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conan-io/conan | 28ec09f6cbf1d7e27ec27393fd7bbc74891e74a8 | conan/tools/apple/xcodedeps.py | python | XcodeDeps._conf_xconfig_file | (self, dep_name, vars_xconfig_name) | return content_multi | content for conan_poco_x86_release.xcconfig, containing the activation | content for conan_poco_x86_release.xcconfig, containing the activation | [
"content",
"for",
"conan_poco_x86_release",
".",
"xcconfig",
"containing",
"the",
"activation"
] | def _conf_xconfig_file(self, dep_name, vars_xconfig_name):
"""
content for conan_poco_x86_release.xcconfig, containing the activation
"""
# TODO: when it's more clear what to do with the sdk, add the condition for it and also
# we are not taking into account the version for the sdk because we probably
# want to model also the sdk version decoupled of the compiler version
# for example XCode 13 is now using sdk=macosx11.3
# related to: https://github.com/conan-io/conan/issues/9608
template = Template(self._conf_xconfig)
content_multi = template.render(name=dep_name, vars_filename=vars_xconfig_name)
return content_multi | [
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phantomcyber/playbooks | 9e850ecc44cb98c5dde53784744213a1ed5799bd | excessive_account_lockouts_enrichment_and_response.py | python | endpoint_rights_mod | (action=None, success=None, container=None, results=None, handle=None, filtered_artifacts=None, filtered_results=None, custom_function=None, **kwargs) | return | [] | def endpoint_rights_mod(action=None, success=None, container=None, results=None, handle=None, filtered_artifacts=None, filtered_results=None, custom_function=None, **kwargs):
phantom.debug('endpoint_rights_mod() called')
template = """| search index=wineventlog (EventCode=4718 OR EventCode=4717) dest={0} | rename user as \"Account Modified\" | table _time, dest, \"Account Modified\", Access_Right, signature"""
# parameter list for template variable replacement
parameters = [
"artifact:*.cef.destinationAddress",
]
phantom.format(container=container, template=template, parameters=parameters, name="endpoint_rights_mod")
query_endpoint_rights(container=container)
return | [
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/python_clients/venv/lib/python2.7/site-packages/pip/_vendor/distlib/locators.py | python | DirectoryLocator.get_distribution_names | (self) | return result | Return all the distribution names known to this locator. | Return all the distribution names known to this locator. | [
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] | def get_distribution_names(self):
"""
Return all the distribution names known to this locator.
"""
result = set()
for root, dirs, files in os.walk(self.base_dir):
for fn in files:
if self.should_include(fn, root):
fn = os.path.join(root, fn)
url = urlunparse(('file', '',
pathname2url(os.path.abspath(fn)),
'', '', ''))
info = self.convert_url_to_download_info(url, None)
if info:
result.add(info['name'])
if not self.recursive:
break
return result | [
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noio/peas | 4c2503388644cc5ca58c501e6c773d53a883538b | peas/methods/evolution.py | python | SimplePopulation._birth | (self) | return self.population | Creates a population if there is none, returns
current population otherwise. | Creates a population if there is none, returns
current population otherwise. | [
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] | def _birth(self):
""" Creates a population if there is none, returns
current population otherwise.
"""
while len(self.population) < self.popsize:
individual = self.geno_factory()
self.population.append(individual)
return self.population | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/ex-submodules/casexml/apps/stock/consumption.py | python | span_days | (start, end) | return span.days + span.seconds / 86400. | [] | def span_days(start, end):
span = end - start
return span.days + span.seconds / 86400. | [
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/twisted/twisted/application/internet.py | python | StreamServerEndpointService.startService | (self) | Start listening on the endpoint, unless L{privilegedStartService} got
around to it already. | Start listening on the endpoint, unless L{privilegedStartService} got
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] | def startService(self):
"""
Start listening on the endpoint, unless L{privilegedStartService} got
around to it already.
"""
service.Service.startService(self)
if self._waitingForPort is None:
self.privilegedStartService() | [
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flopp/GpxTrackPoster | d7ff0ba61f6396938efd075d841a7c4a226a6f5d | gpxtrackposter/track_loader.py | python | TrackLoader.load_strava_tracks | (self, strava_config: str) | return self._filter_and_merge_tracks(tracks) | [] | def load_strava_tracks(self, strava_config: str) -> typing.List[Track]:
tracks = []
tracks_names = []
if self.cache_dir:
self.strava_cache_file = os.path.join(self.cache_dir, strava_config)
if os.path.isfile(self.strava_cache_file):
with open(self.strava_cache_file, encoding="utf8") as f:
strava_cache_data = json.load(f)
tracks = [self._strava_cache_to_track(i) for i in strava_cache_data]
tracks_names = [track.file_names[0] for track in tracks]
with open(strava_config, encoding="utf8") as f:
strava_data = json.load(f)
filter_type = strava_data.pop("activity_type", None)
client = Client()
response = client.refresh_access_token(**strava_data)
client.access_token = response["access_token"]
filter_dict = {"before": datetime.datetime.utcnow()}
if tracks:
max_time = max(track.start_time() for track in tracks)
filter_dict = {"after": max_time - datetime.timedelta(days=2)}
for activity in client.get_activities(**filter_dict):
# tricky to pass the timezone
if str(activity.id) in tracks_names:
continue
if filter_type and activity.type not in (
[filter_type] if isinstance(filter_type, str) else filter_type
): # pylint: disable=superfluous-parens
continue
t = Track()
t.load_strava(activity)
tracks.append(t)
self._store_strava_tracks_to_cache(tracks)
return self._filter_and_merge_tracks(tracks) | [
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zhixinwang/frustum-convnet | 5b1508d3f2140c3c0dd6dd17b5606b532b7a5ec8 | kitti/kitti_util.py | python | inverse_rigid_trans | (Tr) | return inv_Tr | Inverse a rigid body transform matrix (3x4 as [R|t])
[R'|-R't; 0|1] | Inverse a rigid body transform matrix (3x4 as [R|t])
[R'|-R't; 0|1] | [
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"-",
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] | def inverse_rigid_trans(Tr):
''' Inverse a rigid body transform matrix (3x4 as [R|t])
[R'|-R't; 0|1]
'''
inv_Tr = np.zeros_like(Tr) # 3x4
inv_Tr[0:3, 0:3] = np.transpose(Tr[0:3, 0:3])
inv_Tr[0:3, 3] = np.dot(-np.transpose(Tr[0:3, 0:3]), Tr[0:3, 3])
return inv_Tr | [
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kovidgoyal/calibre | 2b41671370f2a9eb1109b9ae901ccf915f1bd0c8 | src/calibre/utils/fonts/utils.py | python | get_font_characteristics | (raw, raw_is_table=False, return_all=False) | return weight, is_italic, is_bold, is_regular, fs_type, panose, width, is_oblique, is_wws, version | Return (weight, is_italic, is_bold, is_regular, fs_type, panose, width,
is_oblique, is_wws). These
values are taken from the OS/2 table of the font. See
http://www.microsoft.com/typography/otspec/os2.htm for details | Return (weight, is_italic, is_bold, is_regular, fs_type, panose, width,
is_oblique, is_wws). These
values are taken from the OS/2 table of the font. See
http://www.microsoft.com/typography/otspec/os2.htm for details | [
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":",
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... | def get_font_characteristics(raw, raw_is_table=False, return_all=False):
'''
Return (weight, is_italic, is_bold, is_regular, fs_type, panose, width,
is_oblique, is_wws). These
values are taken from the OS/2 table of the font. See
http://www.microsoft.com/typography/otspec/os2.htm for details
'''
if raw_is_table:
os2_table = raw
else:
os2_table = get_table(raw, 'os/2')[0]
if os2_table is None:
raise UnsupportedFont('Not a supported font, has no OS/2 table')
common_fields = b'>Hh3H11h'
(version, char_width, weight, width, fs_type, subscript_x_size,
subscript_y_size, subscript_x_offset, subscript_y_offset,
superscript_x_size, superscript_y_size, superscript_x_offset,
superscript_y_offset, strikeout_size, strikeout_position,
family_class) = struct.unpack_from(common_fields, os2_table)
offset = struct.calcsize(common_fields)
panose = struct.unpack_from(b'>10B', os2_table, offset)
offset += 10
(range1, range2, range3, range4) = struct.unpack_from(b'>4L', os2_table, offset)
offset += struct.calcsize(b'>4L')
vendor_id = os2_table[offset:offset+4]
vendor_id
offset += 4
selection, = struct.unpack_from(b'>H', os2_table, offset)
is_italic = (selection & (1 << 0)) != 0
is_bold = (selection & (1 << 5)) != 0
is_regular = (selection & (1 << 6)) != 0
is_wws = (selection & (1 << 8)) != 0
is_oblique = (selection & (1 << 9)) != 0
if return_all:
return (version, char_width, weight, width, fs_type, subscript_x_size,
subscript_y_size, subscript_x_offset, subscript_y_offset,
superscript_x_size, superscript_y_size, superscript_x_offset,
superscript_y_offset, strikeout_size, strikeout_position,
family_class, panose, selection, is_italic, is_bold, is_regular)
return weight, is_italic, is_bold, is_regular, fs_type, panose, width, is_oblique, is_wws, version | [
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googledatalab/pydatalab | 1c86e26a0d24e3bc8097895ddeab4d0607be4c40 | solutionbox/structured_data/mltoolbox/_structured_data/_package.py | python | local_train | (train_dataset,
eval_dataset,
analysis_dir,
output_dir,
features,
model_type,
max_steps,
num_epochs,
train_batch_size,
eval_batch_size,
min_eval_frequency,
top_n,
layer_sizes,
learning_rate,
epsilon) | [] | def local_train(train_dataset,
eval_dataset,
analysis_dir,
output_dir,
features,
model_type,
max_steps,
num_epochs,
train_batch_size,
eval_batch_size,
min_eval_frequency,
top_n,
layer_sizes,
learning_rate,
epsilon):
if len(train_dataset.input_files) != 1 or len(eval_dataset.input_files) != 1:
raise ValueError('CsvDataSets must be built with a file pattern, not list '
'of files.')
if file_io.file_exists(output_dir):
raise ValueError('output_dir already exist. Use a new output path.')
if eval_dataset.size < eval_batch_size:
raise ValueError('Eval batch size must be smaller than the eval data size.')
if isinstance(features, dict):
# Make a features file.
if not file_io.file_exists(output_dir):
file_io.recursive_create_dir(output_dir)
features_file = os.path.join(output_dir, 'features_file.json')
file_io.write_string_to_file(
features_file,
json.dumps(features))
else:
features_file = features
def _get_abs_path(input_path):
cur_path = os.getcwd()
full_path = os.path.abspath(os.path.join(cur_path, input_path))
# put path in quotes as it could contain spaces.
return "'" + full_path + "'"
args = ['cd %s &&' % os.path.abspath(os.path.dirname(__file__)),
'python -m trainer.task',
'--train-data-paths=%s' % _get_abs_path(train_dataset.input_files[0]),
'--eval-data-paths=%s' % _get_abs_path(eval_dataset.input_files[0]),
'--job-dir=%s' % _get_abs_path(output_dir),
'--preprocess-output-dir=%s' % _get_abs_path(analysis_dir),
'--transforms-file=%s' % _get_abs_path(features_file),
'--model-type=%s' % model_type,
'--max-steps=%s' % str(max_steps),
'--train-batch-size=%s' % str(train_batch_size),
'--eval-batch-size=%s' % str(eval_batch_size),
'--min-eval-frequency=%s' % str(min_eval_frequency),
'--learning-rate=%s' % str(learning_rate),
'--epsilon=%s' % str(epsilon)]
if num_epochs:
args.append('--num-epochs=%s' % str(num_epochs))
if top_n:
args.append('--top-n=%s' % str(top_n))
if layer_sizes:
for i in range(len(layer_sizes)):
args.append('--layer-size%s=%s' % (i + 1, str(layer_sizes[i])))
monitor_process = None
try:
p = subprocess.Popen(' '.join(args),
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
pids_to_kill = [p.pid]
# script -> name = datalab_structured_data._package
script = 'import %s; %s._wait_and_kill(%s, %s)' % (__name__, __name__, str(os.getpid()),
str(pids_to_kill))
monitor_process = subprocess.Popen(['python', '-c', script])
while p.poll() is None:
line = p.stdout.readline()
if not six.PY2:
line = line.decode()
if (line.startswith('INFO:tensorflow:global') or line.startswith('INFO:tensorflow:loss') or
line.startswith('INFO:tensorflow:Saving dict')):
sys.stdout.write(line)
finally:
if monitor_process:
monitor_process.kill()
monitor_process.wait() | [
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DSE-MSU/DeepRobust | 2bcde200a5969dae32cddece66206a52c87c43e8 | deeprobust/graph/defense/r_gcn.py | python | GaussianConvolution.reset_parameters | (self) | [] | def reset_parameters(self):
# TODO
torch.nn.init.xavier_uniform_(self.weight_miu)
torch.nn.init.xavier_uniform_(self.weight_sigma) | [
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hyperledger/sawtooth-core | 704cd5837c21f53642c06ffc97ba7978a77940b0 | cli/sawtooth_cli/network_command/compare.py | python | do_compare_chains | (args) | Calculates and outputs comparison between all nodes on the network. | Calculates and outputs comparison between all nodes on the network. | [
"Calculates",
"and",
"outputs",
"comparison",
"between",
"all",
"nodes",
"on",
"the",
"network",
"."
] | def do_compare_chains(args):
"""Calculates and outputs comparison between all nodes on the network."""
urls = split_comma_append_args(args.urls)
users = split_comma_append_args(args.users)
clients = make_rest_apis(urls, users)
broken = []
chains, errors = get_chain_generators(clients, args.limit)
broken.extend(errors)
for node in errors:
print("Error connecting to node %d: %s" % (node, urls[node]))
if not chains:
print("No nodes reporting")
return
tails, errors = get_tails(chains)
broken.extend(errors)
for node in errors:
del chains[node]
for node in errors:
print("Failed to reach common height with node %d: %s" % (
node, urls[node]))
if not chains:
print("Failed to get common height")
return
graph, errors = build_fork_graph(chains, tails)
broken.extend(errors)
for node in errors:
print("Failed to reach common ancestor with node %d: %s" % (
node, urls[node]))
if not graph:
print("Failed to build fork graph")
return
# Transform tails and errors into the format expected by the print
# functions. Because errors can occur while building the graph, we need to
# remove the tails for those clients.
broken.sort()
node_id_map = get_node_id_map(broken, len(clients))
tails = list(map(
lambda item: item[1],
filter(
lambda item: item[0] not in broken,
sorted(tails.items()))))
if args.table:
print_table(graph, tails, node_id_map)
elif args.tree:
print_tree(graph, tails, node_id_map)
else:
print_summary(graph, tails, node_id_map) | [
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kozec/sc-controller | ce92c773b8b26f6404882e9209aff212c4053170 | scc/device_monitor.py | python | DeviceMonitor.get_hidraw | (self, syspath) | return None | For given syspath, returns name of assotiated hidraw device.
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linuxscout/pyarabic | 010bddadb7c9b5c6bd24cc02d4aeddde0c4a10c4 | pyarabic/kalima.py | python | Kalima.__le__ | (self, other) | Compare two vocalized words,
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/pdb.py | python | Pdb.do_whatis | (self, arg) | whatis arg
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# _getval() already printed the error
return
code = None
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self.message('Function %s' % code.co_name)
return
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code = value.__func__.__code__
except Exception:
pass
if code:
self.message('Method %s' % code.co_name)
return
# Is it a class?
if value.__class__ is type:
self.message('Class %s.%s' % (value.__module__, value.__qualname__))
return
# None of the above...
self.message(type(value)) | [
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CTF-MissFeng/bayonet | 360ffeb87025a85b08b4fa56f951936d38f2c109 | web/route/user/html.py | python | html_user_add | () | return render_template('user/user-add.html', title=TITLE) | 新增用户 | 新增用户 | [
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] | def html_user_add():
'''新增用户'''
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | medusa/server/api/v2/providers.py | python | ProvidersHandler.post | (self, identifier, path_param=None) | return self._bad_request('Could not locate provider by id') | Add a new provider or run an operation on a specific provider type.
Without the identifier an arary of provider objects is expected to save the provider order list.
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"""
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"""
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data = json_decode(self.request.body)
sorted_providers = data.get('providers')
if sorted_providers is None:
return self._bad_request('You should provide an array of providers')
self._save_provider_order(sorted_providers)
return self._created(data={'providers': providers})
if identifier:
data = json_decode(self.request.body)
if identifier in ('newznab', 'torznab', 'torrentrss', 'prowlarr'):
if not path_param:
# No path_param passed. Asume we're trying to add a provider.
if identifier == 'newznab':
return self._add_newznab_provider(data)
if identifier == 'torrentrss':
return self._add_torrentrss_provider(data)
if identifier == 'torznab':
return self._add_torznab_provider(data)
if identifier == 'prowlarr':
return self._add_prowlarr_provider(data)
if path_param == 'operation':
if identifier == 'prowlarr':
if data.get('type') == 'TEST':
# Test prowlarr connectivity
prowlarr = ProwlarrManager(data.get('url'), data.get('apikey'))
if prowlarr.test_connectivity():
return self._ok('Connection successfull')
else:
return self._not_found('Çould not connect to prowlarr')
if data.get('type') == 'GETINDEXERS':
prowlarr = ProwlarrManager(data.get('url'), data.get('apikey'))
indexers = prowlarr.get_indexers()
if indexers:
return self._ok(indexers)
return self._internal_server_error()
if identifier in ('newznab', 'torznab'):
if data.get('type') == 'GETCATEGORIES':
return self._get_categories(identifier, data)
if identifier == 'internal':
if path_param == 'operation':
if data.get('type') == 'TESTPROVIDER':
return self._test_provider(data)
return self._bad_request('Could not locate provider by id') | [
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CvvT/dumpDex | 92ab3b7e996194a06bf1dd5538a4954e8a5ee9c1 | python/idaapi.py | python | debug_event_t.bpt_ea | (self, *args) | return _idaapi.debug_event_t_bpt_ea(self, *args) | bpt_ea(self) -> ea_t | bpt_ea(self) -> ea_t | [
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facebookresearch/votenet | 2f6d6d36ff98d96901182e935afe48ccee82d566 | models/loss_helper.py | python | compute_vote_loss | (end_points) | return vote_loss | Compute vote loss: Match predicted votes to GT votes.
Args:
end_points: dict (read-only)
Returns:
vote_loss: scalar Tensor
Overall idea:
If the seed point belongs to an object (votes_label_mask == 1),
then we require it to vote for the object center.
Each seed point may vote for multiple translations v1,v2,v3
A seed point may also be in the boxes of multiple objects:
o1,o2,o3 with corresponding GT votes c1,c2,c3
Then the loss for this seed point is:
min(d(v_i,c_j)) for i=1,2,3 and j=1,2,3 | Compute vote loss: Match predicted votes to GT votes. | [
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] | def compute_vote_loss(end_points):
""" Compute vote loss: Match predicted votes to GT votes.
Args:
end_points: dict (read-only)
Returns:
vote_loss: scalar Tensor
Overall idea:
If the seed point belongs to an object (votes_label_mask == 1),
then we require it to vote for the object center.
Each seed point may vote for multiple translations v1,v2,v3
A seed point may also be in the boxes of multiple objects:
o1,o2,o3 with corresponding GT votes c1,c2,c3
Then the loss for this seed point is:
min(d(v_i,c_j)) for i=1,2,3 and j=1,2,3
"""
# Load ground truth votes and assign them to seed points
batch_size = end_points['seed_xyz'].shape[0]
num_seed = end_points['seed_xyz'].shape[1] # B,num_seed,3
vote_xyz = end_points['vote_xyz'] # B,num_seed*vote_factor,3
seed_inds = end_points['seed_inds'].long() # B,num_seed in [0,num_points-1]
# Get groundtruth votes for the seed points
# vote_label_mask: Use gather to select B,num_seed from B,num_point
# non-object point has no GT vote mask = 0, object point has mask = 1
# vote_label: Use gather to select B,num_seed,9 from B,num_point,9
# with inds in shape B,num_seed,9 and 9 = GT_VOTE_FACTOR * 3
seed_gt_votes_mask = torch.gather(end_points['vote_label_mask'], 1, seed_inds)
seed_inds_expand = seed_inds.view(batch_size,num_seed,1).repeat(1,1,3*GT_VOTE_FACTOR)
seed_gt_votes = torch.gather(end_points['vote_label'], 1, seed_inds_expand)
seed_gt_votes += end_points['seed_xyz'].repeat(1,1,3)
# Compute the min of min of distance
vote_xyz_reshape = vote_xyz.view(batch_size*num_seed, -1, 3) # from B,num_seed*vote_factor,3 to B*num_seed,vote_factor,3
seed_gt_votes_reshape = seed_gt_votes.view(batch_size*num_seed, GT_VOTE_FACTOR, 3) # from B,num_seed,3*GT_VOTE_FACTOR to B*num_seed,GT_VOTE_FACTOR,3
# A predicted vote to no where is not penalized as long as there is a good vote near the GT vote.
dist1, _, dist2, _ = nn_distance(vote_xyz_reshape, seed_gt_votes_reshape, l1=True)
votes_dist, _ = torch.min(dist2, dim=1) # (B*num_seed,vote_factor) to (B*num_seed,)
votes_dist = votes_dist.view(batch_size, num_seed)
vote_loss = torch.sum(votes_dist*seed_gt_votes_mask.float())/(torch.sum(seed_gt_votes_mask.float())+1e-6)
return vote_loss | [
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apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | txweb2/dav/resource.py | python | DAVPrincipalResource.expandedGroupMembers | (self) | return succeed(()) | This implementation returns a Deferred which fires with C{()},
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@see: L{IDAVPrincipalResource.expandedGroupMembers} | This implementation returns a Deferred which fires with C{()},
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/ex-submodules/couchexport/export.py | python | FormattedRow.formatted_id | (self) | return self.separator.join(map(str, self.id)) | [] | def formatted_id(self):
if isinstance(self.id, str):
return self.id
return self.separator.join(map(str, self.id)) | [
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IBM/EvolveGCN | 90869062bbc98d56935e3d92e1d9b1b4c25be593 | logger.py | python | Logger.eval_predicitions | (self, predictions, true_classes, num_classes) | return error, conf_mat_per_class | [] | def eval_predicitions(self, predictions, true_classes, num_classes):
predicted_classes = predictions.argmax(dim=1)
failures = (predicted_classes!=true_classes).sum(dtype=torch.float)
error = failures/predictions.size(0)
conf_mat_per_class = utils.Namespace({})
conf_mat_per_class.true_positives = {}
conf_mat_per_class.false_negatives = {}
conf_mat_per_class.false_positives = {}
for cl in range(num_classes):
cl_indices = true_classes == cl
pos = predicted_classes == cl
hits = (predicted_classes[cl_indices] == true_classes[cl_indices])
tp = hits.sum()
fn = hits.size(0) - tp
fp = pos.sum() - tp
conf_mat_per_class.true_positives[cl] = tp
conf_mat_per_class.false_negatives[cl] = fn
conf_mat_per_class.false_positives[cl] = fp
return error, conf_mat_per_class | [
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IntelPython/sdc | 1ebf55c00ef38dfbd401a70b3945e352a5a38b87 | sdc/hiframes/pd_series_type.py | python | SeriesType.ndim | (self) | return self.data.ndim | [] | def ndim(self):
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lazylibrarian/LazyLibrarian | ae3c14e9db9328ce81765e094ab2a14ed7155624 | cherrypy/wsgiserver/wsgiserver2.py | python | HTTPConnection.communicate | (self) | Read each request and respond appropriately. | Read each request and respond appropriately. | [
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"""Read each request and respond appropriately."""
request_seen = False
try:
while True:
# (re)set req to None so that if something goes wrong in
# the RequestHandlerClass constructor, the error doesn't
# get written to the previous request.
req = None
req = self.RequestHandlerClass(self.server, self)
# This order of operations should guarantee correct pipelining.
req.parse_request()
if self.server.stats['Enabled']:
self.requests_seen += 1
if not req.ready:
# Something went wrong in the parsing (and the server has
# probably already made a simple_response). Return and
# let the conn close.
return
request_seen = True
req.respond()
if req.close_connection:
return
except socket.error:
e = sys.exc_info()[1]
errnum = e.args[0]
# sadly SSL sockets return a different (longer) time out string
if (
errnum == 'timed out' or
errnum == 'The read operation timed out'
):
# Don't error if we're between requests; only error
# if 1) no request has been started at all, or 2) we're
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# See https://bitbucket.org/cherrypy/cherrypy/issue/853
if (not request_seen) or (req and req.started_request):
# Don't bother writing the 408 if the response
# has already started being written.
if req and not req.sent_headers:
try:
req.simple_response("408 Request Timeout")
except FatalSSLAlert:
# Close the connection.
return
elif errnum not in socket_errors_to_ignore:
self.server.error_log("socket.error %s" % repr(errnum),
level=logging.WARNING, traceback=True)
if req and not req.sent_headers:
try:
req.simple_response("500 Internal Server Error")
except FatalSSLAlert:
# Close the connection.
return
return
except (KeyboardInterrupt, SystemExit):
raise
except FatalSSLAlert:
# Close the connection.
return
except NoSSLError:
if req and not req.sent_headers:
# Unwrap our wfile
self.wfile = CP_fileobject(
self.socket._sock, "wb", self.wbufsize)
req.simple_response(
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"The client sent a plain HTTP request, but "
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self.linger = True
except Exception:
e = sys.exc_info()[1]
self.server.error_log(repr(e), level=logging.ERROR, traceback=True)
if req and not req.sent_headers:
try:
req.simple_response("500 Internal Server Error")
except FatalSSLAlert:
# Close the connection.
return | [
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perfectblue/ctf-writeups | 38c81bbce254885da6b485dd1dd76798120bc98c | 2019/ctfzone-quals-2019/ocb2/ocb/aes.py | python | AES._aes_invRound | (self, state, roundKey) | return state | Applies the 4 operations of the inverse round in sequence | Applies the 4 operations of the inverse round in sequence | [
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] | def _aes_invRound(self, state, roundKey):
""" Applies the 4 operations of the inverse round in sequence """
state = self._shiftRows(state, True)
state = self._subBytes(state, True)
state = self._addRoundKey(state, roundKey)
state = self._mixColumns(state, True)
return state | [
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trailofbits/manticore | b050fdf0939f6c63f503cdf87ec0ab159dd41159 | manticore/platforms/evm.py | python | EVMWorld.transaction | (self, address, price=0, data="", caller=None, value=0, gas=2300) | Initiates a CALL transaction on current state.
Do a world.run() after this to explore all _possible_ outputs | Initiates a CALL transaction on current state.
Do a world.run() after this to explore all _possible_ outputs | [
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"""Initiates a CALL transaction on current state.
Do a world.run() after this to explore all _possible_ outputs
"""
self.start_transaction(
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IntelLabs/coach | dea46ae0d22b0a0cd30b9fc138a4a2642e1b9d9d | rl_coach/architectures/mxnet_components/utils.py | python | get_mxnet_activation_name | (activation_name: str) | return activation_functions[activation_name] | Convert coach activation name to mxnet specific activation name
:param activation_name: name of the activation inc coach
:return: name of the activation in mxnet | Convert coach activation name to mxnet specific activation name
:param activation_name: name of the activation inc coach
:return: name of the activation in mxnet | [
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] | def get_mxnet_activation_name(activation_name: str):
"""
Convert coach activation name to mxnet specific activation name
:param activation_name: name of the activation inc coach
:return: name of the activation in mxnet
"""
activation_functions = {
'relu': 'relu',
'tanh': 'tanh',
'sigmoid': 'sigmoid',
# FIXME Add other activations
# 'elu': tf.nn.elu,
'selu': 'softrelu',
# 'leaky_relu': tf.nn.leaky_relu,
'none': None
}
assert activation_name in activation_functions, \
"Activation function must be one of the following {}. instead it was: {}".format(
activation_functions.keys(), activation_name)
return activation_functions[activation_name] | [
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colour-science/colour | 38782ac059e8ddd91939f3432bf06811c16667f0 | colour/plotting/notation.py | python | plot_multi_munsell_value_functions | (functions, **kwargs) | return plot_multi_functions(
functions, samples=np.linspace(0, 100, 1000), **settings) | Plots given *Munsell* value functions.
Parameters
----------
functions : str or object or array_like
*Munsell* value functions to plot. ``functions`` elements can be of any
type or form supported by the
:func:`colour.plotting.filter_passthrough` definition.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`,
:func:`colour.plotting.plot_multi_functions`,
:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_multi_munsell_value_functions(['ASTM D1535', 'McCamy 1987'])
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_Multi_Munsell_Value_Functions.png
:align: center
:alt: plot_multi_munsell_value_functions | Plots given *Munsell* value functions. | [
"Plots",
"given",
"*",
"Munsell",
"*",
"value",
"functions",
"."
] | def plot_multi_munsell_value_functions(functions, **kwargs):
"""
Plots given *Munsell* value functions.
Parameters
----------
functions : str or object or array_like
*Munsell* value functions to plot. ``functions`` elements can be of any
type or form supported by the
:func:`colour.plotting.filter_passthrough` definition.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`,
:func:`colour.plotting.plot_multi_functions`,
:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_multi_munsell_value_functions(['ASTM D1535', 'McCamy 1987'])
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_Multi_Munsell_Value_Functions.png
:align: center
:alt: plot_multi_munsell_value_functions
"""
functions = filter_passthrough(MUNSELL_VALUE_METHODS, functions)
settings = {
'bounding_box': (0, 100, 0, 10),
'legend': True,
'title': '{0} - Munsell Functions'.format(', '.join(functions)),
'x_label': 'Luminance Y',
'y_label': 'Munsell Value V',
}
settings.update(kwargs)
return plot_multi_functions(
functions, samples=np.linspace(0, 100, 1000), **settings) | [
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ghoseb/planet.clojure | a2e10e9e6bbf6bc544fad40beed8d0da7ab9518d | planet/vendor/compat_logging/handlers.py | python | SMTPHandler.getSubject | (self, record) | return self.subject | Determine the subject for the email.
If you want to specify a subject line which is record-dependent,
override this method. | Determine the subject for the email. | [
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] | def getSubject(self, record):
"""
Determine the subject for the email.
If you want to specify a subject line which is record-dependent,
override this method.
"""
return self.subject | [
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openstack/barbican | a9d2b133c8dc3307974f119f9a2b23a4ba82e8ce | barbican/api/controllers/transportkeys.py | python | TransportKeyController.on_get | (self, external_project_id) | return transport_key | [] | def on_get(self, external_project_id):
LOG.debug("== Getting transport key for %s", external_project_id)
transport_key = self.repo.get(entity_id=self.transport_key_id)
if not transport_key:
_transport_key_not_found()
pecan.override_template('json', 'application/json')
return transport_key | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/notify/v1/service/binding.py | python | BindingContext.fetch | (self) | return BindingInstance(
self._version,
payload,
service_sid=self._solution['service_sid'],
sid=self._solution['sid'],
) | Fetch the BindingInstance
:returns: The fetched BindingInstance
:rtype: twilio.rest.notify.v1.service.binding.BindingInstance | Fetch the BindingInstance | [
"Fetch",
"the",
"BindingInstance"
] | def fetch(self):
"""
Fetch the BindingInstance
:returns: The fetched BindingInstance
:rtype: twilio.rest.notify.v1.service.binding.BindingInstance
"""
payload = self._version.fetch(method='GET', uri=self._uri, )
return BindingInstance(
self._version,
payload,
service_sid=self._solution['service_sid'],
sid=self._solution['sid'],
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larryhastings/gilectomy | 4315ec3f1d6d4f813cc82ce27a24e7f784dbfc1a | Lib/_pydecimal.py | python | Context.logical_or | (self, a, b) | return a.logical_or(b, context=self) | Applies the logical operation 'or' between each operand's digits.
The operands must be both logical numbers.
>>> ExtendedContext.logical_or(Decimal('0'), Decimal('0'))
Decimal('0')
>>> ExtendedContext.logical_or(Decimal('0'), Decimal('1'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1'), Decimal('0'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1'), Decimal('1'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1100'), Decimal('1010'))
Decimal('1110')
>>> ExtendedContext.logical_or(Decimal('1110'), Decimal('10'))
Decimal('1110')
>>> ExtendedContext.logical_or(110, 1101)
Decimal('1111')
>>> ExtendedContext.logical_or(Decimal(110), 1101)
Decimal('1111')
>>> ExtendedContext.logical_or(110, Decimal(1101))
Decimal('1111') | Applies the logical operation 'or' between each operand's digits. | [
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"each",
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"s",
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"."
] | def logical_or(self, a, b):
"""Applies the logical operation 'or' between each operand's digits.
The operands must be both logical numbers.
>>> ExtendedContext.logical_or(Decimal('0'), Decimal('0'))
Decimal('0')
>>> ExtendedContext.logical_or(Decimal('0'), Decimal('1'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1'), Decimal('0'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1'), Decimal('1'))
Decimal('1')
>>> ExtendedContext.logical_or(Decimal('1100'), Decimal('1010'))
Decimal('1110')
>>> ExtendedContext.logical_or(Decimal('1110'), Decimal('10'))
Decimal('1110')
>>> ExtendedContext.logical_or(110, 1101)
Decimal('1111')
>>> ExtendedContext.logical_or(Decimal(110), 1101)
Decimal('1111')
>>> ExtendedContext.logical_or(110, Decimal(1101))
Decimal('1111')
"""
a = _convert_other(a, raiseit=True)
return a.logical_or(b, context=self) | [
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yt-project/yt | dc7b24f9b266703db4c843e329c6c8644d47b824 | yt/frontends/enzo/io.py | python | IOHandlerPacked2D._read_fluid_selection | (self, chunks, selector, fields, size) | return rv | [] | def _read_fluid_selection(self, chunks, selector, fields, size):
rv = {}
# Now we have to do something unpleasant
chunks = list(chunks)
if isinstance(selector, GridSelector):
if not (len(chunks) == len(chunks[0].objs) == 1):
raise RuntimeError
g = chunks[0].objs[0]
f = h5py.File(g.filename, mode="r")
gds = f.get("/Grid%08i" % g.id)
for ftype, fname in fields:
rv[(ftype, fname)] = np.atleast_3d(gds.get(fname)[()].transpose())
f.close()
return rv
if size is None:
size = sum(g.count(selector) for chunk in chunks for g in chunk.objs)
for field in fields:
ftype, fname = field
fsize = size
rv[field] = np.empty(fsize, dtype="float64")
ng = sum(len(c.objs) for c in chunks)
mylog.debug(
"Reading %s cells of %s fields in %s grids",
size,
[f2 for f1, f2 in fields],
ng,
)
ind = 0
for chunk in chunks:
f = None
for g in chunk.objs:
if f is None:
# print("Opening (count) %s" % g.filename)
f = h5py.File(g.filename, mode="r")
gds = f.get("/Grid%08i" % g.id)
if gds is None:
gds = f
for field in fields:
ftype, fname = field
ds = np.atleast_3d(gds.get(fname)[()].transpose())
nd = g.select(selector, ds, rv[field], ind) # caches
ind += nd
f.close()
return rv | [
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petercorke/robotics-toolbox-python | 51aa8bbb3663a7c815f9880d538d61e7c85bc470 | roboticstoolbox/backends/VPython/common_functions.py | python | close_localhost_session | (canvas) | Terminate the local host session through JavaScript
:param canvas: The scene to append the JS to the caption
:type canvas:
class:`roboticstoolbox.backends.VPython.graphics_canvas.GraphicsCanvas3D`,
class:`roboticstoolbox.backends.VPython.graphics_canvas.GraphicsCanvas2D` | Terminate the local host session through JavaScript | [
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] | def close_localhost_session(canvas): # pragma nocover
"""
Terminate the local host session through JavaScript
:param canvas: The scene to append the JS to the caption
:type canvas:
class:`roboticstoolbox.backends.VPython.graphics_canvas.GraphicsCanvas3D`,
class:`roboticstoolbox.backends.VPython.graphics_canvas.GraphicsCanvas2D`
"""
canvas.scene.append_to_caption('''
<script type="text/javascript">
close();
</script>
''') | [
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openstack/manila | 142990edc027e14839d5deaf4954dd6fc88de15e | manila/scheduler/filters/json.py | python | JsonFilter._equals | (self, args) | return self._op_compare(args, operator.eq) | First term is == all the other terms. | First term is == all the other terms. | [
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/cheroot/server.py | python | HTTPServer.bind_addr | (self, value) | Set the interface on which to listen for connections. | Set the interface on which to listen for connections. | [
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] | def bind_addr(self, value):
"""Set the interface on which to listen for connections."""
if isinstance(value, tuple) and value[0] in ('', None):
# Despite the socket module docs, using '' does not
# allow AI_PASSIVE to work. Passing None instead
# returns '0.0.0.0' like we want. In other words:
# host AI_PASSIVE result
# '' Y 192.168.x.y
# '' N 192.168.x.y
# None Y 0.0.0.0
# None N 127.0.0.1
# But since you can get the same effect with an explicit
# '0.0.0.0', we deny both the empty string and None as values.
raise ValueError(
"Host values of '' or None are not allowed. "
"Use '0.0.0.0' (IPv4) or '::' (IPv6) instead "
'to listen on all active interfaces.',
)
self._bind_addr = value | [
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kmpm/nodemcu-uploader | 6178f40fff2deadd56b5bc474f9b4475ef444b37 | nodemcu_uploader/uploader.py | python | Uploader.close | (self) | restores the nodemcu to default baudrate and then closes the port | restores the nodemcu to default baudrate and then closes the port | [
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"""restores the nodemcu to default baudrate and then closes the port"""
try:
if self.baud != self.start_baud:
self.__set_baudrate(self.start_baud)
self._port.flush()
self.__clear_buffers()
except serial.serialutil.SerialException:
pass
log.debug('closing port')
self._port.close() | [
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KalleHallden/AutoTimer | 2d954216700c4930baa154e28dbddc34609af7ce | env/lib/python2.7/site-packages/pip/_internal/req/constructors.py | python | install_req_from_req_string | (
req_string, # type: str
comes_from=None, # type: Optional[InstallRequirement]
isolated=False, # type: bool
wheel_cache=None, # type: Optional[WheelCache]
use_pep517=None # type: Optional[bool]
) | return InstallRequirement(
req, comes_from, isolated=isolated, wheel_cache=wheel_cache,
use_pep517=use_pep517
) | [] | def install_req_from_req_string(
req_string, # type: str
comes_from=None, # type: Optional[InstallRequirement]
isolated=False, # type: bool
wheel_cache=None, # type: Optional[WheelCache]
use_pep517=None # type: Optional[bool]
):
# type: (...) -> InstallRequirement
try:
req = Requirement(req_string)
except InvalidRequirement:
raise InstallationError("Invalid requirement: '%s'" % req_string)
domains_not_allowed = [
PyPI.file_storage_domain,
TestPyPI.file_storage_domain,
]
if (req.url and comes_from and comes_from.link and
comes_from.link.netloc in domains_not_allowed):
# Explicitly disallow pypi packages that depend on external urls
raise InstallationError(
"Packages installed from PyPI cannot depend on packages "
"which are not also hosted on PyPI.\n"
"%s depends on %s " % (comes_from.name, req)
)
return InstallRequirement(
req, comes_from, isolated=isolated, wheel_cache=wheel_cache,
use_pep517=use_pep517
) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/sqlalchemy/ext/associationproxy.py | python | AssociationProxy._inflate | (self, proxy) | [] | def _inflate(self, proxy):
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jina-ai/jina | c77a492fcd5adba0fc3de5347bea83dd4e7d8087 | docarray/memmap/__init__.py | python | DocumentArrayMemmap._load_header_body | (self, mode: str = 'a') | [] | def _load_header_body(self, mode: str = 'a'):
if hasattr(self, '_header'):
self._header.close()
if hasattr(self, '_body'):
self._body.close()
open(self._header_path, mode).close()
open(self._body_path, mode).close()
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self._body = open(self._body_path, 'r+b')
tmp = np.frombuffer(
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('', np.int64), # 8 bytes
],
)
self._header_entry_size = 24 + 4 * self._key_length
self._last_header_entry = len(tmp)
self._header_map = OrderedDict()
for idx, r in enumerate(tmp):
if not np.array_equal((r[1], r[2], r[3]), _HEADER_NONE_ENTRY):
self._header_map[r[0]] = (idx, r[1], r[2], r[3])
self._header_keys = list(self._header_map.keys())
self._body_fileno = self._body.fileno()
self._start = 0
if self._header_map:
self._start = tmp[-1][1] + tmp[-1][3]
self._body.seek(self._start)
self._last_mmap = None | [
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cronyo/cronyo | cd5abab0871b68bf31b18aac934303928130a441 | cronyo/vendor/requests/cookies.py | python | cookiejar_from_dict | (cookie_dict, cookiejar=None, overwrite=True) | return cookiejar | Returns a CookieJar from a key/value dictionary.
:param cookie_dict: Dict of key/values to insert into CookieJar.
:param cookiejar: (optional) A cookiejar to add the cookies to.
:param overwrite: (optional) If False, will not replace cookies
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:rtype: CookieJar | Returns a CookieJar from a key/value dictionary. | [
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:param cookie_dict: Dict of key/values to insert into CookieJar.
:param cookiejar: (optional) A cookiejar to add the cookies to.
:param overwrite: (optional) If False, will not replace cookies
already in the jar with new ones.
:rtype: CookieJar
"""
if cookiejar is None:
cookiejar = RequestsCookieJar()
if cookie_dict is not None:
names_from_jar = [cookie.name for cookie in cookiejar]
for name in cookie_dict:
if overwrite or (name not in names_from_jar):
cookiejar.set_cookie(create_cookie(name, cookie_dict[name]))
return cookiejar | [
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ehmatthes/pcc | f555082df0f8268b8f269e59a99da8ed5013f749 | chapter_12/game_functions.py | python | update_bullets | (bullets) | Update position of bullets, and get rid of old bullets. | Update position of bullets, and get rid of old bullets. | [
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] | def update_bullets(bullets):
"""Update position of bullets, and get rid of old bullets."""
# Update bullet positions.
bullets.update()
# Get rid of bullets that have disappeared.
for bullet in bullets.copy():
if bullet.rect.bottom <= 0:
bullets.remove(bullet) | [
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phonopy/phonopy | 816586d0ba8177482ecf40e52f20cbdee2260d51 | phonopy/structure/tetrahedron_method.py | python | get_all_tetrahedra_relative_grid_address | () | return relative_grid_address | Return relative grid addresses dataset.
This exists only for the test. | Return relative grid addresses dataset. | [
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] | def get_all_tetrahedra_relative_grid_address():
"""Return relative grid addresses dataset.
This exists only for the test.
"""
relative_grid_address = np.zeros((4, 24, 4, 3), dtype="int_")
phonoc.all_tetrahedra_relative_grid_address(relative_grid_address)
return relative_grid_address | [
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pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/numpy-1.10.0.dev0_046311a-py3.3-win-amd64.egg/numpy/polynomial/_polybase.py | python | ABCPolyBase.integ | (self, m=1, k=[], lbnd=None) | return self.__class__(coef, self.domain, self.window) | Integrate.
Return a series instance that is the definite integral of the
current series.
Parameters
----------
m : non-negative int
The number of integrations to perform.
k : array_like
Integration constants. The first constant is applied to the
first integration, the second to the second, and so on. The
list of values must less than or equal to `m` in length and any
missing values are set to zero.
lbnd : Scalar
The lower bound of the definite integral.
Returns
-------
new_series : series
A new series representing the integral. The domain is the same
as the domain of the integrated series. | Integrate. | [
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"."
] | def integ(self, m=1, k=[], lbnd=None):
"""Integrate.
Return a series instance that is the definite integral of the
current series.
Parameters
----------
m : non-negative int
The number of integrations to perform.
k : array_like
Integration constants. The first constant is applied to the
first integration, the second to the second, and so on. The
list of values must less than or equal to `m` in length and any
missing values are set to zero.
lbnd : Scalar
The lower bound of the definite integral.
Returns
-------
new_series : series
A new series representing the integral. The domain is the same
as the domain of the integrated series.
"""
off, scl = self.mapparms()
if lbnd is None:
lbnd = 0
else:
lbnd = off + scl*lbnd
coef = self._int(self.coef, m, k, lbnd, 1./scl)
return self.__class__(coef, self.domain, self.window) | [
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v8/services/services/change_status_service/transports/grpc.py | python | ChangeStatusServiceGrpcTransport.get_change_status | (
self,
) | return self._stubs["get_change_status"] | r"""Return a callable for the get change status method over gRPC.
Returns the requested change status in full detail.
List of thrown errors: `AuthenticationError <>`__
`AuthorizationError <>`__ `HeaderError <>`__
`InternalError <>`__ `QuotaError <>`__ `RequestError <>`__
Returns:
Callable[[~.GetChangeStatusRequest],
~.ChangeStatus]:
A function that, when called, will call the underlying RPC
on the server. | r"""Return a callable for the get change status method over gRPC. | [
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] | def get_change_status(
self,
) -> Callable[
[change_status_service.GetChangeStatusRequest],
change_status.ChangeStatus,
]:
r"""Return a callable for the get change status method over gRPC.
Returns the requested change status in full detail.
List of thrown errors: `AuthenticationError <>`__
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`InternalError <>`__ `QuotaError <>`__ `RequestError <>`__
Returns:
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~.ChangeStatus]:
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on the server.
"""
# Generate a "stub function" on-the-fly which will actually make
# the request.
# gRPC handles serialization and deserialization, so we just need
# to pass in the functions for each.
if "get_change_status" not in self._stubs:
self._stubs["get_change_status"] = self.grpc_channel.unary_unary(
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/PIL/FliImagePlugin.py | python | FliImageFile.n_frames | (self) | return self.__framecount | [] | def n_frames(self):
return self.__framecount | [
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caktux/pytrader | b45b216dab3db78d6028d85e9a6f80419c22cea0 | exchanges/kraken.py | python | PollClient.request_lag | (self) | Request server time to calculate lag | Request server time to calculate lag | [
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"lag"
] | def request_lag(self):
"""Request server time to calculate lag"""
def lag_thread():
json_time = http_request("%s://%s/0/public/Time" % (
self.proto,
HTTP_HOST
))
if not self._terminating:
try:
answer = json.loads(json_time)
if not answer["error"]:
lag = time.time() - answer['result']['unixtime']
result = {
'lag': lag * 1000,
'lag_text': "%0.3f s" % lag
}
translated = {
"op": "result",
"result": result,
"id": "order_lag"
}
self.signal_recv(self, (json.dumps(translated)))
except Exception as exc:
self.debug("### exception in lag_thread:", exc)
start_thread(lag_thread, "http request lag") | [
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zedshaw/lamson | 8a8ad546ea746b129fa5f069bf9278f87d01473a | lamson/mail.py | python | MailRequest.all_parts | (self) | return self.base.parts | Returns all multipart mime parts. This could be an empty list. | Returns all multipart mime parts. This could be an empty list. | [
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"""Returns all multipart mime parts. This could be an empty list."""
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CastagnaIT/plugin.video.netflix | 5cf5fa436eb9956576c0f62aa31a4c7d6c5b8a4a | packages/h2/utilities.py | python | _secure_headers | (headers, hdr_validation_flags) | Certain headers are at risk of being attacked during the header compression
phase, and so need to be kept out of header compression contexts. This
function automatically transforms certain specific headers into HPACK
never-indexed fields to ensure they don't get added to header compression
contexts.
This function currently implements two rules:
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never-indexed.
- Any 'cookie' header field shorter than 20 bytes long is made
never-indexed.
These fields are the most at-risk. These rules are inspired by Firefox
and nghttp2. | Certain headers are at risk of being attacked during the header compression
phase, and so need to be kept out of header compression contexts. This
function automatically transforms certain specific headers into HPACK
never-indexed fields to ensure they don't get added to header compression
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Certain headers are at risk of being attacked during the header compression
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function automatically transforms certain specific headers into HPACK
never-indexed fields to ensure they don't get added to header compression
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- Any 'cookie' header field shorter than 20 bytes long is made
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These fields are the most at-risk. These rules are inspired by Firefox
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"""
for header in headers:
if header[0] in _SECURE_HEADERS:
yield NeverIndexedHeaderTuple(*header)
elif header[0] in (b'cookie', u'cookie') and len(header[1]) < 20:
yield NeverIndexedHeaderTuple(*header)
else:
yield header | [
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Ultimaker/Cura | a1622c77ea7259ecb956acd6de07b7d34b7ac52b | plugins/CuraEngineBackend/CuraEngineBackend.py | python | CuraEngineBackend._onBackendConnected | (self) | Called when the back-end connects to the front-end. | Called when the back-end connects to the front-end. | [
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"""Called when the back-end connects to the front-end."""
if self._restart:
self._restart = False
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khanhnamle1994/natural-language-processing | 01d450d5ac002b0156ef4cf93a07cb508c1bcdc5 | assignment1/.env/lib/python2.7/site-packages/pip/_vendor/lockfile/__init__.py | python | MkdirFileLock | (*args, **kwds) | return _fl_helper(mkdirlockfile.MkdirLockFile, "lockfile.mkdirlockfile",
*args, **kwds) | Factory function provided for backwards compatibility.
Do not use in new code. Instead, import MkdirLockFile from the
lockfile.mkdirlockfile module. | Factory function provided for backwards compatibility. | [
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"."
] | def MkdirFileLock(*args, **kwds):
"""Factory function provided for backwards compatibility.
Do not use in new code. Instead, import MkdirLockFile from the
lockfile.mkdirlockfile module.
"""
from . import mkdirlockfile
return _fl_helper(mkdirlockfile.MkdirLockFile, "lockfile.mkdirlockfile",
*args, **kwds) | [
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google/capirca | 679e3885e3a5e5e129dc2dfab204ec44d63b26a4 | capirca/lib/policy.py | python | ParsePolicy | (data, definitions=None, optimize=True, base_dir='',
shade_check=False, filename='') | Parse the policy in 'data', optionally provide a naming object.
Parse a blob of policy text into a policy object.
Args:
data: a string blob of policy data to parse.
definitions: optional naming library definitions object.
optimize: bool - whether to summarize networks and services.
base_dir: base path string to look for acls or include files.
shade_check: bool - whether to raise an exception when a term is shaded.
filename: string - filename used by the policy.
Returns:
policy object or False (if parse error). | Parse the policy in 'data', optionally provide a naming object. | [
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] | def ParsePolicy(data, definitions=None, optimize=True, base_dir='',
shade_check=False, filename=''):
"""Parse the policy in 'data', optionally provide a naming object.
Parse a blob of policy text into a policy object.
Args:
data: a string blob of policy data to parse.
definitions: optional naming library definitions object.
optimize: bool - whether to summarize networks and services.
base_dir: base path string to look for acls or include files.
shade_check: bool - whether to raise an exception when a term is shaded.
filename: string - filename used by the policy.
Returns:
policy object or False (if parse error).
"""
try:
if definitions:
globals()['DEFINITIONS'] = definitions
else:
globals()['DEFINITIONS'] = naming.Naming(DEFAULT_DEFINITIONS)
globals()['_OPTIMIZE'] = optimize
globals()['_SHADE_CHECK'] = shade_check
lexer = lex.lex()
preprocessed_data = '\n'.join(_Preprocess(data, base_dir=base_dir))
global parser
policy = parser.parse(preprocessed_data, lexer=lexer)
policy.filename = filename
return policy
except IndexError:
return False | [
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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/propertyedit.py | python | ColorProperty.get_value_rgba | (self) | return (float(raw_r)/255.0, float(raw_g)/255.0, float(raw_b)/255.0, 1.0) | [] | def get_value_rgba(self):
raw_r, raw_g, raw_b = utils.hex_to_rgb(self.value)
return (float(raw_r)/255.0, float(raw_g)/255.0, float(raw_b)/255.0, 1.0) | [
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microsoft/nni | 31f11f51249660930824e888af0d4e022823285c | nni/compression/pytorch/utils/shape_dependency.py | python | GroupDependency._get_parent_convs | (self, node) | return parent_layers | Find the nearest father conv layers for the target node.
Parameters
---------
node : torch._C.Node
target node.
Returns
-------
parent_layers : list
nearest father conv layers for the target node. Due to the group
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Parameters
---------
node : torch._C.Node
target node.
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parent_layers : list
nearest father conv layers for the target node. Due to the group
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Find the nearest father conv layers for the target node.
Parameters
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node : torch._C.Node
target node.
Returns
-------
parent_layers : list
nearest father conv layers for the target node. Due to the group
dependency only exists between the conv layers, so we only find
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"""
parent_layers = []
# the input node is a Conv node
predeessors = self.graph.find_predecessors(node.unique_name)
predeessors = [self.graph.name_to_node[x] for x in predeessors]
queue = predeessors
while queue:
curnode = queue.pop(0)
if curnode.op_type == 'Conv2d' or curnode.op_type == 'ConvTranspose2d':
# find the first met conv
parent_layers.append(curnode.name)
continue
parents = self.graph.find_predecessors(curnode.unique_name)
parents = [self.graph.name_to_node[name] for name in parents]
for parent in parents:
queue.append(parent)
return parent_layers | [
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timonwong/OmniMarkupPreviewer | 21921ac7a99d2b5924a2219b33679a5b53621392 | OmniMarkupLib/Renderers/libs/python3/creoleparser/core.py | python | Parser.preprocess | (self,text) | return text | This should generally be called before fragmentize().
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text = text.replace("\r\n", "\n")
text = text.replace("\r", "\n")
return text | [
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pypa/pipenv | b21baade71a86ab3ee1429f71fbc14d4f95fb75d | pipenv/patched/notpip/_vendor/pyparsing.py | python | Empty.__init__ | (self) | [] | def __init__(self):
super(Empty, self).__init__()
self.name = "Empty"
self.mayReturnEmpty = True
self.mayIndexError = False | [
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wucng/TensorExpand | 4ea58f64f5c5082b278229b799c9f679536510b7 | TensorExpand/Object detection/Data_interface/Labelme/labelme_draw_json.py | python | main | () | [] | def main():
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
args = parser.parse_args()
json_file = args.json_file
data = json.load(open(json_file)) # 加载json文件
img = utils.img_b64_to_array(data['imageData']) # 解析原图片数据
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data[
'shapes']) # 解析'shapes'中的字段信息，解析出每个对象的mask与对应的label lbl存储 mask，lbl_names 存储对应的label
# lal 像素取值 0、1、2 其中0对应背景，1对应第一个对象，2对应第二个对象
# 使用该方法取出每个对象的mask mask=[] mask.append((lbl==1).astype(np.uint8)) # 解析出像素值为1的对象，对应第一个对象 mask 为0、1组成的（0为背景，1为对象）
# lbl_names ['background','cat_1','cat_2']
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
plt.subplot(121)
plt.imshow(img)
plt.subplot(122)
plt.imshow(lbl_viz)
plt.show() | [
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cltk/cltk | 1a8c2f5ef72389e2579dfce1fa5af8e59ebc9ec1 | src/cltk/utils/file_operations.py | python | open_pickle | (path: str) | Open a pickle and return loaded pickle object.
:type path: str
:param : path: File path to pickle file to be opened.
:rtype : object | Open a pickle and return loaded pickle object.
:type path: str
:param : path: File path to pickle file to be opened.
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] | def open_pickle(path: str) -> Any:
"""Open a pickle and return loaded pickle object.
:type path: str
:param : path: File path to pickle file to be opened.
:rtype : object
"""
try:
with open(path, "rb") as opened_pickle:
try:
return pickle.load(opened_pickle)
except Exception as pickle_error:
logger.error(pickle_error)
raise
except FileNotFoundError as fnf_error:
logger.error(fnf_error)
raise
except IOError as io_err:
logger.error(io_err)
raise
except EOFError as eof_error:
logger.error(eof_error)
raise
except pickle.UnpicklingError as unp_error:
logger.error(unp_error)
raise | [
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TropComplique/FaceBoxes-tensorflow | 0dde35eda1cb3dab6586b94c583029162ec37aa5 | src/input_pipeline/pipeline.py | python | Pipeline.__init__ | (self, filenames, batch_size, image_size,
repeat=False, shuffle=False, augmentation=False) | Note: when evaluating set batch_size to 1.
Arguments:
filenames: a list of strings, paths to tfrecords files.
batch_size: an integer.
image_size: a list with two integers [width, height] or None,
images of this size will be in a batch.
If value is None then images will not be resized.
In this case batch size must be 1.
repeat: a boolean, whether repeat indefinitely.
shuffle: whether to shuffle the dataset.
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"""
Note: when evaluating set batch_size to 1.
Arguments:
filenames: a list of strings, paths to tfrecords files.
batch_size: an integer.
image_size: a list with two integers [width, height] or None,
images of this size will be in a batch.
If value is None then images will not be resized.
In this case batch size must be 1.
repeat: a boolean, whether repeat indefinitely.
shuffle: whether to shuffle the dataset.
augmentation: whether to do data augmentation.
"""
if image_size is not None:
self.image_width, self.image_height = image_size
self.resize = True
else:
assert batch_size == 1
self.image_width, self.image_height = None, None
self.resize = False
self.augmentation = augmentation
self.batch_size = batch_size
def get_num_samples(filename):
return sum(1 for _ in tf.python_io.tf_record_iterator(filename))
num_examples = 0
for filename in filenames:
num_examples_in_file = get_num_samples(filename)
assert num_examples_in_file > 0
num_examples += num_examples_in_file
self.num_examples = num_examples
assert self.num_examples > 0
dataset = tf.data.Dataset.from_tensor_slices(filenames)
num_shards = len(filenames)
if shuffle:
dataset = dataset.shuffle(buffer_size=num_shards)
dataset = dataset.flat_map(tf.data.TFRecordDataset)
dataset = dataset.prefetch(buffer_size=batch_size)
if shuffle:
dataset = dataset.shuffle(buffer_size=SHUFFLE_BUFFER_SIZE)
dataset = dataset.repeat(None if repeat else 1)
dataset = dataset.map(self._parse_and_preprocess, num_parallel_calls=NUM_THREADS)
# we need batches of fixed size
padded_shapes = ([self.image_height, self.image_width, 3], [None, 4], [], [])
dataset = dataset.apply(
tf.contrib.data.padded_batch_and_drop_remainder(batch_size, padded_shapes)
)
dataset = dataset.prefetch(buffer_size=1)
self.iterator = dataset.make_one_shot_iterator() | [
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MillionIntegrals/vel | f3ce7da64362ad207f40f2c0d58d9300a25df3e8 | vel/rl/vecenv/shared_mem.py | python | SharedMemVecEnvWrapper.instantiate_single | (self, seed=0, preset='default') | return env | Create a new Env instance - single | Create a new Env instance - single | [
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env = self.env.instantiate(seed=seed, serial_id=0, preset=preset)
if self.frame_history is not None:
env = FrameStack(env, self.frame_history)
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.4/django/contrib/gis/admin/options.py | python | GeoModelAdmin.media | (self) | return media | Injects OpenLayers JavaScript into the admin. | Injects OpenLayers JavaScript into the admin. | [
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"Injects OpenLayers JavaScript into the admin."
media = super(GeoModelAdmin, self).media
media.add_js([self.openlayers_url])
media.add_js(self.extra_js)
return media | [
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devitocodes/devito | 6abd441e3f5f091775ad332be6b95e017b8cbd16 | devito/types/grid.py | python | AbstractSubDomain.intersection | (self, other) | Return the intersection of two subdomains as a new subdomain. | Return the intersection of two subdomains as a new subdomain. | [
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Return the intersection of two subdomains as a new subdomain.
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raise NotImplementedError | [
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pyload/pyload | 4410827ca7711f1a3cf91a0b11e967b81bbbcaa2 | src/pyload/core/managers/file_manager.py | python | FileManager.update_file_info | (self, data, pid) | updates file info (name, size, status, url) | updates file info (name, size, status, url) | [
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"""
updates file info (name, size, status, url)
"""
self.pyload.db.update_link_info(data)
e = UpdateEvent(
"pack", pid, "collector" if not self.get_package(pid).queue else "queue"
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self.pyload.event_manager.add_event(e) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | kubelet/datadog_checks/kubelet/prometheus.py | python | CadvisorPrometheusScraperMixin._get_container_label | (labels, l_name) | Iter on all labels to find the label.name equal to the l_name
:param labels: list of labels
:param l_name: str
:return: str or None | Iter on all labels to find the label.name equal to the l_name
:param labels: list of labels
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:return: str or None | [
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"""
Iter on all labels to find the label.name equal to the l_name
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"""
if l_name in labels:
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pytorch/translate | 564d011b10b4cef4e110c092c2912277ed64c713 | pytorch_translate/research/deliberation_networks/deliberation_networks.py | python | TransformerDecoderPhase2.upgrade_state_dict_named | (self, state_dict, name) | return state_dict | Upgrade a (possibly old) state dict for new versions of fairseq. | Upgrade a (possibly old) state dict for new versions of fairseq. | [
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"""Upgrade a (possibly old) state dict for new versions of fairseq."""
if isinstance(self.embed_positions, SinusoidalPositionalEmbedding):
weights_key = "{}.embed_positions.weights".format(name)
if weights_key in state_dict:
del state_dict[weights_key]
state_dict[
"{}.embed_positions._float_tensor".format(name)
] = torch.FloatTensor(1)
for i in range(len(self.layers)):
# update layer norms
layer_norm_map = {
"0": "self_attn_layer_norm",
"1": "encoder_attn_layer_norm",
"2": "final_layer_norm",
}
for old, new in layer_norm_map.items():
for m in ("weight", "bias"):
k = "{}.layers.{}.layer_norms.{}.{}".format(name, i, old, m)
if k in state_dict:
state_dict[
"{}.layers.{}.{}.{}".format(name, i, new, m)
] = state_dict[k]
del state_dict[k]
version_key = "{}.version".format(name)
if utils.item(state_dict.get(version_key, torch.Tensor([1]))[0]) < 2:
# earlier checkpoints did not normalize after the stack of layers
self.layer_norm = None
self.normalize = False
state_dict[version_key] = torch.Tensor([1])
return state_dict | [
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sfzhang15/ATSS | 79dfb28bd18c931dd75a3ca2c63d32f5e4b1626a | atss_core/structures/bounding_box.py | python | BoxList.resize | (self, size, *args, **kwargs) | return bbox.convert(self.mode) | Returns a resized copy of this bounding box
:param size: The requested size in pixels, as a 2-tuple:
(width, height). | Returns a resized copy of this bounding box | [
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] | def resize(self, size, *args, **kwargs):
"""
Returns a resized copy of this bounding box
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
"""
ratios = tuple(float(s) / float(s_orig) for s, s_orig in zip(size, self.size))
if ratios[0] == ratios[1]:
ratio = ratios[0]
scaled_box = self.bbox * ratio
bbox = BoxList(scaled_box, size, mode=self.mode)
# bbox._copy_extra_fields(self)
for k, v in self.extra_fields.items():
if not isinstance(v, torch.Tensor):
v = v.resize(size, *args, **kwargs)
bbox.add_field(k, v)
return bbox
ratio_width, ratio_height = ratios
xmin, ymin, xmax, ymax = self._split_into_xyxy()
scaled_xmin = xmin * ratio_width
scaled_xmax = xmax * ratio_width
scaled_ymin = ymin * ratio_height
scaled_ymax = ymax * ratio_height
scaled_box = torch.cat(
(scaled_xmin, scaled_ymin, scaled_xmax, scaled_ymax), dim=-1
)
bbox = BoxList(scaled_box, size, mode="xyxy")
# bbox._copy_extra_fields(self)
for k, v in self.extra_fields.items():
if not isinstance(v, torch.Tensor):
v = v.resize(size, *args, **kwargs)
bbox.add_field(k, v)
return bbox.convert(self.mode) | [
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ecstatic-nobel/Analyst-Arsenal | 7f38854e2383e1b564f67fb9a197a045cb167230 | commons.py | python | download_site | (args, day, protocol, domain, ext_csv, url, resp) | [] | def download_site(args, day, protocol, domain, ext_csv, url, resp):
""" """
directory = "{}{}".format(args.cap_dir, day)
domain_dir = "{}/{}".format(directory, domain)
root_url = "{}//{}/".format(protocol, domain)
try:
if not os.path.exists(domain_dir):
os.makedirs(domain_dir)
if not os.path.exists(domain_dir):
tqdm.tqdm.write(colored("{}: {} is temporarily unavailable.".format(
message_header("directory"),
domain_dir
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tqdm.tqdm.write(colored("{}: Waiting 15s for {} to become available...".format(
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))
time.sleep(15)
if not os.path.exists(domain_dir):
return "continue"
wget_command = format_wget(args, directory, uagent, ext_csv, root_url)
proc = subprocess.Popen(wget_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
_, err = proc.communicate()
if "301 Moved Permanently" in err or "302 Found" in err or "307 Temporary Redirect" in err:
message_failed(args, "Redirects exceeded", root_url)
os.rmdir(domain_dir)
return "continue"
message_complete(url)
remove_empty(domain_dir, args)
return "break"
except Exception as err:
message_failed(args, err, url)
remove_empty(domain_dir, args)
return "continue" | [
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Mariewelt/OpenChem | e612d5cd471079c64e61ceda946c3dc7cf095bd8 | openchem/criterion/multitask_loss.py | python | MultitaskLoss.forward | (self, input, target) | return (loss.sum(dim=0) / n_samples).mean() | [] | def forward(self, input, target):
assert target.size()[1] == self.n_tasks
assert input.size()[1] == self.n_tasks
x = torch.zeros(target.size()).cuda()
y = torch.ones(target.size()).cuda()
mask = torch.where(target == self.ignore_index, x, y)
loss = F.binary_cross_entropy(input, mask * target, weight=self.weight)
loss = loss * mask
n_samples = mask.sum(dim=0)
return (loss.sum(dim=0) / n_samples).mean() | [
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fossasia/x-mario-center | fe67afe28d995dcf4e2498e305825a4859566172 | softwarecenter/ui/gtk3/models/appstore2.py | python | AppListStore.set_from_matches | (self, matches) | set the content of the liststore based on a list of
xapian.MSetItems | set the content of the liststore based on a list of
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""" set the content of the liststore based on a list of
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"""
LOG.debug("set_from_matches len(matches)='%s'" % len(matches))
self.current_matches = matches
n_matches = len(matches)
if n_matches == 0:
return
extent = min(self.LOAD_INITIAL, n_matches)
with ExecutionTime("store.append_initial"):
for doc in [m.document for m in matches][:extent]:
doc.available = doc.installed = doc.purchasable = None
self.append((doc,))
if n_matches == extent:
return
with ExecutionTime("store.append_placeholders"):
for i in range(n_matches - extent):
self.append()
self.emit('appcount-changed', len(matches))
self.buffer_icons() | [
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stefanhoelzl/vue.py | f4256454256ddfe54a8be6dea493d3fc915ef1a2 | examples/element_ui/app.py | python | App.clicked | (self, item) | [] | def clicked(self, item):
print(item)
self.notify.info(
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allenai/savn | 0ce930091e9213b52950143bb43195045ea33437 | datasets/environment.py | python | Environment.reachable_points | (self) | return self._reachable_points | Use the JSON file to get the reachable points. | Use the JSON file to get the reachable points. | [
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""" Use the JSON file to get the reachable points. """
if self._reachable_points is not None:
return self._reachable_points
points_path = os.path.join(self.offline_data_dir, self.scene_name, "grid.json")
if not os.path.exists(points_path):
raise IOError("Path {0} does not exist".format(points_path))
self._reachable_points = json.load(open(points_path))
return self._reachable_points | [
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/urllib3/packages/backports/makefile.py | python | backport_makefile | (self, mode="r", buffering=None, encoding=None,
errors=None, newline=None) | return text | Backport of ``socket.makefile`` from Python 3.5. | Backport of ``socket.makefile`` from Python 3.5. | [
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] | def backport_makefile(self, mode="r", buffering=None, encoding=None,
errors=None, newline=None):
"""
Backport of ``socket.makefile`` from Python 3.5.
"""
if not set(mode) <= {"r", "w", "b"}:
raise ValueError(
"invalid mode %r (only r, w, b allowed)" % (mode,)
)
writing = "w" in mode
reading = "r" in mode or not writing
assert reading or writing
binary = "b" in mode
rawmode = ""
if reading:
rawmode += "r"
if writing:
rawmode += "w"
raw = SocketIO(self, rawmode)
self._makefile_refs += 1
if buffering is None:
buffering = -1
if buffering < 0:
buffering = io.DEFAULT_BUFFER_SIZE
if buffering == 0:
if not binary:
raise ValueError("unbuffered streams must be binary")
return raw
if reading and writing:
buffer = io.BufferedRWPair(raw, raw, buffering)
elif reading:
buffer = io.BufferedReader(raw, buffering)
else:
assert writing
buffer = io.BufferedWriter(raw, buffering)
if binary:
return buffer
text = io.TextIOWrapper(buffer, encoding, errors, newline)
text.mode = mode
return text | [
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mdiazcl/fuzzbunch-debian | 2b76c2249ade83a389ae3badb12a1bd09901fd2c | windows/Resources/Python/Core/Lib/DocXMLRPCServer.py | python | XMLRPCDocGenerator.generate_html_documentation | (self) | return documenter.page(self.server_title, documentation) | generate_html_documentation() => html documentation for the server
Generates HTML documentation for the server using introspection for
installed functions and instances that do not implement the
_dispatch method. Alternatively, instances can choose to implement
the _get_method_argstring(method_name) method to provide the
argument string used in the documentation and the
_methodHelp(method_name) method to provide the help text used
in the documentation. | generate_html_documentation() => html documentation for the server
Generates HTML documentation for the server using introspection for
installed functions and instances that do not implement the
_dispatch method. Alternatively, instances can choose to implement
the _get_method_argstring(method_name) method to provide the
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"""generate_html_documentation() => html documentation for the server
Generates HTML documentation for the server using introspection for
installed functions and instances that do not implement the
_dispatch method. Alternatively, instances can choose to implement
the _get_method_argstring(method_name) method to provide the
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methods = {}
for method_name in self.system_listMethods():
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method_info[1] = self.instance._methodHelp(method_name)
method_info = tuple(method_info)
if method_info != (None, None):
method = method_info
elif not hasattr(self.instance, '_dispatch'):
try:
method = resolve_dotted_attribute(self.instance, method_name)
except AttributeError:
method = method_info
else:
method = method_info
methods[method_name] = method
documenter = ServerHTMLDoc()
documentation = documenter.docserver(self.server_name, self.server_documentation, methods)
return documenter.page(self.server_title, documentation) | [
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Dman95/SASM | 7e3ae6da1c219a68e26d38939338567e5c27151a | Windows/MinGW64/opt/lib/python2.7/codecs.py | python | StreamReader.read | (self, size=-1, chars=-1, firstline=False) | return result | Decodes data from the stream self.stream and returns the
resulting object.
chars indicates the number of characters to read from the
stream. read() will never return more than chars
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definition of the encoding and the given size, e.g. if
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""" Decodes data from the stream self.stream and returns the
resulting object.
chars indicates the number of characters to read from the
stream. read() will never return more than chars
characters, but it might return less, if there are not enough
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size indicates the approximate maximum number of bytes to
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if self.linebuffer:
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self.linebuffer = None
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# can the request can be satisfied from the character buffer?
if chars < 0:
if size < 0:
if self.charbuffer:
break
elif len(self.charbuffer) >= size:
break
else:
if len(self.charbuffer) >= chars:
break
# we need more data
if size < 0:
newdata = self.stream.read()
else:
newdata = self.stream.read(size)
# decode bytes (those remaining from the last call included)
data = self.bytebuffer + newdata
try:
newchars, decodedbytes = self.decode(data, self.errors)
except UnicodeDecodeError, exc:
if firstline:
newchars, decodedbytes = self.decode(data[:exc.start], self.errors)
lines = newchars.splitlines(True)
if len(lines)<=1:
raise
else:
raise
# keep undecoded bytes until the next call
self.bytebuffer = data[decodedbytes:]
# put new characters in the character buffer
self.charbuffer += newchars
# there was no data available
if not newdata:
break
if chars < 0:
# Return everything we've got
result = self.charbuffer
self.charbuffer = ""
else:
# Return the first chars characters
result = self.charbuffer[:chars]
self.charbuffer = self.charbuffer[chars:]
return result | [
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Yelp/clusterman | 54beef89c01a2681aafd1fbb93b6ad5f6252d6cf | clusterman/interfaces/resource_group.py | python | ResourceGroup.fulfilled_capacity | (self) | The actual weighted capacity for this ResourceGroup | The actual weighted capacity for this ResourceGroup | [
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demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/Base/Scripts/CommonServerPython/CommonServerPython.py | python | is_ip_valid | (s, accept_v6_ips=False) | Checks if the given string represents a valid IP address.
By default, will only return 'True' for IPv4 addresses.
:type s: ``str``
:param s: The string to be checked (required)
:type accept_v6_ips: ``bool``
:param accept_v6_ips: A boolean determining whether the
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:return: True if the given string represents a valid IP address, False otherwise
:rtype: ``bool`` | Checks if the given string represents a valid IP address.
By default, will only return 'True' for IPv4 addresses. | [
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"""
Checks if the given string represents a valid IP address.
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:type s: ``str``
:param s: The string to be checked (required)
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i = int(x)
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Jenyay/outwiker | 50530cf7b3f71480bb075b2829bc0669773b835b | src/outwiker/gui/controls/ultimatelistctrl.py | python | UltimateListHeaderData.SetItem | (self, item) | Sets information about the header/footer item.
:param `info`: an instance of :class:`UltimateListHeaderData`. | Sets information about the header/footer item. | [
"Sets",
"information",
"about",
"the",
"header",
"/",
"footer",
"item",
"."
] | def SetItem(self, item):
"""
Sets information about the header/footer item.
:param `info`: an instance of :class:`UltimateListHeaderData`.
"""
self._mask = item._mask
if self._mask & ULC_MASK_TEXT:
self._text = item._text
if self._mask & ULC_MASK_TOOLTIP:
self._tooltip = item._tooltip
if self._mask & ULC_MASK_FOOTER_TEXT:
self._footerText = item._footerText
if self._mask & ULC_MASK_IMAGE:
self._image = item._image[:]
if self._mask & ULC_MASK_FOOTER_IMAGE:
self._footerImage = item._footerImage[:]
if self._mask & ULC_MASK_FORMAT:
self._format = item._format
if self._mask & ULC_MASK_FOOTER_FORMAT:
self._footerFormat = item._footerFormat
if self._mask & ULC_MASK_WIDTH:
self.SetWidth(item._width)
if self._mask & ULC_MASK_FONT:
self._font = item._font
if self._mask & ULC_MASK_FOOTER_FONT:
self._footerFont = item._footerFont
if self._mask & ULC_MASK_FOOTER_KIND:
self._footerKind = item._footerKind
self._footerChecked = item._footerChecked
if self._mask & ULC_MASK_KIND:
self._kind = item._kind
self._checked = item._checked
if self._mask & ULC_MASK_CHECK:
self._kind = item._kind
self._checked = item._checked
if self._mask & ULC_MASK_FOOTER_CHECK:
self._footerKind = item._footerKind
self._footerChecked = item._footerChecked
if self._mask & ULC_MASK_STATE:
self.SetState(item._state)
if self._mask & ULC_MASK_SHOWN:
self._isColumnShown = item._isColumnShown
if self._mask & ULC_MASK_RENDERER:
self._customRenderer = item._customRenderer | [
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quay/quay | b7d325ed42827db9eda2d9f341cb5a6cdfd155a6 | buildman/manager/executor.py | python | LogPipe.run | (self) | Run the thread, logging everything. | Run the thread, logging everything. | [
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] | def run(self):
"""
Run the thread, logging everything.
"""
for line in iter(self.pipe_reader.readline, ""):
logging.log(self.level, line.strip("\n"))
self.pipe_reader.close() | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/data_catalog/data_catalog_client.py | python | DataCatalogClient.create_data_asset_tag | (self, catalog_id, data_asset_key, create_data_asset_tag_details, **kwargs) | Creates a new data asset tag.
:param str catalog_id: (required)
Unique catalog identifier.
:param str data_asset_key: (required)
Unique data asset key.
:param oci.data_catalog.models.CreateTagDetails create_data_asset_tag_details: (required)
The information used to create the data asset tag.
:param str opc_request_id: (optional)
The client request ID for tracing.
:param str opc_retry_token: (optional)
A token that uniquely identifies a request so it can be retried in case of a timeout or
server error without risk of executing that same action again. Retry tokens expire after 24
hours, but can be invalidated before then due to conflicting operations. For example, if a resource
has been deleted and purged from the system, then a retry of the original creation request
might be rejected.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.data_catalog.models.DataAssetTag`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/datacatalog/create_data_asset_tag.py.html>`__ to see an example of how to use create_data_asset_tag API. | Creates a new data asset tag. | [
"Creates",
"a",
"new",
"data",
"asset",
"tag",
"."
] | def create_data_asset_tag(self, catalog_id, data_asset_key, create_data_asset_tag_details, **kwargs):
"""
Creates a new data asset tag.
:param str catalog_id: (required)
Unique catalog identifier.
:param str data_asset_key: (required)
Unique data asset key.
:param oci.data_catalog.models.CreateTagDetails create_data_asset_tag_details: (required)
The information used to create the data asset tag.
:param str opc_request_id: (optional)
The client request ID for tracing.
:param str opc_retry_token: (optional)
A token that uniquely identifies a request so it can be retried in case of a timeout or
server error without risk of executing that same action again. Retry tokens expire after 24
hours, but can be invalidated before then due to conflicting operations. For example, if a resource
has been deleted and purged from the system, then a retry of the original creation request
might be rejected.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.data_catalog.models.DataAssetTag`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/datacatalog/create_data_asset_tag.py.html>`__ to see an example of how to use create_data_asset_tag API.
"""
resource_path = "/catalogs/{catalogId}/dataAssets/{dataAssetKey}/tags"
method = "POST"
# Don't accept unknown kwargs
expected_kwargs = [
"retry_strategy",
"opc_request_id",
"opc_retry_token"
]
extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]
if extra_kwargs:
raise ValueError(
"create_data_asset_tag got unknown kwargs: {!r}".format(extra_kwargs))
path_params = {
"catalogId": catalog_id,
"dataAssetKey": data_asset_key
}
path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}
for (k, v) in six.iteritems(path_params):
if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):
raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))
header_params = {
"accept": "application/json",
"content-type": "application/json",
"opc-request-id": kwargs.get("opc_request_id", missing),
"opc-retry-token": kwargs.get("opc_retry_token", missing)
}
header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}
retry_strategy = self.base_client.get_preferred_retry_strategy(
operation_retry_strategy=kwargs.get('retry_strategy'),
client_retry_strategy=self.retry_strategy
)
if retry_strategy:
if not isinstance(retry_strategy, retry.NoneRetryStrategy):
self.base_client.add_opc_retry_token_if_needed(header_params)
self.base_client.add_opc_client_retries_header(header_params)
retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback)
return retry_strategy.make_retrying_call(
self.base_client.call_api,
resource_path=resource_path,
method=method,
path_params=path_params,
header_params=header_params,
body=create_data_asset_tag_details,
response_type="DataAssetTag")
else:
return self.base_client.call_api(
resource_path=resource_path,
method=method,
path_params=path_params,
header_params=header_params,
body=create_data_asset_tag_details,
response_type="DataAssetTag") | [
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shiyanhui/FileHeader | f347cc134021fb0b710694b71c57742476f5fd2b | jinja2/ext.py | python | Extension.bind | (self, environment) | return rv | Create a copy of this extension bound to another environment. | Create a copy of this extension bound to another environment. | [
"Create",
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"copy",
"of",
"this",
"extension",
"bound",
"to",
"another",
"environment",
"."
] | def bind(self, environment):
"""Create a copy of this extension bound to another environment."""
rv = object.__new__(self.__class__)
rv.__dict__.update(self.__dict__)
rv.environment = environment
return rv | [
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tensorflow/tensor2tensor | 2a33b152d7835af66a6d20afe7961751047e28dd | tensor2tensor/models/basic.py | python | basic_fc_small | () | return hparams | Small fully connected model. | Small fully connected model. | [
"Small",
"fully",
"connected",
"model",
"."
] | def basic_fc_small():
"""Small fully connected model."""
hparams = common_hparams.basic_params1()
hparams.learning_rate = 0.1
hparams.batch_size = 128
hparams.hidden_size = 256
hparams.num_hidden_layers = 2
hparams.initializer = "uniform_unit_scaling"
hparams.initializer_gain = 1.0
hparams.weight_decay = 0.0
hparams.dropout = 0.0
return hparams | [
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YosefLab/scvi-tools | f0a3ba6e11053069fd1857d2381083e5492fa8b8 | scvi/model/base/_log_likelihood.py | python | compute_elbo | (vae, data_loader, feed_labels=True, **kwargs) | return elbo / n_samples | Computes the ELBO.
The ELBO is the reconstruction error + the KL divergences
between the variational distributions and the priors.
It differs from the marginal log likelihood.
Specifically, it is a lower bound on the marginal log likelihood
plus a term that is constant with respect to the variational distribution.
It still gives good insights on the modeling of the data, and is fast to compute. | Computes the ELBO. | [
"Computes",
"the",
"ELBO",
"."
] | def compute_elbo(vae, data_loader, feed_labels=True, **kwargs):
"""
Computes the ELBO.
The ELBO is the reconstruction error + the KL divergences
between the variational distributions and the priors.
It differs from the marginal log likelihood.
Specifically, it is a lower bound on the marginal log likelihood
plus a term that is constant with respect to the variational distribution.
It still gives good insights on the modeling of the data, and is fast to compute.
"""
# Iterate once over the data and compute the elbo
elbo = 0
for tensors in data_loader:
_, _, scvi_loss = vae(tensors, **kwargs)
recon_loss = scvi_loss.reconstruction_loss
kl_local = scvi_loss.kl_local
elbo += torch.sum(recon_loss + kl_local).item()
kl_global = scvi_loss.kl_global
n_samples = len(data_loader.indices)
elbo += kl_global
return elbo / n_samples | [
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/dev/pipelines/pipeline_folders.py | python | pipeline_folder_update | (path, new_path=None, new_description=None,
organization=None, project=None, detect=None) | return client.update_folder(path=path, folder=folder_to_update, project=project) | Update a folder name or description.
:param path: Full path of the folder.
:type path: str
:param new_path: New full path of the folder.
:type new_path: str
:param new_description: New description of the folder.
:type new_description: str
:param project: Name or ID of the team project.
:type project: str
:param detect: Automatically detect organization and project. Default is "on".
:type detect: str | Update a folder name or description.
:param path: Full path of the folder.
:type path: str
:param new_path: New full path of the folder.
:type new_path: str
:param new_description: New description of the folder.
:type new_description: str
:param project: Name or ID of the team project.
:type project: str
:param detect: Automatically detect organization and project. Default is "on".
:type detect: str | [
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"of",
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"folder",
".",
":",
... | def pipeline_folder_update(path, new_path=None, new_description=None,
organization=None, project=None, detect=None):
""" Update a folder name or description.
:param path: Full path of the folder.
:type path: str
:param new_path: New full path of the folder.
:type new_path: str
:param new_description: New description of the folder.
:type new_description: str
:param project: Name or ID of the team project.
:type project: str
:param detect: Automatically detect organization and project. Default is "on".
:type detect: str
"""
if not new_path and not new_description:
raise CLIError('Either --new-path or --new-description should be specified.')
organization, project = resolve_instance_and_project(
detect=detect, organization=organization, project=project)
client = get_build_client(organization)
folders = client.get_folders(path=path, project=project, query_order='folderAscending')
folder_to_update = None
# find matching folder if present
for folder in folders:
if folder.path.strip('\\') == path.strip('\\'):
folder_to_update = folder
break
if not folder_to_update:
raise CLIError('Cannot find folder with path {}. Update operation failed.'.format(path))
if new_description:
folder_to_update.description = new_description
if new_path:
folder_to_update.path = new_path
return client.update_folder(path=path, folder=folder_to_update, project=project) | [
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Quantika14/guasap-whatsapp-foresincs-tool | 68291f781a0483ac0f0fe6c90c7e4395a6d58cea | hashdeep.py | python | extract_mm | (pop_wait) | return md5_cloned, md5_original | Clone media data check | Clone media data check | [
"Clone",
"media",
"data",
"check"
] | def extract_mm(pop_wait):
md5_original=list()
md5_cloned=list()
files=list()
on_rute=False
on_file=False
subdirectoris=list()
modules.functions.create_dir_media()
directory = check_directory()
pull_media(directory)
# --- /helpers ---
# write("""\
# %%%% HASH_CHECK
# %%%% size,sha256,filename
# ##
# ## Clone media hash check
# ##""")
mensaje_deb = Label(pop_wait, text="Creando hash y comparando...")
mensaje_deb.place(x=20,y=80)
pop_wait.update()
mensaje_deb = Label(pop_wait, text="(Este proceso varia su duracion en base a los archivos multimedia)")
mensaje_deb.place(x=20,y=80)
pop_wait.update()
PATH = 'Whatsapp_Extracted_Media/'
""" Clone media data check """
for path, dirs, files in os.walk(PATH):
for fpath in [osp.join(path, f) for f in files]:
md5 = filehash(fpath)
name = osp.relpath(fpath, PATH)
# print "---------------------"
# print "MD5 [>] "+str(md5)
# print "Path [>] "+str(name)
md5_original.append((name,md5))
print "Finish hash cloned..."
# print '\n'
# write("""\
# %%%% HASH_CHECK
# %%%% size,sha256,filename
# ##
# ## Original media hash check
# ##""")
ls=get_subdirectoris(directory)
ls=ls.replace("\r", "").split("\n")
for l in ls:
if "/" in l and on_rute:
if on_file:
files.append(path.replace(":",""))
subdirectoris.append(files)
on_rute=False
on_file=False
files=[]
else:
on_rute=False
on_file=False
files=[]
path=""
if "/" in l:
path = l
on_rute=True
elif "." in l and on_rute:
file_l = l
on_file=True
files.append(file_l)
else:
continue
for directory in subdirectoris:
path=directory[len(directory)-1]
for i in range(len(directory)-1):
name, md5 = get_mdinfo(path, directory[i])
md5_cloned.append((name,md5))
# print "---------------------"
# print "MD5 [>] "+str(md5)
# print "Path [>] "+str(name)
print "Finish hash origin..."
print "Comparing..."
for i in range(len(md5_cloned)):
for has in md5_original:
if has[1] == md5_cloned[i][1]:
print "-----------------------"
print "------- Cloned ------"
print "MD5 [>] "+str(md5_cloned[i][1])
print "Path [>] "+str(md5_cloned[i][0])
print "--------Original-------"
print "MD5 [>] "+str(has[1])
print "Path [>] "+str(has[0])
# time.sleep(1)
return md5_cloned, md5_original | [
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vericast/spylon-kernel | 2d0ddf2aca1b91738f938b72a500c20293e3156c | versioneer.py | python | do_vcs_install | (manifest_in, versionfile_source, ipy) | Git-specific installation logic for Versioneer.
For Git, this means creating/changing .gitattributes to mark _version.py
for export-subst keyword substitution. | Git-specific installation logic for Versioneer. | [
"Git",
"-",
"specific",
"installation",
"logic",
"for",
"Versioneer",
"."
] | def do_vcs_install(manifest_in, versionfile_source, ipy):
"""Git-specific installation logic for Versioneer.
For Git, this means creating/changing .gitattributes to mark _version.py
for export-subst keyword substitution.
"""
GITS = ["git"]
if sys.platform == "win32":
GITS = ["git.cmd", "git.exe"]
files = [manifest_in, versionfile_source]
if ipy:
files.append(ipy)
try:
me = __file__
if me.endswith(".pyc") or me.endswith(".pyo"):
me = os.path.splitext(me)[0] + ".py"
versioneer_file = os.path.relpath(me)
except NameError:
versioneer_file = "versioneer.py"
files.append(versioneer_file)
present = False
try:
f = open(".gitattributes", "r")
for line in f.readlines():
if line.strip().startswith(versionfile_source):
if "export-subst" in line.strip().split()[1:]:
present = True
f.close()
except EnvironmentError:
pass
if not present:
f = open(".gitattributes", "a+")
f.write("%s export-subst\n" % versionfile_source)
f.close()
files.append(".gitattributes")
run_command(GITS, ["add", "--"] + files) | [
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... | https://github.com/vericast/spylon-kernel/blob/2d0ddf2aca1b91738f938b72a500c20293e3156c/versioneer.py#L1117-L1152 | ||
dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/accounting/subscription_changes.py | python | _get_active_immediate_broadcasts | (domain, survey_only=False) | return result | [] | def _get_active_immediate_broadcasts(domain, survey_only=False):
result = list(ImmediateBroadcast.objects.filter(domain=domain.name, deleted=False, schedule__active=True))
if survey_only:
result = [broadcast for broadcast in result if broadcast.schedule.memoized_uses_sms_survey]
return result | [
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Pylons/pyramid | 0b24ac16cc04746b25cf460f1497c157f6d3d6f4 | src/pyramid/interfaces.py | python | IAuthenticationPolicy.unauthenticated_userid | (request) | Return the *unauthenticated* userid. This method
performs the same duty as ``authenticated_userid`` but is
permitted to return the userid based only on data present
in the request; it needn't (and shouldn't) check any
persistent store to ensure that the user record related to
the request userid exists.
This method is intended primarily a helper to assist the
``authenticated_userid`` method in pulling credentials out
of the request data, abstracting away the specific headers,
query strings, etc that are used to authenticate the request. | Return the *unauthenticated* userid. This method
performs the same duty as ``authenticated_userid`` but is
permitted to return the userid based only on data present
in the request; it needn't (and shouldn't) check any
persistent store to ensure that the user record related to
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"""Return the *unauthenticated* userid. This method
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permitted to return the userid based only on data present
in the request; it needn't (and shouldn't) check any
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This method is intended primarily a helper to assist the
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rhinstaller/anaconda | 63edc8680f1b05cbfe11bef28703acba808c5174 | pyanaconda/ui/gui/spokes/installation_source.py | python | SourceSpoke._reset_repo_store | (self) | Reset the list of repos.
Populate the list with all the addon repos from payload.addons.
If the list has no element, clear the repo entry fields. | Reset the list of repos. | [
"Reset",
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] | def _reset_repo_store(self):
""" Reset the list of repos.
Populate the list with all the addon repos from payload.addons.
If the list has no element, clear the repo entry fields.
"""
log.debug("Clearing checks in source spoke")
# Remove the repo checks
for checks in self._repo_checks.values():
self.remove_check(checks.name_check)
self.remove_check(checks.url_check)
self.remove_check(checks.proxy_check)
self._repo_checks = {}
with self._repo_store_lock:
self._repo_store.clear()
for repo in self.data.repo.dataList():
log.debug("Setting up repo: %s", repo.name)
ks_repo = self.data.RepoData.create_copy(repo)
# Track the original name, user may change .name
ks_repo.orig_name = repo.name
# Add addon repository id for identification
ks_repo.repo_id = next(self._repo_counter)
self._repo_store.append([self.payload.is_repo_enabled(repo.name),
ks_repo.name,
ks_repo])
if len(self._repo_store) > 0:
self._repo_selection.select_path(0)
else:
self._clear_repo_info()
self._repo_entry_box.set_sensitive(False) | [
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circus-tent/circus | 4b8aaca9470e3fd1ab115b14c8b1d1bf9b5b3c5e | circus/consumer.py | python | CircusConsumer.iter_messages | (self) | Yields tuples of (topic, message) | Yields tuples of (topic, message) | [
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""" Yields tuples of (topic, message) """
with self:
while True:
try:
events = dict(self.poller.poll(self.timeout * 1000))
except zmq.ZMQError as e:
if e.errno == errno.EINTR:
continue
raise
if len(events) == 0:
continue
topic, message = self.pubsub_socket.recv_multipart()
yield topic, message | [
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joe42/CloudFusion | c4b94124e74a81e0634578c7754d62160081f7a1 | cloudfusion/util/lru_cache.py | python | LRUCache.delete | (self, key) | Remove current entry associated with key from the LRU queue. | Remove current entry associated with key from the LRU queue. | [
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"""Remove current entry associated with key from the LRU queue."""
if key in self.entries:
entry = self.entries[key]
self.entries[CACHESIZE] -= self._get_size_of_entry(entry)
self._unlink(key)
del self.entries[key] | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/uwsgidecorators.py | python | spoolforever | (f=None, pass_arguments=False) | return spool_decorate(f, pass_arguments, _spoolforever) | [] | def spoolforever(f=None, pass_arguments=False):
return spool_decorate(f, pass_arguments, _spoolforever) | [
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/metagoofil/pdfminer/layout.py | python | LTItem.voverlap | (self, obj) | [] | def voverlap(self, obj):
assert isinstance(obj, LTItem)
if self.is_voverlap(obj):
return min(abs(self.y0-obj.y1), abs(self.y1-obj.y0))
else:
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perrygeo/simanneal | 951e7d89a8b7f19aeb05b64e7cc8b844a734af89 | examples/watershed/shapefile.py | python | Writer.field | (self, name, fieldType="C", size="50", decimal=0) | Adds a dbf field descriptor to the shapefile. | Adds a dbf field descriptor to the shapefile. | [
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] | def field(self, name, fieldType="C", size="50", decimal=0):
"""Adds a dbf field descriptor to the shapefile."""
self.fields.append((name, fieldType, size, decimal)) | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_vendored_deps/library/oc_route.py | python | Utils.openshift_installed | () | return rpmquery.count() > 0 | check if openshift is installed | check if openshift is installed | [
"check",
"if",
"openshift",
"is",
"installed"
] | def openshift_installed():
''' check if openshift is installed '''
import rpm
transaction_set = rpm.TransactionSet()
rpmquery = transaction_set.dbMatch("name", "atomic-openshift")
return rpmquery.count() > 0 | [
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SoCo/SoCo | e83fef84d2645d05265dbd574598518655a9c125 | soco/events_base.py | python | get_listen_ip | (ip_address) | Find the listen ip address. | Find the listen ip address. | [
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"."
] | def get_listen_ip(ip_address):
"""Find the listen ip address."""
if config.EVENT_LISTENER_IP:
return config.EVENT_LISTENER_IP
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
try:
sock.connect((ip_address, config.EVENT_LISTENER_PORT))
return sock.getsockname()[0]
except socket.error:
return None
finally:
sock.close() | [
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TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e | tensorflow_dl_models/research/slim/deployment/model_deploy.py | python | optimize_clones | (clones, optimizer,
regularization_losses=None,
**kwargs) | return total_loss, grads_and_vars | Compute clone losses and gradients for the given list of `Clones`.
Note: The regularization_losses are added to the first clone losses.
Args:
clones: List of `Clones` created by `create_clones()`.
optimizer: An `Optimizer` object.
regularization_losses: Optional list of regularization losses. If None it
will gather them from tf.GraphKeys.REGULARIZATION_LOSSES. Pass `[]` to
exclude them.
**kwargs: Optional list of keyword arguments to pass to `compute_gradients`.
Returns:
A tuple (total_loss, grads_and_vars).
- total_loss: A Tensor containing the average of the clone losses including
the regularization loss.
- grads_and_vars: A List of tuples (gradient, variable) containing the sum
of the gradients for each variable. | Compute clone losses and gradients for the given list of `Clones`. | [
"Compute",
"clone",
"losses",
"and",
"gradients",
"for",
"the",
"given",
"list",
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"Clones",
"."
] | def optimize_clones(clones, optimizer,
regularization_losses=None,
**kwargs):
"""Compute clone losses and gradients for the given list of `Clones`.
Note: The regularization_losses are added to the first clone losses.
Args:
clones: List of `Clones` created by `create_clones()`.
optimizer: An `Optimizer` object.
regularization_losses: Optional list of regularization losses. If None it
will gather them from tf.GraphKeys.REGULARIZATION_LOSSES. Pass `[]` to
exclude them.
**kwargs: Optional list of keyword arguments to pass to `compute_gradients`.
Returns:
A tuple (total_loss, grads_and_vars).
- total_loss: A Tensor containing the average of the clone losses including
the regularization loss.
- grads_and_vars: A List of tuples (gradient, variable) containing the sum
of the gradients for each variable.
"""
grads_and_vars = []
clones_losses = []
num_clones = len(clones)
if regularization_losses is None:
regularization_losses = tf.get_collection(
tf.GraphKeys.REGULARIZATION_LOSSES)
for clone in clones:
with tf.name_scope(clone.scope):
clone_loss, clone_grad = _optimize_clone(
optimizer, clone, num_clones, regularization_losses, **kwargs)
if clone_loss is not None:
clones_losses.append(clone_loss)
grads_and_vars.append(clone_grad)
# Only use regularization_losses for the first clone
regularization_losses = None
# Compute the total_loss summing all the clones_losses.
total_loss = tf.add_n(clones_losses, name='total_loss')
# Sum the gradients across clones.
grads_and_vars = _sum_clones_gradients(grads_and_vars)
return total_loss, grads_and_vars | [
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seantis/seantis-questionnaire | 698c77b3d707635f50bcd86e7f1c94e94061b0f5 | questionnaire/models.py | python | QuestionSet.questions | (self) | return self.__qcache | [] | def questions(self):
if not hasattr(self, "__qcache"):
def numeric_number(val):
matches = re.findall(r'^\d+', val)
return int(matches[0]) if matches else 0
self.__qcache = sorted(
Question.objects.filter(questionset=self.id),
key=lambda q: (numeric_number(q.number), q.number)
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return self.__qcache | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/_collections_abc.py | python | Callable.__call__ | (self, *args, **kwds) | return False | [] | def __call__(self, *args, **kwds):
return False | [
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mongodb/motor | 055f5e05abf1f15e64ae43fb8c680d2706f3c419 | motor/metaprogramming.py | python | AsyncRead.__init__ | (self, attr_name=None, doc=None) | A descriptor that wraps a PyMongo read method like find_one() that
returns a Future. | A descriptor that wraps a PyMongo read method like find_one() that
returns a Future. | [
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] | def __init__(self, attr_name=None, doc=None):
"""A descriptor that wraps a PyMongo read method like find_one() that
returns a Future.
"""
Async.__init__(self, attr_name=attr_name, doc=doc) | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/utils/dummy_pt_objects.py | python | PerceiverPreTrainedModel.from_pretrained | (cls, *args, **kwargs) | [] | def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"]) | [
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