(vendor_id)
if not vendor_exists_file(vendor_id, vendors):
vendor_add_listing(vendor_id, vendor_name) | [
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fossasia/pslab-python | bb53a334b729d0956ed9f4ce6899903f3e4868ef | pslab/bus/spi.py | python | SPISlave.transfer16_bulk | (self, data: List[int]) | return data_in | Transfer 16-bit data array over SPI.
Parameters
----------
data : list of int
List of 16-bit data to transmit.
Returns
-------
data_in : list of int
List of 16-bit data returned by slave device. | Transfer 16-bit data array over SPI. | [
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] | def transfer16_bulk(self, data: List[int]) -> List[int]:
"""Transfer 16-bit data array over SPI.
Parameters
----------
data : list of int
List of 16-bit data to transmit.
Returns
-------
data_in : list of int
List of 16-bit data returned by slave device.
"""
self._start()
data_in = self._transfer_bulk(data, 16)
self._stop()
return data_in | [
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abseil/abseil-py | a1c1af693b9f15bd0f67fe383cb05e7cc955556b | absl/logging/__init__.py | python | level_error | () | return get_verbosity() >= ERROR | Returns True if error logging is turned on. | Returns True if error logging is turned on. | [
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"""Returns True if error logging is turned on."""
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inasafe/inasafe | 355eb2ce63f516b9c26af0c86a24f99e53f63f87 | safe/gui/widgets/dock.py | python | Dock.toggle_aggregation_layer_combo | (self) | Toggle the aggregation combo enabled status.
Whether the combo is toggled on or off will depend on the current dock
status. | Toggle the aggregation combo enabled status. | [
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"status",
"."
] | def toggle_aggregation_layer_combo(self):
"""Toggle the aggregation combo enabled status.
Whether the combo is toggled on or off will depend on the current dock
status.
"""
selected_hazard_layer = layer_from_combo(self.hazard_layer_combo)
selected_exposure_layer = layer_from_combo(self.exposure_layer_combo)
# more than 1 because No aggregation is always there
if ((self.aggregation_layer_combo.count() > 1)
and (selected_hazard_layer is not None)
and (selected_exposure_layer is not None)):
self.aggregation_layer_combo.setEnabled(True)
else:
self.aggregation_layer_combo.setCurrentIndex(0)
self.aggregation_layer_combo.setEnabled(False) | [
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frappe/frappe | b64cab6867dfd860f10ccaf41a4ec04bc890b583 | frappe/__init__.py | python | scrub | (txt) | return txt.replace(' ', '_').replace('-', '_').lower() | Returns sluggified string. e.g. `Sales Order` becomes `sales_order`. | Returns sluggified string. e.g. `Sales Order` becomes `sales_order`. | [
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] | def scrub(txt):
"""Returns sluggified string. e.g. `Sales Order` becomes `sales_order`."""
return txt.replace(' ', '_').replace('-', '_').lower() | [
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gdlg/pytorch_compact_bilinear_pooling | ecbb98bdccaf8987f2c2432ac0f1db5f370811e8 | compact_bilinear_pooling/__init__.py | python | ComplexMultiply.backward | (ctx,grad_Z_re, grad_Z_im) | return ComplexMultiply_backward(X_re,X_im,Y_re,Y_im, grad_Z_re, grad_Z_im) | [] | def backward(ctx,grad_Z_re, grad_Z_im):
X_re,X_im,Y_re,Y_im = ctx.saved_tensors
return ComplexMultiply_backward(X_re,X_im,Y_re,Y_im, grad_Z_re, grad_Z_im) | [
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MeanEYE/Sunflower | 1024bbdde3b8e202ddad3553b321a7b6230bffc9 | sunflower/gui/preferences/associations.py | python | AssociationsOptions.__add_mime_type | (self, widget, data=None) | Show dialog for adding mime type | Show dialog for adding mime type | [
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"mime",
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] | def __add_mime_type(self, widget, data=None):
"""Show dialog for adding mime type"""
dialog = InputDialog(self._application)
dialog.set_title(_('Add mime type'))
dialog.set_label(_('Enter MIME type (eg. image/png):'))
response = dialog.get_response()
# add new mime type to the table
if response[0] == Gtk.ResponseType.OK:
mime_type = response[1]
description = self._application.associations_manager.get_mime_description(mime_type)
# add item to the store
self._associations.append(None, (description, mime_type))
# enable save button on parent
self._parent.enable_save() | [
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qutebrowser/qutebrowser | 3a2aaaacbf97f4bf0c72463f3da94ed2822a5442 | qutebrowser/config/websettings.py | python | AbstractSettings.set_default_text_encoding | (self, encoding: Union[str, usertypes.Unset]) | Set the default text encoding to use. | Set the default text encoding to use. | [
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] | def set_default_text_encoding(self, encoding: Union[str, usertypes.Unset]) -> None:
"""Set the default text encoding to use."""
assert encoding is not usertypes.UNSET # unclear how to reset
self._settings.setDefaultTextEncoding(encoding) | [
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dswah/pyGAM | b57b4cf8783a90976031e1857e748ca3e6ec650b | pygam/utils.py | python | check_iterable_depth | (obj, max_depth=100) | return depth | find the maximum depth of nesting of the iterable
Parameters
----------
obj : iterable
max_depth : int, default: 100
maximum depth beyond which we stop counting
Returns
-------
int | find the maximum depth of nesting of the iterable | [
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] | def check_iterable_depth(obj, max_depth=100):
"""find the maximum depth of nesting of the iterable
Parameters
----------
obj : iterable
max_depth : int, default: 100
maximum depth beyond which we stop counting
Returns
-------
int
"""
def find_iterables(obj):
iterables = []
for item in obj:
if isiterable(item):
iterables += list(item)
return iterables
depth = 0
while (depth < max_depth) and isiterable(obj) and len(obj) > 0:
depth += 1
obj = find_iterables(obj)
return depth | [
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saltstack/pepper | 8096e0896417ef9b533c7b99dac77535c6eba15d | pepper/libpepper.py | python | Pepper.req_requests | (self, path, data=None) | return resp.json() | A thin wrapper around request and request_kerberos to send
requests and return the response
If the current instance contains an authentication token it will be
attached to the request as a custom header.
:rtype: dictionary | A thin wrapper around request and request_kerberos to send
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] | def req_requests(self, path, data=None):
'''
A thin wrapper around request and request_kerberos to send
requests and return the response
If the current instance contains an authentication token it will be
attached to the request as a custom header.
:rtype: dictionary
'''
import requests
from requests_gssapi import HTTPSPNEGOAuth, OPTIONAL
auth = HTTPSPNEGOAuth(mutual_authentication=OPTIONAL)
headers = {
'Accept': 'application/json',
'Content-Type': 'application/json',
'X-Requested-With': 'XMLHttpRequest',
}
if self.auth and 'token' in self.auth and self.auth['token']:
headers.setdefault('X-Auth-Token', self.auth['token'])
# Optionally toggle SSL verification
params = {'url': self._construct_url(path),
'headers': headers,
'verify': self._ssl_verify is True,
'auth': auth,
'data': json.dumps(data),
}
logger.debug('postdata {0}'.format(params))
resp = requests.post(**params)
if resp.status_code == 401:
# TODO should be resp.raise_from_status
raise PepperException('Authentication denied')
if resp.status_code == 500:
# TODO should be resp.raise_from_status
raise PepperException('Server error.')
if not self.salt_version and 'x-salt-version' in resp.headers:
self._parse_salt_version(resp.headers['x-salt-version'])
return resp.json() | [
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JBakamovic/cxxd | 142c19649b036bd6f6bdcd4684de735ea11a6c94 | api.py | python | project_builder_start | (handle) | [] | def project_builder_start(handle):
_server_start_service(handle, ServiceId.PROJECT_BUILDER) | [
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | lms/djangoapps/commerce/utils.py | python | EcommerceService.get_order_dashboard_url | (self) | return self.get_absolute_ecommerce_url(CommerceConfiguration.DEFAULT_ORDER_DASHBOARD_URL) | Return the URL to the ecommerce dashboard orders page.
Returns:
String: order dashboard url. | Return the URL to the ecommerce dashboard orders page. | [
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] | def get_order_dashboard_url(self):
""" Return the URL to the ecommerce dashboard orders page.
Returns:
String: order dashboard url.
"""
return self.get_absolute_ecommerce_url(CommerceConfiguration.DEFAULT_ORDER_DASHBOARD_URL) | [
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phaethon/kamene | bf679a65d456411942ee4a907818ba3d6a183bfe | kamene/fields.py | python | Field.i2len | (self, pkt, x) | return self.sz | Convert internal value to a length usable by a FieldLenField | Convert internal value to a length usable by a FieldLenField | [
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] | def i2len(self, pkt, x):
"""Convert internal value to a length usable by a FieldLenField"""
return self.sz | [
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SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/op2/tables/geom/edt.py | python | EDT._read_uxvec | (self, data: bytes, n: int) | return n | MSC 2020
Word Name Type Description
1 ID I Control vector identification number
2 LABEL(2) CHAR4 Controller name
4 UX RS Magnitude of aerodynamic extra point dof
Words 2 thru 4 repeat until (-1,-1) occurs
data = (5001, 'PLOAD ', 1.0, 'INTERCPT', 0.0, -1, -1) | MSC 2020 | [
"MSC",
"2020"
] | def _read_uxvec(self, data: bytes, n: int) -> int:
"""
MSC 2020
Word Name Type Description
1 ID I Control vector identification number
2 LABEL(2) CHAR4 Controller name
4 UX RS Magnitude of aerodynamic extra point dof
Words 2 thru 4 repeat until (-1,-1) occurs
data = (5001, 'PLOAD ', 1.0, 'INTERCPT', 0.0, -1, -1)
"""
op2 = self.op2
ntotal1 = 4 * self.factor # 4*1
ntotal_end = 8 * self.factor # 4*2
ntotal2 = 12 * self.factor # 4*3
#ndatai = len(data) - n
#ncards = ndatai // ntotal
#assert ndatai % ntotal == 0
struct1 = Struct(mapfmt(op2._endian + b'i', self.size))
struct2 = Struct(mapfmt(op2._endian + b'8s f', self.size))
struct_end = Struct(mapfmt(op2._endian + b'2i', self.size))
#for unused_i in range(ncards):
#edata = data[n:n + ntotal]
#aeparm_id, label_bytes, units_bytes = structi.unpack(edata)
#label = label_bytes.decode(op2._encoding).rstrip()
#units = units_bytes.decode(op2._encoding).rstrip()
#op2.add_uxvec()
#n += ntotal
while n < len(data):
edata1 = data[n:n+ntotal1]
idi, = struct1.unpack(edata1)
n += ntotal1
labels = []
uxs = []
edata_end = data[n:n+ntotal_end]
while struct_end.unpack(edata_end) != (-1, -1):
edata2 = data[n:n+ntotal2]
label_bytes, ux = struct2.unpack(edata2)
label = reshape_bytes_block_size(label_bytes, self.size)
labels.append(label)
uxs.append(ux)
n += ntotal2
edata_end = data[n:n+ntotal_end]
n += ntotal_end
uxvec = op2.add_uxvec(idi, labels, uxs)
str(uxvec)
return n | [
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omriher/CapTipper | 3fb2836c0afe60eb6bd5902b4214f564268e9b4d | pefile.py | python | PE.trim | (self) | return self.__data__[:] | Return the just data defined by the PE headers, removing any overlayed data. | Return the just data defined by the PE headers, removing any overlayed data. | [
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] | def trim(self):
"""Return the just data defined by the PE headers, removing any overlayed data."""
overlay_data_offset = self.get_overlay_data_start_offset()
if overlay_data_offset is not None:
return self.__data__[ : overlay_data_offset ]
return self.__data__[:] | [
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ray-project/ray | 703c1610348615dcb8c2d141a0c46675084660f5 | python/ray/serve/storage/checkpoint_path.py | python | make_kv_store | (checkpoint_path, namespace) | Create KVStore instance based on checkpoint_path configuration | Create KVStore instance based on checkpoint_path configuration | [
"Create",
"KVStore",
"instance",
"based",
"on",
"checkpoint_path",
"configuration"
] | def make_kv_store(checkpoint_path, namespace):
"""Create KVStore instance based on checkpoint_path configuration"""
if checkpoint_path == DEFAULT_CHECKPOINT_PATH:
logger.info("Using RayInternalKVStore for controller "
"checkpoint and recovery.")
return RayInternalKVStore(namespace)
else:
parsed_url = urlparse(checkpoint_path)
if parsed_url.scheme not in {"gs", "s3", "file", "custom"}:
raise ValueError(
f"Checkpoint must be one of `{DEFAULT_CHECKPOINT_PATH}`, "
"`file://path...`, `gs://path...`, `s3://path...`, or "
"`custom://my_module.ClassName?arg1=val1`. But it is "
f"{checkpoint_path}")
if parsed_url.scheme == "file":
db_path = parsed_url.netloc + parsed_url.path
logger.info("Using RayLocalKVStore for controller "
f"checkpoint and recovery: path={db_path}")
return RayLocalKVStore(namespace, db_path)
if parsed_url.scheme == "gs":
bucket = parsed_url.netloc
# We need to strip leading "/" in path as right key to use in
# gcs. Ex: gs://bucket/folder/file.zip -> key = "folder/file.zip"
prefix = parsed_url.path.lstrip("/")
logger.info("Using Ray GCS KVStore for controller checkpoint and"
" recovery: "
f"bucket={bucket} checkpoint_path={checkpoint_path}")
return RayGcsKVStore(
namespace,
bucket=bucket,
prefix=prefix,
)
if parsed_url.scheme == "s3":
bucket = parsed_url.netloc
# We need to strip leading "/" in path as right key to use in
# boto3. Ex: s3://bucket/folder/file.zip -> key = "folder/file.zip"
prefix = parsed_url.path.lstrip("/")
logger.info(
"Using Ray S3 KVStore for controller checkpoint and recovery: "
f"bucket={bucket} checkpoint_path={checkpoint_path}")
return RayS3KVStore(
namespace,
bucket=bucket,
prefix=prefix,
)
if parsed_url.scheme == "custom":
kwargs = dict(parse_qsl(parsed_url.query))
# Prepare the parameters to initialize imported class.
checkpoint_provider = parsed_url.netloc
KVStoreClass = import_attr(checkpoint_provider)
if not issubclass(KVStoreClass, KVStoreBase):
raise ValueError(
f"{KVStoreClass} doesn't inherit from "
"`ray.serve.storage.kv_store_base.KVStoreBase`.")
logger.info(
f"Using {checkpoint_provider} for controller checkpoint and "
f"recovery: kwargs={kwargs}")
return KVStoreClass(namespace=namespace, **kwargs)
raise RuntimeError("This shouldn't be reachable.") | [
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vmware/vsphere-automation-sdk-python | ba7d4e0742f58a641dfed9538ecbbb1db4f3891e | samples/vmc/draas/site_recovery_activation_ops.py | python | main | () | [] | def main():
srm_activation_ops = SiteRecoveryActivationOperations()
srm_activation_ops.setup()
srm_activation_ops.activate_srm()
srm_activation_ops.deactivate_srm() | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/whoosh/matching/binary.py | python | DisjunctionMaxMatcher.block_quality | (self) | return max(self.a.block_quality(), self.b.block_quality()) | [] | def block_quality(self):
return max(self.a.block_quality(), self.b.block_quality()) | [
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gavinfish/leetcode-share | 92bf28abf81a4cbf988d6595b9e42a6ee1b9071d | python/142 Linked List Cycle II.py | python | Solution.detectCycle | (self, head) | return None | :type head: ListNode
:rtype: ListNode | :type head: ListNode
:rtype: ListNode | [
":",
"type",
"head",
":",
"ListNode",
":",
"rtype",
":",
"ListNode"
] | def detectCycle(self, head):
"""
:type head: ListNode
:rtype: ListNode
"""
slow = fast = head
while fast and fast.next:
slow = slow.next
fast = fast.next.next
if slow == fast:
node = head
while node != slow:
node = node.next
slow = slow.next
return node
return None | [
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SimonShi1994/Princess-connection-farm | c189de660677602167b7245846c2b0e53d5e777e | core/MoveRecord.py | python | moveset.T_if | (self, key, value=1, mode="==") | return self._T_if(cmd) | 模板：只有当key满足条件时才执行后续语句块内容
:param key: key名称
:param value: key比较值
:param mode: 比较模式(==,<=,>=,!=,<,>...)
:return: start的ID | 模板：只有当key满足条件时才执行后续语句块内容
:param key: key名称
:param value: key比较值
:param mode: 比较模式(==,<=,>=,!=,<,>...)
:return: start的ID | [
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] | def T_if(self, key, value=1, mode="=="):
"""
模板：只有当key满足条件时才执行后续语句块内容
:param key: key名称
:param value: key比较值
:param mode: 比较模式(==,<=,>=,!=,<,>...)
:return: start的ID
"""
cmd = "'%s' in var and var['%s']%s%s" % (str(key), str(key), mode, str(value))
return self._T_if(cmd) | [
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PySimpleGUI/PySimpleGUI | 6c0d1fb54f493d45e90180b322fbbe70f7a5af3c | DemoPrograms/Demo_Desktop_Widget_RAM_Square.py | python | human_size | (bytes, units=(' bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB')) | return str(bytes) + ' ' + units[0] if bytes < 1024 else human_size(bytes >> 10, units[1:]) | Returns a human readable string reprentation of bytes | Returns a human readable string reprentation of bytes | [
"Returns",
"a",
"human",
"readable",
"string",
"reprentation",
"of",
"bytes"
] | def human_size(bytes, units=(' bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB')):
""" Returns a human readable string reprentation of bytes"""
return str(bytes) + ' ' + units[0] if bytes < 1024 else human_size(bytes >> 10, units[1:]) | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/Lib/decimal.py | python | Context.number_class | (self, a) | return a.number_class(context=self) | Returns an indication of the class of the operand.
The class is one of the following strings:
-sNaN
-NaN
-Infinity
-Normal
-Subnormal
-Zero
+Zero
+Subnormal
+Normal
+Infinity
>>> c = Context(ExtendedContext)
>>> c.Emin = -999
>>> c.Emax = 999
>>> c.number_class(Decimal('Infinity'))
'+Infinity'
>>> c.number_class(Decimal('1E-10'))
'+Normal'
>>> c.number_class(Decimal('2.50'))
'+Normal'
>>> c.number_class(Decimal('0.1E-999'))
'+Subnormal'
>>> c.number_class(Decimal('0'))
'+Zero'
>>> c.number_class(Decimal('-0'))
'-Zero'
>>> c.number_class(Decimal('-0.1E-999'))
'-Subnormal'
>>> c.number_class(Decimal('-1E-10'))
'-Normal'
>>> c.number_class(Decimal('-2.50'))
'-Normal'
>>> c.number_class(Decimal('-Infinity'))
'-Infinity'
>>> c.number_class(Decimal('NaN'))
'NaN'
>>> c.number_class(Decimal('-NaN'))
'NaN'
>>> c.number_class(Decimal('sNaN'))
'sNaN'
>>> c.number_class(123)
'+Normal' | Returns an indication of the class of the operand. | [
"Returns",
"an",
"indication",
"of",
"the",
"class",
"of",
"the",
"operand",
"."
] | def number_class(self, a):
"""Returns an indication of the class of the operand.
The class is one of the following strings:
-sNaN
-NaN
-Infinity
-Normal
-Subnormal
-Zero
+Zero
+Subnormal
+Normal
+Infinity
>>> c = Context(ExtendedContext)
>>> c.Emin = -999
>>> c.Emax = 999
>>> c.number_class(Decimal('Infinity'))
'+Infinity'
>>> c.number_class(Decimal('1E-10'))
'+Normal'
>>> c.number_class(Decimal('2.50'))
'+Normal'
>>> c.number_class(Decimal('0.1E-999'))
'+Subnormal'
>>> c.number_class(Decimal('0'))
'+Zero'
>>> c.number_class(Decimal('-0'))
'-Zero'
>>> c.number_class(Decimal('-0.1E-999'))
'-Subnormal'
>>> c.number_class(Decimal('-1E-10'))
'-Normal'
>>> c.number_class(Decimal('-2.50'))
'-Normal'
>>> c.number_class(Decimal('-Infinity'))
'-Infinity'
>>> c.number_class(Decimal('NaN'))
'NaN'
>>> c.number_class(Decimal('-NaN'))
'NaN'
>>> c.number_class(Decimal('sNaN'))
'sNaN'
>>> c.number_class(123)
'+Normal'
"""
a = _convert_other(a, raiseit=True)
return a.number_class(context=self) | [
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googlearchive/pywebsocket | c459a5f9a04714e596726e876fcb46951c61a5f7 | mod_pywebsocket/http_header_util.py | python | _is_char | (c) | return ord(c) <= 127 | Returns true iff c is in CHAR as specified in HTTP RFC. | Returns true iff c is in CHAR as specified in HTTP RFC. | [
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"iff",
"c",
"is",
"in",
"CHAR",
"as",
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"in",
"HTTP",
"RFC",
"."
] | def _is_char(c):
"""Returns true iff c is in CHAR as specified in HTTP RFC."""
return ord(c) <= 127 | [
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django-mptt/django-mptt | 7a6a54c6d2572a45ea63bd639c25507108fff3e6 | mptt/managers.py | python | TreeManager.left_attr | (self) | return self.model._mptt_meta.left_attr | [] | def left_attr(self):
return self.model._mptt_meta.left_attr | [
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] | https://github.com/django-mptt/django-mptt/blob/7a6a54c6d2572a45ea63bd639c25507108fff3e6/mptt/managers.py#L353-L354 | |||
rowliny/DiffHelper | ab3a96f58f9579d0023aed9ebd785f4edf26f8af | Tool/SitePackages/nltk/sentiment/util.py | python | demo_vader_tweets | (n_instances=None, output=None) | Classify 10000 positive and negative tweets using Vader approach.
:param n_instances: the number of total tweets that have to be classified.
:param output: the output file where results have to be reported. | Classify 10000 positive and negative tweets using Vader approach. | [
"Classify",
"10000",
"positive",
"and",
"negative",
"tweets",
"using",
"Vader",
"approach",
"."
] | def demo_vader_tweets(n_instances=None, output=None):
"""
Classify 10000 positive and negative tweets using Vader approach.
:param n_instances: the number of total tweets that have to be classified.
:param output: the output file where results have to be reported.
"""
from collections import defaultdict
from nltk.corpus import twitter_samples
from nltk.metrics import accuracy as eval_accuracy
from nltk.metrics import f_measure as eval_f_measure
from nltk.metrics import precision as eval_precision
from nltk.metrics import recall as eval_recall
from nltk.sentiment import SentimentIntensityAnalyzer
if n_instances is not None:
n_instances = int(n_instances / 2)
fields = ["id", "text"]
positive_json = twitter_samples.abspath("positive_tweets.json")
positive_csv = "positive_tweets.csv"
json2csv_preprocess(
positive_json,
positive_csv,
fields,
strip_off_emoticons=False,
limit=n_instances,
)
negative_json = twitter_samples.abspath("negative_tweets.json")
negative_csv = "negative_tweets.csv"
json2csv_preprocess(
negative_json,
negative_csv,
fields,
strip_off_emoticons=False,
limit=n_instances,
)
pos_docs = parse_tweets_set(positive_csv, label="pos")
neg_docs = parse_tweets_set(negative_csv, label="neg")
# We separately split subjective and objective instances to keep a balanced
# uniform class distribution in both train and test sets.
train_pos_docs, test_pos_docs = split_train_test(pos_docs)
train_neg_docs, test_neg_docs = split_train_test(neg_docs)
training_tweets = train_pos_docs + train_neg_docs
testing_tweets = test_pos_docs + test_neg_docs
vader_analyzer = SentimentIntensityAnalyzer()
gold_results = defaultdict(set)
test_results = defaultdict(set)
acc_gold_results = []
acc_test_results = []
labels = set()
num = 0
for i, (text, label) in enumerate(testing_tweets):
labels.add(label)
gold_results[label].add(i)
acc_gold_results.append(label)
score = vader_analyzer.polarity_scores(text)["compound"]
if score > 0:
observed = "pos"
else:
observed = "neg"
num += 1
acc_test_results.append(observed)
test_results[observed].add(i)
metrics_results = {}
for label in labels:
accuracy_score = eval_accuracy(acc_gold_results, acc_test_results)
metrics_results["Accuracy"] = accuracy_score
precision_score = eval_precision(gold_results[label], test_results[label])
metrics_results[f"Precision [{label}]"] = precision_score
recall_score = eval_recall(gold_results[label], test_results[label])
metrics_results[f"Recall [{label}]"] = recall_score
f_measure_score = eval_f_measure(gold_results[label], test_results[label])
metrics_results[f"F-measure [{label}]"] = f_measure_score
for result in sorted(metrics_results):
print(f"{result}: {metrics_results[result]}")
if output:
output_markdown(
output,
Approach="Vader",
Dataset="labeled_tweets",
Instances=n_instances,
Results=metrics_results,
) | [
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bikalims/bika.lims | 35e4bbdb5a3912cae0b5eb13e51097c8b0486349 | bika/lims/upgrade/to320.py | python | create_CAS_IdentifierType | (portal) | LIMS-1391 The CAS Nr IdentifierType is normally created by
setuphandlers during site initialisation. | LIMS-1391 The CAS Nr IdentifierType is normally created by
setuphandlers during site initialisation. | [
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] | def create_CAS_IdentifierType(portal):
"""LIMS-1391 The CAS Nr IdentifierType is normally created by
setuphandlers during site initialisation.
"""
bsc = getToolByName(portal, 'bika_catalog', None)
idtypes = bsc(portal_type = 'IdentifierType', title='CAS Nr')
if not idtypes:
folder = portal.bika_setup.bika_identifiertypes
idtype = _createObjectByType('IdentifierType', folder, tmpID())
idtype.processForm()
idtype.edit(title='CAS Nr',
description='Chemical Abstracts Registry number',
portal_types=['Analysis Service']) | [
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weechat/scripts | 99ec0e7eceefabb9efb0f11ec26d45d6e8e84335 | python/listbuffer.py | python | lb_close_cb | (*kwargs) | return weechat.WEECHAT_RC_OK | A callback for buffer closing. | A callback for buffer closing. | [
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] | def lb_close_cb(*kwargs):
""" A callback for buffer closing. """
global lb_buffer
lb_buffer = None
return weechat.WEECHAT_RC_OK | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/solvers/ode.py | python | lie_heuristic_bivariate | (match, comp=False) | r"""
The third heuristic assumes the infinitesimals `\xi` and `\eta`
to be bi-variate polynomials in `x` and `y`. The assumption made here
for the logic below is that `h` is a rational function in `x` and `y`
though that may not be necessary for the infinitesimals to be
bivariate polynomials. The coefficients of the infinitesimals
are found out by substituting them in the PDE and grouping similar terms
that are polynomials and since they form a linear system, solve and check
for non trivial solutions. The degree of the assumed bivariates
are increased till a certain maximum value.
References
==========
- Lie Groups and Differential Equations
pp. 327 - pp. 329 | r"""
The third heuristic assumes the infinitesimals `\xi` and `\eta`
to be bi-variate polynomials in `x` and `y`. The assumption made here
for the logic below is that `h` is a rational function in `x` and `y`
though that may not be necessary for the infinitesimals to be
bivariate polynomials. The coefficients of the infinitesimals
are found out by substituting them in the PDE and grouping similar terms
that are polynomials and since they form a linear system, solve and check
for non trivial solutions. The degree of the assumed bivariates
are increased till a certain maximum value. | [
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r"""
The third heuristic assumes the infinitesimals `\xi` and `\eta`
to be bi-variate polynomials in `x` and `y`. The assumption made here
for the logic below is that `h` is a rational function in `x` and `y`
though that may not be necessary for the infinitesimals to be
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are found out by substituting them in the PDE and grouping similar terms
that are polynomials and since they form a linear system, solve and check
for non trivial solutions. The degree of the assumed bivariates
are increased till a certain maximum value.
References
==========
- Lie Groups and Differential Equations
pp. 327 - pp. 329
"""
h = match['h']
hx = match['hx']
hy = match['hy']
func = match['func']
x = func.args[0]
y = match['y']
xi = Function('xi')(x, func)
eta = Function('eta')(x, func)
if h.is_rational_function():
# The maximum degree that the infinitesimals can take is
# calculated by this technique.
etax, etay, etad, xix, xiy, xid = symbols("etax etay etad xix xiy xid")
ipde = etax + (etay - xix)*h - xiy*h**2 - xid*hx - etad*hy
num, denom = cancel(ipde).as_numer_denom()
deg = Poly(num, x, y).total_degree()
deta = Function('deta')(x, y)
dxi = Function('dxi')(x, y)
ipde = (deta.diff(x) + (deta.diff(y) - dxi.diff(x))*h - (dxi.diff(y))*h**2
- dxi*hx - deta*hy)
xieq = Symbol("xi0")
etaeq = Symbol("eta0")
for i in range(deg + 1):
if i:
xieq += Add(*[
Symbol("xi_" + str(power) + "_" + str(i - power))*x**power*y**(i - power)
for power in range(i + 1)])
etaeq += Add(*[
Symbol("eta_" + str(power) + "_" + str(i - power))*x**power*y**(i - power)
for power in range(i + 1)])
pden, denom = (ipde.subs({dxi: xieq, deta: etaeq}).doit()).as_numer_denom()
pden = expand(pden)
# If the individual terms are monomials, the coefficients
# are grouped
if pden.is_polynomial(x, y) and pden.is_Add:
polyy = Poly(pden, x, y).as_dict()
if polyy:
symset = xieq.free_symbols.union(etaeq.free_symbols) - {x, y}
soldict = solve(polyy.values(), *symset)
if isinstance(soldict, list):
soldict = soldict[0]
if any(soldict.values()):
xired = xieq.subs(soldict)
etared = etaeq.subs(soldict)
# Scaling is done by substituting one for the parameters
# This can be any number except zero.
dict_ = dict((sym, 1) for sym in symset)
inf = {eta: etared.subs(dict_).subs(y, func),
xi: xired.subs(dict_).subs(y, func)}
return [inf] | [
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tribe29/checkmk | 6260f2512e159e311f426e16b84b19d0b8e9ad0c | cmk/gui/views/__init__.py | python | _get_combined_graphs_entry | (
view: View, info: VisualInfo, is_single_info: bool
) | return PageMenuEntry(
title=_("All metrics of same type in one graph"),
icon_name="graph",
item=make_simple_link(url),
) | Detect whether or not to add a combined graphs link to the dropdown currently being rendered
In which dropdown to expect the "All metrics of same type in one graph" link? | Detect whether or not to add a combined graphs link to the dropdown currently being rendered | [
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view: View, info: VisualInfo, is_single_info: bool
) -> Optional[PageMenuEntry]:
"""Detect whether or not to add a combined graphs link to the dropdown currently being rendered
In which dropdown to expect the "All metrics of same type in one graph" link?
"""
if not _show_combined_graphs_context_button(view):
return None
if not _show_in_current_dropdown(view, info.ident, is_single_info):
return None
httpvars: HTTPVariables = [
("single_infos", ",".join(view.spec["single_infos"])),
("datasource", view.datasource.ident),
("view_title", view_title(view.spec, view.context)),
]
url = makeuri(request, httpvars, filename="combined_graphs.py")
return PageMenuEntry(
title=_("All metrics of same type in one graph"),
icon_name="graph",
item=make_simple_link(url),
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/iai/v20200303/models.py | python | FaceQualityInfo.__init__ | (self) | r"""
:param Score: 质量分: [0,100]，综合评价图像质量是否适合人脸识别，分数越高质量越好。
正常情况，只需要使用Score作为质量分总体的判断标准即可。Sharpness、Brightness、Completeness等细项分仅供参考。
参考范围：[0,40]较差，[40,60] 一般，[60,80]较好，[80,100]很好。
建议：人脸入库选取70以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Score: int
:param Sharpness: 清晰分：[0,100]，评价图片清晰程度，分数越高越清晰。
参考范围：[0,40]特别模糊，[40,60]模糊，[60,80]一般，[80,100]清晰。
建议：人脸入库选取80以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Sharpness: int
:param Brightness: 光照分：[0,100]，评价图片光照程度，分数越高越亮。
参考范围： [0,30]偏暗，[30,70]光照正常，[70,100]偏亮。
建议：人脸入库选取[30,70]的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Brightness: int
:param Completeness: 五官遮挡分，评价眉毛（Eyebrow）、眼睛（Eye）、鼻子（Nose）、脸颊（Cheek）、嘴巴（Mouth）、下巴（Chin）的被遮挡程度。
注意：此字段可能返回 null，表示取不到有效值。
:type Completeness: :class:`tencentcloud.iai.v20200303.models.FaceQualityCompleteness` | r"""
:param Score: 质量分: [0,100]，综合评价图像质量是否适合人脸识别，分数越高质量越好。
正常情况，只需要使用Score作为质量分总体的判断标准即可。Sharpness、Brightness、Completeness等细项分仅供参考。
参考范围：[0,40]较差，[40,60] 一般，[60,80]较好，[80,100]很好。
建议：人脸入库选取70以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Score: int
:param Sharpness: 清晰分：[0,100]，评价图片清晰程度，分数越高越清晰。
参考范围：[0,40]特别模糊，[40,60]模糊，[60,80]一般，[80,100]清晰。
建议：人脸入库选取80以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Sharpness: int
:param Brightness: 光照分：[0,100]，评价图片光照程度，分数越高越亮。
参考范围： [0,30]偏暗，[30,70]光照正常，[70,100]偏亮。
建议：人脸入库选取[30,70]的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Brightness: int
:param Completeness: 五官遮挡分，评价眉毛（Eyebrow）、眼睛（Eye）、鼻子（Nose）、脸颊（Cheek）、嘴巴（Mouth）、下巴（Chin）的被遮挡程度。
注意：此字段可能返回 null，表示取不到有效值。
:type Completeness: :class:`tencentcloud.iai.v20200303.models.FaceQualityCompleteness` | [
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:param Score: 质量分: [0,100]，综合评价图像质量是否适合人脸识别，分数越高质量越好。
正常情况，只需要使用Score作为质量分总体的判断标准即可。Sharpness、Brightness、Completeness等细项分仅供参考。
参考范围：[0,40]较差，[40,60] 一般，[60,80]较好，[80,100]很好。
建议：人脸入库选取70以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Score: int
:param Sharpness: 清晰分：[0,100]，评价图片清晰程度，分数越高越清晰。
参考范围：[0,40]特别模糊，[40,60]模糊，[60,80]一般，[80,100]清晰。
建议：人脸入库选取80以上的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Sharpness: int
:param Brightness: 光照分：[0,100]，评价图片光照程度，分数越高越亮。
参考范围： [0,30]偏暗，[30,70]光照正常，[70,100]偏亮。
建议：人脸入库选取[30,70]的图片。
注意：此字段可能返回 null，表示取不到有效值。
:type Brightness: int
:param Completeness: 五官遮挡分，评价眉毛（Eyebrow）、眼睛（Eye）、鼻子（Nose）、脸颊（Cheek）、嘴巴（Mouth）、下巴（Chin）的被遮挡程度。
注意：此字段可能返回 null，表示取不到有效值。
:type Completeness: :class:`tencentcloud.iai.v20200303.models.FaceQualityCompleteness`
"""
self.Score = None
self.Sharpness = None
self.Brightness = None
self.Completeness = None | [
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cloudera/impyla | 0c736af4cad2bade9b8e313badc08ec50e81c948 | impala/_thrift_gen/TCLIService/ttypes.py | python | TGetTypeInfoReq.read | (self, iprot) | [] | def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
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break
if fid == 1:
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self.sessionHandle = TSessionHandle()
self.sessionHandle.read(iprot)
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iprot.skip(ftype)
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/models/gpt_neo/modeling_flax_gpt_neo.py | python | FlaxGPTNeoSelfAttention._concatenate_to_cache | (self, key, value, query, attention_mask) | return key, value, attention_mask | This function takes projected key, value states from a single input token and concatenates the states to cached
states from previous steps. This function is slighly adapted from the official Flax repository:
https://github.com/google/flax/blob/491ce18759622506588784b4fca0e4bf05f8c8cd/flax/linen/attention.py#L252 | This function takes projected key, value states from a single input token and concatenates the states to cached
states from previous steps. This function is slighly adapted from the official Flax repository:
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# detect if we're initializing by absence of existing cache data.
is_initialized = self.has_variable("cache", "cached_key")
cached_key = self.variable("cache", "cached_key", jnp.zeros, key.shape, key.dtype)
cached_value = self.variable("cache", "cached_value", jnp.zeros, value.shape, value.dtype)
cache_index = self.variable("cache", "cache_index", lambda: jnp.array(0, dtype=jnp.int32))
if is_initialized:
*batch_dims, max_length, num_heads, depth_per_head = cached_key.value.shape
# update key, value caches with our new 1d spatial slices
cur_index = cache_index.value
indices = (0,) * len(batch_dims) + (cur_index, 0, 0)
key = lax.dynamic_update_slice(cached_key.value, key, indices)
value = lax.dynamic_update_slice(cached_value.value, value, indices)
cached_key.value = key
cached_value.value = value
num_updated_cache_vectors = query.shape[1]
cache_index.value = cache_index.value + num_updated_cache_vectors
# causal mask for cached decoder self-attention: our single query position should only attend to those key positions that have already been generated and cached, not the remaining zero elements.
pad_mask = jnp.broadcast_to(
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attention_mask = combine_masks(pad_mask, attention_mask)
return key, value, attention_mask | [
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glue-viz/glue | 840b4c1364b0fa63bf67c914540c93dd71df41e1 | glue/core/layer_artist.py | python | LayerArtistBase.disable_invalid_attributes | (self, *attributes) | Disable a layer because visualization depends on knowing a set
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Automatically generates a disabled message.
Parameters
----------
attributes : sequence of ComponentIDs | Disable a layer because visualization depends on knowing a set
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"""
Disable a layer because visualization depends on knowing a set
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Automatically generates a disabled message.
Parameters
----------
attributes : sequence of ComponentIDs
"""
if len(attributes) == 0:
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return
datasets = ', '.join(sorted(set([cid.parent.label for cid in attributes])))
self.disable(DISABLED_LAYER_WARNING.format(datasets)) | [
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daniilidis-group/neural_renderer | b2a1e6ce16a54f94f26f86fe1dc3814637e15251 | neural_renderer/perspective.py | python | perspective | (vertices, angle=30.) | return vertices | Compute perspective distortion from a given angle | Compute perspective distortion from a given angle | [
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'''
Compute perspective distortion from a given angle
'''
if (vertices.ndimension() != 3):
raise ValueError('vertices Tensor should have 3 dimensions')
device = vertices.device
angle = torch.tensor(angle / 180 * math.pi, dtype=torch.float32, device=device)
angle = angle[None]
width = torch.tan(angle)
width = width[:, None]
z = vertices[:, :, 2]
x = vertices[:, :, 0] / z / width
y = vertices[:, :, 1] / z / width
vertices = torch.stack((x,y,z), dim=2)
return vertices | [
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tensorflow/lingvo | ce10019243d954c3c3ebe739f7589b5eebfdf907 | lingvo/core/py_utils.py | python | TensorSpecs | (nmap, keep_shape=True) | return Transform(fn, nmap) | Transforms tensors in the input nested structure to TensorSpecs. | Transforms tensors in the input nested structure to TensorSpecs. | [
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] | def TensorSpecs(nmap, keep_shape=True):
"""Transforms tensors in the input nested structure to TensorSpecs."""
if nmap is None:
return None
fn = lambda t: tf.TensorSpec(t.shape if keep_shape else None, t.dtype)
return Transform(fn, nmap) | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/boto-2.46.1/boto/s3/multipart.py | python | MultiPartUpload.copy_part_from_key | (self, src_bucket_name, src_key_name, part_num,
start=None, end=None, src_version_id=None,
headers=None) | return self.bucket.copy_key(self.key_name, src_bucket_name,
src_key_name,
src_version_id=src_version_id,
storage_class=None,
headers=headers,
query_args=query_args) | Copy another part of this MultiPart Upload.
:type src_bucket_name: string
:param src_bucket_name: Name of the bucket containing the source key
:type src_key_name: string
:param src_key_name: Name of the source key
:type part_num: int
:param part_num: The number of this part.
:type start: int
:param start: Zero-based byte offset to start copying from
:type end: int
:param end: Zero-based byte offset to copy to
:type src_version_id: string
:param src_version_id: version_id of source object to copy from
:type headers: dict
:param headers: Any headers to pass along in the request | Copy another part of this MultiPart Upload. | [
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] | def copy_part_from_key(self, src_bucket_name, src_key_name, part_num,
start=None, end=None, src_version_id=None,
headers=None):
"""
Copy another part of this MultiPart Upload.
:type src_bucket_name: string
:param src_bucket_name: Name of the bucket containing the source key
:type src_key_name: string
:param src_key_name: Name of the source key
:type part_num: int
:param part_num: The number of this part.
:type start: int
:param start: Zero-based byte offset to start copying from
:type end: int
:param end: Zero-based byte offset to copy to
:type src_version_id: string
:param src_version_id: version_id of source object to copy from
:type headers: dict
:param headers: Any headers to pass along in the request
"""
if part_num < 1:
raise ValueError('Part numbers must be greater than zero')
query_args = 'uploadId=%s&partNumber=%d' % (self.id, part_num)
if start is not None and end is not None:
rng = 'bytes=%s-%s' % (start, end)
provider = self.bucket.connection.provider
if headers is None:
headers = {}
else:
headers = headers.copy()
headers[provider.copy_source_range_header] = rng
return self.bucket.copy_key(self.key_name, src_bucket_name,
src_key_name,
src_version_id=src_version_id,
storage_class=None,
headers=headers,
query_args=query_args) | [
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GiulioRossetti/cdlib | b2c6311b99725bb2b029556f531d244a2af14a2a | cdlib/algorithms/internal/CONGA.py | python | remove_edge_or_split_vertex | (G) | return split | The heart of the CONGA algorithm. Decides which edge should be
removed or which vertex should be split. Returns True if the
modification split the graph. | The heart of the CONGA algorithm. Decides which edge should be
removed or which vertex should be split. Returns True if the
modification split the graph. | [
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] | def remove_edge_or_split_vertex(G):
"""
The heart of the CONGA algorithm. Decides which edge should be
removed or which vertex should be split. Returns True if the
modification split the graph.
"""
# has the graph split this iteration?
split = False
eb = G.edge_betweenness()
maxIndex, maxEb = max(enumerate(eb), key=operator.itemgetter(1))
# We might be able to calculate vertex betweenness and edge
# betweenness at the same time. The current internal is slower
# than the builtin, though.
vb = G.betweenness()
# Only consider vertices with vertex betweenness >= max
# edge betweenness. From Gregory 2007 step 3
vi = [i for i, b in enumerate(vb) if b > maxEb]
edge = G.es[maxIndex].tuple
if not vi:
split = delete_edge(G, edge)
else:
pb = pair_betweenness(G, vi)
maxSplit, vNum, splitInstructions = max_split_betweenness(G, pb)
if maxSplit > maxEb:
split = split_vertex(G, vNum, splitInstructions[0])
else:
split = delete_edge(G, edge)
return split | [
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"... | https://github.com/GiulioRossetti/cdlib/blob/b2c6311b99725bb2b029556f531d244a2af14a2a/cdlib/algorithms/internal/CONGA.py#L314-L345 | |
plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/_cone.py | python | Cone.xhoverformat | (self) | return self["xhoverformat"] | Sets the hover text formatting rulefor `x` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `xaxis.hoverformat`.
The 'xhoverformat' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | Sets the hover text formatting rulefor `x` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `xaxis.hoverformat`.
The 'xhoverformat' property is a string and must be specified as:
- A string
- A number that will be converted to a string | [
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"... | def xhoverformat(self):
"""
Sets the hover text formatting rulefor `x` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `xaxis.hoverformat`.
The 'xhoverformat' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["xhoverformat"] | [
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] | https://github.com/plotly/plotly.py/blob/cfad7862594b35965c0e000813bd7805e8494a5b/packages/python/plotly/plotly/graph_objs/_cone.py#L1617-L1639 | |
riverloopsec/tumblerf | ad79f9dbbfee0612433be3d71c859d6918395f10 | tumblerf/generators/base.py | python | BaseTestCaseGenerator.yield_control_case | (self, count=1) | Is a Python generator which yields potential control cases.
These can be transmitted to gauge if the environment is ready for testing.
These should cause the expected "valid" behavior on the target, e.g., causing an ACK response.
:yield: A byte array generated as a control case. | Is a Python generator which yields potential control cases.
These can be transmitted to gauge if the environment is ready for testing.
These should cause the expected "valid" behavior on the target, e.g., causing an ACK response.
:yield: A byte array generated as a control case. | [
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"These",
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"v... | def yield_control_case(self, count=1):
"""
Is a Python generator which yields potential control cases.
These can be transmitted to gauge if the environment is ready for testing.
These should cause the expected "valid" behavior on the target, e.g., causing an ACK response.
:yield: A byte array generated as a control case.
"""
raise NotImplementedError | [
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python-openxml/python-docx | 36cac78de080d412e9e50d56c2784e33655cad59 | docx/table.py | python | Table.cell | (self, row_idx, col_idx) | return self._cells[cell_idx] | Return |_Cell| instance correponding to table cell at *row_idx*,
*col_idx* intersection, where (0, 0) is the top, left-most cell. | Return |_Cell| instance correponding to table cell at *row_idx*,
*col_idx* intersection, where (0, 0) is the top, left-most cell. | [
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] | def cell(self, row_idx, col_idx):
"""
Return |_Cell| instance correponding to table cell at *row_idx*,
*col_idx* intersection, where (0, 0) is the top, left-most cell.
"""
cell_idx = col_idx + (row_idx * self._column_count)
return self._cells[cell_idx] | [
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] | https://github.com/python-openxml/python-docx/blob/36cac78de080d412e9e50d56c2784e33655cad59/docx/table.py#L75-L81 | |
deepfakes/faceswap | 09c7d8aca3c608d1afad941ea78e9fd9b64d9219 | plugins/train/model/_base.py | python | _Inference._get_filtered_structure | (self) | return struct | Obtain the structure of the inference model.
This parses the model config (in reverse) to obtain the required layers for an inference
model.
Returns
-------
:class:`collections.OrderedDict`
The layer name as key with the input name and output index as value. | Obtain the structure of the inference model. | [
"Obtain",
"the",
"structure",
"of",
"the",
"inference",
"model",
"."
] | def _get_filtered_structure(self):
""" Obtain the structure of the inference model.
This parses the model config (in reverse) to obtain the required layers for an inference
model.
Returns
-------
:class:`collections.OrderedDict`
The layer name as key with the input name and output index as value.
"""
# Filter output layer
out = np.array(self._config["output_layers"], dtype="object")
if out.ndim == 2:
out = np.expand_dims(out, axis=1) # Needs to be expanded for _get_nodes
outputs = self._get_nodes(out)
# Iterate backwards from the required output to get the reversed model structure
current_layers = [outputs[0]]
next_layers = []
struct = OrderedDict()
drop_input = self._input_names[abs(self._input_idx - 1)]
switch_input = self._input_names[self._input_idx]
while True:
layer_info = current_layers.pop(0)
current_layer = next(lyr for lyr in self._config["layers"]
if lyr["name"] == layer_info[0])
inbound = current_layer["inbound_nodes"]
if not inbound:
break
inbound_info = self._get_nodes(inbound)
if any(inb[0] == drop_input for inb in inbound_info): # Switch inputs
inbound_info = [(switch_input if inb[0] == drop_input else inb[0], inb[1])
for inb in inbound_info]
struct[layer_info[0]] = inbound_info
next_layers.extend(inbound_info)
if not current_layers:
current_layers = next_layers
next_layers = []
struct[switch_input] = [] # Add the input layer
logger.debug("Model structure: %s", struct)
return struct | [
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... | https://github.com/deepfakes/faceswap/blob/09c7d8aca3c608d1afad941ea78e9fd9b64d9219/plugins/train/model/_base.py#L1711-L1757 |
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