code stringlengths 281 23.7M |
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def update_hint_locations(game: RandovaniaGame, hint_tree_widget: QtWidgets.QTreeWidget):
game_description = default_database.game_description_for(game)
used_hint_kind = set()
hint_tree_widget.clear()
hint_tree_widget.setSortingEnabled(False)
hint_type_tree = collections.defaultdict(dict)
for re... |
def preprocess_input(tokenizer, sentences):
inputs = []
MAX_LEN = 64
for sentence in sentences:
encoded_sent = tokenizer.encode(sentence, add_special_tokens=True)
if (len(encoded_sent) < MAX_LEN):
encoded_sent.extend(([0] * (MAX_LEN - len(encoded_sent))))
if (len(encoded_... |
def timeout(seconds=10):
def decorator(func):
(func)
def wrapper(*args, **kwargs):
def handle_timeout(signum, frame):
raise Exception()
signal(SIGALRM, handle_timeout)
alarm(seconds)
result = None
try:
result... |
def start_global_server( (int | None)=None, urls: list[str]=['.'], server: type[ServerType]=BottleServer, **server_args: Unpack[ServerArgs]) -> tuple[(str, (str | None), BottleServer)]:
global global_server
(address, common_path, global_server) = start_server(urls=urls, server=server, **server_args)
return... |
.mosaiqdb
def test_get_patient_fields(connection: pymedphys.mosaiq.Connection):
mock_patient_ident_df = mocks.create_mock_patients()
mock_site_df = mocks.create_mock_treatment_sites(mock_patient_ident_df)
mocks.create_mock_treatment_fields(mock_site_df)
fields_for_moe_df = helpers.get_patient_fields(con... |
def resolve_remote(uri, handlers):
scheme = urlparse.urlsplit(uri).scheme
if (scheme in handlers):
result = handlers[scheme](uri)
else:
from urllib.request import urlopen
req = urlopen(uri)
encoding = (req.info().get_content_charset() or 'utf-8')
try:
resu... |
_families
def test_logging_passing_tests_disabled_does_not_log_test_output(pytester: Pytester, run_and_parse: RunAndParse, xunit_family: str) -> None:
pytester.makeini('\n [pytest]\n junit_log_passing_tests=False\n junit_logging=system-out\n junit_family={family}\n '.format(family=xun... |
class TransactWrite(Transaction):
def __init__(self, client_request_token: Optional[str]=None, return_item_collection_metrics: Optional[str]=None, **kwargs: Any) -> None:
super(TransactWrite, self).__init__(**kwargs)
self._client_request_token: Optional[str] = client_request_token
self._retu... |
class ConflictCause(IncompatibilityCause):
def __init__(self, conflict: Incompatibility, other: Incompatibility) -> None:
self._conflict = conflict
self._other = other
def conflict(self) -> Incompatibility:
return self._conflict
def other(self) -> Incompatibility:
return self... |
_criterion('winogrande')
class WinograndeCriterion(WSCCriterion):
def forward(self, model, sample, reduce=True):
query_lprobs = self.get_lprobs(model, sample['query_tokens'], sample['query_masks'])
cand_lprobs = self.get_lprobs(model, sample['candidate_tokens'], sample['candidate_masks'])
pr... |
class ModelFormTagFieldRequiredTest(TagTestManager, TestCase):
manage_models = [test_models.TagFieldRequiredModel]
def setUpExtra(self):
self.form = test_forms.TagFieldRequiredModelForm
self.model = test_models.TagFieldRequiredModel
self.tag_model = self.model.tag.tag_model
def test_... |
def test_get_conference_roles_for_user(conference_factory, requests_mock):
conference = conference_factory()
requests_mock.get(f'{settings.PRETIX_API}organizers/base-pretix-organizer-id/events/base-pretix-event-id/vouchers', status_code=200, json={'next': None, 'results': []})
requests_mock.get(f'{settings.... |
def download_huggingface_tokenizers():
huggingface_dir = './data/huggingface'
if (not os.path.isdir(huggingface_dir)):
os.makedirs(huggingface_dir, exist_ok=True)
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
tokenizer.save_pretrained('{}/bert-base-uncased'.format(huggin... |
def get_video_dataset_dicts(dataset_names, gen_inst_id=False):
assert len(dataset_names)
dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in dataset_names]
for (dataset_name, dicts) in zip(dataset_names, dataset_dicts):
assert len(dicts), "Dataset '{}' is empty!".format(dataset_nam... |
class TestTimePoolHead(nn.Module):
def __init__(self, base, original_pool=7):
super(TestTimePoolHead, self).__init__()
self.base = base
self.original_pool = original_pool
base_fc = self.base.get_classifier()
if isinstance(base_fc, nn.Conv2d):
self.fc = base_fc
... |
class WarmupConstantSchedule(LambdaLR):
def __init__(self, optimizer, warmup_steps, last_epoch=(- 1)):
self.warmup_steps = warmup_steps
super(WarmupConstantSchedule, self).__init__(optimizer, self.lr_lambda, last_epoch=last_epoch)
def lr_lambda(self, step):
if (step < self.warmup_steps):... |
class ConferenceModeratorAdmin(AuditAdmin):
list_display = (('conference', 'moderator', 'active') + AuditAdmin.list_display)
list_filter = ('conference',)
def get_queryset(self, request):
qs = super(ConferenceModeratorAdmin, self).get_queryset(request)
if request.user.is_superuser:
... |
class PlanSelector(discord.ui.Select):
def __init__(self, plans: List[PremiumPlan]):
super().__init__(placeholder='Select a Quotient Premium Plan... ')
for _ in plans:
self.add_option(label=f'{_.name} - {_.price}', description=_.description, value=_.id)
async def callback(self, inter... |
def run_params(args):
params = deepcopy(vars(args))
params['model'] = 'MLP_SIG'
params['optimizer'] = 'Adam'
if (args.data_cache_path != 'None'):
pathlib.Path(args.data_cache_path).mkdir(parents=True, exist_ok=True)
if (args.mode == 'pretrain'):
if (args.method == 'Pretrain'):
... |
def test_registry():
registry = Registry()
assert ('DIFF' not in registry)
assert (len(registry) == 0)
('DIFF')
def difference(a, b):
return (a - b)
assert ('DIFF' in registry)
assert (len(registry) == 1)
assert (registry['DIFF'] == difference)
with pytest.raises(KeyError):
... |
def test_field_renaming(converter: Converter):
class A():
a: int
class B():
a: int
converter.register_structure_hook(B, make_dict_structure_fn(B, converter, a=override(rename='b')))
assert (converter.structure({'a': 1}, Union[(A, B)]) == A(1))
assert (converter.structure({'b': 1}, Un... |
class TestTradingControls(zf.WithMakeAlgo, zf.ZiplineTestCase):
START_DATE = pd.Timestamp('2006-01-03', tz='utc')
END_DATE = pd.Timestamp('2006-01-06', tz='utc')
sid = 133
sids = ASSET_FINDER_EQUITY_SIDS = (133, 134)
SIM_PARAMS_DATA_FREQUENCY = 'daily'
DATA_PORTAL_USE_MINUTE_DATA = True
def ... |
def is2_use(use):
def factory():
from qiime2.core.testing.format import IntSequenceFormatV2
from qiime2.plugin.util import transform
ff = transform([1, 2, 3], to_type=IntSequenceFormatV2)
ff.validate()
return ff
to_import = use.init_format('to_import', factory, ext='.hell... |
def process_dis_batch_recur(input_filename_list, dim_input, num, reshape_with_one=False):
img_list = []
random.seed(6)
random.shuffle(input_filename_list)
for filepath in input_filename_list:
filepath2 = (FLAGS.data_path + filepath)
this_img = scm.imread(filepath2)
this_img = np.... |
def test_scene_to_pixmap_exporter_export_with_worker(view, tmpdir):
filename = os.path.join(tmpdir, 'foo.png')
item_img = QtGui.QImage(1000, 1200, QtGui.QImage.Format.Format_RGB32)
item = BeePixmapItem(item_img)
view.scene.addItem(item)
exporter = SceneToPixmapExporter(view.scene)
exporter.size ... |
def assert_reversible_orbit(inst, iterations):
n_time = []
p_time = []
control = inst.copy()
for j in range(iterations):
n_time.append(inst.index[0])
inst.orbits.next()
for j in range(iterations):
inst.orbits.prev()
p_time.append(inst.index[0])
assert all((control... |
class MapsGrid():
def __init__(self, r=2, c=2, crs=None, m_inits=None, ax_inits=None, figsize=None, layer='base', f=None, **kwargs):
self._Maps = []
self._names = dict()
if (WebMapContainer is not None):
self._wms_container = WebMapContainer(self)
gskwargs = dict(bottom=0... |
class _ADTSStream(object):
parsed_frames = 0
offset = 0
def find_stream(cls, fileobj, max_bytes):
r = BitReader(fileobj)
stream = cls(r)
if stream.sync(max_bytes):
stream.offset = ((r.get_position() - 12) // 8)
return stream
def sync(self, max_bytes):
... |
class RegisterFileRst(Component):
def construct(s, Type, nregs=32, rd_ports=1, wr_ports=1, const_zero=False, reset_value=0):
addr_type = mk_bits(max(1, clog2(nregs)))
s.raddr = [InPort(addr_type) for i in range(rd_ports)]
s.rdata = [OutPort(Type) for i in range(rd_ports)]
s.waddr = [... |
def get_type_desktop():
cmd_status_gui = Command(shlex.split('systemctl get-default'))
status = 0
try:
status_gui = cmd_status_gui()[0]
if (status_gui == 'multi-user.target'):
status = 1
if os.path.isfile('/etc/systemd/system/.service.d/autologin.conf'):
... |
class ManiSkill2Dataset(Dataset):
def __init__(self, dataset_file: str, load_count=(- 1)) -> None:
self.dataset_file = dataset_file
import h5py
from mani_skill2.utils.io_utils import load_json
self.data = h5py.File(dataset_file, 'r')
json_path = dataset_file.replace('.h5', '.... |
class Encoder(Ranker):
def __init__(self, on: typing.Union[(str, typing.List[str])], key: str, encoder, normalize: bool=True, k: typing.Optional[int]=None, batch_size: int=64) -> None:
super().__init__(key=key, on=on, encoder=encoder, normalize=normalize, k=k, batch_size=batch_size)
def __call__(self, q... |
def open_circuit_potential(c_surf):
stretch = 1.062
sto = ((stretch * c_surf) / c_max)
u_eq = ((((((2.16216 + (0.07645 * tanh((30.834 - (54.4806 * sto))))) + (2.1581 * tanh((52.294 - (50.294 * sto))))) - (0.14169 * tanh((11.0923 - (19.8543 * sto))))) + (0.2051 * tanh((1.4684 - (5.4888 * sto))))) + (0.2531 *... |
def encode_report(rpt, rpt_path):
rpt_dict = {}
parcels = spatial.read_shapefile(sg.config.parcels_shapefile)
parcels = parcels[['PARCELID', 'coords']]
flooded = rpt.alt_report.parcel_flooding
flooded = pd.merge(flooded, parcels, right_on='PARCELID', left_index=True)
rpt_dict['parcels'] = spatia... |
class Infraction(ModelReprMixin, models.Model):
TYPE_CHOICES = (('note', 'Note'), ('warning', 'Warning'), ('watch', 'Watch'), ('timeout', 'Timeout'), ('kick', 'Kick'), ('ban', 'Ban'), ('superstar', 'Superstar'), ('voice_ban', 'Voice Ban'), ('voice_mute', 'Voice Mute'))
inserted_at = models.DateTimeField(default... |
class SubscriptionHandler(object):
def __init__(self, obj):
self.obj = obj
self._cache = None
def _recache(self):
self._cache = {account: True for account in self.obj.db_account_subscriptions.all() if (hasattr(account, 'pk') and account.pk)}
self._cache.update({obj: True for obj ... |
(scope='session', autouse=True)
def symbols_by_file() -> Dict[(str, Set[str])]:
sys.stdout = StringIO()
lint.Run(['--reports=n', '--rcfile=python_ta/config/.pylintrc', '--output-format=json', *get_file_paths()], exit=False)
jsons_output = sys.stdout.getvalue()
sys.stdout = sys.__stdout__
pylint_list... |
class Attention(nn.Module):
def __init__(self, dim, num_heads=8, sr_ratio=1):
super().__init__()
self.num_heads = num_heads
head_dim = (dim // num_heads)
self.scale = (head_dim ** (- 0.5))
self.dim = dim
self.q = nn.Linear(dim, dim, bias=True)
self.kv = nn.Lin... |
def _test_false_cyclic_dependency():
class Top(Component):
def construct(s):
s.a = Wire(int)
s.b = Wire(int)
s.c = Wire(int)
s.d = Wire(int)
s.e = Wire(int)
s.f = Wire(int)
s.g = Wire(int)
s.h = Wire(int)
... |
def flatten_settings(json: dict) -> dict:
settings = json.pop('settings', {})
flattened_settings = {}
for (entry, value) in settings.items():
if isinstance(value, dict):
flattened_settings.update(value)
else:
flattened_settings[entry] = value
json.update(flattened... |
def eval_auto_attack(model, device, cfgs, logger, test_loader, individual=False, print_freq=20, mode='test', train_val=False):
logger.info('Evaluating Auto Attack!')
model.eval()
attacks_to_run = ['apgd-ce', 'apgd-t']
adversary = AutoAttack(model, norm='Linf', eps=cfgs.test_epsilon, version='standard', ... |
def get_predictions(example, features, all_results, n_best_size, max_answer_length, do_lower_case, version_2_with_negative, null_score_diff_threshold):
unique_id_to_result = {}
for result in all_results:
unique_id_to_result[result.unique_id] = result
_PrelimPrediction = collections.namedtuple('Preli... |
.parametrize('name', 'test tests whatever .dotdir'.split())
def test_setinitial_conftest_subdirs(pytester: Pytester, name: str) -> None:
sub = pytester.mkdir(name)
subconftest = sub.joinpath('conftest.py')
subconftest.touch()
pm = PytestPluginManager()
conftest_setinitial(pm, [sub.parent], confcutdi... |
(cc=STDCALL, params={'pIdentifierAuthority': PSID_IDENTIFIER_AUTHORITY, 'nSubAuthorityCount': BYTE, 'nSubAuthority0': DWORD, 'nSubAuthority1': DWORD, 'nSubAuthority2': DWORD, 'nSubAuthority3': DWORD, 'nSubAuthority4': DWORD, 'nSubAuthority5': DWORD, 'nSubAuthority6': DWORD, 'nSubAuthority7': DWORD, 'pSid': POINTER})
de... |
class KNearestPMedian(PMedian):
def __init__(self, name: str, ai_sum: (int | float), clients: np.array, facilities: np.array, weights: np.array, k_array: np.array, p_facilities: int, capacities: np.array=None, distance_metric: str='euclidean'):
self.ai_sum = ai_sum
self.clients = clients
sel... |
class HDDFeatureExtractor(nn.Module):
def __init__(self, args):
super(HDDFeatureExtractor, self).__init__()
if (args.inputs in ['camera', 'sensor', 'multimodal']):
self.with_camera = ('sensor' not in args.inputs)
self.with_sensor = ('camera' not in args.inputs)
else:
... |
def relayfee(network: 'Network'=None) -> int:
from .simple_config import FEERATE_DEFAULT_RELAY, FEERATE_MAX_RELAY
if (network and (network.relay_fee is not None)):
fee = network.relay_fee
else:
fee = FEERATE_DEFAULT_RELAY
fee = min(fee, FEERATE_MAX_RELAY)
fee = max(fee, FEERATE_DEFAU... |
class TestMulticlassPrecisionRecallCurve(unittest.TestCase):
def test_multiclass_precision_recall_curve_base(self) -> None:
input = torch.tensor([[0.1, 0.2, 0.1], [0.4, 0.2, 0.1], [0.6, 0.1, 0.2], [0.4, 0.2, 0.3], [0.6, 0.2, 0.4]])
target = torch.tensor([0, 1, 2, 1, 0])
my_compute_result = m... |
def find_dataset_using_name(dataset_name):
dataset_filename = (('data.' + dataset_name) + '_dataset')
datasetlib = importlib.import_module(dataset_filename)
dataset = None
target_dataset_name = (dataset_name.replace('_', '') + 'dataset')
for (name, cls) in datasetlib.__dict__.items():
if (na... |
class W_ThreadCell(W_Object):
errorname = 'thread-cell'
_immutable_fields_ = ['initial', 'preserved']
_attrs_ = ['initial', 'preserved', 'value']
_table = ThreadCellTable()
def __init__(self, val, preserved):
self.value = val
self.initial = val
self.preserved = preserved
... |
_model_architecture('char_source_transformer', 'char_source_transformer')
def base_architecture(args):
transformer.base_architecture(args)
args.char_cnn_params = getattr(args, 'char_cnn_params', '[(50, 1), (100,2)]')
args.char_cnn_nonlinear_fn = getattr(args, 'chr_cnn_nonlinear_fn', 'relu')
args.char_cn... |
def test_sample_partially_observed():
with pm.Model() as m:
with pytest.warns(ImputationWarning):
x = pm.Normal('x', observed=np.array([0, 1, np.nan]))
idata = pm.sample(nuts_sampler='numpyro', chains=1, draws=10, tune=10)
assert (idata.observed_data['x_observed'].shape == (2,))
... |
def split_documents(documents: dict) -> dict:
(titles, texts) = ([], [])
for (title, text) in zip(documents['title'], documents['text']):
if (text is not None):
for passage in split_text(text):
titles.append((title if (title is not None) else ''))
texts.append... |
.parametrize('add_version_condition', [True, False])
def test_model_version_attribute_save(add_version_condition: bool) -> None:
item = VersionedModel('test_user_name', email='test_')
with patch(PATCH_METHOD) as req:
req.return_value = {}
item.save(add_version_condition=add_version_condition)
... |
_pypy
def test_class_method_with_metaclass_spy(mocker: MockerFixture) -> None:
class MetaFoo(type):
pass
class Foo():
__metaclass__ = MetaFoo
def bar(cls, arg):
return (arg * 2)
spy = mocker.spy(Foo, 'bar')
assert (Foo.bar(arg=10) == 20)
Foo.bar.assert_called_once... |
class GreedyBipartiteMatcherTest(tf.test.TestCase):
def test_get_expected_matches_when_all_rows_are_valid(self):
similarity_matrix = tf.constant([[0.5, 0.1, 0.8], [0.15, 0.2, 0.3]])
num_valid_rows = 2
expected_match_results = [(- 1), 1, 0]
matcher = bipartite_matcher.GreedyBipartiteM... |
def read_yaml_file(filename):
try:
with open(filename) as yaml_file:
data = yaml.safe_load(yaml_file)
return data
except IOError as error:
if (LOGGER is None):
print(f'File error: {str(error)}')
else:
LOGGER.error(f'File error: {str(error)}... |
def pretty_print_results(args, address_to_index, p2p_bw, results):
if args.markdown:
print('```')
print('Shuffle benchmark')
print_separator(separator='-')
print_key_value(key='Backend', value=f'{args.backend}')
print_key_value(key='Partition size', value=f'{format_bytes(args.partition_size)... |
def rename_state_to_visibility(migrator: playhouse.migrate.SqliteMigrator):
with database.db.atomic():
database.db.execute(migrator._alter_table(migrator.make_context(), 'multiplayer_session').literal(' RENAME COLUMN ').sql(peewee.Entity('state')).literal(' TO ').sql(peewee.Entity('visibility')))
da... |
def all_scores(mols, data, norm=False, reconstruction=False):
m0 = {k: list(filter((lambda e: (e is not None)), v)) for (k, v) in {'NP score': MolecularMetrics.natural_product_scores(mols, norm=norm), 'QED score': MolecularMetrics.quantitative_estimation_druglikeness_scores(mols), 'logP score': MolecularMetrics.wat... |
def _fix_indentation(content: str) -> str:
lines = content.splitlines(keepends=True)
first_indent = _get_leading_spaces(content)
first_line = lines[0][first_indent:]
if (len(lines) == 1):
return first_line
second_indent = _get_leading_spaces(lines[1])
if first_line.rstrip().endswith(':')... |
class unit_gtcn_689(nn.Module):
def __init__(self, in_channels, out_channels, A, coff_embedding=4, num_subset=3):
super(unit_gtcn_689, self).__init__()
inter_channels = (out_channels // coff_embedding)
self.inter_c = inter_channels
self.PA = nn.Parameter(torch.from_numpy(A.astype(np.... |
class MatchingForTraining(torch.nn.Module):
def __init__(self, config={}):
super().__init__()
self.superpoint = SuperPoint(config.get('superpoint', {}))
self.superglue = SuperGlue(config.get('superglue', {}))
def forward(self, data):
pred = {}
if ('keypoints0' not in data... |
(repr=False, frozen=True, slots=True)
class _MaxLengthValidator():
max_length = attrib()
def __call__(self, inst, attr, value):
if (len(value) > self.max_length):
msg = f"Length of '{attr.name}' must be <= {self.max_length}: {len(value)}"
raise ValueError(msg)
def __repr__(se... |
def _throughput_compute(num_processed: int, elapsed_time_sec: float) -> torch.Tensor:
if (num_processed < 0):
raise ValueError(f'Expected num_processed to be a non-negative number, but received {num_processed}.')
if (elapsed_time_sec <= 0):
raise ValueError(f'Expected elapsed_time_sec to be a po... |
class GamePresetDescriber():
def _calculate_pickup_pool(self, configuration: BaseConfiguration) -> list[str]:
expected_starting_count = self.expected_starting_item_count(configuration)
expected_shuffled_count = self.expected_shuffled_pickup_count(configuration)
shuffled_list = []
sta... |
def adam(func, x, n_iter, learning_rate=0.001, beta1=0.9, beta2=0.999, eps=1e-08):
V = 0.0
S = 0.0
for i in range((n_iter + 1)):
(_, grad) = func(x)
V = ((beta1 * V) + ((1 - beta1) * grad))
S = ((beta2 * S) + ((1 - beta2) * (grad ** 2)))
V_hat = (V / (1 - (beta1 ** (i + 1))))... |
class TestDriverHDF5Save(QiskitChemistryTestCase, TestDriver):
def setUp(self):
super().setUp()
driver = HDF5Driver(hdf5_input=self.get_resource_path('test_driver_hdf5.hdf5'))
temp_qmolecule = driver.run()
(file, self.save_file) = tempfile.mkstemp(suffix='.hdf5')
os.close(fil... |
def parse_args():
parser = optparse.OptionParser()
parser.add_option('-f', '--file', dest='file_path')
parser.add_option('-a', '--append', action='store_true', default=False)
parser.add_option('-Q', '--quote', action='store_true', default=False)
parser.add_option('-s', '--addspace', action='store_tr... |
def upgrade(saveddata_engine):
saveddata_engine.execute(tmpTable)
saveddata_engine.execute('INSERT INTO damagePatternsTemp (ID, name, emAmount, thermalAmount, kineticAmount, explosiveAmount, ownerID, created, modified) SELECT ID, name, emAmount, thermalAmount, kineticAmount, explosiveAmount, ownerID, created, m... |
.parametrize('bin_op', [pytest.param((lambda a, b: (a + b)), id='add'), pytest.param((lambda a, b: (a - b)), id='sub'), pytest.param((lambda a, b: (a * b)), id='mul'), pytest.param(_div, id='div')])
def test_binopt_scalar(all_qevo, bin_op):
obj = all_qevo
scalar = (0.5 + 1j)
for t in TESTTIMES:
as_q... |
class DepositfilesCom(BaseAccount):
__name__ = 'DepositfilesCom'
__type__ = 'account'
__version__ = '0.39'
__status__ = 'testing'
__description__ = 'Depositfiles.com account plugin'
__license__ = 'GPLv3'
__authors__ = [('mkaay', ''), ('stickell', 'l.'), ('Walter Purcaro', '')]
def grab_i... |
def cross_validation(edge_embs, edge_labels):
(auc, mrr) = ([], [])
(seed_nodes, num_nodes) = (np.array(list(edge_embs.keys())), len(edge_embs))
skf = KFold(n_splits=5, shuffle=True, random_state=seed)
for (fold, (train_idx, test_idx)) in enumerate(skf.split(np.zeros((num_nodes, 1)), np.zeros(num_nodes)... |
class SpMatrix(_PackedMatrixBase, _sp_matrix.SpMatrix):
def __init__(self, num_rows=None, resize_type=_matrix_common.MatrixResizeType.SET_ZERO):
super(SpMatrix, self).__init__()
if (num_rows is not None):
if (isinstance(num_rows, int) and (num_rows >= 0)):
self.resize_(nu... |
def EfficientNetB0(include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000, **kwargs):
return EfficientNet(1.0, 1.0, 224, 0.2, model_name='efficientnet-b0', include_top=include_top, weights=weights, input_tensor=input_tensor, input_shape=input_shape, pooling=pooling, cl... |
def cast_waveunit(unit, force_match=True):
if (unit in WAVELEN_UNITS):
return 'nm'
if (unit in WAVELENVAC_UNITS):
return 'nm_vac'
elif (unit in WAVENUM_UNITS):
return 'cm-1'
elif force_match:
raise ValueError('Unknown wavespace unit: {0}. Should be one of {1}'.format(unit... |
class Effect744(BaseEffect):
type = 'passive'
def handler(fit, container, context, projectionRange, **kwargs):
level = (container.level if ('skill' in context) else 1)
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('CPU Management')), 'duration', (container.getModifiedItemAttr... |
def target():
options = ['A', 'B', 'C']
put_input('input', label='input')
put_textarea('textarea', label='textarea', rows=3, code=None, maxlength=10, minlength=20, value=None, placeholder='placeholder', readonly=False, help_text='help_text')
put_textarea('code', label='code', rows=4, code=True, maxlengt... |
class CmdLearnSpell(Command):
key = 'learnspell'
help_category = 'magic'
def func(self):
spell_list = sorted(SPELLS.keys())
args = self.args.lower()
args = args.strip(' ')
caller = self.caller
spell_to_learn = []
if ((not args) or (len(args) < 3)):
... |
(frozen=True)
class ReceiveWithdrawExpired(AuthenticatedSenderStateChange):
message_identifier: MessageID
canonical_identifier: CanonicalIdentifier
total_withdraw: WithdrawAmount
expiration: BlockExpiration
nonce: Nonce
participant: Address
def channel_identifier(self) -> ChannelID:
... |
def host_tuple(url: QUrl) -> HostTupleType:
ensure_valid(url)
(scheme, host, port) = (url.scheme(), url.host(), url.port())
assert scheme
if (not host):
raise ValueError('Got URL {} without host.'.format(url.toDisplayString()))
if (port == (- 1)):
port_mapping = {' 80, ' 443, 'ftp': ... |
def test_AddValueToZero_simple_weights():
dm = skcriteria.mkdm(matrix=[[1, 0, 3], [0, 5, 6]], objectives=[min, max, min], weights=[1, 2, 0])
expected = skcriteria.mkdm(matrix=[[1, 0, 3], [0, 5, 6]], objectives=[min, max, min], weights=[1.5, 2.5, 0.5])
scaler = AddValueToZero(value=0.5, target='weights')
... |
def main():
learning_rate = 0.001
parser = argparse.ArgumentParser('Self-Supervised')
parser.add_argument('--tau', type=float, default=1.0, metavar='LR')
parser.add_argument('--EPS', type=float, default=1e-05, help='episillon')
parser.add_argument('--weight-decay', type=float, default=1.5e-06, help=... |
class GasMeter(GasMeterAPI):
start_gas: int = None
gas_refunded: int = None
gas_remaining: int = None
logger = get_extended_debug_logger('eth.gas.GasMeter')
def __init__(self, start_gas: int, refund_strategy: RefundStrategy=default_refund_strategy) -> None:
validate_uint256(start_gas, title=... |
class ST_plus_TR_block_cross(nn.Module):
def __init__(self, config, embed_feat):
super(ST_plus_TR_block_cross, self).__init__()
self.embed_features = embed_feat
encoder_layer_actor = TransformerEncoderLayer_cluster(self.embed_features, config.Nhead, total_size=config.total_size, window_size=... |
class QlOsPosix(QlOs):
def __init__(self, ql: Qiling):
super().__init__(ql)
self.ql = ql
self.sigaction_act = ([0] * 256)
conf = self.profile['KERNEL']
self.uid = self.euid = conf.getint('uid')
self.gid = self.egid = conf.getint('gid')
self.pid = conf.getint('... |
def set_flat_params(model, flat_params, trainable=False):
prev_ind = 0
for param in model.parameters():
if (trainable and (not param.requires_grad)):
continue
flat_size = int(param.numel())
param.data.copy_(flat_params[prev_ind:(prev_ind + flat_size)].view(param.size()))
... |
class Effect6724(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Remote Armor Repair Systems')), 'duration', src.getModifiedItemAttr('eliteBonusLogistics3'), skill='Logistics Cruisers', **kwargs) |
def _orient(array, wcs):
if (array.ndim != 3):
raise ValueError('Input array must be 3-dimensional')
if (wcs.wcs.naxis != 3):
raise ValueError('Input WCS must be 3-dimensional')
wcs = wcs_utils.diagonal_wcs_to_cdelt(_fix_spectral(wcs))
axtypes = wcs.get_axis_types()[::(- 1)]
types = ... |
class Package(models.Model):
is_active = models.BooleanField(verbose_name=_('Is active'), default=True)
name = models.CharField(verbose_name=_('Name'), max_length=255)
description = models.TextField(verbose_name=_('Description'), blank=True)
link = models.URLField(verbose_name=_('URL'), max_length=255)
... |
_metaclass(abc.ABCMeta)
class BaseGraph(object):
def __init__(self, machine):
self.machine = machine
self.fsm_graph = None
self.generate()
def generate(self):
def set_previous_transition(self, src, dst):
def reset_styling(self):
def set_node_style(self, state, style):
def... |
class keep_wl():
def __init__(self, labels):
self.loss = torch.zeros(labels.shape[0], 1, dtype=torch.float).cuda(non_blocking=True)
self.weight = torch.zeros(labels.shape[0], dtype=torch.float).cuda(non_blocking=True)
def __call__(self, epoch_loss=None, epoch_weight=None, index=None):
se... |
def weight_pad(sim: QuantizationSimModel, layer_bw_dict: Dict[(str, WeightPaddingParams)]):
for (layer_name, layer) in sim.quant_wrappers():
bw_values = layer_bw_dict[layer_name]
param_quant_dict = layer.param_quantizers
if (('weight' in param_quant_dict) and (bw_values.target_kernel_bw > bw... |
class NodeLaunchActor():
def run(self, master_addr, master_port, node_rank, dist_world_size, args):
processes = []
current_env = os.environ.copy()
current_env['MASTER_ADDR'] = master_addr
current_env['MASTER_PORT'] = str(master_port)
current_env['WORLD_SIZE'] = str(dist_world... |
def test_submit_forms_by_get(app, client):
crawler = Crawler(client=client, initial_paths=['/'], rules=(PERMISSIVE_HYPERLINKS_ONLY_RULE_SET + SUBMIT_GET_FORMS_RULE_SET))
crawler.crawl()
submitted_forms = [form for form in crawler.graph.get_nodes_by_source(FORM) if form.requested]
assert (len(submitted_f... |
def handle_long_project_instruments_request(**kwargs) -> Any:
headers = kwargs['headers']
resp = [{'instrument_name': 'form_1', 'instrument_label': 'Form 1'}, {'instrument_name': 'form_2', 'instrument_label': 'Form 2'}, {'instrument_name': 'form_3', 'instrument_label': 'Form 3'}]
return (201, headers, json.... |
def test_run_tests_in_workers_error_traceback():
def target_fn():
def inner_2():
def inner_1():
raise ValueError('42')
inner_1()
inner_2()
try:
run_tests_in_workers(target=target_fn, num_workers=1)
except ValueError:
(exc_type, exc_valu... |
class ViewProviderAsmGroup(ViewProviderAsmBase):
def claimChildren(self):
return getattr(self.ViewObject.Object, 'Group', [])
def doubleClicked(self, _vobj):
return False
def canDropObject(self, _child):
return False
def canReplaceObject(self, _oldObj, newObj):
return (ne... |
def tankSection(fit):
ehp = ([fit.ehp[tank] for tank in tankTypes] if (fit.ehp is not None) else [0, 0, 0])
ehp.append(sum(ehp))
ehpStr = [formatAmount(ehpVal, 3, 0, 9) for ehpVal in ehp]
resists = {tankType: [(1 - fit.ship.getModifiedItemAttr(s)) for s in resonanceNames[tankType]] for tankType in tankT... |
class TestChangeOrganizationDetails(ApiTestCase):
def test_changeinvoiceemail(self):
self.login(ADMIN_ACCESS_USER)
json = self.putJsonResponse(Organization, params=dict(orgname=ORGANIZATION), data=dict(invoice_email=True))
self.assertEqual(True, json['invoice_email'])
json = self.put... |
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