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assertpy/assertpy | c970c6612a80aa10769dc612324630d27019e1b5 | assertpy/helpers.py | python | HelpersMixin._validate_close_to_args | (self, val, other, tolerance) | Helper for validate given arg and delta. | Helper for validate given arg and delta. | [
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] | def _validate_close_to_args(self, val, other, tolerance):
"""Helper for validate given arg and delta."""
if type(val) is complex or type(other) is complex or type(tolerance) is complex:
raise TypeError('ordering is not defined for complex numbers')
if isinstance(val, numbers.Number) is False and type(val) is not datetime.datetime:
raise TypeError('val is not numeric or datetime')
if type(val) is datetime.datetime:
if type(other) is not datetime.datetime:
raise TypeError('given arg must be datetime, but was <%s>' % type(other).__name__)
if type(tolerance) is not datetime.timedelta:
raise TypeError('given tolerance arg must be timedelta, but was <%s>' % type(tolerance).__name__)
else:
if isinstance(other, numbers.Number) is False:
raise TypeError('given arg must be numeric')
if isinstance(tolerance, numbers.Number) is False:
raise TypeError('given tolerance arg must be numeric')
if tolerance < 0:
raise ValueError('given tolerance arg must be positive') | [
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bnpy/bnpy | d5b311e8f58ccd98477f4a0c8a4d4982e3fca424 | bnpy/obsmodel/MultObsModel.py | python | MultObsModel.calcMargLik | (self, SS) | return self.calcMargLik_CFuncForLoop(SS) | Calc log marginal likelihood combining all comps, given suff stats
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--------
logM : scalar real
logM = \sum_{k=1}^K log p( data assigned to comp k | Prior) | Calc log marginal likelihood combining all comps, given suff stats | [
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Returns
--------
logM : scalar real
logM = \sum_{k=1}^K log p( data assigned to comp k | Prior)
'''
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/glance/glance/image_cache/drivers/base.py | python | Driver.set_paths | (self) | Creates all necessary directories under the base cache directory | Creates all necessary directories under the base cache directory | [
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"""
Creates all necessary directories under the base cache directory
"""
self.base_dir = CONF.image_cache_dir
if self.base_dir is None:
msg = _('Failed to read %s from config') % 'image_cache_dir'
LOG.error(msg)
driver = self.__class__.__module__
raise exception.BadDriverConfiguration(driver_name=driver,
reason=msg)
self.incomplete_dir = os.path.join(self.base_dir, 'incomplete')
self.invalid_dir = os.path.join(self.base_dir, 'invalid')
self.queue_dir = os.path.join(self.base_dir, 'queue')
dirs = [self.incomplete_dir, self.invalid_dir, self.queue_dir]
for path in dirs:
utils.safe_mkdirs(path) | [
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AstroPrint/AstroBox | e7e3b8a7d33ea85fcb6b2696869c0d719ceb8b75 | src/astroprint/api/connection.py | python | connectionState | () | return jsonify({"current": current, "options": pm.getConnectionOptions()}) | [] | def connectionState():
pm = printerManager()
state, port, baudrate = pm.getCurrentConnection()
current = {
"state": state,
"port": port,
"baudrate": baudrate
}
return jsonify({"current": current, "options": pm.getConnectionOptions()}) | [
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WerWolv/EdiZon_CheatsConfigsAndScripts | d16d36c7509c01dca770f402babd83ff2e9ae6e7 | Scripts/lib/python3.5/importlib/_bootstrap.py | python | FrozenImporter.module_repr | (m) | return '<module {!r} (frozen)>'.format(m.__name__) | Return repr for the module.
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"""Return repr for the module.
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espnet/espnet | ea411f3f627b8f101c211e107d0ff7053344ac80 | espnet/nets/pytorch_backend/e2e_vc_tacotron2.py | python | Tacotron2.inference | (self, x, inference_args, spemb=None, *args, **kwargs) | Generate the sequence of features given the sequences of characters.
Args:
x (Tensor): Input sequence of acoustic features (T, idim).
inference_args (Namespace):
- threshold (float): Threshold in inference.
- minlenratio (float): Minimum length ratio in inference.
- maxlenratio (float): Maximum length ratio in inference.
spemb (Tensor, optional): Speaker embedding vector (spk_embed_dim).
Returns:
Tensor: Output sequence of features (L, odim).
Tensor: Output sequence of stop probabilities (L,).
Tensor: Attention weights (L, T). | Generate the sequence of features given the sequences of characters. | [
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"""Generate the sequence of features given the sequences of characters.
Args:
x (Tensor): Input sequence of acoustic features (T, idim).
inference_args (Namespace):
- threshold (float): Threshold in inference.
- minlenratio (float): Minimum length ratio in inference.
- maxlenratio (float): Maximum length ratio in inference.
spemb (Tensor, optional): Speaker embedding vector (spk_embed_dim).
Returns:
Tensor: Output sequence of features (L, odim).
Tensor: Output sequence of stop probabilities (L,).
Tensor: Attention weights (L, T).
"""
# get options
threshold = inference_args.threshold
minlenratio = inference_args.minlenratio
maxlenratio = inference_args.maxlenratio
# thin out input frames for reduction factor
# (B, Lmax, idim) -> (B, Lmax // r, idim * r)
if self.encoder_reduction_factor > 1:
Lmax, idim = x.shape
if Lmax % self.encoder_reduction_factor != 0:
x = x[: -(Lmax % self.encoder_reduction_factor), :]
x_ds = x.contiguous().view(
int(Lmax / self.encoder_reduction_factor),
idim * self.encoder_reduction_factor,
)
else:
x_ds = x
# inference
h = self.enc.inference(x_ds)
if self.spk_embed_dim is not None:
spemb = F.normalize(spemb, dim=0).unsqueeze(0).expand(h.size(0), -1)
h = torch.cat([h, spemb], dim=-1)
outs, probs, att_ws = self.dec.inference(h, threshold, minlenratio, maxlenratio)
if self.use_cbhg:
cbhg_outs = self.cbhg.inference(outs)
return cbhg_outs, probs, att_ws
else:
return outs, probs, att_ws | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/fmu/v20191213/models.py | python | CancelBeautifyVideoJobRequest.__init__ | (self) | r"""
:param JobId: 美颜视频的Job id
:type JobId: str | r"""
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r"""
:param JobId: 美颜视频的Job id
:type JobId: str
"""
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/IronPython/27/Lib/mailbox.py | python | _singlefileMailbox.close | (self) | Flush and close the mailbox. | Flush and close the mailbox. | [
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] | def close(self):
"""Flush and close the mailbox."""
try:
self.flush()
finally:
try:
if self._locked:
self.unlock()
finally:
self._file.close() | [
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TUDelft-CNS-ATM/bluesky | 55a538a3cd936f33cff9df650c38924aa97557b1 | bluesky/ui/qtgl/glhelpers.py | python | Rectangle.create | (self, w, h, fill=False) | Create the Rectangle VAO. | Create the Rectangle VAO. | [
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] | def create(self, w, h, fill=False):
''' Create the Rectangle VAO.'''
if fill:
self.set_primitive_type(gl.GL_TRIANGLE_FAN)
vrect = np.array([(-0.5 * h, 0.5 * w), (-0.5 * h, -0.5 * w),
(0.5 * h, -0.5 * w), (0.5 * h, 0.5 * w)], dtype=np.float32)
super().create(vertex=vrect) | [
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pybuilder/pybuilder | 12ea2f54e04f97daada375dc3309a3f525f1b5e1 | src/main/python/pybuilder/_vendor/pkg_resources/__init__.py | python | invalid_marker | (text) | return False | Validate text as a PEP 508 environment marker; return an exception
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"""
Validate text as a PEP 508 environment marker; return an exception
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try:
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securityclippy/elasticintel | aa08d3e9f5ab1c000128e95161139ce97ff0e334 | ingest_feed_lambda/pandas/core/internals.py | python | _multi_blockify | (tuples, dtype=None) | return new_blocks | return an array of blocks that potentially have different dtypes | return an array of blocks that potentially have different dtypes | [
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""" return an array of blocks that potentially have different dtypes """
# group by dtype
grouper = itertools.groupby(tuples, lambda x: x[2].dtype)
new_blocks = []
for dtype, tup_block in grouper:
values, placement = _stack_arrays(list(tup_block), dtype)
block = make_block(values, placement=placement)
new_blocks.append(block)
return new_blocks | [
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rhinstaller/anaconda | 63edc8680f1b05cbfe11bef28703acba808c5174 | pyanaconda/ui/gui/helpers.py | python | GUISpokeInputCheckHandler.on_password_changed | (self, editable, data=None) | Tell checker that the content of the password field changed. | Tell checker that the content of the password field changed. | [
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"""Tell checker that the content of the password field changed."""
self.checker.password.content = self.password | [
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anforaProject/anfora | a8efa2a3039955d2623d003bfc920c5d24641e93 | src/managers/notification_manager.py | python | NotificationManager.create_follow_notification | (self, target:UserProfile) | return n | target: The user receiving the notification | target: The user receiving the notification | [
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target: The user receiving the notification
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n = Notification.create(
target = target,
user = self.user,
notification_type = 'follow',
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self._notify_user(n)
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NervanaSystems/neon | 8c3fb8a93b4a89303467b25817c60536542d08bd | neon/data/convert_manifest.py | python | convert_manifest | (source_manifest, output_manifest) | Converts manifest created for previous aeon versions for
use with aeon v1.0+.
Args:
source_manifest: Path to old manifest
output_manifest: Path to save converted manifest. | Converts manifest created for previous aeon versions for
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"""
Converts manifest created for previous aeon versions for
use with aeon v1.0+.
Args:
source_manifest: Path to old manifest
output_manifest: Path to save converted manifest.
"""
tmp_manifest = '/tmp/manifest{}'.format(os.getpid())
tmp_dest = open(tmp_manifest, 'w')
source = open(source_manifest, 'r')
record = source.readline()
splited = record.split(',')
headerbody = "FILE\t" * len(splited)
header = "@" + headerbody[:-1] + '\n'
tmp_dest.write(header)
record = record.replace(',', '\t')
tmp_dest.write(record)
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tmp_dest.write(record)
source.close()
tmp_dest.close()
if output_manifest is None:
output_manifest = source_manifest
if os.path.exists(output_manifest):
os.remove(output_manifest)
shutil.move(tmp_manifest, output_manifest) | [
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dmsimard/ara-archive | 8747ff45004fd962337587c7c13d725797cd2d40 | ara/config.py | python | _ara_config | (config, key, env_var, default=None, section='ara',
value_type=None) | return get_config(config, section, key, env_var, default,
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value_type=None):
"""
Wrapper around Ansible's get_config backward/forward compatibility
"""
if default is None:
try:
# We're using env_var as keys in the DEFAULTS dict
default = DEFAULTS.get(env_var)
except KeyError as e:
msg = 'There is no default value for {0}: {1}'.format(key, str(e))
raise KeyError(msg)
# >= 2.3.0.0 (NOTE: Ansible trunk versioning scheme has 3 digits, not 4)
if LooseVersion(ansible_version) >= LooseVersion('2.3.0'):
return get_config(config, section, key, env_var, default,
value_type=value_type)
# < 2.3.0.0 compatibility
if value_type is None:
return get_config(config, section, key, env_var, default)
args = {
'boolean': dict(boolean=True),
'integer': dict(integer=True),
'list': dict(islist=True),
'tmppath': dict(istmppath=True)
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return get_config(config, section, key, env_var, default,
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | osh/builtin_comp.py | python | CompAdjust.__init__ | (self, mem) | [] | def __init__(self, mem):
# type: (Mem) -> None
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GalSim-developers/GalSim | a05d4ec3b8d8574f99d3b0606ad882cbba53f345 | galsim/chromatic.py | python | ChromaticSum.withScaledFlux | (self, flux_ratio) | return new_obj | Multiply the flux of the object by ``flux_ratio``
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flux_ratio: The factor by which to scale the flux.
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Parameters:
flux_ratio: The factor by which to scale the flux.
Returns:
the object with the new flux.
"""
new_obj = ChromaticSum([ obj.withScaledFlux(flux_ratio) for obj in self.obj_list ])
if hasattr(self, 'covspec'):
new_covspec = self.covspec * flux_ratio**2
new_obj.covspec = new_covspec
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/django/http/request.py | python | HttpRequest.xreadlines | (self) | [] | def xreadlines(self):
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lmfit/lmfit-py | 47219daa401639831136d39aa472ccee9a712320 | lmfit/parameter.py | python | Parameter.expr | (self, val) | Set the mathematical expression used to constrain the value in fit.
To remove a constraint you must supply an empty string. | Set the mathematical expression used to constrain the value in fit. | [
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pympler/pympler | 8019a883eec547d91ecda6ba12669d4f4504c625 | pympler/refgraph.py | python | ReferenceGraph.reduce_to_cycles | (self) | return self._reduced | Iteratively eliminate leafs to reduce the set of objects to only those
that build cycles. Return the reduced graph. If there are no cycles,
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"""
Iteratively eliminate leafs to reduce the set of objects to only those
that build cycles. Return the reduced graph. If there are no cycles,
None is returned.
"""
if not self._reduced:
reduced = copy(self)
reduced.objects = self.objects[:]
reduced.metadata = []
reduced.edges = []
self.num_in_cycles = reduced._reduce_to_cycles()
reduced.num_in_cycles = self.num_in_cycles
if self.num_in_cycles:
reduced._get_edges()
reduced._annotate_objects()
for meta in reduced.metadata:
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nlloyd/SubliminalCollaborator | 5c619e17ddbe8acb9eea8996ec038169ddcd50a1 | libs/twisted/internet/cfreactor.py | python | CFReactor.removeWriter | (self, writer) | Implement L{IReactorFDSet.removeWriter}. | Implement L{IReactorFDSet.removeWriter}. | [
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karanchahal/distiller | a17ec06cbeafcdd2aea19d7c7663033c951392f5 | distill_archive/research_seed/baselines/rkd_baseline/losses.py | python | HardDarkRank.forward | (self, student, teacher) | return loss | [] | def forward(self, student, teacher):
score_teacher = -1 * self.alpha * pdist(teacher, squared=False).pow(self.beta)
score_student = -1 * self.alpha * pdist(student, squared=False).pow(self.beta)
permute_idx = score_teacher.sort(dim=1, descending=True)[1][:, 1:(self.permute_len+1)]
ordered_student = torch.gather(score_student, 1, permute_idx)
log_prob = (ordered_student - torch.stack([torch.logsumexp(ordered_student[:, i:], dim=1) for i in range(permute_idx.size(1))], dim=1)).sum(dim=1)
loss = (-1 * log_prob).mean()
return loss | [
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cournape/Bento | 37de23d784407a7c98a4a15770ffc570d5f32d70 | bento/private/_simplejson/simplejson/ordered_dict.py | python | OrderedDict.__iter__ | (self) | [] | def __iter__(self):
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | ext/github/Issue.py | python | Issue.title | (self) | return self._title.value | :type: string | :type: string | [
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"""
:type: string
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dabeaz-course/practical-python | 92a8a73c078e7721d75fd0400e973b44bf7639b8 | Solutions/7_11/stock.py | python | Stock.cost | (self) | return self.shares * self.price | Return the cost as shares*price | Return the cost as shares*price | [
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'''
Return the cost as shares*price
'''
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qinxuye/cola | 9b4803dfef8d91f80c6787dea953bf9f5830818b | cola/core/mq/node.py | python | LocalMessageQueueNode.remove_node | (self, addr) | For the removed node, this method is for the cleaning job including
shutting down the backup storage for the removed node. | For the removed node, this method is for the cleaning job including
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if addr not in self.addrs: return
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eggnogdb/eggnog-mapper | d6e6cdf0a829f2bd85480f3f3f16e38c213cd091 | eggnogmapper/annotation/annotator_worker.py | python | get_member_ogs | (name, eggnog_db) | return ogs | [] | def get_member_ogs(name, eggnog_db):
ogs = None
match = eggnog_db.get_member_ogs(name)
if match is not None and match[0] is not None:
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enzienaudio/hvcc | 30e47328958d600c54889e2a254c3f17f2b2fd06 | generators/ir2c/ControlSwitchcase.py | python | ControlSwitchcase.get_C_onMessage | (clazz, obj_type, obj_id, inlet_index, args) | return [
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obj_id,
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VingtCinq/python-mailchimp | babf492a4ee14782b0c883ddbbbb15c275655ba9 | mailchimp3/entities/listsegmentmembers.py | python | ListSegmentMembers.create | (self, list_id, segment_id, data) | return response | Add a member to a static segment.
The documentation does not currently elaborate on the path or request
body parameters. Looking at the example provided, it will be assumed
that email_address and status are required request body parameters and
they are documented and error-checked as such.
:param list_id: The unique id for the list.
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:type segment_id: :py:class:`str`
:param data: The request body parameters
:type data: :py:class:`dict`
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Add a member to a static segment.
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:type data: :py:class:`dict`
data = {
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}
"""
self.list_id = list_id
self.segment_id = segment_id
if 'email_address' not in data:
raise KeyError('The list segment member must have an email_address')
check_email(data['email_address'])
if 'status' not in data:
raise KeyError('The list segment member must have a status')
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response = self._mc_client._post(url=self._build_path(list_id, 'segments', segment_id, 'members'), data=data)
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self.subscriber_hash = response['id']
else:
self.subscriber_hash = None
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/email/header.py | python | _ValueFormatter._str | (self, linesep) | return linesep.join(self._lines) | [] | def _str(self, linesep):
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/gse/v20191112/models.py | python | GetGameServerSessionLogUrlRequest.__init__ | (self) | r"""
:param GameServerSessionId: 游戏服务器会话ID，最小长度不小于1个ASCII字符，最大长度不超过48个ASCII字符
:type GameServerSessionId: str | r"""
:param GameServerSessionId: 游戏服务器会话ID，最小长度不小于1个ASCII字符，最大长度不超过48个ASCII字符
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r"""
:param GameServerSessionId: 游戏服务器会话ID，最小长度不小于1个ASCII字符，最大长度不超过48个ASCII字符
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qiucheng025/zao- | 3a5edf3607b3a523f95746bc69b688090c76d89a | lib/queue_manager.py | python | QueueManager.add_queue | (self, name, maxsize=0, multiprocessing_queue=True) | Add a queue to the manager
Adds an event "shutdown" to the queue that can be used to indicate
to a process that any activity on the queue should cease | Add a queue to the manager | [
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""" Add a queue to the manager
Adds an event "shutdown" to the queue that can be used to indicate
to a process that any activity on the queue should cease """
logger.debug("QueueManager adding: (name: '%s', maxsize: %s)", name, maxsize)
if name in self.queues.keys():
raise ValueError("Queue '{}' already exists.".format(name))
if multiprocessing_queue:
queue = self.manager.Queue(maxsize=maxsize)
else:
queue = Queue(maxsize=maxsize)
setattr(queue, "shutdown", self.shutdown)
self.queues[name] = queue
logger.debug("QueueManager added: (name: '%s')", name) | [
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tensorflow/datasets | 2e496976d7d45550508395fb2f35cf958c8a3414 | tensorflow_datasets/core/decode/partial_decode.py | python | _normalize_feature_item | (
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# If user provide a FeatureConnector, use this
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return expected_feature
# If the user provide a bool, use the matching feature connector
# Example: {'cameras': True} -> `{'camera': FeatureDict({'image': Image()})}`
elif isinstance(expected_feature, bool):
assert expected_feature # `False` values should have been filtered already
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elif isinstance(expected_feature, (list, set, dict)):
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-graalpython/python_cext.py | python | PyTruffle_GetBuiltin | (name) | return getattr(sys.modules["builtins"], name) | [] | def PyTruffle_GetBuiltin(name):
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/collections.py | python | OrderedDict.keys | (self) | return list(self) | od.keys() -> list of keys in od | od.keys() -> list of keys in od | [
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pypa/pipenv | b21baade71a86ab3ee1429f71fbc14d4f95fb75d | pipenv/patched/notpip/_vendor/msgpack/__init__.py | python | packb | (o, **kwargs) | return Packer(**kwargs).pack(o) | Pack object `o` and return packed bytes
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glue-viz/glue | 840b4c1364b0fa63bf67c914540c93dd71df41e1 | glue/app/qt/layer_tree_widget.py | python | LayerTreeWidget.is_checkable | (self) | return self.ui.layerTree.checkable | Return whether checkboxes appear next o layers | Return whether checkboxes appear next o layers | [
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jython/frozen-mirror | b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99 | lib-python/2.7/plat-mac/lib-scriptpackages/Finder/Finder_items.py | python | Finder_items_Events.reveal | (self, _object, _attributes={}, **_arguments) | reveal: Bring the specified object(s) into view
Required argument: the object to be made visible
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open-mmlab/mmcv | 48419395e3220af5b6df78346d6ce58991e8ba90 | mmcv/fileio/file_client.py | python | FileClient.parse_uri_prefix | (uri: Union[str, Path]) | Parse the prefix of a uri.
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Examples:
>>> FileClient.parse_uri_prefix('s3://path/of/your/file')
's3'
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"""
assert is_filepath(uri)
uri = str(uri)
if '://' not in uri:
return None
else:
prefix, _ = uri.split('://')
# In the case of PetrelBackend, the prefix may contains the cluster
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if ':' in prefix:
_, prefix = prefix.split(':')
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evennia/evennia | fa79110ba6b219932f22297838e8ac72ebc0be0e | evennia/utils/evtable.py | python | EvCell._center | (self, text, width, pad_char) | Horizontally center text on line of certain width, using padding.
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text (str): The text to center.
width (int): How wide the area is (in characters) where `text`
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Horizontally center text on line of certain width, using padding.
Args:
text (str): The text to center.
width (int): How wide the area is (in characters) where `text`
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pad_char (str): Which padding character to use.
Returns:
text (str): Centered text.
"""
excess = width - d_len(text)
if excess <= 0:
return text
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# uneven padding
narrowside = (excess // 2) * pad_char
widerside = narrowside + pad_char
if width % 2:
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freedombox/FreedomBox | 335a7f92cc08f27981f838a7cddfc67740598e54 | plinth/setup.py | python | Helper.run | (self, allow_install=True) | Execute the setup process. | Execute the setup process. | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/flaskbb/plugins/utils.py | python | remove_zombie_plugins_from_db | () | return remove_me | Removes 'zombie' plugins from the db. A zombie plugin is a plugin
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"""
d_fs_plugins = [p[0] for p in current_app.pluggy.list_disabled_plugins()]
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/iotvideoindustry/v20201201/models.py | python | DescribeScenesResponse.__init__ | (self) | r"""
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:param List: 场景列表
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/requests/models.py | python | PreparedRequest.prepare_cookies | (self, cookies) | Prepares the given HTTP cookie data.
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given cookies using cookielib. Due to cookielib's design, the header
will not be regenerated if it already exists, meaning this function
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"""Prepares the given HTTP cookie data.
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will not be regenerated if it already exists, meaning this function
can only be called once for the life of the
:class:`PreparedRequest <PreparedRequest>` object. Any subsequent calls
to ``prepare_cookies`` will have no actual effect, unless the "Cookie"
header is removed beforehand."""
if isinstance(cookies, cookielib.CookieJar):
self._cookies = cookies
else:
self._cookies = cookiejar_from_dict(cookies)
cookie_header = get_cookie_header(self._cookies, self)
if cookie_header is not None:
self.headers['Cookie'] = cookie_header | [
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robclewley/pydstool | 939e3abc9dd1f180d35152bacbde57e24c85ff26 | PyDSTool/PyCont/misc.py | python | hess3 | (func, x0, ind) | return C | Computes third derivative using hess function. | Computes third derivative using hess function. | [
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tableau/server-client-python | b3ca20e6765c7cff2d5b095e880dc2b2a811d825 | tableauserverclient/_version.py | python | get_keywords | () | return keywords | Get the keywords needed to look up the version information. | Get the keywords needed to look up the version information. | [
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# these strings will be replaced by git during git-archive.
# setup.py/versioneer.py will grep for the variable names, so they must
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git_full = "$Format:%H$"
git_date = "$Format:%ci$"
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postlund/pyatv | 4ed1f5539f37d86d80272663d1f2ea34a6c41ec4 | pyatv/protocols/companion/__init__.py | python | CompanionRemoteControl.previous | (self) | Press key previous. | Press key previous. | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/idlelib/EditorWindow.py | python | EditorWindow.get_selection_indices | (self) | [] | def get_selection_indices(self):
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Pymol-Scripts/Pymol-script-repo | bcd7bb7812dc6db1595953dfa4471fa15fb68c77 | modules/pdb2pqr/main_cgi.py | python | redirector | (name) | return string | Prints a page which redirects the user to querystatus.cgi and writes starting time to file | Prints a page which redirects the user to querystatus.cgi and writes starting time to file | [
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] | def redirector(name):
"""
Prints a page which redirects the user to querystatus.cgi and writes starting time to file
"""
utilities.appendToLogFile(name, 'pdb2pqr_start_time', str(time.time()))
string = ""
string+= "<html>\n"
string+= "\t<head>\n"
string+= "\t\t<meta http-equiv=\"Refresh\" content=\"0; url=%squerystatus.cgi?jobid=%s&calctype=pdb2pqr\">\n" % (WEBSITE, name)
string+= "\t</head>\n"
string+= "</html>\n"
return string | [
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evennia/evennia | fa79110ba6b219932f22297838e8ac72ebc0be0e | evennia/commands/default/admin.py | python | CmdBoot.func | (self) | Implementing the function | Implementing the function | [
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"""Implementing the function"""
caller = self.caller
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return
if ":" in args:
args, reason = [a.strip() for a in args.split(":", 1)]
else:
args, reason = args, ""
boot_list = []
if "sid" in self.switches:
# Boot a particular session id.
sessions = SESSIONS.get_sessions(True)
for sess in sessions:
# Find the session with the matching session id.
if sess.sessid == int(args):
boot_list.append(sess)
break
else:
# Boot by account object
pobj = search.account_search(args)
if not pobj:
caller.msg("Account %s was not found." % args)
return
pobj = pobj[0]
if not pobj.access(caller, "boot"):
string = "You don't have the permission to boot %s." % (pobj.key,)
caller.msg(string)
return
# we have a bootable object with a connected user
matches = SESSIONS.sessions_from_account(pobj)
for match in matches:
boot_list.append(match)
if not boot_list:
caller.msg("No matching sessions found. The Account does not seem to be online.")
return
# Carry out the booting of the sessions in the boot list.
feedback = None
if "quiet" not in self.switches:
feedback = "You have been disconnected by %s.\n" % caller.name
if reason:
feedback += "\nReason given: %s" % reason
for session in boot_list:
session.msg(feedback)
session.account.disconnect_session_from_account(session)
if pobj and boot_list:
logger.log_sec(
"Booted: %s (Reason: %s, Caller: %s, IP: %s)."
% (pobj, reason, caller, self.session.address)
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v7/services/services/ad_group_label_service/client.py | python | AdGroupLabelServiceClient.common_organization_path | (organization: str,) | return "organizations/{organization}".format(organization=organization,) | Return a fully-qualified organization string. | Return a fully-qualified organization string. | [
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tribe29/checkmk | 6260f2512e159e311f426e16b84b19d0b8e9ad0c | cmk/gui/plugins/views/utils.py | python | ViewStore.get_instance | (cls) | return cls() | Return the request bound instance | Return the request bound instance | [
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pts/pdfsizeopt | 33ec5e5c637fc8967d6d238dfdaf8c55605efe83 | lib/pdfsizeopt/main.py | python | PdfObj.ResolveReferencesChanged | (cls, data, objs, do_strings=False) | return data2, data2 != data | Resolve references (<x> <y> R) in a PDF token sequence.
Like ResolveReferences, but returns has_changed as well.
Returns:
(new_data, has_changed). has_changed may be True even if there
were no references found, but comments were removed. | Resolve references (<x> <y> R) in a PDF token sequence. | [
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] | def ResolveReferencesChanged(cls, data, objs, do_strings=False):
"""Resolve references (<x> <y> R) in a PDF token sequence.
Like ResolveReferences, but returns has_changed as well.
Returns:
(new_data, has_changed). has_changed may be True even if there
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"""
if not isinstance(data, str):
return data, False
data2 = cls.ResolveReferences(data, objs, do_strings)
return data2, data2 != data | [
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oauthlib/oauthlib | 553850bc85dfd408be0dae9884b4a0aefda8e579 | oauthlib/oauth1/rfc5849/endpoints/base.py | python | BaseEndpoint._get_signature_type_and_params | (self, request) | return signature_type, params, oauth_params | Extracts parameters from query, headers and body. Signature type
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"""Extracts parameters from query, headers and body. Signature type
is set to the source in which parameters were found.
"""
# Per RFC5849, only the Authorization header may contain the 'realm'
# optional parameter.
header_params = signature.collect_parameters(headers=request.headers,
exclude_oauth_signature=False, with_realm=True)
body_params = signature.collect_parameters(body=request.body,
exclude_oauth_signature=False)
query_params = signature.collect_parameters(uri_query=request.uri_query,
exclude_oauth_signature=False)
params = []
params.extend(header_params)
params.extend(body_params)
params.extend(query_params)
signature_types_with_oauth_params = list(filter(lambda s: s[2], (
(SIGNATURE_TYPE_AUTH_HEADER, params,
utils.filter_oauth_params(header_params)),
(SIGNATURE_TYPE_BODY, params,
utils.filter_oauth_params(body_params)),
(SIGNATURE_TYPE_QUERY, params,
utils.filter_oauth_params(query_params))
)))
if len(signature_types_with_oauth_params) > 1:
found_types = [s[0] for s in signature_types_with_oauth_params]
raise errors.InvalidRequestError(
description=('oauth_ params must come from only 1 signature'
'type but were found in %s',
', '.join(found_types)))
try:
signature_type, params, oauth_params = signature_types_with_oauth_params[
0]
except IndexError:
raise errors.InvalidRequestError(
description='Missing mandatory OAuth parameters.')
return signature_type, params, oauth_params | [
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OpenCobolIDE/OpenCobolIDE | c78d0d335378e5fe0a5e74f53c19b68b55e85388 | open_cobol_ide/extlibs/pyqode/core/widgets/_pty.py | python | spawn | (argv, master_read=_read, stdin_read=_read) | return os.waitpid(pid, 0)[1] | Create a spawned process. | Create a spawned process. | [
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] | def spawn(argv, master_read=_read, stdin_read=_read):
"""Create a spawned process."""
if type(argv) == type(''):
argv = (argv,)
pid, master_fd = fork()
if pid == CHILD:
try:
os.execlp(argv[0], *argv)
except:
# If we wanted to be really clever, we would use
# the same method as subprocess() to pass the error
# back to the parent. For now just dump stack trace.
traceback.print_exc()
finally:
os._exit(1)
try:
mode = tty.tcgetattr(STDIN_FILENO)
tty.setraw(STDIN_FILENO)
restore = 1
except tty.error: # This is the same as termios.error
restore = 0
try:
_copy(master_fd, master_read, stdin_read)
except OSError:
# Some OSes never return an EOF on pty, just raise
# an error instead.
pass
finally:
if restore:
tty.tcsetattr(STDIN_FILENO, tty.TCSAFLUSH, mode)
os.close(master_fd)
return os.waitpid(pid, 0)[1] | [
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ppizarror/pygame-menu | da5827a1ad0686e8ff2aa536b74bbfba73967bcf | pygame_menu/widgets/widget/textinput.py | python | TextInput._check_input_size | (self) | return self._maxchar <= len(self._input_string) | Check input size.
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"""
Check input size.
:return: ``True`` if the input must be limited
"""
if self._maxchar == 0:
return False
return self._maxchar <= len(self._input_string) | [
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lykops/lykchat | 9efe12ad5a4fa079f700b183476a4c7b3322e135 | library/storage/database/mongo.py | python | Op_Mongo._handler_condition | (self, condition_dict) | return condition_dict | 在查询或更新数据时，对查询条件进行处理 | 在查询或更新数据时，对查询条件进行处理 | [
"在查询或更新数据时，对查询条件进行处理"
] | def _handler_condition(self, condition_dict):
'''
在查询或更新数据时，对查询条件进行处理
'''
condition_dict = dot2_(condition_dict)
for k, v in condition_dict.items() :
if k == '_id' :
# 把_id的值进行转化
if isinstance(v, str) :
try :
v = int(v)
except :
v = ObjectId(v)
condition_dict[k] = v
return condition_dict | [
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almarklein/visvis | 766ed97767b44a55a6ff72c742d7385e074d3d55 | core/cameras.py | python | ThreeDCamera.OnResize | (self, event) | OnResize(event)
Callback that adjusts the daspect (if axes.daspectAuto is True)
when the window dimensions change. | OnResize(event)
Callback that adjusts the daspect (if axes.daspectAuto is True)
when the window dimensions change. | [
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""" OnResize(event)
Callback that adjusts the daspect (if axes.daspectAuto is True)
when the window dimensions change.
"""
# Get new size factor
w,h = self.axes.position.size
sizeFactor1 = float(h) / w
# Get old size factor
sizeFactor2 = self._windowSizeFactor
# Make it quick if daspect is not in auto-mode
if not self.axes.daspectAuto:
self._windowSizeFactor = sizeFactor1
return
# Get daspect factor
daspectFactor = sizeFactor1
if sizeFactor2:
daspectFactor /= sizeFactor2
# Set size factor for next time
self._windowSizeFactor = sizeFactor1
# Change daspect. Zoom is never changed
self._SetDaspect(daspectFactor, 2, 2) | [
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tensorwerk/hangar-py | a6deb22854a6c9e9709011b91c1c0eeda7f47bb0 | src/hangar/repository.py | python | Repository.force_release_writer_lock | (self) | return success | Force release the lock left behind by an unclosed writer-checkout
.. warning::
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"""Force release the lock left behind by an unclosed writer-checkout
.. warning::
*NEVER USE THIS METHOD IF WRITER PROCESS IS CURRENTLY ACTIVE.* At the time
of writing, the implications of improper/malicious use of this are not
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.. note::
This entire mechanism is subject to review/replacement in the future.
Returns
-------
bool
if the operation was successful.
"""
self.__verify_repo_initialized()
forceReleaseSentinal = parsing.repo_writer_lock_force_release_sentinal()
success = heads.release_writer_lock(self._env.branchenv, forceReleaseSentinal)
return success | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/django_opentracing-1.1.0/versioneer.py | python | render_git_describe_long | (pieces) | return rendered | TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
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"""TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
rendered += "-%d-g%s" % (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered | [
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tlsfuzzer/tlsfuzzer | fe2e4af145446d603a9da2e202e10ea80ccd298d | tlsfuzzer/analysis.py | python | Analysis.ecdf_plot | (self) | Generate ECDF plot comparing distributions of the test classes. | Generate ECDF plot comparing distributions of the test classes. | [
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] | def ecdf_plot(self):
"""Generate ECDF plot comparing distributions of the test classes."""
if not self.draw_ecdf_plot:
return None
data = self.load_data()
fig = Figure(figsize=(16, 12))
canvas = FigureCanvas(fig)
ax = fig.add_subplot(1, 1, 1)
for classname in data:
values = data.loc[:, classname]
levels = np.linspace(1. / len(values), 1, len(values))
ax.step(sorted(values), levels, where='post')
self.make_legend(ax)
ax.set_title("Empirical Cumulative Distribution Function")
ax.set_xlabel("Time [s]")
ax.set_ylabel("Cumulative probability")
canvas.print_figure(join(self.output, "ecdf_plot.png"),
bbox_inches="tight")
quant = np.quantile(values, [0.01, 0.95])
quant[0] *= 0.98
quant[1] *= 1.02
ax.set_xlim(quant)
canvas.print_figure(join(self.output, "ecdf_plot_zoom_in.png"),
bbox_inches="tight") | [
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firewalld/firewalld | 368e5a1e3eeff21ed55d4f2549836d45d8636ab5 | src/firewall/server/config.py | python | FirewallDConfig.addService2 | (self, service, settings, sender=None) | return config_service | add service with given name and settings | add service with given name and settings | [
"add",
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"with",
"given",
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"settings"
] | def addService2(self, service, settings, sender=None):
"""add service with given name and settings
"""
service = dbus_to_python(service, str)
settings = dbus_to_python(settings)
log.debug1("config.addService2('%s')", service)
self.accessCheck(sender)
obj = self.config.new_service_dict(service, settings)
config_service = self._addService(obj)
return config_service | [
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akanazawa/human_dynamics | 0887f37464c9a079ad7d69c8358cecd0f43c4f2a | src/omega.py | python | OmegasPred.set_cams | (self, cams) | Only used for opt_cam | Only used for opt_cam | [
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] | def set_cams(self, cams):
"""
Only used for opt_cam
"""
assert self.use_optcam
self.cams = cams | [
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espnet/espnet | ea411f3f627b8f101c211e107d0ff7053344ac80 | espnet/optimizer/chainer.py | python | SGDFactory.from_args | (target, args: argparse.Namespace) | return opt | Initialize optimizer from argparse Namespace.
Args:
target: for pytorch `model.parameters()`,
for chainer `model`
args (argparse.Namespace): parsed command-line args | Initialize optimizer from argparse Namespace. | [
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] | def from_args(target, args: argparse.Namespace):
"""Initialize optimizer from argparse Namespace.
Args:
target: for pytorch `model.parameters()`,
for chainer `model`
args (argparse.Namespace): parsed command-line args
"""
opt = chainer.optimizers.SGD(
lr=args.lr,
)
opt.setup(target)
opt.add_hook(WeightDecay(args.weight_decay))
return opt | [
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frappe/frappe | b64cab6867dfd860f10ccaf41a4ec04bc890b583 | frappe/core/doctype/file/file.py | python | delete_file | (path) | Delete file from `public folder` | Delete file from `public folder` | [
"Delete",
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] | def delete_file(path):
"""Delete file from `public folder`"""
if path:
if ".." in path.split("/"):
frappe.msgprint(_("It is risky to delete this file: {0}. Please contact your System Manager.").format(path))
parts = os.path.split(path.strip("/"))
if parts[0]=="files":
path = frappe.utils.get_site_path("public", "files", parts[-1])
else:
path = frappe.utils.get_site_path("private", "files", parts[-1])
path = encode(path)
if os.path.exists(path):
os.remove(path) | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/utils/dummy_pt_objects.py | python | ConvBertForMaskedLM.forward | (self, *args, **kwargs) | [] | def forward(self, *args, **kwargs):
requires_backends(self, ["torch"]) | [
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apache/tvm | 6eb4ed813ebcdcd9558f0906a1870db8302ff1e0 | python/tvm/relay/op/transform.py | python | expand_dims | (data, axis, num_newaxis=1) | Insert `num_newaxis` axes at the position given by `axis`.
Parameters
----------
data : relay.Expr
The input data to the operator.
axis : Union[int, Expr]
The axis at which the input array is expanded.
Should lie in range `[-data.ndim - 1, data.ndim]`.
If `axis < 0`, it is the first axis inserted;
If `axis >= 0`, it is the last axis inserted in Python's negative indexing.
num_newaxis : int
Number of axes to be inserted. Should be >= 0.
Returns
-------
result : relay.Expr
The reshaped result. | Insert `num_newaxis` axes at the position given by `axis`. | [
"Insert",
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"at",
"the",
"position",
"given",
"by",
"axis",
"."
] | def expand_dims(data, axis, num_newaxis=1):
"""Insert `num_newaxis` axes at the position given by `axis`.
Parameters
----------
data : relay.Expr
The input data to the operator.
axis : Union[int, Expr]
The axis at which the input array is expanded.
Should lie in range `[-data.ndim - 1, data.ndim]`.
If `axis < 0`, it is the first axis inserted;
If `axis >= 0`, it is the last axis inserted in Python's negative indexing.
num_newaxis : int
Number of axes to be inserted. Should be >= 0.
Returns
-------
result : relay.Expr
The reshaped result.
"""
if isinstance(axis, int):
return _make.expand_dims(data, axis, num_newaxis)
if isinstance(axis, Expr):
# TODO (AndrewZhaoLuo): investigate performance issues with consecutive
# dynamic expand_dims on non-llvm targets.
return _dyn_make.expand_dims(data, axis, num_newaxis)
raise ValueError(f"Unknown type for axis: {type(axis)}") | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/myq/light.py | python | MyQLight.is_on | (self) | return MYQ_TO_HASS.get(self._device.state) == STATE_ON | Return true if the light is on, else False. | Return true if the light is on, else False. | [
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] | def is_on(self):
"""Return true if the light is on, else False."""
return MYQ_TO_HASS.get(self._device.state) == STATE_ON | [
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django-nonrel/django-nonrel | 4fbfe7344481a5eab8698f79207f09124310131b | django/contrib/contenttypes/generic.py | python | GenericRelation.extra_filters | (self, pieces, pos, negate) | return [("%s__%s" % (prefix, self.content_type_field_name),
content_type)] | Return an extra filter to the queryset so that the results are filtered
on the appropriate content type. | Return an extra filter to the queryset so that the results are filtered
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] | def extra_filters(self, pieces, pos, negate):
"""
Return an extra filter to the queryset so that the results are filtered
on the appropriate content type.
"""
if negate:
return []
ContentType = get_model("contenttypes", "contenttype")
content_type = ContentType.objects.get_for_model(self.model)
prefix = "__".join(pieces[:pos + 1])
return [("%s__%s" % (prefix, self.content_type_field_name),
content_type)] | [
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pengming617/bert_textMatching | b79c9110447b0eef2c1919bf8bf3c8e3656900a8 | modeling.py | python | BertConfig.__init__ | (self,
vocab_size,
hidden_size=768,
num_hidden_layers=12,
num_attention_heads=12,
intermediate_size=3072,
hidden_act="gelu",
hidden_dropout_prob=0.1,
attention_probs_dropout_prob=0.1,
max_position_embeddings=512,
type_vocab_size=16,
initializer_range=0.02) | Constructs BertConfig.
Args:
vocab_size: Vocabulary size of `inputs_ids` in `BertModel`.
hidden_size: Size of the encoder layers and the pooler layer.
num_hidden_layers: Number of hidden layers in the Transformer encoder.
num_attention_heads: Number of attention heads for each attention layer in
the Transformer encoder.
intermediate_size: The size of the "intermediate" (i.e., feed-forward)
layer in the Transformer encoder.
hidden_act: The non-linear activation function (function or string) in the
encoder and pooler.
hidden_dropout_prob: The dropout probability for all fully connected
layers in the embeddings, encoder, and pooler.
attention_probs_dropout_prob: The dropout ratio for the attention
probabilities.
max_position_embeddings: The maximum sequence length that this model might
ever be used with. Typically set this to something large just in case
(e.g., 512 or 1024 or 2048).
type_vocab_size: The vocabulary size of the `token_type_ids` passed into
`BertModel`.
initializer_range: The stdev of the truncated_normal_initializer for
initializing all weight matrices. | Constructs BertConfig. | [
"Constructs",
"BertConfig",
"."
] | def __init__(self,
vocab_size,
hidden_size=768,
num_hidden_layers=12,
num_attention_heads=12,
intermediate_size=3072,
hidden_act="gelu",
hidden_dropout_prob=0.1,
attention_probs_dropout_prob=0.1,
max_position_embeddings=512,
type_vocab_size=16,
initializer_range=0.02):
"""Constructs BertConfig.
Args:
vocab_size: Vocabulary size of `inputs_ids` in `BertModel`.
hidden_size: Size of the encoder layers and the pooler layer.
num_hidden_layers: Number of hidden layers in the Transformer encoder.
num_attention_heads: Number of attention heads for each attention layer in
the Transformer encoder.
intermediate_size: The size of the "intermediate" (i.e., feed-forward)
layer in the Transformer encoder.
hidden_act: The non-linear activation function (function or string) in the
encoder and pooler.
hidden_dropout_prob: The dropout probability for all fully connected
layers in the embeddings, encoder, and pooler.
attention_probs_dropout_prob: The dropout ratio for the attention
probabilities.
max_position_embeddings: The maximum sequence length that this model might
ever be used with. Typically set this to something large just in case
(e.g., 512 or 1024 or 2048).
type_vocab_size: The vocabulary size of the `token_type_ids` passed into
`BertModel`.
initializer_range: The stdev of the truncated_normal_initializer for
initializing all weight matrices.
"""
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.hidden_act = hidden_act
self.intermediate_size = intermediate_size
self.hidden_dropout_prob = hidden_dropout_prob
self.attention_probs_dropout_prob = attention_probs_dropout_prob
self.max_position_embeddings = max_position_embeddings
self.type_vocab_size = type_vocab_size
self.initializer_range = initializer_range | [
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BillBillBillBill/Tickeys-linux | 2df31b8665004c58a5d4ab05277f245267d96364 | tickeys/kivy/support.py | python | install_android | () | Install hooks for the android platform.
* Automatically sleep when the device is paused.
* Automatically kill the application when the return key is pressed. | Install hooks for the android platform. | [
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] | def install_android():
'''Install hooks for the android platform.
* Automatically sleep when the device is paused.
* Automatically kill the application when the return key is pressed.
'''
try:
import android
except ImportError:
print('Android lib is missing, cannot install android hooks')
return
from kivy.clock import Clock
from kivy.logger import Logger
import pygame
Logger.info('Support: Android install hooks')
# Init the library
android.init()
android.map_key(android.KEYCODE_MENU, pygame.K_MENU)
android.map_key(android.KEYCODE_BACK, pygame.K_ESCAPE)
# Check if android should be paused or not.
# If pause is requested, just leave the app.
def android_check_pause(*largs):
# do nothing until android asks for it.
if not android.check_pause():
return
from kivy.app import App
from kivy.base import stopTouchApp
from kivy.logger import Logger
from kivy.core.window import Window
global g_android_redraw_count
# try to get the current running application
Logger.info('Android: Must go into sleep mode, check the app')
app = App.get_running_app()
# no running application, stop our loop.
if app is None:
Logger.info('Android: No app running, stop everything.')
stopTouchApp()
return
# try to go to pause mode
if app.dispatch('on_pause'):
Logger.info('Android: App paused, now wait for resume.')
# app goes in pause mode, wait.
android.wait_for_resume()
# is it a stop or resume ?
if android.check_stop():
# app must stop
Logger.info('Android: Android wants to close our app.')
stopTouchApp()
else:
# app resuming now !
Logger.info('Android: Android has resumed, resume the app.')
app.dispatch('on_resume')
Window.canvas.ask_update()
g_android_redraw_count = 25 # 5 frames/seconds for 5 seconds
Clock.unschedule(_android_ask_redraw)
Clock.schedule_interval(_android_ask_redraw, 1 / 5)
Logger.info('Android: App resume completed.')
# app doesn't support pause mode, just stop it.
else:
Logger.info('Android: App doesn\'t support pause mode, stop.')
stopTouchApp()
Clock.schedule_interval(android_check_pause, 0) | [
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DonnchaC/shadowbrokers-exploits | 42d8265db860b634717da4faa668b2670457cf7e | windows/fuzzbunch/env.py | python | setup_lib_paths | (fbdir, libdir) | This is a little bit of a hack, but it should work. If we detect that the EDFLIB_DIR is
not in LD_LIBRARY_PATH, restart after adding it. | This is a little bit of a hack, but it should work. If we detect that the EDFLIB_DIR is
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] | def setup_lib_paths(fbdir, libdir):
"""This is a little bit of a hack, but it should work. If we detect that the EDFLIB_DIR is
not in LD_LIBRARY_PATH, restart after adding it.
"""
try:
libpath = os.environ['LD_LIBRARY_PATH']
except KeyError:
libpath = ""
if not (sys.platform == "win32") and (libdir not in libpath):
# To get the Fuzzbunch environment setup properly, we need to modify LD_LIBRARY_PATH.
# To do that, we need to rerun Fuzzbunch so that it picks up the new LD_LIBRARY_PATH
os.environ['LD_LIBRARY_PATH'] = "%s:%s" % (libdir,libpath) | [
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brython-dev/brython | 9cba5fb7f43a9b52fff13e89b403e02a1dfaa5f3 | www/src/Lib/genericpath.py | python | isfile | (path) | return stat.S_ISREG(st.st_mode) | Test whether a path is a regular file | Test whether a path is a regular file | [
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"""Test whether a path is a regular file"""
try:
st = os.stat(path)
except (OSError, ValueError):
return False
return stat.S_ISREG(st.st_mode) | [
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sqall01/alertR | e1d1a83e54f876cc4cd7bd87387e05cb75d4dc13 | alertClientRaspberryPi/lib/client/util.py | python | MsgBuilder.build_auth_msg | (username: str,
password: str,
version: float,
rev: int,
regMessageSize: int) | return json.dumps(message) | Internal function that builds the client authentication message.
:param username:
:param password:
:param version:
:param rev:
:param regMessageSize:
:return: | Internal function that builds the client authentication message. | [
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] | def build_auth_msg(username: str,
password: str,
version: float,
rev: int,
regMessageSize: int) -> str:
"""
Internal function that builds the client authentication message.
:param username:
:param password:
:param version:
:param rev:
:param regMessageSize:
:return:
"""
payload = {"type": "request",
"version": version,
"rev": rev,
"username": username,
"password": password}
utc_timestamp = int(time.time())
message = {"msgTime": utc_timestamp,
"size": regMessageSize,
"message": "initialization",
"payload": payload}
return json.dumps(message) | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/groups/cubic_braid.py | python | CubicBraidGroup.braid_group | (self) | return self._braid_group | r"""
Return an Instance of :class:`BraidGroup` with identical generators, such that
there exists an epimorphism to ``self``.
OUTPUT:
Instance of :class:`BraidGroup` having conversion maps to and from ``self``
(which is just a section in the latter case).
EXAMPLES::
sage: U5 = AssionGroupU(5); U5
Assion group on 5 strands of type U
sage: B5 = U5.braid_group(); B5
Braid group on 5 strands
sage: b = B5([4,3,2,-4,1])
sage: u = U5([4,3,2,-4,1])
sage: u == b
False
sage: b.burau_matrix()
[ 1 - t t 0 0 0]
[ 1 - t 0 t 0 0]
[ 1 - t 0 0 0 t]
[ 1 - t 0 0 1 -1 + t]
[ 1 0 0 0 0]
sage: u.burau_matrix()
[t + 1 t 0 0 0]
[t + 1 0 t 0 0]
[t + 1 0 0 0 t]
[t + 1 0 0 1 t + 1]
[ 1 0 0 0 0]
sage: bU = U5(b)
sage: uB = B5(u)
sage: bU == u
True
sage: uB == b
True | r"""
Return an Instance of :class:`BraidGroup` with identical generators, such that
there exists an epimorphism to ``self``. | [
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] | def braid_group(self):
r"""
Return an Instance of :class:`BraidGroup` with identical generators, such that
there exists an epimorphism to ``self``.
OUTPUT:
Instance of :class:`BraidGroup` having conversion maps to and from ``self``
(which is just a section in the latter case).
EXAMPLES::
sage: U5 = AssionGroupU(5); U5
Assion group on 5 strands of type U
sage: B5 = U5.braid_group(); B5
Braid group on 5 strands
sage: b = B5([4,3,2,-4,1])
sage: u = U5([4,3,2,-4,1])
sage: u == b
False
sage: b.burau_matrix()
[ 1 - t t 0 0 0]
[ 1 - t 0 t 0 0]
[ 1 - t 0 0 0 t]
[ 1 - t 0 0 1 -1 + t]
[ 1 0 0 0 0]
sage: u.burau_matrix()
[t + 1 t 0 0 0]
[t + 1 0 t 0 0]
[t + 1 0 0 0 t]
[t + 1 0 0 1 t + 1]
[ 1 0 0 0 0]
sage: bU = U5(b)
sage: uB = B5(u)
sage: bU == u
True
sage: uB == b
True
"""
return self._braid_group | [
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] | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/groups/cubic_braid.py#L1346-L1385 | |
googleapis/python-ndb | e780c81cde1016651afbfcad8180d9912722cf1b | google/cloud/ndb/_datastore_api.py | python | _LookupBatch.idle_callback | (self) | Perform a Datastore Lookup on all batched Lookup requests. | Perform a Datastore Lookup on all batched Lookup requests. | [
"Perform",
"a",
"Datastore",
"Lookup",
"on",
"all",
"batched",
"Lookup",
"requests",
"."
] | def idle_callback(self):
"""Perform a Datastore Lookup on all batched Lookup requests."""
keys = []
for todo_key in self.todo.keys():
key_pb = entity_pb2.Key()
key_pb.ParseFromString(todo_key)
keys.append(key_pb)
read_options = get_read_options(self.options)
rpc = _datastore_lookup(
keys,
read_options,
retries=self.options.retries,
timeout=self.options.timeout,
)
rpc.add_done_callback(self.lookup_callback) | [
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larryhastings/gilectomy | 4315ec3f1d6d4f813cc82ce27a24e7f784dbfc1a | Lib/distutils/command/install.py | python | install.create_home_path | (self) | Create directories under ~. | Create directories under ~. | [
"Create",
"directories",
"under",
"~",
"."
] | def create_home_path(self):
"""Create directories under ~."""
if not self.user:
return
home = convert_path(os.path.expanduser("~"))
for name, path in self.config_vars.items():
if path.startswith(home) and not os.path.isdir(path):
self.debug_print("os.makedirs('%s', 0o700)" % path)
os.makedirs(path, 0o700) | [
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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/guicomponents.py | python | BinInfoPanel.__init__ | (self) | [] | def __init__(self):
GObject.GObject.__init__(self)
self.set_homogeneous(False)
if editorstate.screen_size_small_height() == True:
font_desc = "sans bold 8"
else:
font_desc = "sans bold 9"
self.bin_name = Gtk.Label()
self.bin_name.modify_font(Pango.FontDescription(font_desc))
self.bin_name.set_sensitive(False)
self.items = Gtk.Label()
self.items_value = Gtk.Label()
self.items.modify_font(Pango.FontDescription(font_desc))
self.items_value.modify_font(Pango.FontDescription(font_desc))
self.items.set_sensitive(False)
self.items_value.set_sensitive(False)
info_col_2 = Gtk.HBox()
info_col_2.pack_start(self.bin_name, False, True, 0)
info_col_2.pack_start(Gtk.Label(), True, True, 0)
info_col_3 = Gtk.HBox()
info_col_3.pack_start(self.items, False, False, 0)
info_col_3.pack_start(self.items_value, False, False, 0)
info_col_3.pack_start(Gtk.Label(), True, True, 0)
self.pack_start(guiutils.pad_label(24, 4), False, False, 0)
self.pack_start(info_col_2, False, False, 0)
self.pack_start(guiutils.pad_label(12, 4), False, False, 0)
self.pack_start(info_col_3, False, False, 0)
self.pack_start(Gtk.Label(), True, True, 0)
self.set_spacing(4) | [
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keras-team/keras-contrib | 3fc5ef709e061416f4bc8a92ca3750c824b5d2b0 | keras_contrib/utils/save_load_utils.py | python | save_all_weights | (model, filepath, include_optimizer=True) | Save model weights and optimizer weights but not configuration to a HDF5 file.
Functionally between `save` and `save_weights`.
The HDF5 file contains:
- the model's weights
- the model's optimizer's state (if any)
If you have a complicated model or set of models that do not serialize
to JSON correctly, use this method.
# Arguments
model: Keras model instance to be saved.
filepath: String, path where to save the model.
include_optimizer: If True, save optimizer's state together.
# Raises
ImportError: if h5py is not available. | Save model weights and optimizer weights but not configuration to a HDF5 file.
Functionally between `save` and `save_weights`. | [
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"HDF5",
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".",
"Functionally",
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"save",
"and",
"save_weights",
"."
] | def save_all_weights(model, filepath, include_optimizer=True):
"""
Save model weights and optimizer weights but not configuration to a HDF5 file.
Functionally between `save` and `save_weights`.
The HDF5 file contains:
- the model's weights
- the model's optimizer's state (if any)
If you have a complicated model or set of models that do not serialize
to JSON correctly, use this method.
# Arguments
model: Keras model instance to be saved.
filepath: String, path where to save the model.
include_optimizer: If True, save optimizer's state together.
# Raises
ImportError: if h5py is not available.
"""
if h5py is None:
raise ImportError('`save_all_weights` requires h5py.')
with h5py.File(filepath, 'w') as f:
model_weights_group = f.create_group('model_weights')
model_layers = model.layers
saving.save_weights_to_hdf5_group(model_weights_group, model_layers)
if include_optimizer and hasattr(model, 'optimizer') and model.optimizer:
if isinstance(model.optimizer, optimizers.TFOptimizer):
warnings.warn(
'TensorFlow optimizers do not '
'make it possible to access '
'optimizer attributes or optimizer state '
'after instantiation. '
'As a result, we cannot save the optimizer '
'as part of the model save file.'
'You will have to compile your model again after loading it. '
'Prefer using a Keras optimizer instead '
'(see keras.io/optimizers).')
else:
# Save optimizer weights.
symbolic_weights = getattr(model.optimizer, 'weights')
if symbolic_weights:
optimizer_weights_group = f.create_group('optimizer_weights')
weight_values = K.batch_get_value(symbolic_weights)
weight_names = []
for i, (w, val) in enumerate(zip(symbolic_weights, weight_values)):
# Default values of symbolic_weights is /variable for theano
if K.backend() == 'theano':
if hasattr(w, 'name') and w.name != "/variable":
name = str(w.name)
else:
name = 'param_' + str(i)
else:
if hasattr(w, 'name') and w.name:
name = str(w.name)
else:
name = 'param_' + str(i)
weight_names.append(name.encode('utf8'))
optimizer_weights_group.attrs['weight_names'] = weight_names
for name, val in zip(weight_names, weight_values):
param_dset = optimizer_weights_group.create_dataset(
name,
val.shape,
dtype=val.dtype)
if not val.shape:
# scalar
param_dset[()] = val
else:
param_dset[:] = val | [
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spesmilo/electrum | bdbd59300fbd35b01605e66145458e5f396108e8 | electrum/wallet.py | python | Abstract_Wallet.relayfee | (self) | return relayfee(self.network) | [] | def relayfee(self):
return relayfee(self.network) | [
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warfares/pretty-json | 2bf88fc675f684b95ea01af31014b9fac206b6b7 | build/tools/BeautifulSoup.py | python | BeautifulStoneSoup.reset | (self) | [] | def reset(self):
Tag.__init__(self, self, self.ROOT_TAG_NAME)
self.hidden = 1
SGMLParser.reset(self)
self.currentData = []
self.currentTag = None
self.tagStack = []
self.quoteStack = []
self.pushTag(self) | [
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"]... | https://github.com/warfares/pretty-json/blob/2bf88fc675f684b95ea01af31014b9fac206b6b7/build/tools/BeautifulSoup.py#L996-L1004 | ||||
adulau/Forban | 4b06c8a2e2f18ff872ca20a534587a5f15a692fa | lib/ext/cherrypy/_cpcompat.py | python | base64_decode | (n, encoding='ISO-8859-1') | Return the native string base64-decoded (as a native string). | Return the native string base64-decoded (as a native string). | [
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"string",
"base64",
"-",
"decoded",
"(",
"as",
"a",
"native",
"string",
")",
"."
] | def base64_decode(n, encoding='ISO-8859-1'):
"""Return the native string base64-decoded (as a native string)."""
if isinstance(n, unicodestr):
b = n.encode(encoding)
else:
b = n
b = _base64_decodebytes(b)
if nativestr is unicodestr:
return b.decode(encoding)
else:
return b | [
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gmr/queries | 6995ad18ee2b7fe2ce36d75f50979a47e3e2171d | queries/session.py | python | Session._incr_exceptions | (self) | Increment the number of exceptions for the current connection. | Increment the number of exceptions for the current connection. | [
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"the",
"number",
"of",
"exceptions",
"for",
"the",
"current",
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"."
] | def _incr_exceptions(self):
"""Increment the number of exceptions for the current connection."""
self._pool_manager.get_connection(self.pid, self._conn).exceptions += 1 | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/gzip.py | python | GzipFile.__init__ | (self, filename=None, mode=None,
compresslevel=9, fileobj=None, mtime=None) | Constructor for the GzipFile class.
At least one of fileobj and filename must be given a
non-trivial value.
The new class instance is based on fileobj, which can be a regular
file, a StringIO object, or any other object which simulates a file.
It defaults to None, in which case filename is opened to provide
a file object.
When fileobj is not None, the filename argument is only used to be
included in the gzip file header, which may includes the original
filename of the uncompressed file. It defaults to the filename of
fileobj, if discernible; otherwise, it defaults to the empty string,
and in this case the original filename is not included in the header.
The mode argument can be any of 'r', 'rb', 'a', 'ab', 'w', or 'wb',
depending on whether the file will be read or written. The default
is the mode of fileobj if discernible; otherwise, the default is 'rb'.
Be aware that only the 'rb', 'ab', and 'wb' values should be used
for cross-platform portability.
The compresslevel argument is an integer from 1 to 9 controlling the
level of compression; 1 is fastest and produces the least compression,
and 9 is slowest and produces the most compression. The default is 9.
The mtime argument is an optional numeric timestamp to be written
to the stream when compressing. All gzip compressed streams
are required to contain a timestamp. If omitted or None, the
current time is used. This module ignores the timestamp when
decompressing; however, some programs, such as gunzip, make use
of it. The format of the timestamp is the same as that of the
return value of time.time() and of the st_mtime member of the
object returned by os.stat(). | Constructor for the GzipFile class. | [
"Constructor",
"for",
"the",
"GzipFile",
"class",
"."
] | def __init__(self, filename=None, mode=None,
compresslevel=9, fileobj=None, mtime=None):
"""Constructor for the GzipFile class.
At least one of fileobj and filename must be given a
non-trivial value.
The new class instance is based on fileobj, which can be a regular
file, a StringIO object, or any other object which simulates a file.
It defaults to None, in which case filename is opened to provide
a file object.
When fileobj is not None, the filename argument is only used to be
included in the gzip file header, which may includes the original
filename of the uncompressed file. It defaults to the filename of
fileobj, if discernible; otherwise, it defaults to the empty string,
and in this case the original filename is not included in the header.
The mode argument can be any of 'r', 'rb', 'a', 'ab', 'w', or 'wb',
depending on whether the file will be read or written. The default
is the mode of fileobj if discernible; otherwise, the default is 'rb'.
Be aware that only the 'rb', 'ab', and 'wb' values should be used
for cross-platform portability.
The compresslevel argument is an integer from 1 to 9 controlling the
level of compression; 1 is fastest and produces the least compression,
and 9 is slowest and produces the most compression. The default is 9.
The mtime argument is an optional numeric timestamp to be written
to the stream when compressing. All gzip compressed streams
are required to contain a timestamp. If omitted or None, the
current time is used. This module ignores the timestamp when
decompressing; however, some programs, such as gunzip, make use
of it. The format of the timestamp is the same as that of the
return value of time.time() and of the st_mtime member of the
object returned by os.stat().
"""
# guarantee the file is opened in binary mode on platforms
# that care about that sort of thing
if mode and 'b' not in mode:
mode += 'b'
if fileobj is None:
fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
if filename is None:
if hasattr(fileobj, 'name'): filename = fileobj.name
else: filename = ''
if mode is None:
if hasattr(fileobj, 'mode'): mode = fileobj.mode
else: mode = 'rb'
if mode[0:1] == 'r':
self.mode = READ
# Set flag indicating start of a new member
self._new_member = True
# Buffer data read from gzip file. extrastart is offset in
# stream where buffer starts. extrasize is number of
# bytes remaining in buffer from current stream position.
self.extrabuf = ""
self.extrasize = 0
self.extrastart = 0
self.name = filename
# Starts small, scales exponentially
self.min_readsize = 100
elif mode[0:1] == 'w' or mode[0:1] == 'a':
self.mode = WRITE
self._init_write(filename)
self.compress = zlib.compressobj(compresslevel,
zlib.DEFLATED,
-zlib.MAX_WBITS,
zlib.DEF_MEM_LEVEL,
0)
else:
raise IOError, "Mode " + mode + " not supported"
self.fileobj = fileobj
self.offset = 0
self.mtime = mtime
if self.mode == WRITE:
self._write_gzip_header() | [
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transferwise/pipelinewise | 6934b3851512dbdd4280790bf253a0a13ab65684 | pipelinewise/cli/pipelinewise.py | python | PipelineWise.status | (self) | Prints a status summary table of every imported pipeline with their tap and target. | Prints a status summary table of every imported pipeline with their tap and target. | [
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"with",
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"target",
"."
] | def status(self):
"""
Prints a status summary table of every imported pipeline with their tap and target.
"""
targets = self.get_targets()
tab_headers = [
'Tap ID',
'Tap Type',
'Target ID',
'Target Type',
'Enabled',
'Status',
'Last Sync',
'Last Sync Result',
]
tab_body = []
pipelines = 0
for target in targets:
taps = self.get_taps(target['id'])
for tap in taps:
tab_body.append(
[
tap.get('id', '<Unknown>'),
tap.get('type', '<Unknown>'),
target.get('id', '<Unknown>'),
target.get('type', '<Unknown>'),
tap.get('enabled', '<Unknown>'),
tap.get('status', {}).get('currentStatus', '<Unknown>'),
tap.get('status', {}).get('lastTimestamp', '<Unknown>'),
tap.get('status', {}).get('lastStatus', '<Unknown>'),
]
)
pipelines += 1
print(tabulate(tab_body, headers=tab_headers, tablefmt='simple'))
print(f'{pipelines} pipeline(s)') | [
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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/middlebar.py | python | _get_conf_panel | () | return pane | [] | def _get_conf_panel():
prefs = editorpersistance.prefs
global toolbar_list_box
# Widgets
layout_select = Gtk.ComboBoxText()
layout_select.set_tooltip_text(_("Select Render quality"))
layout_select.append_text(_("Timecode Left"))
layout_select.append_text(_("Timecode Center"))
layout_select.append_text(_("Components Centered"))
layout_select.set_active(prefs.midbar_layout) # indexes correspond with appconsts values.
layout_select.connect("changed", lambda w,e: _layout_conf_changed(w), None)
layout_row = guiutils.get_left_justified_box([layout_select])
layout_frame = guiutils.get_named_frame(_("Layout"), layout_row)
vbox = Gtk.Box(orientation=Gtk.Orientation.VERTICAL, spacing=10)
choice = Gtk.Label(_("Set button group active state and position."))
toolbar_list_box = Gtk.ListBox()
toolbar_list_box.set_selection_mode(Gtk.SelectionMode.SINGLE)
box_move = Gtk.Box(orientation=Gtk.Orientation.HORIZONTAL, spacing=10)
button_up = Gtk.Button(label=_("Up"))
button_up.connect("clicked", row_up, vbox)
box_move.pack_start(button_up, False, False, 0)
button_down = Gtk.Button(label=_("Down"))
button_down.connect("clicked", row_down, vbox)
box_move.pack_start(button_down, False, False, 0)
button_reset = Gtk.Button(label=_("Reset Positions"))
button_reset.connect("clicked", row_down, vbox)
box_move.pack_start(Gtk.Label(), True, True, 0)
box_move.pack_start(button_reset, False, False, 0)
vbox.pack_start(choice, False, False, 0)
vbox.pack_start(toolbar_list_box, False, False, 0)
vbox.pack_start(box_move, False, False, 0)
draw_listbox(vbox)
vbox.set_size_request(400, 200)
groups_frame = guiutils.get_named_frame(_("Buttons Groups"), vbox)
pane = Gtk.Box(orientation=Gtk.Orientation.VERTICAL, spacing=10)
pane.pack_start(layout_frame, False, False, 0)
pane.pack_start(groups_frame, False, False, 0)
return pane | [
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tobegit3hub/deep_image_model | 8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e | java_predict_client/src/main/proto/tensorflow/contrib/layers/python/layers/feature_column.py | python | _SparseColumn.weight_tensor | (self, input_tensor) | return None | Returns the weight tensor from the given transformed input_tensor. | Returns the weight tensor from the given transformed input_tensor. | [
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trakt/Plex-Trakt-Scrobbler | aeb0bfbe62fad4b06c164f1b95581da7f35dce0b | Trakttv.bundle/Contents/Libraries/Shared/requests/packages/urllib3/fields.py | python | guess_content_type | (filename, default='application/octet-stream') | return default | Guess the "Content-Type" of a file.
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The filename to guess the "Content-Type" of using :mod:`mimetypes`.
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Guess the "Content-Type" of a file.
:param filename:
The filename to guess the "Content-Type" of using :mod:`mimetypes`.
:param default:
If no "Content-Type" can be guessed, default to `default`.
"""
if filename:
return mimetypes.guess_type(filename)[0] or default
return default | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/inspect.py | python | isclass | (object) | return isinstance(object, (type, types.ClassType)) | Return true if the object is a class.
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__doc__ documentation string
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"""Return true if the object is a class.
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WikidPad/WikidPad | 558109638807bc76b4672922686e416ab2d5f79c | WikidPad/lib/pwiki/customtreectrl.py | python | CustomTreeCtrl.GetTreeStyle | (self) | return self._windowStyle | Returns the CustomTreeCtrl style. | Returns the CustomTreeCtrl style. | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/cookielib.py | python | DefaultCookiePolicy.set_allowed_domains | (self, allowed_domains) | Set the sequence of allowed domains, or None. | Set the sequence of allowed domains, or None. | [
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numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/core/debuginfo.py | python | NvvmDIBuilder.mark_location | (self, builder, line) | [] | def mark_location(self, builder, line):
# Avoid duplication
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self._last_lineno = line
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asmty = ir.FunctionType(ir.VoidType(), [])
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md = self._di_location(line)
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Nuitka/Nuitka | 39262276993757fa4e299f497654065600453fc9 | nuitka/build/inline_copy/pkg_resources/pkg_resources/__init__.py | python | _ReqExtras.markers_pass | (self, req, extras=None) | return not req.marker or any(extra_evals) | Evaluate markers for req against each extra that
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Evaluate markers for req against each extra that
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Return False if the req has a marker and fails
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"""
extra_evals = (
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return not req.marker or any(extra_evals) | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/cwp/v20180228/models.py | python | DescribeAssetCoreModuleInfoResponse.__init__ | (self) | r"""
:param Module: 内核模块详情
:type Module: :class:`tencentcloud.cwp.v20180228.models.AssetCoreModuleDetail`
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | r"""
:param Module: 内核模块详情
:type Module: :class:`tencentcloud.cwp.v20180228.models.AssetCoreModuleDetail`
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:type Module: :class:`tencentcloud.cwp.v20180228.models.AssetCoreModuleDetail`
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
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mrkipling/maraschino | c6be9286937783ae01df2d6d8cebfc8b2734a7d7 | lib/sqlalchemy/schema.py | python | Table.drop | (self, bind=None, checkfirst=False) | Issue a ``DROP`` statement for this
:class:`.Table`, using the given :class:`.Connectable`
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See also :meth:`.MetaData.drop_all`. | Issue a ``DROP`` statement for this
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] | def drop(self, bind=None, checkfirst=False):
"""Issue a ``DROP`` statement for this
:class:`.Table`, using the given :class:`.Connectable`
for connectivity.
See also :meth:`.MetaData.drop_all`.
"""
if bind is None:
bind = _bind_or_error(self)
bind._run_visitor(ddl.SchemaDropper,
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isnowfy/pydown | 71ecc891868cd2a34b7e5fe662c99474f2d0fd7f | pygments/formatters/img.py | python | ImageFormatter._get_char_width | (self) | return self.fontw | Get the width of a character. | Get the width of a character. | [
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Get the width of a character.
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StorjOld/pyp2p | 7024208c3af20511496a652ff212f54c420e0464 | pyp2p/rendezvous_client.py | python | RendezvousClient.parse_remote_port | (self, reply) | return remote_port | Parses a remote port from a Rendezvous Server's
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Parses a remote port from a Rendezvous Server's
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remote_port = re.findall("^REMOTE (TCP|UDP) ([0-9]+)$", reply)
if not len(remote_port):
remote_port = 0
else:
remote_port = int(remote_port[0][1])
if remote_port < 1 or remote_port > 65535:
remote_port = 0
return remote_port | [
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microsoft/TextWorld | c419bb63a92c7f6960aa004a367fb18894043e7f | textworld/logic/__init__.py | python | Action.added | (self) | return self._post_set - self._pre_set | All the new propositions being introduced by this action. | All the new propositions being introduced by this action. | [
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Pymol-Scripts/Pymol-script-repo | bcd7bb7812dc6db1595953dfa4471fa15fb68c77 | modules/pdb2pqr/contrib/ZSI-2.1-a1/ZSI/wstools/XMLSchema.py | python | XMLSchemaComponent.getAttributeName | (self) | return self.getAttribute('name') | return attribute name or None | return attribute name or None | [
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redhat-imaging/imagefactory | 176f6e045e1df049d50f33a924653128d5ab8b27 | imgfac/rest/bottle.py | python | StplParser.write_code | (self, line, comment='') | [] | def write_code(self, line, comment=''):
line, comment = self.fix_backward_compatibility(line, comment)
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code += line.lstrip() + comment + '\n'
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