nwo stringlengths 5 106 | sha stringlengths 40 40 | path stringlengths 4 174 | language stringclasses 1
value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarFile._check | (self, mode=None) | Check if TarFile is still open, and if the operation's mode
corresponds to TarFile's mode. | Check if TarFile is still open, and if the operation's mode
corresponds to TarFile's mode. | [
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"mode",
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"to",
"TarFile",
"s",
"mode",
"."
] | def _check(self, mode=None):
"""Check if TarFile is still open, and if the operation's mode
corresponds to TarFile's mode.
"""
if self.closed:
raise IOError("%s is closed" % self.__class__.__name__)
if mode is not None and self.mode not in mode:
raise IOError("bad operation for mode %r" % self.mode) | [
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etetoolkit/ete | 2b207357dc2a40ccad7bfd8f54964472c72e4726 | ete3/treeview/faces.py | python | BarChartFace._height | (self) | return self.item.rect().height() | [] | def _height(self):
return self.item.rect().height() | [
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] | https://github.com/etetoolkit/ete/blob/2b207357dc2a40ccad7bfd8f54964472c72e4726/ete3/treeview/faces.py#L1381-L1382 | |||
pyjs/pyjs | 6c4a3d3a67300cd5df7f95a67ca9dcdc06950523 | pyjswaddons/SWFUpload.py | python | Settings.setButtonHTML | (self, button_text) | @param button_text: Buttons html text | [] | def setButtonHTML(self, button_text):
"""
@param button_text: Buttons html text
"""
self.button_text = button_text | [
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getavalon/core | 31e8cb4760e00e3db64443f6f932b7fd8e96d41d | avalon/tools/models.py | python | AssetModel.refresh | (self) | Refresh the data for the model. | Refresh the data for the model. | [
"Refresh",
"the",
"data",
"for",
"the",
"model",
"."
] | def refresh(self):
"""Refresh the data for the model."""
self.clear()
self.beginResetModel()
# Get all assets sorted by name
db_assets = io.find({"type": "asset"}).sort("name", 1)
project_doc = io.find_one({"type": "project"})
silos = None
if lib.project_use_silo(project_doc):
silos = db_assets.distinct("silo")
# Group the assets by their visual parent's id
assets_by_parent = collections.defaultdict(list)
for asset in db_assets:
parent_id = asset.get("data", {}).get("visualParent")
if parent_id is None and silos is not None:
parent_id = asset.get("silo")
assets_by_parent[parent_id].append(asset)
# Build the hierarchical tree items recursively
self._add_hierarchy(
assets_by_parent,
parent=None,
silos=silos
)
self.endResetModel() | [
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facebookarchive/doh-proxy | 8622150e6a96e91bfb168c847d084bba67355c9b | dohproxy/proxy.py | python | H2Protocol.return_415 | (self, stream_id: int) | We don't support the given media, so we want to return a 415 response. | We don't support the given media, so we want to return a 415 response. | [
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] | def return_415(self, stream_id: int):
"""
We don't support the given media, so we want to return a 415 response.
"""
self.return_XXX(stream_id, 415, body=b"Unsupported content type") | [
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/beets/autotag/match.py | python | _recommendation | (results) | return rec | Given a sorted list of AlbumMatch or TrackMatch objects, return a
recommendation based on the results' distances.
If the recommendation is higher than the configured maximum for
an applied penalty, the recommendation will be downgraded to the
configured maximum for that penalty. | Given a sorted list of AlbumMatch or TrackMatch objects, return a
recommendation based on the results' distances. | [
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] | def _recommendation(results):
"""Given a sorted list of AlbumMatch or TrackMatch objects, return a
recommendation based on the results' distances.
If the recommendation is higher than the configured maximum for
an applied penalty, the recommendation will be downgraded to the
configured maximum for that penalty.
"""
if not results:
# No candidates: no recommendation.
return Recommendation.none
# Basic distance thresholding.
min_dist = results[0].distance
if min_dist < config['match']['strong_rec_thresh'].as_number():
# Strong recommendation level.
rec = Recommendation.strong
elif min_dist <= config['match']['medium_rec_thresh'].as_number():
# Medium recommendation level.
rec = Recommendation.medium
elif len(results) == 1:
# Only a single candidate.
rec = Recommendation.low
elif results[1].distance - min_dist >= \
config['match']['rec_gap_thresh'].as_number():
# Gap between first two candidates is large.
rec = Recommendation.low
else:
# No conclusion. Return immediately. Can't be downgraded any further.
return Recommendation.none
# Downgrade to the max rec if it is lower than the current rec for an
# applied penalty.
keys = set(min_dist.keys())
if isinstance(results[0], hooks.AlbumMatch):
for track_dist in min_dist.tracks.values():
keys.update(list(track_dist.keys()))
max_rec_view = config['match']['max_rec']
for key in keys:
if key in list(max_rec_view.keys()):
max_rec = max_rec_view[key].as_choice({
'strong': Recommendation.strong,
'medium': Recommendation.medium,
'low': Recommendation.low,
'none': Recommendation.none,
})
rec = min(rec, max_rec)
return rec | [
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wxGlade/wxGlade | 44ed0d1cba78f27c5c0a56918112a737653b7b27 | config.py | python | get_hg_version | () | return ver | Query the local hg repository to get the current release or return None | Query the local hg repository to get the current release or return None | [
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] | def get_hg_version():
"Query the local hg repository to get the current release or return None"
try:
from mercurial.hg import repository
from mercurial.ui import ui
from mercurial.node import short
from mercurial.error import RepoError
except:
return None
# try to open local hg repository
try:
repo = repository(ui(), os.path.dirname(__file__))
except RepoError:
# no mercurial repository found
return None
release = ''
context = repo[None]
parents = context.parents()
repo_changed = context.files() + context.deleted()
if len(parents) == 1 and not repo_changed:
# release tag isn't at tip it's -2 (one below tip)
parents = parents[0].parents()
node = parents[0].node()
tags = repo.nodetags(node)
# look for the special 'rel_X_X_X' or 'rel_X_X' tag
for tag in tags:
if tag.startswith('rel_') and len(tag) > 4:
release = tag[4:].replace('_', '.')
break
# handle untagged release e.g. tip
if not release:
release = short(node)
else:
release = '%s' % '+'.join([short(p.node()) for p in parents])
suffix_changed = repo_changed and '+' or ''
ver = '%s%s' % (release, suffix_changed)
return ver | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tiia/v20190529/tiia_client.py | python | TiiaClient.CreateGroup | (self, request) | 用于创建一个空的图片库，如果图片库已存在则返回错误。
:param request: Request instance for CreateGroup.
:type request: :class:`tencentcloud.tiia.v20190529.models.CreateGroupRequest`
:rtype: :class:`tencentcloud.tiia.v20190529.models.CreateGroupResponse` | 用于创建一个空的图片库，如果图片库已存在则返回错误。 | [
"用于创建一个空的图片库，如果图片库已存在则返回错误。"
] | def CreateGroup(self, request):
"""用于创建一个空的图片库，如果图片库已存在则返回错误。
:param request: Request instance for CreateGroup.
:type request: :class:`tencentcloud.tiia.v20190529.models.CreateGroupRequest`
:rtype: :class:`tencentcloud.tiia.v20190529.models.CreateGroupResponse`
"""
try:
params = request._serialize()
body = self.call("CreateGroup", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateGroupResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/qtconsole/console_widget.py | python | ConsoleWidget._control_key_down | (self, modifiers, include_command=False) | Given a KeyboardModifiers flags object, return whether the Control
key is down.
Parameters
----------
include_command : bool, optional (default True)
Whether to treat the Command key as a (mutually exclusive) synonym
for Control when in Mac OS. | Given a KeyboardModifiers flags object, return whether the Control
key is down. | [
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] | def _control_key_down(self, modifiers, include_command=False):
""" Given a KeyboardModifiers flags object, return whether the Control
key is down.
Parameters
----------
include_command : bool, optional (default True)
Whether to treat the Command key as a (mutually exclusive) synonym
for Control when in Mac OS.
"""
# Note that on Mac OS, ControlModifier corresponds to the Command key
# while MetaModifier corresponds to the Control key.
if sys.platform == 'darwin':
down = include_command and (modifiers & QtCore.Qt.ControlModifier)
return bool(down) ^ bool(modifiers & QtCore.Qt.MetaModifier)
else:
return bool(modifiers & QtCore.Qt.ControlModifier) | [
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AutodeskRoboticsLab/Mimic | 85447f0d346be66988303a6a054473d92f1ed6f4 | mimic/scripts/extern/pyqtgraph_0_11_0/pyqtgraph/graphicsItems/PlotCurveItem.py | python | PlotCurveItem.setClickable | (self, s, width=None) | Sets whether the item responds to mouse clicks.
The *width* argument specifies the width in pixels orthogonal to the
curve that will respond to a mouse click. | Sets whether the item responds to mouse clicks. | [
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] | def setClickable(self, s, width=None):
"""Sets whether the item responds to mouse clicks.
The *width* argument specifies the width in pixels orthogonal to the
curve that will respond to a mouse click.
"""
self.clickable = s
if width is not None:
self.opts['mouseWidth'] = width
self._mouseShape = None
self._boundingRect = None | [
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nschloe/quadpy | c4c076d8ddfa968486a2443a95e2fb3780dcde0f | src/quadpy/c2/_sommariva/__init__.py | python | sommariva_41 | () | return _read(this_dir / "sommariva_41.json", _source) | [] | def sommariva_41():
return _read(this_dir / "sommariva_41.json", _source) | [
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kovidgoyal/calibre | 2b41671370f2a9eb1109b9ae901ccf915f1bd0c8 | src/calibre/ebooks/docx/block_styles.py | python | twips | (val, mult=0.05) | Parse val as either a pure number representing twentieths of a point or a number followed by the suffix pt, representing pts. | Parse val as either a pure number representing twentieths of a point or a number followed by the suffix pt, representing pts. | [
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] | def twips(val, mult=0.05):
''' Parse val as either a pure number representing twentieths of a point or a number followed by the suffix pt, representing pts.'''
try:
return float(val) * mult
except (ValueError, TypeError, AttributeError, KeyError):
if val and val.endswith('pt') and mult == 0.05:
return twips(val[:-2], mult=1.0) | [
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sailfish-team/sailfish | b7140c580e1f4cb406dde947c8d8d5a8a6b2d79e | sailfish/subdomain_runner.py | python | SubdomainRunner._get_global_idx | (self, location, dist_num=0) | Returns a global index (in the distributions array).
:param location: position of the node in the natural order
:param dist_num: distribution number | Returns a global index (in the distributions array). | [
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] | def _get_global_idx(self, location, dist_num=0):
"""Returns a global index (in the distributions array).
:param location: position of the node in the natural order
:param dist_num: distribution number
"""
def _indirect(idxs):
if self.config.node_addressing == 'indirect':
# Get actual node addresses.
# TODO: Ideally, we would filter out unused nodes here. This
# requires careful handling between what the source domain and the
# destination domain see/expect.
ret = self._host_indirect_address.flat[idxs]
mask = ret != self.INVALID_NODE
if ret.size == 1:
if ret != self.INVALID_NODE:
ret += self.num_active_nodes * dist_num
else:
if np.array(dist_num).size == 1:
ret[mask] += self.num_active_nodes * dist_num
else:
ret[mask] += (self.num_active_nodes * dist_num)[mask]
return ret
else:
return idxs + self.num_phys_nodes * dist_num
# XXX: handle indirect here
if self.dim == 2:
gx, gy = location
arr_nx = self._physical_size[1]
return _indirect(gx + arr_nx * gy)
else:
gx, gy, gz = location
arr_nx = self._physical_size[2]
arr_ny = self._physical_size[1]
return _indirect(gx + arr_nx * gy + arr_nx * arr_ny * gz) | [
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GoogleCloudPlatform/PerfKitBenchmarker | 6e3412d7d5e414b8ca30ed5eaf970cef1d919a67 | perfkitbenchmarker/linux_packages/ycsb.py | python | _GetWorkloadFileList | () | return [data.ResourcePath(workload)
for workload in FLAGS.ycsb_workload_files] | Returns the list of workload files to run.
Returns:
In order of preference:
* The argument to --ycsb_workload_files.
* Bundled YCSB workloads A and B. | Returns the list of workload files to run. | [
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] | def _GetWorkloadFileList():
"""Returns the list of workload files to run.
Returns:
In order of preference:
* The argument to --ycsb_workload_files.
* Bundled YCSB workloads A and B.
"""
return [data.ResourcePath(workload)
for workload in FLAGS.ycsb_workload_files] | [
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timonwong/OmniMarkupPreviewer | 21921ac7a99d2b5924a2219b33679a5b53621392 | OmniMarkupLib/Renderers/libs/python3/docutils/utils/math/math2html.py | python | TextParser.parse | (self, reader) | return contents | Parse lines as long as they are text | Parse lines as long as they are text | [
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] | def parse(self, reader):
"Parse lines as long as they are text"
TextParser.stack.append(self.ending)
self.endings = TextParser.stack + [ContainerConfig.endings['Layout'],
ContainerConfig.endings['Inset'], self.ending]
contents = []
while not self.isending(reader):
self.parsecontainer(reader, contents)
return contents | [
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PixarAnimationStudios/OpenTimelineIO | 990a54ccbe6488180a93753370fc87902b982962 | src/py-opentimelineio/opentimelineio/schema/timeline.py | python | each_child | (self, search_range=None, descended_from_type=_otio.Composable) | Generator that returns each child contained in the timeline
in the order in which it is found.
Note that this function is now deprecated, please consider using
children_if() instead.
Arguments:
search_range: if specified, only children whose range overlaps with
the search range will be yielded.
descended_from_type: if specified, only children who are a
descendent of the descended_from_type will be yielded. | Generator that returns each child contained in the timeline
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""" Generator that returns each child contained in the timeline
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Note that this function is now deprecated, please consider using
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Arguments:
search_range: if specified, only children whose range overlaps with
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for child in self.children_if(descended_from_type, search_range):
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datacenter/ACI | 9240622e6be03047f48628deacb5450212bd7ebe | configuration-python/generic_code/apicPython/createRoutedOutside.py | python | create_routed_outside | (fv_tenant, routed_outside_name, **args) | return l3ext_out | Create a Routed Outside policy | Create a Routed Outside policy | [
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] | def create_routed_outside(fv_tenant, routed_outside_name, **args):
"""Create a Routed Outside policy"""
args = args['optional_args'] if 'optional_args' in args.keys() else args
l3ext_out = Out(fv_tenant, routed_outside_name)
if 'private_network' in args.keys():
l3ext_rsectx = RsEctx(l3ext_out, tnFvCtxName=args['private_network'])
if 'bgp' in args.keys() and args['bgp']:
bgp_extp = bgpExtP(l3ext_out)
if 'ospf' in args.keys() and args['ospf']:
ospf_extp = ospfExtP(l3ext_out, areaId='0.0.0.' + str(get_value(args, 'ospf_area_id', '1')))
if 'tags' in args.keys() and is_valid(args['tags']):
tag_inst = Inst(l3ext_out, args['tags'])
return l3ext_out | [
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apple/coremltools | 141a83af482fcbdd5179807c9eaff9a7999c2c49 | deps/protobuf/objectivec/DevTools/pddm.py | python | SourceFile.__init__ | (self, a_file, import_resolver=None) | Initializes the file reading in the file.
Args:
a_file: The file to read in.
import_resolver: a function that given a path will return a stream for
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Raises:
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"""Initializes the file reading in the file.
Args:
a_file: The file to read in.
import_resolver: a function that given a path will return a stream for
the contents.
Raises:
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self._sections = []
self._original_content = a_file.read()
self._import_resolver = import_resolver
self._processed_content = None | [
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srusskih/SublimeJEDI | 8a5054f0a053c8a8170c06c56216245240551d54 | dependencies/jedi/api/classes.py | python | ParamName.to_string | (self) | return self._name.to_string() | Returns a simple representation of a param, like
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"""
Returns a simple representation of a param, like
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:rtype: str
"""
return self._name.to_string() | [
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santatic/web2attack | 44b6e481a3d56cf0d98073ae0fb69833dda563d9 | w2a/lib/smtpd.py | python | SMTPChannel.__line | (self, value) | [] | def __line(self, value):
warn("Setting __line attribute on SMTPChannel is deprecated, "
"set 'received_lines' instead", PendingDeprecationWarning, 2)
self.received_lines = value | [
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ytdl-org/youtube-dl | 5014bd67c22b421207b2650d4dc874b95b36dda1 | youtube_dl/utils.py | python | unified_strdate | (date_str, day_first=True) | Return a string with the date in the format YYYYMMDD | Return a string with the date in the format YYYYMMDD | [
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] | def unified_strdate(date_str, day_first=True):
"""Return a string with the date in the format YYYYMMDD"""
if date_str is None:
return None
upload_date = None
# Replace commas
date_str = date_str.replace(',', ' ')
# Remove AM/PM + timezone
date_str = re.sub(r'(?i)\s*(?:AM|PM)(?:\s+[A-Z]+)?', '', date_str)
_, date_str = extract_timezone(date_str)
for expression in date_formats(day_first):
try:
upload_date = datetime.datetime.strptime(date_str, expression).strftime('%Y%m%d')
except ValueError:
pass
if upload_date is None:
timetuple = email.utils.parsedate_tz(date_str)
if timetuple:
try:
upload_date = datetime.datetime(*timetuple[:6]).strftime('%Y%m%d')
except ValueError:
pass
if upload_date is not None:
return compat_str(upload_date) | [
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vijos/vj4 | 1c80506bafee31c028042ab3020a2273bf0930b9 | vj4/service/bus.py | python | unsubscribe | (callback) | Unsubscribe buses for a callback.
Args:
callback: coroutine function for bus callback. | Unsubscribe buses for a callback. | [
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"""Unsubscribe buses for a callback.
Args:
callback: coroutine function for bus callback.
"""
if callback in _subscribers:
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mininet/mininet | 8a50d3867c49781c60b6171acc6e4b46954b4281 | examples/consoles.py | python | Graph.yview | ( self, *args ) | Scroll both scale and graph. | Scroll both scale and graph. | [
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"Scroll both scale and graph."
self.graph.yview( *args )
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dbt-labs/dbt-core | e943b9fc842535e958ef4fd0b8703adc91556bc6 | core/dbt/parser/manifest.py | python | _process_docs_for_source | (
context: Dict[str, Any],
source: ParsedSourceDefinition,
) | [] | def _process_docs_for_source(
context: Dict[str, Any],
source: ParsedSourceDefinition,
):
table_description = source.description
source_description = source.source_description
table_description = get_rendered(table_description, context)
source_description = get_rendered(source_description, context)
source.description = table_description
source.source_description = source_description
for column in source.columns.values():
column_desc = column.description
column_desc = get_rendered(column_desc, context)
column.description = column_desc | [
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haoctopus/molohub | 7699ef2b8b92bfddd2726b966b927648aa44395f | molohub/molo_client_config.py | python | MoloConfigs.get_config_object | (self) | return self.config_object | Get config_object, reload if not exist. | Get config_object, reload if not exist. | [
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] | def get_config_object(self):
"""Get config_object, reload if not exist."""
if not self.config_object:
self.load('release')
return self.config_object | [
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facebookresearch/ParlAI | e4d59c30eef44f1f67105961b82a83fd28d7d78b | parlai/agents/rag/retrievers.py | python | DPRThenTorchReranker._retrieve_initial | (
self, query: torch.LongTensor
) | return DPRRetriever.retrieve_and_score(self, query) | Initial DPR retrieval.
Just call superclass to retrieve first stage.
:param query:
encoding of query
:param mask:
optional query mask
:return (docs, scores):
docs: list of (text, title) tuples for each batch example
scores: doc scores | Initial DPR retrieval. | [
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"retrieval",
"."
] | def _retrieve_initial(
self, query: torch.LongTensor
) -> Tuple[List[List[Document]], torch.Tensor]:
"""
Initial DPR retrieval.
Just call superclass to retrieve first stage.
:param query:
encoding of query
:param mask:
optional query mask
:return (docs, scores):
docs: list of (text, title) tuples for each batch example
scores: doc scores
"""
return DPRRetriever.retrieve_and_score(self, query) | [
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DamnWidget/anaconda | a9998fb362320f907d5ccbc6fcf5b62baca677c0 | anaconda_lib/jedi/inference/docstrings.py | python | _execute_types_in_stmt | (module_context, stmt) | return ValueSet.from_sets(
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for d in definitions
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doesn't include tuple, list and dict literals, because the stuff they
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definitions = module_context.infer_node(stmt)
return ValueSet.from_sets(
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mfessenden/SceneGraph | 0fa3429059c77c881d1b58b28e89dcb44c609909 | core/plugins.py | python | parse_module_variable | (module, key) | return None | Parse a named variable from a given module.
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module (module) - module object.
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module (module) - module object.
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returns:
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mozman/ezdxf | 59d0fc2ea63f5cf82293428f5931da7e9f9718e9 | src/ezdxf/addons/r12writer.py | python | R12FastStreamWriter.add_text | (
self,
text: str,
insert: Vertex = (0, 0),
height: float = 1.0,
width: float = 1.0,
align: str = "LEFT",
rotation: float = 0.0,
oblique: float = 0.0,
style: str = "STANDARD",
layer: str = "0",
color: int = None,
) | Add a one line TEXT entity.
Args:
text: the text as string
insert: insert location as ``(x, y)`` tuple
height: text height in drawing units
width: text width as factor
align: text alignment, see table below
rotation: text rotation in degrees as float
oblique: oblique in degrees as float, vertical = ``0`` (default)
style: text style name as string, if FIXED-TABLES are written some
predefined text styles are available, else text style is
always ``'STANDARD'``.
layer: layer name as string see :meth:`add_line`
color: color as :ref:`ACI` see :meth:`add_line`
============ =============== ================= =====
Vert/Horiz Left Center Right
============ =============== ================= =====
Top ``TOP_LEFT`` ``TOP_CENTER`` ``TOP_RIGHT``
Middle ``MIDDLE_LEFT`` ``MIDDLE_CENTER`` ``MIDDLE_RIGHT``
Bottom ``BOTTOM_LEFT`` ``BOTTOM_CENTER`` ``BOTTOM_RIGHT``
Baseline ``LEFT`` ``CENTER`` ``RIGHT``
============ =============== ================= =====
The special alignments ``ALIGNED`` and ``FIT`` are not available. | Add a one line TEXT entity. | [
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"."
] | def add_text(
self,
text: str,
insert: Vertex = (0, 0),
height: float = 1.0,
width: float = 1.0,
align: str = "LEFT",
rotation: float = 0.0,
oblique: float = 0.0,
style: str = "STANDARD",
layer: str = "0",
color: int = None,
) -> None:
"""Add a one line TEXT entity.
Args:
text: the text as string
insert: insert location as ``(x, y)`` tuple
height: text height in drawing units
width: text width as factor
align: text alignment, see table below
rotation: text rotation in degrees as float
oblique: oblique in degrees as float, vertical = ``0`` (default)
style: text style name as string, if FIXED-TABLES are written some
predefined text styles are available, else text style is
always ``'STANDARD'``.
layer: layer name as string see :meth:`add_line`
color: color as :ref:`ACI` see :meth:`add_line`
============ =============== ================= =====
Vert/Horiz Left Center Right
============ =============== ================= =====
Top ``TOP_LEFT`` ``TOP_CENTER`` ``TOP_RIGHT``
Middle ``MIDDLE_LEFT`` ``MIDDLE_CENTER`` ``MIDDLE_RIGHT``
Bottom ``BOTTOM_LEFT`` ``BOTTOM_CENTER`` ``BOTTOM_RIGHT``
Baseline ``LEFT`` ``CENTER`` ``RIGHT``
============ =============== ================= =====
The special alignments ``ALIGNED`` and ``FIT`` are not available.
"""
# text style is always STANDARD without a TABLES section
dxf = ["0\nTEXT\n"]
dxf.append(dxf_attribs(layer, color))
dxf.append(dxf_vertex(insert, code=10))
dxf.append(dxf_tag(1, str(text)))
dxf.append(dxf_tag(40, str(rnd(height))))
if width != 1.0:
dxf.append(dxf_tag(41, str(rnd(width))))
if rotation != 0.0:
dxf.append(dxf_tag(50, str(rnd(rotation))))
if oblique != 0.0:
dxf.append(dxf_tag(51, str(rnd(oblique))))
if style != "STANDARD":
dxf.append(dxf_tag(7, str(style)))
halign, valign = TEXT_ALIGN_FLAGS[align.upper()]
dxf.append(dxf_tag(72, str(halign)))
dxf.append(dxf_tag(73, str(valign)))
dxf.append(dxf_vertex(insert, code=11)) # align point
self.stream.write("".join(dxf)) | [
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LumaPictures/pymel | fa88a3f4fa18e09bb8aa9bdf4dab53d984bada72 | pymel/core/language.py | python | Env.setUpAxis | (self, axis, rotateView=False) | This flag specifies the axis as the world up direction. The valid
axis are either 'y' or 'z'. | This flag specifies the axis as the world up direction. The valid
axis are either 'y' or 'z'. | [
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"""This flag specifies the axis as the world up direction. The valid
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LiDan456/MAD-GANs | 3139a73a4112d3f3f18182c9a6cdc2c671e7cfe8 | differential_privacy/privacy_accountant/tf/accountant.py | python | GaussianMomentsAccountant.__init__ | (self, total_examples, moment_orders=32) | Initialization.
Args:
total_examples: total number of examples.
moment_orders: the order of moments to keep. | Initialization. | [
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"""Initialization.
Args:
total_examples: total number of examples.
moment_orders: the order of moments to keep.
"""
super(self.__class__, self).__init__(total_examples, moment_orders)
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hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/modules/sniffer/parser_mysql.py | python | num_fields | (pkt) | return int(pkt[4], 16) | Return the number of fields in a query response | Return the number of fields in a query response | [
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guildai/guildai | 1665985a3d4d788efc1a3180ca51cc417f71ca78 | guild/external/pip/_vendor/lockfile/pidlockfile.py | python | PIDLockFile.acquire | (self, timeout=None) | Acquire the lock.
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""" Acquire the lock.
Creates the PID file for this lock, or raises an error if
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"""
timeout = timeout if timeout is not None else self.timeout
end_time = time.time()
if timeout is not None and timeout > 0:
end_time += timeout
while True:
try:
write_pid_to_pidfile(self.path)
except OSError as exc:
if exc.errno == errno.EEXIST:
# The lock creation failed. Maybe sleep a bit.
if time.time() > end_time:
if timeout is not None and timeout > 0:
raise LockTimeout("Timeout waiting to acquire"
" lock for %s" %
self.path)
else:
raise AlreadyLocked("%s is already locked" %
self.path)
time.sleep(timeout is not None and timeout / 10 or 0.1)
else:
raise LockFailed("failed to create %s" % self.path)
else:
return | [
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Fizzadar/pyinfra | ff0913d6a172966760b63fe59e55dff9ea852e0d | pyinfra/facts/pacman.py | python | PacmanUnpackGroup.process | (self, output) | return output | [] | def process(self, output):
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malwaredllc/byob | 3924dd6aea6d0421397cdf35f692933b340bfccf | web-gui/buildyourownbotnet/core/payloads.py | python | Payload.escalate | (self) | Attempt UAC bypass to escalate privileges | Attempt UAC bypass to escalate privileges | [
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"""
Attempt UAC bypass to escalate privileges
"""
try:
if 'escalate' not in globals():
self.load('escalate')
return globals()['escalate'].run(sys.argv[0])
except Exception as e:
log("{} error: {}".format(self.escalate.__name__, str(e))) | [
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Chaffelson/nipyapi | d3b186fd701ce308c2812746d98af9120955e810 | nipyapi/nifi/models/controller_status_dto.py | python | ControllerStatusDTO.invalid_count | (self) | return self._invalid_count | Gets the invalid_count of this ControllerStatusDTO.
The number of invalid components in the NiFi.
:return: The invalid_count of this ControllerStatusDTO.
:rtype: int | Gets the invalid_count of this ControllerStatusDTO.
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"""
Gets the invalid_count of this ControllerStatusDTO.
The number of invalid components in the NiFi.
:return: The invalid_count of this ControllerStatusDTO.
:rtype: int
"""
return self._invalid_count | [
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evhub/coconut | 27a4af9dc06667870f736f20c862930001b8cbb2 | coconut/compiler/util.py | python | ComputationNode.name | (self) | return name if name is not None else repr(self.action) | Get the name of the action. | Get the name of the action. | [
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"""Get the name of the action."""
name = getattr(self.action, "__name__", None)
# repr(action) not defined for all actions, so must only be evaluated if getattr fails
return name if name is not None else repr(self.action) | [
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mapproxy/mapproxy | 45ae81b3dd6c8a1a0b473ba8c669afd0ec7ecd10 | mapproxy/cache/riak.py | python | RiakCache._key_iterator | (self, level) | Generator for all tile keys in `level`. | Generator for all tile keys in `level`. | [
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# index() returns a list of all keys so we check for tiles in
# batches of `chunk_size`*`chunk_size`.
grid_size = self.tile_grid.grid_sizes[level]
chunk_size = 256
for x in range(grid_size[0]/chunk_size):
start_x = x * chunk_size
end_x = start_x + chunk_size - 1
for y in range(grid_size[1]/chunk_size):
start_y = y * chunk_size
end_y = start_y + chunk_size - 1
query = self.bucket.get_index('tile_coord_bin',
'%02d-%07d-%07d' % (level, start_x, start_y),
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for link in query.run():
yield link.get_key() | [
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Yelp/mrjob | 091572e87bc24cc64be40278dd0f5c3617c98d4b | mrjob/cmd.py | python | _command | (name, description=None) | return decorator | Decorate a function used to call a command.
If you don't set *description*, it won't be included in help
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def decorator(f):
commands[name] = f
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descriptions[name] = description
return f
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GoogleCloudPlatform/PerfKitBenchmarker | 6e3412d7d5e414b8ca30ed5eaf970cef1d919a67 | perfkitbenchmarker/linux_benchmarks/openssl_speed_benchmark.py | python | ParseOpenSSLOutput | (raw_result: str, version: str, parallelism: int) | return results | Parse output from openssl speed and return as samples. | Parse output from openssl speed and return as samples. | [
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"""Parse output from openssl speed and return as samples."""
matches = regex_util.ExtractExactlyOneMatch(r'evp\s+(.*)', raw_result).split()
results = []
for idx, blocksize in enumerate(BLOCKSIZES_IN_BYTES):
value_unit_tuple = regex_util.ExtractExactlyOneMatch(
r'([\d\.]+)(\w+)', matches[idx])
metadata = {
'duration': _OPENSSL_SPEED_DURATION.value,
'algorithm': _OPENSSL_SPEED_ALGORITHM.value,
'parallelism': parallelism,
'version': version,
'blocksize': blocksize
}
results.append(
sample.Sample('Throughput', float(value_unit_tuple[0]),
value_unit_tuple[1], metadata))
return results | [
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numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/core/base.py | python | BaseContext.unpack_value | (self, builder, ty, ptr, align=None) | return dm.load_from_data_pointer(builder, ptr, align) | Unpack value from the array storage at *ptr*.
If *align* is given, it is the guaranteed alignment for *ptr*
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If *align* is given, it is the guaranteed alignment for *ptr*
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osmr/imgclsmob | f2993d3ce73a2f7ddba05da3891defb08547d504 | gluon/gluoncv2/models/preresnet.py | python | preresnetbc14b | (**kwargs) | return get_preresnet(blocks=14, bottleneck=True, conv1_stride=False, model_name="preresnetbc14b", **kwargs) | PreResNet-BC-14b model from 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
It's an experimental model (bottleneck compressed).
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
ctx : Context, default CPU
The context in which to load the pretrained weights.
root : str, default '~/.mxnet/models'
Location for keeping the model parameters. | PreResNet-BC-14b model from 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
It's an experimental model (bottleneck compressed). | [
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It's an experimental model (bottleneck compressed).
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
ctx : Context, default CPU
The context in which to load the pretrained weights.
root : str, default '~/.mxnet/models'
Location for keeping the model parameters.
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return get_preresnet(blocks=14, bottleneck=True, conv1_stride=False, model_name="preresnetbc14b", **kwargs) | [
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microsoft/MPNet | 081523a788c1556f28dd90cbc629810f48b083fb | pretraining/fairseq/data/legacy/masked_lm_dictionary.py | python | BertDictionary.cls | (self) | return self.cls_index | Helper to get index of cls symbol | Helper to get index of cls symbol | [
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"""Helper to get index of cls symbol"""
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googleapis/python-dialogflow | e48ea001b7c8a4a5c1fe4b162bad49ea397458e9 | google/cloud/dialogflow_v2/services/knowledge_bases/async_client.py | python | KnowledgeBasesAsyncClient.list_knowledge_bases | (
self,
request: Union[knowledge_base.ListKnowledgeBasesRequest, dict] = None,
*,
parent: str = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) | return response | r"""Returns the list of all knowledge bases of the
specified agent.
Args:
request (Union[google.cloud.dialogflow_v2.types.ListKnowledgeBasesRequest, dict]):
The request object. Request message for
[KnowledgeBases.ListKnowledgeBases][google.cloud.dialogflow.v2.KnowledgeBases.ListKnowledgeBases].
parent (:class:`str`):
Required. The project to list of knowledge bases for.
Format:
``projects/<Project ID>/locations/<Location ID>``.
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.cloud.dialogflow_v2.services.knowledge_bases.pagers.ListKnowledgeBasesAsyncPager:
Response message for
[KnowledgeBases.ListKnowledgeBases][google.cloud.dialogflow.v2.KnowledgeBases.ListKnowledgeBases].
Iterating over this object will yield results and
resolve additional pages automatically. | r"""Returns the list of all knowledge bases of the
specified agent. | [
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] | async def list_knowledge_bases(
self,
request: Union[knowledge_base.ListKnowledgeBasesRequest, dict] = None,
*,
parent: str = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListKnowledgeBasesAsyncPager:
r"""Returns the list of all knowledge bases of the
specified agent.
Args:
request (Union[google.cloud.dialogflow_v2.types.ListKnowledgeBasesRequest, dict]):
The request object. Request message for
[KnowledgeBases.ListKnowledgeBases][google.cloud.dialogflow.v2.KnowledgeBases.ListKnowledgeBases].
parent (:class:`str`):
Required. The project to list of knowledge bases for.
Format:
``projects/<Project ID>/locations/<Location ID>``.
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.cloud.dialogflow_v2.services.knowledge_bases.pagers.ListKnowledgeBasesAsyncPager:
Response message for
[KnowledgeBases.ListKnowledgeBases][google.cloud.dialogflow.v2.KnowledgeBases.ListKnowledgeBases].
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
request = knowledge_base.ListKnowledgeBasesRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method_async.wrap_method(
self._client._transport.list_knowledge_bases,
default_timeout=None,
client_info=DEFAULT_CLIENT_INFO,
)
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Send the request.
response = await rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
# This method is paged; wrap the response in a pager, which provides
# an `__aiter__` convenience method.
response = pagers.ListKnowledgeBasesAsyncPager(
method=rpc, request=request, response=response, metadata=metadata,
)
# Done; return the response.
return response | [
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uqfoundation/multiprocess | 028cc73f02655e6451d92e5147d19d8c10aebe50 | py3.6/multiprocess/managers.py | python | Server.number_of_objects | (self, c) | return len(self.id_to_refcount) | Number of shared objects | Number of shared objects | [
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'''
Number of shared objects
'''
# Doesn't use (len(self.id_to_obj) - 1) as we shouldn't count ident='0'
return len(self.id_to_refcount) | [
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tryolabs/luminoth | 9109d8b98bcbb0ad4e8e0c928da0b20627fa774f | luminoth/models/base/truncated_base_network.py | python | TruncatedBaseNetwork.get_trainable_vars | (self) | return trainable_vars | Returns a list of the variables that are trainable.
Returns:
trainable_variables: a tuple of `tf.Variable`. | Returns a list of the variables that are trainable. | [
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] | def get_trainable_vars(self):
"""
Returns a list of the variables that are trainable.
Returns:
trainable_variables: a tuple of `tf.Variable`.
"""
all_trainable = super(TruncatedBaseNetwork, self).get_trainable_vars()
# Get the index of the last endpoint scope variable.
# For example, if the endpoint for ResNet-50 is set as
# "block4/unit_3/bottleneck_v1/conv2", then it will get 155,
# because the variables (with their indexes) are:
# 153 block4/unit_3/bottleneck_v1/conv2/weights:0
# 154 block4/unit_3/bottleneck_v1/conv2/BatchNorm/beta:0
# 155 block4/unit_3/bottleneck_v1/conv2/BatchNorm/gamma:0
var_iter = enumerate(v.name for v in all_trainable)
scope_var_index_iter = (
i for i, name in var_iter if self._endpoint in name
)
index = None
for index in scope_var_index_iter:
pass
if index is None:
# Resulting `trainable_vars` is empty, possibly due to the
# `fine_tune_from` starting after the endpoint.
trainable_vars = tuple()
else:
trainable_vars = all_trainable[:index + 1]
if self._use_tail and not self._freeze_tail:
if self._architecture == 'resnet_v1_101':
# Retrieve the trainable vars out of the tail.
# TODO: Tail should be configurable too, to avoid hard-coding
# the trainable portion to `block4` and allow using something
# in block4 as endpoint.
var_iter = enumerate(v.name for v in all_trainable)
try:
index = next(i for i, name in var_iter if 'block4' in name)
except StopIteration:
raise ValueError(
'"block4" not present in the trainable vars retrieved '
'from base network.'
)
trainable_vars += all_trainable[index:]
return trainable_vars | [
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romanvm/python-web-pdb | 243f69b91907af97f0c14e91c30217f8850eea6c | web_pdb/__init__.py | python | set_trace | (host='', port=5555, patch_stdstreams=False) | Start the debugger
This method suspends execution of the current script
and starts a PDB debugging session. The web-interface is opened
on the specified port (default: ``5555``).
Example::
import web_pdb;web_pdb.set_trace()
Subsequent :func:`set_trace` calls can be used as hardcoded breakpoints.
:param host: web-UI hostname or IP-address
:type host: str
:param port: web-UI port. If ``port=-1``, choose a random port value
between 32768 and 65536.
:type port: int
:param patch_stdstreams: redirect all standard input and output
streams to the web-UI.
:type patch_stdstreams: bool | Start the debugger | [
"Start",
"the",
"debugger"
] | def set_trace(host='', port=5555, patch_stdstreams=False):
"""
Start the debugger
This method suspends execution of the current script
and starts a PDB debugging session. The web-interface is opened
on the specified port (default: ``5555``).
Example::
import web_pdb;web_pdb.set_trace()
Subsequent :func:`set_trace` calls can be used as hardcoded breakpoints.
:param host: web-UI hostname or IP-address
:type host: str
:param port: web-UI port. If ``port=-1``, choose a random port value
between 32768 and 65536.
:type port: int
:param patch_stdstreams: redirect all standard input and output
streams to the web-UI.
:type patch_stdstreams: bool
"""
pdb = WebPdb.active_instance
if pdb is None:
pdb = WebPdb(host, port, patch_stdstreams)
else:
# If the debugger is still attached reset trace to a new location
pdb.remove_trace()
pdb.set_trace(sys._getframe().f_back) | [
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yuanxiaosc/Schema-based-Knowledge-Extraction | ac0f07cd1088f24cb8f76c271fd2b49ea6100ca8 | evaluation.py | python | del_bookname | (entity_name) | return entity_name | delete the book name | delete the book name | [
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"book",
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] | def del_bookname(entity_name):
"""delete the book name"""
if entity_name.startswith(u'《') and entity_name.endswith(u'》'):
entity_name = entity_name[1:-1]
return entity_name | [
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kanzure/nanoengineer | 874e4c9f8a9190f093625b267f9767e19f82e6c4 | cad/src/graphics/widgets/ThumbView.py | python | ElementView.resetView | (self, scale = 2.0) | Reset current view. | Reset current view. | [
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] | def resetView(self, scale = 2.0):
"""
Reset current view.
"""
ThumbView.resetView(self)
self.scale = scale | [
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leo-editor/leo-editor | 383d6776d135ef17d73d935a2f0ecb3ac0e99494 | leo/core/leoGlobals.py | python | KeyStroke.finalize_char | (self, s) | return self.strip_shift(s) | Perform very-last-minute translations on bindings. | Perform very-last-minute translations on bindings. | [
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] | def finalize_char(self, s):
"""Perform very-last-minute translations on bindings."""
#
# Retain "bigger" spelling for gang-of-four bindings with modifiers.
shift_d = {
'bksp': 'BackSpace',
'backspace': 'BackSpace',
'backtab': 'Tab', # The shift mod will convert to 'Shift+Tab',
'linefeed': 'Return',
'\r': 'Return',
'return': 'Return',
'tab': 'Tab',
}
if self.mods and s.lower() in shift_d:
return shift_d.get(s.lower())
# Returning '' breaks existing code.
#
# Make all other translations...
#
# This dict ensures proper capitalization.
# It also translates legacy Tk binding names to ascii chars.
translate_d = {
#
# The gang of four...
'bksp': 'BackSpace',
'backspace': 'BackSpace',
'backtab': 'Tab', # The shift mod will convert to 'Shift+Tab',
'linefeed': '\n',
'\r': '\n',
'return': '\n',
'tab': 'Tab',
#
# Special chars...
'delete': 'Delete',
'down': 'Down',
'end': 'End',
'enter': 'Enter',
'escape': 'Escape',
'home': 'Home',
'insert': 'Insert',
'left': 'Left',
'next': 'Next',
'prior': 'Prior',
'right': 'Right',
'up': 'Up',
#
# Qt key names...
'del': 'Delete',
'dnarrow': 'Down',
'esc': 'Escape',
'ins': 'Insert',
'ltarrow': 'Left',
'pagedn': 'Next',
'pageup': 'Prior',
'pgdown': 'Next',
'pgup': 'Prior',
'rtarrow': 'Right',
'uparrow': 'Up',
#
# Legacy Tk binding names...
"ampersand": "&",
"asciicircum": "^",
"asciitilde": "~",
"asterisk": "*",
"at": "@",
"backslash": "\\",
"bar": "|",
"braceleft": "{",
"braceright": "}",
"bracketleft": "[",
"bracketright": "]",
"colon": ":",
"comma": ",",
"dollar": "$",
"equal": "=",
"exclam": "!",
"greater": ">",
"less": "<",
"minus": "-",
"numbersign": "#",
"quotedbl": '"',
"quoteright": "'",
"parenleft": "(",
"parenright": ")",
"percent": "%",
"period": ".",
"plus": "+",
"question": "?",
"quoteleft": "`",
"semicolon": ";",
"slash": "/",
"space": " ",
"underscore": "_",
}
#
# pylint: disable=undefined-loop-variable
# Looks like a pylint bug.
if s in (None, 'none', 'None'):
return 'None'
if s.lower() in translate_d:
s = translate_d.get(s.lower())
return self.strip_shift(s)
if len(s) > 1 and s.find(' ') > -1:
# #917: not a pure, but should be ignored.
return ''
if s.isalpha():
if len(s) == 1:
if 'shift' in self.mods:
if len(self.mods) == 1:
self.mods.remove('shift')
s = s.upper()
else:
s = s.lower()
elif self.mods:
s = s.lower()
else:
# 917: Ignore multi-byte alphas not in the table.
s = ''
if 0:
# Make sure all special chars are in translate_d.
if g.app.gui: # It may not exist yet.
if s.capitalize() in g.app.gui.specialChars:
s = s.capitalize()
return s
#
# Translate shifted keys to their appropriate alternatives.
return self.strip_shift(s) | [
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leaderj1001/Stand-Alone-Self-Attention | a983f0f643632b1f2b7b8b27693182f22e9e574c | model.py | python | Model._make_layer | (self, block, planes, num_blocks, stride) | return nn.Sequential(*layers) | [] | def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1] * (num_blocks - 1)
layers = []
for stride in strides:
layers.append(block(self.in_places, planes, stride))
self.in_places = planes * block.expansion
return nn.Sequential(*layers) | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/db/backends/base/base.py | python | BaseDatabaseWrapper.disable_constraint_checking | (self) | return False | Backends can implement as needed to temporarily disable foreign key
constraint checking. Should return True if the constraints were
disabled and will need to be reenabled. | Backends can implement as needed to temporarily disable foreign key
constraint checking. Should return True if the constraints were
disabled and will need to be reenabled. | [
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] | def disable_constraint_checking(self):
"""
Backends can implement as needed to temporarily disable foreign key
constraint checking. Should return True if the constraints were
disabled and will need to be reenabled.
"""
return False | [
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openai/mujoco-worldgen | 39f52b1b47aed499925a6a214b58bdbdb4e2f75e | mujoco_worldgen/objs/obj.py | python | Obj.set_absolute_position | (self, origin) | Set absolute position of objects, recursing throught all children.
origin - absolute position of this object's origin | Set absolute position of objects, recursing throught all children.
origin - absolute position of this object's origin | [
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"-",
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"of",
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"s",
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] | def set_absolute_position(self, origin):
'''
Set absolute position of objects, recursing throught all children.
origin - absolute position of this object's origin
'''
assert len(origin) == 3, "Invalid origin: {}".format(origin)
assert len(self.relative_position) == 2, \
"Invalid relative_position: {}".format(self.relative_position)
self.absolute_position = np.array(origin, dtype=np.float)
# Note relative_position is X,Y but our absolute_position is X,Y,Z
self.absolute_position[:2] += self.relative_position
for placement_name, children in self.children.items():
placement = self.placements[placement_name]
offset = self.absolute_position + placement['origin']
for child, _ in children:
if child.placeable:
child.set_absolute_position(offset)
# Calculate positions of markers
for marker in self.markers:
if marker['relative_xyz'] is not None:
relative_xyz = np.array(marker['relative_xyz'], dtype='f8')
marker['position'] = relative_xyz * np.array(self.size, dtype=np.float)
for i in range(3):
if np.abs(self.size[i]) < 1e-4:
marker["position"][i] = relative_xyz[i]
marker['position'] -= self.size * 0.5
elif marker['absolute_xyz'] is not None:
marker['position'] = np.array(marker['absolute_xyz'], dtype='f8')
else:
assert False, 'Neither absolute nor relative xyz provided.' | [
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NervanaSystems/neon | 8c3fb8a93b4a89303467b25817c60536542d08bd | neon/backends/layer_mkl.py | python | BatchNormLayerMKL.__init__ | (self, in_shape) | [] | def __init__(self, in_shape):
self.dnnPrimitives = np.zeros((1, 20), dtype=np.uint64)
self.init_f = 0
self.init_b = 0
self.in_shape = in_shape
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django-haystack/django-haystack | b6dd72e6b5c97b782f5436b7bb4e8227ba6e3b06 | haystack/views.py | python | SearchView.get_context | (self) | return context | [] | def get_context(self):
(paginator, page) = self.build_page()
context = {
"query": self.query,
"form": self.form,
"page": page,
"paginator": paginator,
"suggestion": None,
}
if (
hasattr(self.results, "query")
and self.results.query.backend.include_spelling
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context["suggestion"] = self.form.get_suggestion()
context.update(self.extra_context())
return context | [
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celery/billiard | 269ef67354a3a205cea780aa8ea451e0d17cd37c | billiard/util.py | python | get_pdeathsig | () | Return the current value of the parent process death signal | Return the current value of the parent process death signal | [
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"of",
"the",
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] | def get_pdeathsig():
"""
Return the current value of the parent process death signal
"""
if not sys.platform.startswith('linux'):
# currently we support only linux platform.
raise OSError()
try:
if 'cffi' in sys.modules:
ffi = cffi.FFI()
ffi.cdef("int prctl (int __option, ...);")
arg = ffi.new("int *")
C = ffi.dlopen(None)
C.prctl(PR_GET_PDEATHSIG, arg)
return arg[0]
else:
sig = ctypes.c_int()
libc = ctypes.cdll.LoadLibrary("libc.so.6")
libc.prctl(PR_GET_PDEATHSIG, ctypes.byref(sig))
return sig.value
except Exception:
raise OSError() | [
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WikidPad/WikidPad | 558109638807bc76b4672922686e416ab2d5f79c | WikidPad/lib/aui/tabart.py | python | AuiCommandCapture.ProcessEvent | (self, event) | return False | Processes an event, searching event tables and calling zero or more suitable
event handler function(s).
:param `event`: the event to process.
:note: Normally, your application would not call this function: it is called
in the wxPython implementation to dispatch incoming user interface events
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However, you might need to call it if implementing new functionality (such as
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An instance where you might actually override the :meth:`ProcessEvent` function is where
you want to direct event processing to event handlers not normally noticed by
wxPython. For example, in the document/view architecture, documents and views
are potential event handlers. When an event reaches a frame, :meth:`ProcessEvent` will
need to be called on the associated document and view in case event handler
functions are associated with these objects.
The normal order of event table searching is as follows:
1. If the object is disabled (via a call to :meth:`EvtHandler.SetEvtHandlerEnabled`) the function
skips to step (6).
2. If the object is a :class:`wx.Window`, :meth:`ProcessEvent` is recursively called on the window's
:class:`wx.Validator`. If this returns ``True``, the function exits.
3. wxWidgets `SearchEventTable` is called for this event handler. If this fails, the
base class table is tried, and so on until no more tables exist or an appropriate
function was found, in which case the function exits.
4. The search is applied down the entire chain of event handlers (usually the chain
has a length of one). If this succeeds, the function exits.
5. If the object is a :class:`wx.Window` and the event is a :class:`CommandEvent`, :meth:`ProcessEvent` is
recursively applied to the parent window's event handler. If this returns ``True``,
the function exits.
6. Finally, :meth:`ProcessEvent` is called on the :class:`App` object. | Processes an event, searching event tables and calling zero or more suitable
event handler function(s). | [
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"""
Processes an event, searching event tables and calling zero or more suitable
event handler function(s).
:param `event`: the event to process.
:note: Normally, your application would not call this function: it is called
in the wxPython implementation to dispatch incoming user interface events
to the framework (and application).
However, you might need to call it if implementing new functionality (such as
a new control) where you define new event types, as opposed to allowing the
user to override functions.
An instance where you might actually override the :meth:`ProcessEvent` function is where
you want to direct event processing to event handlers not normally noticed by
wxPython. For example, in the document/view architecture, documents and views
are potential event handlers. When an event reaches a frame, :meth:`ProcessEvent` will
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1. If the object is disabled (via a call to :meth:`EvtHandler.SetEvtHandlerEnabled`) the function
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2. If the object is a :class:`wx.Window`, :meth:`ProcessEvent` is recursively called on the window's
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3. wxWidgets `SearchEventTable` is called for this event handler. If this fails, the
base class table is tried, and so on until no more tables exist or an appropriate
function was found, in which case the function exits.
4. The search is applied down the entire chain of event handlers (usually the chain
has a length of one). If this succeeds, the function exits.
5. If the object is a :class:`wx.Window` and the event is a :class:`CommandEvent`, :meth:`ProcessEvent` is
recursively applied to the parent window's event handler. If this returns ``True``,
the function exits.
6. Finally, :meth:`ProcessEvent` is called on the :class:`App` object.
"""
if event.GetEventType() == wx.wxEVT_COMMAND_MENU_SELECTED:
self._last_id = event.GetId()
return True
if self.GetNextHandler():
return self.GetNextHandler().ProcessEvent(event)
return False | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/cgi.py | python | FieldStorage.make_file | (self) | Overridable: return a readable & writable file.
The file will be used as follows:
- data is written to it
- seek(0)
- data is read from it
The file is opened in binary mode for files, in text mode
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"""Overridable: return a readable & writable file.
The file will be used as follows:
- data is written to it
- seek(0)
- data is read from it
The file is opened in binary mode for files, in text mode
for other fields
This version opens a temporary file for reading and writing,
and immediately deletes (unlinks) it. The trick (on Unix!) is
that the file can still be used, but it can't be opened by
another process, and it will automatically be deleted when it
is closed or when the current process terminates.
If you want a more permanent file, you derive a class which
overrides this method. If you want a visible temporary file
that is nevertheless automatically deleted when the script
terminates, try defining a __del__ method in a derived class
which unlinks the temporary files you have created.
"""
if self._binary_file:
return tempfile.TemporaryFile("wb+")
else:
return tempfile.TemporaryFile("w+",
encoding=self.encoding, newline = '\n') | [
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conan7882/adversarial-autoencoders | 4960f252784a7dd2fbe203d7dad65938b57ee9c2 | src/models/layers.py | python | transpose_conv | (
filter_size,
out_dim,
layer_dict,
inputs=None,
out_shape=None,
stride=2,
padding='SAME',
trainable=True,
nl=tf.identity,
init_w=None,
init_b=tf.zeros_initializer(),
wd=0,
constant_init=False,
name='dconv') | [] | def transpose_conv(
filter_size,
out_dim,
layer_dict,
inputs=None,
out_shape=None,
stride=2,
padding='SAME',
trainable=True,
nl=tf.identity,
init_w=None,
init_b=tf.zeros_initializer(),
wd=0,
constant_init=False,
name='dconv'):
if inputs is None:
inputs = layer_dict['cur_input']
stride = get_shape4D(stride)
in_dim = inputs.get_shape().as_list()[-1]
# TODO other ways to determine the output shape
x_shape = tf.shape(inputs)
# assume output shape is input_shape*stride
if out_shape is None:
out_shape = tf.stack([x_shape[0],
tf.multiply(x_shape[1], stride[1]),
tf.multiply(x_shape[2], stride[2]),
out_dim])
filter_shape = get_shape2D(filter_size) + [out_dim, in_dim]
with tf.variable_scope(name) as scope:
if wd > 0:
regularizer = tf.contrib.layers.l2_regularizer(scale=wd)
else:
regularizer=None
weights = tf.get_variable('weights',
filter_shape,
initializer=init_w,
trainable=trainable,
regularizer=regularizer)
biases = tf.get_variable('biases',
[out_dim],
initializer=init_b,
trainable=trainable)
output = tf.nn.conv2d_transpose(inputs,
weights,
output_shape=out_shape,
strides=stride,
padding=padding,
name=scope.name)
output = tf.nn.bias_add(output, biases)
output.set_shape([None, None, None, out_dim])
output = nl(output, name='output')
layer_dict['cur_input'] = output
return output | [
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lovelylain/pyctp | fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d | example/ctp/option/ApiStruct.py | python | QryExchangeMarginRateAdjust.__init__ | (self, BrokerID='', InstrumentID='', HedgeFlag=HF_Speculation) | [] | def __init__(self, BrokerID='', InstrumentID='', HedgeFlag=HF_Speculation):
self.BrokerID = '' #经纪公司代码, char[11]
self.InstrumentID = '' #合约代码, char[31]
self.HedgeFlag = '' | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/build/lib.linux-x86_64-2.7/flaskbb/utils/populate.py | python | create_latest_db | (target="default@head") | Creates the database including the schema using SQLAlchemy's
db.create_all method instead of going through all the database revisions.
The revision will be set to 'head' which indicates the latest alembic
revision.
:param target: The target branch. Defaults to 'default@head'. | Creates the database including the schema using SQLAlchemy's
db.create_all method instead of going through all the database revisions.
The revision will be set to 'head' which indicates the latest alembic
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"""Creates the database including the schema using SQLAlchemy's
db.create_all method instead of going through all the database revisions.
The revision will be set to 'head' which indicates the latest alembic
revision.
:param target: The target branch. Defaults to 'default@head'.
"""
if not database_exists(db.engine.url):
create_database(db.engine.url)
db.create_all()
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ScrumDoLLC/ScrumDo | 641729480c79d706e63bb6f1e15c5a9eac11ba6b | scrumdo-web/apps/django_evolution/mutations.py | python | SQLMutation.simulate | (self, app_label, proj_sig, database=None) | SQL mutations cannot be simulated unless an update function is
provided | SQL mutations cannot be simulated unless an update function is
provided | [
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"unless",
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"function",
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] | def simulate(self, app_label, proj_sig, database=None):
"""SQL mutations cannot be simulated unless an update function is
provided"""
if callable(self.update_func):
self.update_func(app_label, proj_sig)
else:
raise CannotSimulate('Cannot simulate SQLMutations') | [
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home-assistant-libs/pytradfri | ef2614b0ccdf628abc3b9559dc00b95ec6e4bd72 | pytradfri/gateway.py | python | GatewayInfo.id | (self) | return self.raw.get(ATTR_GATEWAY_ID) | Return the gateway id. | Return the gateway id. | [
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"""Return the gateway id."""
return self.raw.get(ATTR_GATEWAY_ID) | [
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snorkel-team/snorkel | 942e8a7b3af2bf108ef82c920bc7c2ddcbf9eda7 | snorkel/augmentation/apply/pandas.py | python | PandasTFApplier.apply | (self, df: pd.DataFrame, progress_bar: bool = True) | return pd.concat(x_transformed, axis=1).T.infer_objects() | Augment a Pandas DataFrame of data points using TFs and policy.
Parameters
----------
df
Pandas DataFrame containing data points to be transformed
progress_bar
Display a progress bar?
Returns
-------
pd.DataFrame
Pandas DataFrame of data points in augmented data set | Augment a Pandas DataFrame of data points using TFs and policy. | [
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"."
] | def apply(self, df: pd.DataFrame, progress_bar: bool = True) -> pd.DataFrame:
"""Augment a Pandas DataFrame of data points using TFs and policy.
Parameters
----------
df
Pandas DataFrame containing data points to be transformed
progress_bar
Display a progress bar?
Returns
-------
pd.DataFrame
Pandas DataFrame of data points in augmented data set
"""
x_transformed: List[pd.Series] = []
for _, x in tqdm(df.iterrows(), total=len(df), disable=(not progress_bar)):
x_transformed.extend(self._apply_policy_to_data_point(x))
return pd.concat(x_transformed, axis=1).T.infer_objects() | [
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w3h/isf | 6faf0a3df185465ec17369c90ccc16e2a03a1870 | lib/thirdparty/scapy/packet.py | python | Packet.sprintf | (self, fmt, relax=1) | return s | sprintf(format, [relax=1]) -> str
where format is a string that can include directives. A directive begins and
ends by % and has the following format %[fmt[r],][cls[:nb].]field%.
fmt is a classic printf directive, "r" can be appended for raw substitution
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Ex : p.sprintf("%.time% %-15s,IP.src% -> %-15s,IP.dst% %IP.chksum% "
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Moreover, the format string can include conditionnal statements. A conditionnal
statement looks like : {layer:string} where layer is a layer name, and string
is the string to insert in place of the condition if it is true, i.e. if layer
is present. If layer is preceded by a "!", the result si inverted. Conditions
can be imbricated. A valid statement can be :
p.sprintf("This is a{TCP: TCP}{UDP: UDP}{ICMP:n ICMP} packet")
p.sprintf("{IP:%IP.dst% {ICMP:%ICMP.type%}{TCP:%TCP.dport%}}")
A side effect is that, to obtain "{" and "}" characters, you must use
"%(" and "%)". | sprintf(format, [relax=1]) -> str
where format is a string that can include directives. A directive begins and
ends by % and has the following format %[fmt[r],][cls[:nb].]field%. | [
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"""sprintf(format, [relax=1]) -> str
where format is a string that can include directives. A directive begins and
ends by % and has the following format %[fmt[r],][cls[:nb].]field%.
fmt is a classic printf directive, "r" can be appended for raw substitution
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Moreover, the format string can include conditionnal statements. A conditionnal
statement looks like : {layer:string} where layer is a layer name, and string
is the string to insert in place of the condition if it is true, i.e. if layer
is present. If layer is preceded by a "!", the result si inverted. Conditions
can be imbricated. A valid statement can be :
p.sprintf("This is a{TCP: TCP}{UDP: UDP}{ICMP:n ICMP} packet")
p.sprintf("{IP:%IP.dst% {ICMP:%ICMP.type%}{TCP:%TCP.dport%}}")
A side effect is that, to obtain "{" and "}" characters, you must use
"%(" and "%)".
"""
escape = { "%": "%",
"(": "{",
")": "}" }
# Evaluate conditions
while "{" in fmt:
i = fmt.rindex("{")
j = fmt[i+1:].index("}")
cond = fmt[i+1:i+j+1]
k = cond.find(":")
if k < 0:
raise Scapy_Exception("Bad condition in format string: [%s] (read sprintf doc!)"%cond)
cond,format = cond[:k],cond[k+1:]
res = False
if cond[0] == "!":
res = True
cond = cond[1:]
if self.haslayer(cond):
res = not res
if not res:
format = ""
fmt = fmt[:i]+format+fmt[i+j+2:]
# Evaluate directives
s = ""
while "%" in fmt:
i = fmt.index("%")
s += fmt[:i]
fmt = fmt[i+1:]
if fmt and fmt[0] in escape:
s += escape[fmt[0]]
fmt = fmt[1:]
continue
try:
i = fmt.index("%")
sfclsfld = fmt[:i]
fclsfld = sfclsfld.split(",")
if len(fclsfld) == 1:
f = "s"
clsfld = fclsfld[0]
elif len(fclsfld) == 2:
f,clsfld = fclsfld
else:
raise Scapy_Exception
if "." in clsfld:
cls,fld = clsfld.split(".")
else:
cls = self.__class__.__name__
fld = clsfld
num = 1
if ":" in cls:
cls,num = cls.split(":")
num = int(num)
fmt = fmt[i+1:]
except:
raise Scapy_Exception("Bad format string [%%%s%s]" % (fmt[:25], fmt[25:] and "..."))
else:
if fld == "time":
val = time.strftime("%H:%M:%S.%%06i", time.localtime(self.time)) % int((self.time-int(self.time))*1000000)
elif cls == self.__class__.__name__ and hasattr(self, fld):
if num > 1:
val = self.payload.sprintf("%%%s,%s:%s.%s%%" % (f,cls,num-1,fld), relax)
f = "s"
elif f[-1] == "r": # Raw field value
val = getattr(self,fld)
f = f[:-1]
if not f:
f = "s"
else:
val = getattr(self,fld)
if fld in self.fieldtype:
val = self.fieldtype[fld].i2repr(self,val)
else:
val = self.payload.sprintf("%%%s%%" % sfclsfld, relax)
f = "s"
s += ("%"+f) % val
s += fmt
return s | [
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krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit /tools/inject/plugins/generic/takeover.py | python | Takeover.osSmb | (self) | [] | def osSmb(self):
self.checkDbmsOs()
if not Backend.isOs(OS.WINDOWS):
errMsg = "the back-end DBMS underlying operating system is "
errMsg += "not Windows: it is not possible to perform the SMB "
errMsg += "relay attack"
raise SqlmapUnsupportedDBMSException(errMsg)
if not isStackingAvailable() and not conf.direct:
if Backend.getIdentifiedDbms() in (DBMS.PGSQL, DBMS.MSSQL):
errMsg = "on this back-end DBMS it is only possible to "
errMsg += "perform the SMB relay attack if stacked "
errMsg += "queries are supported"
raise SqlmapUnsupportedDBMSException(errMsg)
elif Backend.isDbms(DBMS.MYSQL):
debugMsg = "since stacked queries are not supported, "
debugMsg += "sqlmap is going to perform the SMB relay "
debugMsg += "attack via inference blind SQL injection"
logger.debug(debugMsg)
printWarn = True
warnMsg = "it is unlikely that this attack will be successful "
if Backend.isDbms(DBMS.MYSQL):
warnMsg += "because by default MySQL on Windows runs as "
warnMsg += "Local System which is not a real user, it does "
warnMsg += "not send the NTLM session hash when connecting to "
warnMsg += "a SMB service"
elif Backend.isDbms(DBMS.PGSQL):
warnMsg += "because by default PostgreSQL on Windows runs "
warnMsg += "as postgres user which is a real user of the "
warnMsg += "system, but not within the Administrators group"
elif Backend.isDbms(DBMS.MSSQL) and Backend.isVersionWithin(("2005", "2008")):
warnMsg += "because often Microsoft SQL Server %s " % Backend.getVersion()
warnMsg += "runs as Network Service which is not a real user, "
warnMsg += "it does not send the NTLM session hash when "
warnMsg += "connecting to a SMB service"
else:
printWarn = False
if printWarn:
logger.warn(warnMsg)
self.smb() | [
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Yelp/elastalert | 1dc4f30f30d39a689f419ce19c7e2e4d67a50be3 | elastalert/ruletypes.py | python | SpikeRule.add_count_data | (self, data) | Add count data to the rule. Data should be of the form {ts: count}. | Add count data to the rule. Data should be of the form {ts: count}. | [
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""" Add count data to the rule. Data should be of the form {ts: count}. """
if len(data) > 1:
raise EAException('add_count_data can only accept one count at a time')
for ts, count in data.items():
self.handle_event({self.ts_field: ts}, count, 'all') | [
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sergioburdisso/pyss3 | 70c37853f3f56a60c3df9b94b678ca3f0db843de | pyss3/util.py | python | is_a_collection | (o) | return hasattr(o, "__getitem__") and ((PY2 and not isinstance(o, basestring)) or
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/simulators/middlewares/robots/ur5.py | python | UR5ROSMiddleware.get_pid | (self, joint_ids) | Get the PID coefficients associated to the given joint ids.
Args:
joint_ids (list[int]): list of unique joint ids.
Returns:
list[np.array[float[3]]]: list of PID coefficients for each joint. | Get the PID coefficients associated to the given joint ids. | [
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"""
Get the PID coefficients associated to the given joint ids.
Args:
joint_ids (list[int]): list of unique joint ids.
Returns:
list[np.array[float[3]]]: list of PID coefficients for each joint.
"""
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brightmart/slot_filling_intent_joint_model | 06ee6932bca2e07b3667e7edbef878a79cdcf2d1 | joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py | python | index_sentence_with_vocabulary | (sentence,word2id,sequence_length=None,knowledge_path=None) | return index_list | index sentence with vocabulary, return list of index | index sentence with vocabulary, return list of index | [
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"""index sentence with vocabulary, return list of index"""
#print("index_sentence_with_vocabulary:",knowledge_path)
result_list=tokenize_sentence(sentence,knowledge_path=knowledge_path)
result_list=result_list[0:sequence_length] #truncate
unk_id=word2id[UNK]
index_list=[word2id[PAD]]*sequence_length #pad
for i,element in enumerate(result_list):
index_list[i]=word2id.get(element,unk_id)
#print("####index_sentence_with_vocabulary.sentence:",sentence);print(index_list)
return index_list | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/idlelib/RemoteDebugger.py | python | IdbProxy.run | (self, cmd, locals) | [] | def run(self, cmd, locals):
# Ignores locals on purpose!
seq = self.conn.asyncqueue(self.oid, "run", (cmd,), {})
self.shell.interp.active_seq = seq | [
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tartiflette/tartiflette | e292c28ed4fa279ecedb8980fc3741965bd28c87 | tartiflette/language/parsers/lark/transformers/converters.py | python | lark_to_non_null_type_node | (tree: "Tree") | return NonNullTypeNode(
type=tree.children[0].value, location=lark_to_location_node(tree.meta)
) | Creates and returns a NonNullTypeNode instance extracted from the parsing
of the tree instance.
:param tree: the Tree to parse in order to extract the proper node
:type tree: Tree
:return: a NonNullTypeNode instance extracted from the parsing of the tree
:rtype: NonNullTypeNode | Creates and returns a NonNullTypeNode instance extracted from the parsing
of the tree instance.
:param tree: the Tree to parse in order to extract the proper node
:type tree: Tree
:return: a NonNullTypeNode instance extracted from the parsing of the tree
:rtype: NonNullTypeNode | [
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"""
Creates and returns a NonNullTypeNode instance extracted from the parsing
of the tree instance.
:param tree: the Tree to parse in order to extract the proper node
:type tree: Tree
:return: a NonNullTypeNode instance extracted from the parsing of the tree
:rtype: NonNullTypeNode
"""
return NonNullTypeNode(
type=tree.children[0].value, location=lark_to_location_node(tree.meta)
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mikecrittenden/zen-coding-gedit | 49966219b1e9b7a1d0d8b4def6a32b6c386b8041 | zencoding/filters/haml.py | python | make_attributes_string | (tag, profile) | return attrs | Creates HTML attributes string from tag according to profile settings
@type tag: ZenNode
@type profile: dict | Creates HTML attributes string from tag according to profile settings | [
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] | def make_attributes_string(tag, profile):
"""
Creates HTML attributes string from tag according to profile settings
@type tag: ZenNode
@type profile: dict
"""
# make attribute string
attrs = ''
attr_quote = profile['attr_quotes'] == 'single' and "'" or '"'
cursor = profile['place_cursor'] and zen_coding.get_caret_placeholder() or ''
# use short notation for ID and CLASS attributes
for a in tag.attributes:
name_lower = a['name'].lower()
if name_lower == 'id':
attrs += '#' + (a['value'] or cursor)
elif name_lower == 'class':
attrs += '.' + (a['value'] or cursor)
other_attrs = []
# process other attributes
for a in tag.attributes:
name_lower = a['name'].lower()
if name_lower != 'id' and name_lower != 'class':
attr_name = profile['attr_case'] == 'upper' and a['name'].upper() or name_lower
other_attrs.append(':' + attr_name + ' => ' + attr_quote + (a['value'] or cursor) + attr_quote)
if other_attrs:
attrs += '{' + ', '.join(other_attrs) + '}'
return attrs | [
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respeaker/get_started_with_respeaker | ec859759fcec7e683a5e09328a8ea307046f353d | files/usr/lib/python2.7/site-packages/tornado/auth.py | python | TwitterMixin.authenticate_redirect | (self, callback_uri=None) | Just like `~OAuthMixin.authorize_redirect`, but
auto-redirects if authorized.
This is generally the right interface to use if you are using
Twitter for single-sign on. | Just like `~OAuthMixin.authorize_redirect`, but
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"""Just like `~OAuthMixin.authorize_redirect`, but
auto-redirects if authorized.
This is generally the right interface to use if you are using
Twitter for single-sign on.
"""
http = self.get_auth_http_client()
http.fetch(self._oauth_request_token_url(callback_uri=callback_uri), self.async_callback(
self._on_request_token, self._OAUTH_AUTHENTICATE_URL, None)) | [
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anson0910/CNN_face_detection | 62cf7ea5a737b758095a9b7e7a07760cb4f306df | face_detection/face_48_fddb_fullconv.py | python | cal_face_24c | (caffe_img, rectangles) | return result | :param caffe_image: image in caffe style to detect faces
:param rectangles: rectangles in form [x11, y11, x12, y12, confidence, current_scale]
:return: rectangles after calibration | :param caffe_image: image in caffe style to detect faces
:param rectangles: rectangles in form [x11, y11, x12, y12, confidence, current_scale]
:return: rectangles after calibration | [
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'''
:param caffe_image: image in caffe style to detect faces
:param rectangles: rectangles in form [x11, y11, x12, y12, confidence, current_scale]
:return: rectangles after calibration
'''
height, width, channels = caffe_img.shape
result = []
for cur_rectangle in rectangles:
original_x1 = cur_rectangle[0]
original_y1 = cur_rectangle[1]
original_x2 = cur_rectangle[2]
original_y2 = cur_rectangle[3]
original_w = original_x2 - original_x1
original_h = original_y2 - original_y1
cropped_caffe_img = caffe_img[original_y1:original_y2, original_x1:original_x2] # crop image
output = net_24_cal.predict([cropped_caffe_img]) # predict through caffe
prediction = output[0] # (44, 1) ndarray
threshold = 0.1
indices = np.nonzero(prediction > threshold)[0] # ndarray of indices where prediction is larger than threshold
number_of_cals = len(indices) # number of calibrations larger than threshold
if number_of_cals == 0: # if no calibration is needed, check next rectangle
result.append(cur_rectangle)
continue
total_s_change = 0
total_x_change = 0
total_y_change = 0
for current_cal in range(number_of_cals): # accumulate changes, and calculate average
cal_label = int(indices[current_cal]) # should be number in 0~44
if (cal_label >= 0) and (cal_label <= 8): # decide s change
total_s_change += 0.83
elif (cal_label >= 9) and (cal_label <= 17):
total_s_change += 0.91
elif (cal_label >= 18) and (cal_label <= 26):
total_s_change += 1.0
elif (cal_label >= 27) and (cal_label <= 35):
total_s_change += 1.10
else:
total_s_change += 1.21
if cal_label % 9 <= 2: # decide x change
total_x_change += -0.17
elif (cal_label % 9 >= 6) and (cal_label % 9 <= 8): # ignore case when 3<=x<=5, since adding 0 doesn't change
total_x_change += 0.17
if cal_label % 3 == 0: # decide y change
total_y_change += -0.17
elif cal_label % 3 == 2: # ignore case when 1, since adding 0 doesn't change
total_y_change += 0.17
s_change = total_s_change / number_of_cals # calculate average
x_change = total_x_change / number_of_cals
y_change = total_y_change / number_of_cals
cur_result = cur_rectangle # inherit format and last two attributes from original rectangle
cur_result[0] = int(max(0, original_x1 - original_w * x_change / s_change))
cur_result[1] = int(max(0, original_y1 - original_h * y_change / s_change))
cur_result[2] = int(min(width, cur_result[0] + original_w / s_change))
cur_result[3] = int(min(height, cur_result[1] + original_h / s_change))
result.append(cur_result)
return result | [
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KeplerGO/pyke | c74a62e48e3cf1ea367524656cd836283c5ddd94 | kepcotrend.py | python | get_pcompsum | (pcomps,s) | return pcompsum | calculates the sum of basis vectors which are to be subtracted from the
light curve to produce the corrected data. | calculates the sum of basis vectors which are to be subtracted from the
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"""
calculates the sum of basis vectors which are to be subtracted from the
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"""
pcompsum = 0.
for i in range(len(s)):
pcompsum += s[i]*pcomps[i]
return pcompsum | [
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FSecureLABS/Jandroid | e31d0dab58a2bfd6ed8e0a387172b8bd7c893436 | libs/platform-tools/platform-tools_windows/systrace/catapult/third_party/pyserial/serial/rfc2217.py | python | TelnetOption.__init__ | (self, connection, name, option, send_yes, send_no, ack_yes, ack_no, initial_state, activation_callback=None) | \
Initialize option.
:param connection: connection used to transmit answers
:param name: a readable name for debug outputs
:param send_yes: what to send when option is to be enabled.
:param send_no: what to send when option is to be disabled.
:param ack_yes: what to expect when remote agrees on option.
:param ack_no: what to expect when remote disagrees on option.
:param initial_state: options initialized with REQUESTED are tried to
be enabled on startup. use INACTIVE for all others. | \
Initialize option.
:param connection: connection used to transmit answers
:param name: a readable name for debug outputs
:param send_yes: what to send when option is to be enabled.
:param send_no: what to send when option is to be disabled.
:param ack_yes: what to expect when remote agrees on option.
:param ack_no: what to expect when remote disagrees on option.
:param initial_state: options initialized with REQUESTED are tried to
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"""\
Initialize option.
:param connection: connection used to transmit answers
:param name: a readable name for debug outputs
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self.connection = connection
self.name = name
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self.send_no = send_no
self.ack_yes = ack_yes
self.ack_no = ack_no
self.state = initial_state
self.active = False
self.activation_callback = activation_callback | [
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/bleach/_vendor/parse.py | python | _checknetloc | (netloc) | [] | def _checknetloc(netloc):
if not netloc or not any(ord(c) > 127 for c in netloc):
return
# looking for characters like \u2100 that expand to 'a/c'
# IDNA uses NFKC equivalence, so normalize for this check
import unicodedata
n = netloc.replace('@', '') # ignore characters already included
n = n.replace(':', '') # but not the surrounding text
n = n.replace('#', '')
n = n.replace('?', '')
netloc2 = unicodedata.normalize('NFKC', n)
if n == netloc2:
return
for c in '/?#@:':
if c in netloc2:
raise ValueError("netloc '" + netloc + "' contains invalid " +
"characters under NFKC normalization") | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/reports/generic.py | python | GenericReportView.template_report | (self) | return original_template | [] | def template_report(self):
original_template = self.report_template_path or "reports/async/basic.html"
if self.is_rendered_as_email:
self.context.update(original_template=original_template)
return self.override_template
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IBM/lale | b4d6829c143a4735b06083a0e6c70d2cca244162 | lale/search/search_space.py | python | SearchSpace.default | (self) | return self._default | Return an optional default value, if None.
if not None, the default value should be in the
search space | Return an optional default value, if None.
if not None, the default value should be in the
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"""Return an optional default value, if None.
if not None, the default value should be in the
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return self._default | [
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hyperledger/aries-cloudagent-python | 2f36776e99f6053ae92eed8123b5b1b2e891c02a | aries_cloudagent/transport/queue/base.py | python | BaseMessageQueue.enqueue | (self, message) | Enqueue a message.
Args:
message: The message to add to the end of the queue
Raises:
asyncio.CancelledError if the queue has been stopped | Enqueue a message. | [
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] | async def enqueue(self, message):
"""
Enqueue a message.
Args:
message: The message to add to the end of the queue
Raises:
asyncio.CancelledError if the queue has been stopped
""" | [
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/released/work_item_tracking/work_item_tracking_client.py | python | WorkItemTrackingClient.get_deleted_work_item_shallow_references | (self, project=None) | return self._deserialize('[WorkItemDeleteShallowReference]', self._unwrap_collection(response)) | GetDeletedWorkItemShallowReferences.
Gets a list of the IDs and the URLs of the deleted the work items in the Recycle Bin.
:param str project: Project ID or project name
:rtype: [WorkItemDeleteShallowReference] | GetDeletedWorkItemShallowReferences.
Gets a list of the IDs and the URLs of the deleted the work items in the Recycle Bin.
:param str project: Project ID or project name
:rtype: [WorkItemDeleteShallowReference] | [
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"""GetDeletedWorkItemShallowReferences.
Gets a list of the IDs and the URLs of the deleted the work items in the Recycle Bin.
:param str project: Project ID or project name
:rtype: [WorkItemDeleteShallowReference]
"""
route_values = {}
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version='5.1',
route_values=route_values)
return self._deserialize('[WorkItemDeleteShallowReference]', self._unwrap_collection(response)) | [
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IntelLabs/nlp-architect | 60afd0dd1bfd74f01b4ac8f613cb484777b80284 | solutions/trend_analysis/topic_extraction.py | python | write_folder_corpus_to_file | (corpus, writer) | Merge content of a folder into a single text file
Args:
corpus: A folder containing text files (String)
writer: A file writer | Merge content of a folder into a single text file | [
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] | def write_folder_corpus_to_file(corpus, writer):
"""
Merge content of a folder into a single text file
Args:
corpus: A folder containing text files (String)
writer: A file writer
"""
for filename in os.listdir(corpus):
try:
file_path = str(path.join(corpus, filename))
with open(file_path, "r", encoding="utf-8") as f:
lines = f.readlines()
writer.writelines(lines)
except Exception as e:
logger.error("Error: %s. skipping file: %s", str(e), str(filename)) | [
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facelessuser/ColorHelper | cfed17c35dbae4db49a14165ef222407c48a3014 | lib/coloraide/spaces/hsl/__init__.py | python | HSL.s | (self, value: float) | Saturate or unsaturate the color by the given factor. | Saturate or unsaturate the color by the given factor. | [
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] | def s(self, value: float) -> None:
"""Saturate or unsaturate the color by the given factor."""
self._coords[1] = self._handle_input(value) | [
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yongzhuo/Keras-TextClassification | 640e3f44f90d9d8046546f7e1a93a29ebe5c8d30 | keras_textclassification/m03_CharCNN/graph_yoon_kim.py | python | Highway.call | (self, x) | return value | [] | def call(self, x):
dim = K.int_shape(x)[-1]
transform_gate = self.dense_1(x)
transform_gate = Activation("sigmoid")(transform_gate)
carry_gate = Lambda(lambda x: 1.0 - x, output_shape=(dim,))(transform_gate)
transformed_data = self.dense_2(x)
transformed_data = Activation(self.activation)(transformed_data)
transformed_gated = Multiply()([transform_gate, transformed_data])
identity_gated = Multiply()([carry_gate, x])
value = Add()([transformed_gated, identity_gated])
return value | [
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LiuChangFreeman/C--Compiler | 99fd44982c54310e8eba4133653e3d9a7736a499 | SyntaxParser/LR(0)/prettytable.py | python | PrettyTable._get_attributes | (self) | return self._attributes | A dictionary of HTML attribute name/type pairs to be included in the <Table> tag when printing HTML
Arguments:
attributes - dictionary of attributes | A dictionary of HTML attribute name/type pairs to be included in the <Table> tag when printing HTML | [
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] | def _get_attributes(self):
"""A dictionary of HTML attribute name/type pairs to be included in the <Table> tag when printing HTML
Arguments:
attributes - dictionary of attributes"""
return self._attributes | [
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buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | runtime/python/lib/python2.7/lib-tk/Tkinter.py | python | Canvas.create_arc | (self, *args, **kw) | return self._create('arc', args, kw) | Create arc shaped region with coordinates x1,y1,x2,y2. | Create arc shaped region with coordinates x1,y1,x2,y2. | [
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] | def create_arc(self, *args, **kw):
"""Create arc shaped region with coordinates x1,y1,x2,y2."""
return self._create('arc', args, kw) | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/SQLAlchemy-1.3.17/lib/sqlalchemy/engine/default.py | python | DefaultExecutionContext._init_ddl | (cls, dialect, connection, dbapi_connection, compiled_ddl) | return self | Initialize execution context for a DDLElement construct. | Initialize execution context for a DDLElement construct. | [
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] | def _init_ddl(cls, dialect, connection, dbapi_connection, compiled_ddl):
"""Initialize execution context for a DDLElement construct."""
self = cls.__new__(cls)
self.root_connection = connection
self._dbapi_connection = dbapi_connection
self.dialect = connection.dialect
self.compiled = compiled = compiled_ddl
self.isddl = True
self.execution_options = compiled.execution_options
if connection._execution_options:
self.execution_options = dict(self.execution_options)
self.execution_options.update(connection._execution_options)
if not dialect.supports_unicode_statements:
self.unicode_statement = util.text_type(compiled)
self.statement = dialect._encoder(self.unicode_statement)[0]
else:
self.statement = self.unicode_statement = util.text_type(compiled)
self.cursor = self.create_cursor()
self.compiled_parameters = []
if dialect.positional:
self.parameters = [dialect.execute_sequence_format()]
else:
self.parameters = [{}]
return self | [
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DrewNF/Tensorflow_Object_Tracking_Video | e183c292651fd635dba0e2236ee93b85da447d5f | INCEPTION/image_retraining/retrain.py | python | cache_bottlenecks | (sess, image_lists, image_dir, bottleneck_dir,
jpeg_data_tensor, bottleneck_tensor) | Ensures all the training, testing, and validation bottlenecks are cached.
Because we're likely to read the same image multiple times (if there are no
distortions applied during training) it can speed things up a lot if we
calculate the bottleneck layer values once for each image during
preprocessing, and then just read those cached values repeatedly during
training. Here we go through all the images we've found, calculate those
values, and save them off.
Args:
sess: The current active TensorFlow Session.
image_lists: Dictionary of training images for each label.
image_dir: Root folder string of the subfolders containing the training
images.
bottleneck_dir: Folder string holding cached files of bottleneck values.
jpeg_data_tensor: Input tensor for jpeg data from file.
bottleneck_tensor: The penultimate output layer of the graph.
Returns:
Nothing. | Ensures all the training, testing, and validation bottlenecks are cached. | [
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] | def cache_bottlenecks(sess, image_lists, image_dir, bottleneck_dir,
jpeg_data_tensor, bottleneck_tensor):
"""Ensures all the training, testing, and validation bottlenecks are cached.
Because we're likely to read the same image multiple times (if there are no
distortions applied during training) it can speed things up a lot if we
calculate the bottleneck layer values once for each image during
preprocessing, and then just read those cached values repeatedly during
training. Here we go through all the images we've found, calculate those
values, and save them off.
Args:
sess: The current active TensorFlow Session.
image_lists: Dictionary of training images for each label.
image_dir: Root folder string of the subfolders containing the training
images.
bottleneck_dir: Folder string holding cached files of bottleneck values.
jpeg_data_tensor: Input tensor for jpeg data from file.
bottleneck_tensor: The penultimate output layer of the graph.
Returns:
Nothing.
"""
how_many_bottlenecks = 0
ensure_dir_exists(bottleneck_dir)
for label_name, label_lists in image_lists.items():
for category in ['training', 'testing', 'validation']:
category_list = label_lists[category]
for index, unused_base_name in enumerate(category_list):
get_or_create_bottleneck(sess, image_lists, label_name, index,
image_dir, category, bottleneck_dir,
jpeg_data_tensor, bottleneck_tensor)
how_many_bottlenecks += 1
if how_many_bottlenecks % 100 == 0:
print(str(how_many_bottlenecks) + ' bottleneck files created.') | [
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fritzy/SleekXMPP | cc1d470397de768ffcc41d2ed5ac3118d19f09f5 | examples/echo_client.py | python | EchoBot.start | (self, event) | Process the session_start event.
Typical actions for the session_start event are
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Arguments:
event -- An empty dictionary. The session_start
event does not provide any additional
data. | Process the session_start event. | [
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"""
Process the session_start event.
Typical actions for the session_start event are
requesting the roster and broadcasting an initial
presence stanza.
Arguments:
event -- An empty dictionary. The session_start
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"""
self.send_presence()
self.get_roster() | [
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gammapy/gammapy | 735b25cd5bbed35e2004d633621896dcd5295e8b | gammapy/datasets/map.py | python | MapDataset.npred_background | (self) | return background | Predicted background counts
The predicted background counts depend on the parameters
of the `FoVBackgroundModel` defined in the dataset.
Returns
-------
npred_background : `Map`
Predicted counts from the background. | Predicted background counts | [
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] | def npred_background(self):
"""Predicted background counts
The predicted background counts depend on the parameters
of the `FoVBackgroundModel` defined in the dataset.
Returns
-------
npred_background : `Map`
Predicted counts from the background.
"""
background = self.background
if self.background_model and background:
if self._background_parameters_changed:
values = self.background_model.evaluate_geom(geom=self.background.geom)
if self._background_cached is None:
self._background_cached = background * values
else:
self._background_cached.data = background.data * values.value
self._background_cached.unit = background.unit
return self._background_cached
else:
return background
return background | [
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miguelgrinberg/python-socketio | 4ee3649514b98c50cc0bf70d3f269389da52772d | src/socketio/client.py | python | Client._handle_eio_disconnect | (self) | Handle the Engine.IO disconnection event. | Handle the Engine.IO disconnection event. | [
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"""Handle the Engine.IO disconnection event."""
self.logger.info('Engine.IO connection dropped')
if self.connected:
for n in self.namespaces:
self._trigger_event('disconnect', namespace=n)
self.namespaces = {}
self.connected = False
self.callbacks = {}
self._binary_packet = None
self.sid = None
if self.eio.state == 'connected' and self.reconnection:
self._reconnect_task = self.start_background_task(
self._handle_reconnect) | [
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Accenture/AmpliGraph | 97a0bb6b6b74531cb4e2f71fc6c5a8b18a445cfa | ampligraph/latent_features/models/EmbeddingModel.py | python | EmbeddingModel._generate_corruptions_for_large_graphs | (self) | Corruption generator for large graph mode only.
It generates corruptions in batches and also yields the corresponding entity embeddings. | Corruption generator for large graph mode only.
It generates corruptions in batches and also yields the corresponding entity embeddings. | [
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] | def _generate_corruptions_for_large_graphs(self):
"""Corruption generator for large graph mode only.
It generates corruptions in batches and also yields the corresponding entity embeddings.
"""
corruption_entities = self.eval_config.get('corruption_entities', constants.DEFAULT_CORRUPTION_ENTITIES)
if corruption_entities == 'all':
all_entities_np = np.arange(len(self.ent_to_idx))
corruption_entities = all_entities_np
elif isinstance(corruption_entities, np.ndarray):
corruption_entities = corruption_entities
else:
msg = 'Invalid type for corruption entities.'
logger.error(msg)
raise ValueError(msg)
entity_embeddings = np.empty(shape=(0, self.internal_k), dtype=np.float32)
for i in range(self.corr_batches_count):
all_ent = corruption_entities[i * self.corr_batch_size:(i + 1) * self.corr_batch_size]
needed = (self.corr_batch_size - all_ent.shape[0])
large_number = np.zeros((needed, self.ent_emb_cpu.shape[1]), dtype=np.float32) + np.nan
entity_embeddings = np.concatenate((self.ent_emb_cpu[all_ent, :], large_number), axis=0)
all_ent = all_ent.reshape(-1, 1)
yield all_ent, entity_embeddings | [
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fuzzbunch/fuzzbunch | 4b60a6c7cf9f84cf389d3fcdb9281de84ffb5802 | fuzzbunch/pyreadline/modes/emacs.py | python | EmacsMode.next_history | (self, e) | Move forward through the history list, fetching the next command. | Move forward through the history list, fetching the next command. | [
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] | def next_history(self, e): # (C-n)
'''Move forward through the history list, fetching the next command. '''
self._history.next_history(self.l_buffer) | [
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OpenMDAO/OpenMDAO-Framework | f2e37b7de3edeaaeb2d251b375917adec059db9b | openmdao.main/src/openmdao/main/container.py | python | Container.set_metadata | (self, traitpath, metaname, value) | Set the metadata associated with the trait found using traitpath. | Set the metadata associated with the trait found using traitpath. | [
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] | def set_metadata(self, traitpath, metaname, value):
"""Set the metadata associated with the trait found using traitpath."""
if metaname in ('iotype',):
self.raise_exception("Can't set %s on %s, read-only"
% (metaname, traitpath), TypeError)
self.get_metadata(traitpath)[metaname] = value | [
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palantir/python-language-server | a91a257d2c8687a7931721d387b2ffeb6aa71fc2 | versioneer.py | python | render_pep440_pre | (pieces) | return rendered | TAG[.post.devDISTANCE] -- No -dirty.
Exceptions:
1: no tags. 0.post.devDISTANCE | TAG[.post.devDISTANCE] -- No -dirty. | [
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"[",
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"devDISTANCE",
"]",
"--",
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"-",
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"."
] | def render_pep440_pre(pieces):
"""TAG[.post.devDISTANCE] -- No -dirty.
Exceptions:
1: no tags. 0.post.devDISTANCE
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += ".post.dev%d" % pieces["distance"]
else:
# exception #1
rendered = "0.post.dev%d" % pieces["distance"]
return rendered | [
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... | https://github.com/palantir/python-language-server/blob/a91a257d2c8687a7931721d387b2ffeb6aa71fc2/versioneer.py#L1261-L1274 | |
shiweibsw/Translation-Tools | 2fbbf902364e557fa7017f9a74a8797b7440c077 | venv/Lib/site-packages/pip-9.0.3-py3.6.egg/pip/_vendor/html5lib/treebuilders/etree_lxml.py | python | TreeBuilder.reset | (self) | [] | def reset(self):
base.TreeBuilder.reset(self)
self.insertComment = self.insertCommentInitial
self.initial_comments = []
self.doctype = None | [
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leo-editor/leo-editor | 383d6776d135ef17d73d935a2f0ecb3ac0e99494 | leo/plugins/leo_to_html.py | python | pluginController.show_html_number | (self, event=None) | Command handler for leo_to_html. See modules docstring for details. | Command handler for leo_to_html. See modules docstring for details. | [
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] | def show_html_number(self, event=None):
"""Command handler for leo_to_html. See modules docstring for details."""
self.show_html(bullet='number') | [
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myquant/strategy | 17595e6bf4a118e1fa87c90bfb0fd78afa69a60b | AR_MA_STOCK/python/ar_ma_stock.py | python | AR_MA_STOCK.cal_ar_index | (self, ticker) | return ar_index | 功能：计算ar指标 | 功能：计算ar指标 | [
"功能：计算ar指标"
] | def cal_ar_index(self, ticker):
"""
功能：计算ar指标
"""
ar_index = None
if (len(self.dict_price[ticker][0]) < self.ar_period or abs(
self.dict_price[ticker][0][-1] - INIT_OPEN_PRICE) < EPS) \
or (len(self.dict_price[ticker][1]) < self.ar_period or abs(
self.dict_price[ticker][1][-1] - INIT_HIGH_PRICE) < EPS) \
or (len(self.dict_price[ticker][2]) < self.ar_period or abs(
self.dict_price[ticker][2][-1] - INIT_LOW_PRICE) < EPS) \
or (len(self.dict_price[ticker][3]) < self.ar_period or abs(
self.dict_price[ticker][3][-1] - INIT_CLOSE_PRICE) < EPS):
# 历史数据不足
return ar_index
open_ls = self.dict_price[ticker][0][len(self.dict_price[ticker][0]) - self.ar_period:]
high_ls = self.dict_price[ticker][1][len(self.dict_price[ticker][1]) - self.ar_period:]
low_ls = self.dict_price[ticker][2][len(self.dict_price[ticker][2]) - self.ar_period:]
high_minus_ls = [a_b[0] - a_b[1] for a_b in zip(high_ls, open_ls)]
low_minus_ls = [a_b1[0] - a_b1[1] for a_b1 in zip(open_ls, low_ls)]
ar_index = 0.0
for pos in range(len(high_minus_ls)):
if low_minus_ls[pos] > EPS:
ar_index += high_minus_ls[pos] / low_minus_ls[pos]
return ar_index | [
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pjkundert/cpppo | 4c217b6c06b88bede3888cc5ea2731f271a95086 | server/enip/parser.py | python | communications_service.__init__ | ( self, name=None, **kwds ) | [] | def __init__( self, name=None, **kwds ):
name = name or kwds.setdefault( 'context', self.__class__.__name__ )
vers = UINT( context='version' )
vers[True] = capa = UINT( context='capability' )
capa[True] = svnm = string_bytes( 'service_name',
context='service_name', greedy=True,
initial='[^\x00]*', decode='iso-8859-1' )
svnm[b'\0'[0]] = octets_drop( 'NUL', repeat=1, terminal=True )
super( communications_service, self ).__init__( name=name, initial=vers, **kwds ) | [
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