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def define_G(model_opt):
from .sr3_modules import unet
if (('norm_groups' not in model_opt) or (model_opt['norm_groups'] is None)):
model_opt['norm_groups'] = 32
model = unet.UNet(in_channel=model_opt['in_channel'], out_channel=model_opt['out_channel'], norm_groups=model_opt['norm_groups'], inner_ch... |
class TPaneEntry(TestCase):
def test_all_have(self):
sel = SongsEntry('foo', 'foo', SONGS)
self.assertFalse(sel.all_have('artist', 'one'))
self.assertFalse(sel.all_have('~#mtime', 4))
self.assertTrue(sel.all_have('foo', 'bar'))
def test_all(self):
entry = AllEntry()
... |
class FeatureExtractionPipeline(Pipeline):
def _sanitize_parameters(self, truncation=None, **kwargs):
preprocess_params = {}
if (truncation is not None):
preprocess_params['truncation'] = truncation
return (preprocess_params, {}, {})
def preprocess(self, inputs, truncation=No... |
def get_template_files(template_name, project_name, **kwargs):
kwargs['project_name'] = project_name
kwargs['project_name_normalized'] = project_name.lower().replace('.', '-')
kwargs['package_name'] = kwargs['project_name_normalized'].replace('-', '_')
config = RootConfig({})
kwargs.setdefault('auth... |
class Solution(object):
def isIsomorphic(self, s, t):
if (len(s) != len(t)):
return False
ls = len(s)
mapStoT = ([0] * 127)
mapTtoS = ([0] * 127)
for i in range(ls):
(s_num, t_num) = (ord(s[i]), ord(t[i]))
if ((mapStoT[s_num] == 0) and (map... |
def test_conftest_symlink(pytester: Pytester) -> None:
real = pytester.mkdir('real')
realtests = real.joinpath('app/tests')
realtests.mkdir(parents=True)
symlink_or_skip(realtests, pytester.path.joinpath('symlinktests'))
symlink_or_skip(real, pytester.path.joinpath('symlink'))
pytester.makepyfil... |
def test_multitensor_offsetmap():
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
assert (mt.off_set_map == {'a':... |
class MultiloadCz(BaseDecrypter):
__name__ = 'MultiloadCz'
__type__ = 'decrypter'
__version__ = '0.46'
__status__ = 'testing'
__pattern__ = '
__config__ = [('enabled', 'bool', 'Activated', True), ('use_premium', 'bool', 'Use premium account if available', True), ('use_subfolder', 'bool', 'Save p... |
class ViewProviderAsmConstraint(ViewProviderAsmGroup):
def setupContextMenu(self, vobj, menu):
obj = vobj.Object
action = QtGui.QAction(QtGui.QIcon(), ('Enable constraint' if obj.Disabled else 'Disable constraint'), menu)
QtCore.QObject.connect(action, QtCore.SIGNAL('triggered()'), self.togg... |
class AttrVI_ATTR_4882_COMPLIANT(BooleanAttribute):
resources = [(constants.InterfaceType.usb, 'INSTR'), (constants.InterfaceType.vxi, 'INSTR')]
py_name = 'is_4882_compliant'
visa_name = 'VI_ATTR_4882_COMPLIANT'
visa_type = 'ViBoolean'
default = NotAvailable
(read, write, local) = (True, False, ... |
class PluginEnabledFilterCombo(Gtk.ComboBox):
def __init__(self):
combo_store = Gtk.ListStore(str, int)
super().__init__(model=combo_store)
cell = Gtk.CellRendererText()
cell.props.ellipsize = Pango.EllipsizeMode.END
self.pack_start(cell, True)
self.add_attribute(cell... |
class CTOCFlagsSpec(ByteSpec):
def read(self, header, frame, data):
(value, data) = ByteSpec.read(self, header, frame, data)
return (CTOCFlags(value), data)
def validate(self, frame, value):
value = ByteSpec.validate(self, frame, value)
if (value is not None):
return ... |
def test_transform_bounds_densify_out_of_bounds():
transformer = Transformer.from_crs('EPSG:4326', '+proj=laea +lat_0=45 +lon_0=-100 +x_0=0 +y_0=0 +a=6370997 +b=6370997 +units=m +no_defs', always_xy=True)
with pytest.raises(ProjError):
transformer.transform_bounds((- 120), 40, (- 80), 64, densify_pts=(-... |
class LRSchedulerStep(object):
def __init__(self, fai_optimizer: OptimWrapper, total_step, lr_phases, mom_phases):
self.optimizer = fai_optimizer
self.total_step = total_step
self.lr_phases = []
for (i, (start, lambda_func)) in enumerate(lr_phases):
if (len(self.lr_phases... |
class Condition(models.Model):
RELATION_EQUAL = 'eq'
RELATION_NOT_EQUAL = 'neq'
RELATION_CONTAINS = 'contains'
RELATION_GREATER_THAN = 'gt'
RELATION_GREATER_THAN_EQUAL = 'gte'
RELATION_LESSER_THAN = 'lt'
RELATION_LESSER_THAN_EQUAL = 'lte'
RELATION_EMPTY = 'empty'
RELATION_NOT_EMPTY =... |
class GroupPushRulesManager(GetWithoutIdMixin, CreateMixin, UpdateMixin, DeleteMixin, RESTManager):
_path = '/groups/{group_id}/push_rule'
_obj_cls = GroupPushRules
_from_parent_attrs = {'group_id': 'id'}
_create_attrs = RequiredOptional(optional=('deny_delete_tag', 'member_check', 'prevent_secrets', 'c... |
class OpVisitor(Generic[T]):
def visit_goto(self, op: Goto) -> T:
raise NotImplementedError
def visit_branch(self, op: Branch) -> T:
raise NotImplementedError
def visit_return(self, op: Return) -> T:
raise NotImplementedError
def visit_unreachable(self, op: Unreachable) -> T:
... |
class Block(nn.Module):
def __init__(self, channels):
super(Block, self).__init__()
self.conv1 = nn.Conv2d(channels, channels, 3, 1, 1, bias=False)
self.bn1 = nn.BatchNorm2d(channels)
self.prelu1 = nn.PReLU(channels)
self.conv2 = nn.Conv2d(channels, channels, 3, 1, 1, bias=Fa... |
def test_bng_printer():
assert (_bng_print(sympy.pi) == '_pi')
assert (_bng_print(sympy.E) == '_e')
(x, y) = sympy.symbols('x y')
assert (_bng_print(sympy.sympify('x & y')) == 'x && y')
assert (_bng_print(sympy.sympify('x | y')) == 'x || y')
assert (_bng_print(sympy.sin(x)) == 'sin(x)')
asse... |
(params=[_PROJECT_TASK, _PROJECT_TASK_NEW_INTERFACE])
def project(request, tmp_path):
tmp_path.joinpath('task_module.py').write_text(textwrap.dedent(request.param))
tmp_path.joinpath('in.txt').touch()
tmp_path.joinpath('to_be_deleted_file_1.txt').touch()
tmp_path.joinpath('to_be_deleted_folder_1').mkdir... |
class UploaderBase(object):
__metaclass__ = abc.ABCMeta
def __init__(self, bucket_name, **kwargs):
self.bucket_name = bucket_name
self.auth = kwargs.get('auth', None)
regions = kwargs.get('regions', [])
self.regions = regions
hosts_cache_dir = kwargs.get('hosts_cache_dir'... |
def get_train_dataloader(data_pth, max_seq_length, train_batch_size):
print('processing training data')
data = get_data(data_pth)
(features, vocab) = convert_example_to_feature(data, max_seq_length, None, sum_mode=args.sum_mode, context_mode=args.context_mode, get_vocab=True)
train_data = PGNDataset(fea... |
def process_squad_data(data, morphological_analyzer):
for article in data:
tokenized_title = morphological_analyzer.get_tokenized_string(article['title'])
for paragraph in article['paragraphs']:
title_context = paragraph['context']
(_, context) = title_context.split(' [SEP] '... |
class FakeTestCase(unittest.TestCase):
def runTest(self):
pass
def subTest(self, *args, **kwargs):
try:
self._subtest = unittest.case._SubTest(self, object(), {})
(yield)
finally:
self._subtest = None
def __call__(self, result):
pass |
def load_parent(**kwargs: Any) -> CompletedProcess:
frame = inspect.currentframe()
if (not frame):
raise Exception('workflow: load_parent() called from unknown frame')
caller_frame = frame.f_back
if (not caller_frame):
raise Exception('workflow: load_parent() called from unknown caller')... |
def generate_class_type_decl(cl: ClassIR, c_emitter: Emitter, external_emitter: Emitter, emitter: Emitter) -> None:
context = c_emitter.context
name = emitter.type_struct_name(cl)
context.declarations[name] = HeaderDeclaration(f'PyTypeObject *{emitter.type_struct_name(cl)};', needs_export=True)
if (not ... |
class TestLoadNetCDF2DPandas(TestLoadNetCDF):
def setup_method(self):
self.tempdir = tempfile.TemporaryDirectory()
self.saved_path = pysat.params['data_dirs']
pysat.params['data_dirs'] = self.tempdir.name
self.testInst = pysat.Instrument(platform='pysat', name='testing2d', update_fil... |
def check_other_isdataclass_overloads(x: type, y: object) -> None:
dc.fields(y)
dc.asdict(x)
dc.asdict(y)
dc.astuple(x)
dc.astuple(y)
dc.replace(x)
dc.replace(y)
if dc.is_dataclass(x):
assert_type(x, Type['DataclassInstance'])
assert_type(dc.fields(x), Tuple[(dc.Field[Any... |
def get_args_tuple(args, kwargs, arg_names, kwargs_defaults):
args_list = list(args)
args_len = len(args)
all_args_len = len(arg_names)
try:
while (args_len < all_args_len):
arg_name = arg_names[args_len]
if (arg_name in kwargs_defaults):
args_list.append(... |
def test_mlpg_gradcheck():
static_dim = 2
T = 10
for windows in _get_windows_set():
torch.manual_seed(1234)
means = torch.rand(T, (static_dim * len(windows)), requires_grad=True)
variances = torch.ones((static_dim * len(windows))).expand(T, (static_dim * len(windows)))
inputs... |
def handle_long_project_survey_participants_request(**kwargs) -> Any:
data = kwargs['data']
headers = kwargs['headers']
resp = None
if (('test' in data.get('instrument')) and ('raw' in data.get('event'))):
resp = [{'email': '', 'email_occurrence': 1, 'identifier': '', 'record': '', 'invitation_s... |
def test_class_interact():
parent = Parameter.create(name='parent', type='group')
interactor = Interactor(parent=parent, nest=False)
def outside_class_deco(func):
(func)
def wrapper(*args, **kwargs):
return func(*args, **kwargs)
return wrapper
class A():
def a... |
_optionals.HAS_PYSCF.require_in_instance
class PySCFDriver(ElectronicStructureDriver):
def __init__(self, atom: (str | list[str])='H 0.0 0.0 0.0; H 0.0 0.0 0.735', *, unit: DistanceUnit=DistanceUnit.ANGSTROM, charge: int=0, spin: int=0, basis: str='sto3g', method: MethodType=MethodType.RHF, xc_functional: str='lda,... |
class TestParameterValuesWithModel(TestCase):
def test_parameter_values_with_model(self):
param_to_model = {'Ai2020': pybamm.lithium_ion.DFN({'particle mechanics': 'swelling and cracking'}), 'Chen2020': pybamm.lithium_ion.DFN(), 'Chen2020_composite': pybamm.lithium_ion.DFN({'particle phases': ('2', '1'), 'o... |
def properties_of_geometric_objects():
Print_Function()
global n, nbar
g = (((('# # # 0 0,' + '# # # 0 0,') + '# # # 0 0,') + '0 0 0 0 2,') + '0 0 0 2 0')
c3d = Ga('p1 p2 p3 n nbar', g=g)
(p1, p2, p3, n, nbar) = c3d.mv()
print('g_{ij} =\n', c3d.g)
P1 = F(p1)
P2 = F(p2)
P3 = F(p3)
... |
def add_default_codecs():
try:
from pyglet.image.codecs import dds
registry.add_encoders(dds)
registry.add_decoders(dds)
except ImportError:
pass
if (compat_platform == 'darwin'):
try:
from pyglet.image.codecs import quartz
registry.add_encoder... |
def test_many2one_match_ic13():
det_id = 0
recall_mat = np.array([[1, 0], [0, 0]])
precision_mat = np.array([[1, 0], [0, 0]])
recall_thr = 0.5
precision_thr = 0.5
gt_match_flag = [0, 0]
det_match_flag = [0, 0]
gt_dont_care_index = []
with pytest.raises(AssertionError):
det_id... |
def get_resnext_cifar(num_classes, blocks, cardinality, bottleneck_width, model_name=None, pretrained=False, root=os.path.join('~', '.torch', 'models'), **kwargs):
assert (((blocks - 2) % 9) == 0)
layers = ([((blocks - 2) // 9)] * 3)
channels_per_layers = [256, 512, 1024]
init_block_channels = 64
ch... |
.parametrize('marker1, marker2, expected', [('python_version >= "3" and sys_platform == "win32"', 'python_version >= "3" and sys_platform != "win32" and sys_platform != "linux"', 'python_version >= "3" and sys_platform != "linux"'), ('python_version >= "3.8" and python_version < "4.0" and sys_platform == "win32"', 'pyt... |
def test_spa_python_numpy_physical_dst(expected_solpos, golden):
times = pd.date_range(datetime.datetime(2003, 10, 17, 13, 30, 30), periods=1, freq='D', tz=golden.tz)
ephem_data = solarposition.spa_python(times, golden.latitude, golden.longitude, pressure=82000, temperature=11, delta_t=67, atmos_refract=0.5667,... |
class DeepMimicEnv(Env):
def __init__(self, args, enable_draw):
super().__init__(args, enable_draw)
self._core = DeepMimicCore.cDeepMimicCore(enable_draw)
rand_seed = np.random.randint(np.iinfo(np.int32).max)
self._core.SeedRand(rand_seed)
self._core.ParseArgs(args)
s... |
class TDBase(rhf.TDBase):
_keys = {'cell'}
def __init__(self, mf):
rhf.TDBase.__init__(self, mf)
self.cell = mf.cell
def get_ab(self, mf=None):
raise NotImplementedError
def nuc_grad_method(self):
raise NotImplementedError
get_nto = rhf.TDBase.get_nto
analyze = li... |
def plot(t_plot, z_plot, t_slices, var_name, units, comsol_var_fun, dfn_var_fun, dfncc_var_fun, param, cmap='viridis'):
(fig, ax) = plt.subplots(2, 2, figsize=(13, 7))
fig.subplots_adjust(left=0.15, bottom=0.1, right=0.95, top=0.95, wspace=0.4, hspace=0.8)
comsol_var = comsol_var_fun(t=t_plot, z=z_plot)
... |
class TestLDIFParser(unittest.TestCase):
def _parse_records(self, ldif_string, ignored_attr_types=None, max_entries=0):
ldif_file = StringIO(ldif_string)
ldif_parser = ldif.LDIFRecordList(ldif_file, ignored_attr_types=ignored_attr_types, max_entries=max_entries)
parser_method = getattr(ldif_... |
def evaluation(myNet, test_loader, args):
myNet.eval()
num_correct = 0
num_total = 0
with torch.no_grad():
for (xs, ys) in test_loader:
if torch.cuda.is_available():
(xs, ys) = (xs.cuda(), ys.cuda())
ypreds = myNet(xs)
(_, preds) = torch.max(yp... |
def create_motion_model_widgets() -> dict[(str, tuple[(str, QtWidgets.QWidget)])]:
widgets = _create_sigma_widgets()
accuracy = QtWidgets.QDoubleSpinBox()
accuracy.setRange(0.1, 10)
accuracy.setStepType(QtWidgets.QAbstractSpinBox.AdaptiveDecimalStepType)
accuracy.setToolTip('Integration limits for c... |
class Ensemble(nn.Module):
def __init__(self, models, name=None):
super(Ensemble, self).__init__()
if (name is not None):
self.name = name
else:
self.name = ('%s_ensemble' % models[0].name)
self.models = nn.ModuleList(models)
def forward(self, x):
... |
def makeMetaChild(name, cfgDict):
children = []
for (chName, chOpts) in cfgDict.items():
if (not isinstance(chOpts, dict)):
ch = Parameter.create(name=chName, type=chName, value=chOpts)
else:
ch = Parameter.create(name=chName, **chOpts)
_encounteredTypes.add(ch.ty... |
class _march_rays(Function):
_fwd(cast_inputs=torch.float32)
def forward(ctx, n_alive, n_step, rays_alive, rays_t, rays_o, rays_d, bound, density_bitfield, C, H, near, far, align=(- 1), perturb=False, dt_gamma=0, max_steps=1024):
if (not rays_o.is_cuda):
rays_o = rays_o.cuda()
if (no... |
def _migrate_v17(preset: dict) -> dict:
if (preset['game'] == 'prime1'):
preset['configuration']['elevators']['excluded_teleporters'].append({'world_name': 'Impact Crater', 'area_name': 'Metroid Prime Lair', 'node_name': 'Teleporter to Credits'})
preset['configuration']['elevators']['excluded_telepo... |
class Keynote():
id: ID
title: str = strawberry.field(resolver=make_localized_resolver('title'))
description: str = strawberry.field(resolver=make_localized_resolver('description'))
slug: str = strawberry.field(resolver=make_localized_resolver('slug'))
topic: Optional[Topic]
speakers: List[Sched... |
def test_multiple_constraints_on_root(package: ProjectPackage, solver: Solver, repo: Repository) -> None:
package.add_dependency(Factory.create_dependency('foo', {'version': '^1.0', 'python': '^2.7'}))
package.add_dependency(Factory.create_dependency('foo', {'version': '^2.0', 'python': '^3.7'}))
foo15 = ge... |
class TestPyfakefsTestCase(unittest.TestCase):
def setUp(self):
class TestTestCase(fake_filesystem_unittest.TestCase):
def runTest(self):
pass
self.test_case = TestTestCase('runTest')
def test_test_case_type(self):
self.assertIsInstance(self.test_case, unittes... |
class Parameterized(object):
def __init__(self):
self._cached_params = {}
self._cached_param_dtypes = {}
self._cached_param_shapes = {}
self._cached_assign_ops = {}
self._cached_assign_placeholders = {}
def get_params_internal(self, **tags):
raise NotImplementedEr... |
class TestVersionSourceName():
def test_empty(self, isolation):
with pytest.raises(ValueError, match='The `source` option under the `tool.hatch.version` table must not be empty if defined'):
_ = HatchMetadata(isolation, {'version': {'source': ''}}, None).version.source_name
def test_not_tabl... |
class TrezorKeyStore(Hardware_KeyStore):
hw_type = 'trezor'
device = TREZOR_PRODUCT_KEY
plugin: 'TrezorPlugin'
def get_client(self, force_pair=True):
return self.plugin.get_client(self, force_pair)
def decrypt_message(self, sequence, message, password):
raise UserFacingException(_('E... |
_collator('multicrop_collator')
def multicrop_collator(batch):
assert ('data' in batch[0]), 'data not found in sample'
assert ('label' in batch[0]), 'label not found in sample'
data = [x['data'] for x in batch]
labels = [torch.tensor(x['label']) for x in batch]
data_valid = [torch.tensor(x['data_val... |
def test_convert_variable_mixed_specificity():
type1 = TensorType(config.floatX, shape=(1, None, 3))
type2 = TensorType(config.floatX, shape=(None, 5, 3))
type3 = TensorType(config.floatX, shape=(1, 5, 3))
test_var1 = type1()
test_var2 = type2()
assert (type1.convert_variable(test_var2).type == ... |
def all_gather(data):
world_size = get_world_size()
if (world_size == 1):
return [data]
buffer = pickle.dumps(data)
storage = torch.ByteStorage.from_buffer(buffer)
tensor = torch.ByteTensor(storage).to('cuda')
local_size = torch.tensor([tensor.numel()], device='cuda')
size_list = [to... |
class TestNodePosition():
def test_position_class() -> None:
code = textwrap.dedent("\n class A: #\n ...\n\n class B(A): #\n pass\n\n class C: #\n '''Docstring'''\n\n class D: #\n ...\n\n class E: #\n def ... |
()
def mocked_stream_df() -> Mock:
mock = Mock()
mock.isStreaming = True
mock.writeStream = mock
mock.trigger.return_value = mock
mock.outputMode.return_value = mock
mock.option.return_value = mock
mock.foreachBatch.return_value = mock
mock.start.return_value = Mock(spec=StreamingQuery)
... |
class CrossEntropyLIDLoss(_Loss):
def __init__(self, output_size, label_smoothing):
super().__init__()
self.output_size = output_size
self.padding_idx = (- 1)
self.smoothing_value = label_smoothing
self.confidence = (1.0 - label_smoothing)
self.label_smoothing = label... |
class ChamferLossMetric(TensorMetric):
def __init__(self, chamfer_loss_params, name: str, reduce_op: Optional[Any]=None):
super(ChamferLossMetric, self).__init__(name=name, reduce_op=reduce_op)
self.loss = ChamferLoss(**chamfer_loss_params)
def forward(self, pc_source: torch.Tensor, pc_target: t... |
def get_leaf_jaw_positions_for_type(beam_limiting_device_position_sequences, rt_beam_limiting_device_type):
leaf_jaw_positions = []
for sequence in beam_limiting_device_position_sequences:
matching_type = [item for item in sequence if (item.RTBeamLimitingDeviceType == rt_beam_limiting_device_type)]
... |
def test_show_nested_fixtures(pytester: Pytester, mode) -> None:
pytester.makeconftest('\n import pytest\n (scope=\'session\')\n def arg_same():\n """session scoped fixture"""\n ')
p = pytester.makepyfile('\n import pytest\n (scope=\'function\')\n def ... |
def main(args):
modelpath = (args.loadDir + args.loadModel)
weightspath = (args.loadDir + args.loadWeights)
print(('Loading model: ' + modelpath))
print(('Loading weights: ' + weightspath))
model = Net(NUM_CLASSES)
model = torch.nn.DataParallel(model)
if (not args.cpu):
model = model... |
class COCOClsDatasetMS(Dataset):
def __init__(self, img_name_list_path, coco_root, label_file_path, scales, train=True, transform=None, gen_attn=False, unit=1):
img_name_list_path = os.path.join(img_name_list_path, f"{('train' if (train or gen_attn) else 'val')}_id.txt")
self.img_name_list = load_im... |
class PartialFC(torch.nn.Module):
_version = 1
def __init__(self, margin_loss: Callable, embedding_size: int, num_classes: int, sample_rate: float=1.0, fp16: bool=False):
super(PartialFC, self).__init__()
assert distributed.is_initialized(), 'must initialize distributed before create this'
... |
class MetaRLScreener_pro(torch.nn.Module):
def __init__(self, model, epochs=100, lr=0.01, log=True):
super(MetaRLScreener_pro, self).__init__()
self.model = model
self.model.to(device)
self.epochs = epochs
self.lr = lr
self.log = log
self.temperature = 0.5
... |
class ZoneUpdateHandler(threading.Thread):
def __init__(self, queue, handler):
super(ZoneUpdateHandler, self).__init__()
self.event = threading.Event()
self.lock = threading.Lock()
self.zones_to_update = set()
self.zones_queues = Queue()
self.queue_name = queue
... |
def test_losses_models_ext_def(pvwatts_dc_pvwatts_ac_system, location, weather, mocker):
m = mocker.spy(sys.modules[__name__], 'constant_losses')
mc = ModelChain(pvwatts_dc_pvwatts_ac_system, location, dc_model='pvwatts', aoi_model='no_loss', spectral_model='no_loss', losses_model=constant_losses)
mc.run_mo... |
def test_mismatch_private_key():
(public_key_data, _) = generate_test_cert()
(_, private_key_data) = generate_test_cert()
private_key = NamedTemporaryFile(delete=True)
private_key.write(private_key_data)
private_key.seek(0)
cert = load_certificate(public_key_data)
with pytest.raises(KeyInval... |
def retrieve_cdn_ip_networks(retrieve_new_data=False):
cdn_ip_networks = []
cloudfront_dict = retrieve_amazon_cloudfront_ip_ranges(retrieve_new_data)
cdn_ip_networks += cloudfront_dict['list_of_ipaddress_objects']
cloudflare_dict = retrieve_cloudflare_ip_networks(retrieve_new_data)
cdn_ip_networks +... |
class DKKKU2(FinTS3Segment):
account = DataElementGroupField(type=Account2, _d='Kontoverbindung Auftraggeber')
credit_card_number = DataElementField(type='an', _d='Kreditkartennummer')
subaccount = DataElementField(type='an', required=False, _d='Subaccount?')
date_start = DataElementField(type='dat', re... |
def test_format_variety():
def _(fmt, matches):
d = parse.extract_format(fmt, {'spam': 'spam'})
for k in matches:
assert (d.get(k) == matches[k])
for t in '%obxegfdDwWsS':
_(t, {'type': t})
_(('10' + t), {'type': t, 'width': '10'})
_('05d', {'type': 'd', 'width': ... |
def project_onto_sector(operator, qubits, sectors):
if (not isinstance(operator, QubitOperator)):
raise TypeError('Input operator must be a QubitOperator.')
if (not isinstance(qubits, (list, numpy.ndarray))):
raise TypeError('Qubit input must be an array-like.')
if (not isinstance(sectors, (... |
def test_get_observation_histogram(requests_mock):
requests_mock.get(f'{API_V1}/observations/histogram', json=SAMPLE_DATA['get_observation_histogram_month'], status_code=200)
histogram = get_observation_histogram(interval='month', place_id=24, d1='2020-01-01', d2='2020-12-31')
assert (len(histogram) == 12)
... |
class TestOptimizerStateShardingIntegration(unittest.TestCase, TestOptimizer):
def _maybe_destro_dist():
if dist.is_initialized():
logging.debug('Destroy previous torch dist process group')
dist.destroy_process_group()
def setUp(self):
self._maybe_destro_dist()
di... |
def test_colorinterp_like_all(runner, path_4band_no_colorinterp, path_rgba_byte_tif, tmpdir):
noci = str(tmpdir.join('test_colorinterp_like_all.tif'))
rasterio.shutil.copy(path_4band_no_colorinterp, noci)
result = runner.invoke(main_group, ['edit-info', noci, '--like', path_rgba_byte_tif, '--all'])
asse... |
class Train_config():
world_size = 0
mini_batch_size = 0
iter_per_epoch = 0
total_epoch = 0
warm_iter = 0
learning_rate = 0
momentum = 0
weight_decay = 0
lr_decay = []
log_dump_interval = 0
resume_weights = None
init_weights = None
model_dir = ''
log_path = '' |
def _populate():
for name in ('allowed_functions', 'bytecode_analysis', 'bytecode_transformation', 'codegen', 'config', 'convert_frame', 'debug_utils', 'eval_frame', 'exc', 'guards', 'logging', 'mutation_guard', 'optimizations', 'output_graph', 'profiler', 'replay_record', 'resume_execution', 'side_effects', 'skipf... |
class Snapshot(Model):
objects = SnapshotManager()
project = models.ForeignKey('Project', related_name='snapshots', on_delete=models.CASCADE, null=True, verbose_name=_('Project'), help_text=_('The project this snapshot belongs to.'))
title = models.CharField(max_length=256, verbose_name=_('Title'), help_tex... |
def loadUtilitySpectra():
global am_zero_wavelength, am_zero_irradiance, waterspectra, ozonespectra, uniformgasspectra
spctra = numpy.loadtxt(os.path.join(this_dir, 'SPCTRAL_si_units.txt'), unpack=True)
(am_zero_wavelength, am_zero_irradiance, waterspectra, ozonespectra, uniformgasspectra) = spctra
wate... |
class LoginForm(Form):
def __init__(self, view):
super().__init__(view, 'login')
self.use_layout(FormLayout())
accounts = AccountManagementInterface.for_current_session()
if self.exception:
self.layout.add_alert_for_domain_exception(self.exception)
self.layout.add... |
def main():
opts = parse_args()
if ((not opts.overwrite) and isfile(opts.out_path)):
return
mkdir2(dirname(opts.out_path))
time_info = pickle.load(open(opts.time_info, 'rb'))
if (opts.method_type == 'det'):
rt_samples = time_info['runtime_all']
rt_dist = {'type': 'empirical',... |
class Element(BaseElement):
def children(self):
return [self.__class__(el) for el in self._js.children]
def append(self, child):
if isinstance(child, JsProxy):
return self.append(Element(child))
elif isinstance(child, Element):
self._js.appendChild(child._js)
... |
class FusedAdamV1(torch.optim.Optimizer):
def __init__(self, params, lr=0.001, bias_correction=True, betas=(0.9, 0.999), eps=1e-08, eps_inside_sqrt=False, weight_decay=0.0, max_grad_norm=0.0, amsgrad=False):
global fused_adam_cuda
import importlib
fused_adam_cuda = importlib.import_module('f... |
def convert(comp_type: str, src_file: Path, dest_dir: Path):
dest_dir = Path(dest_dir)
dest_dir.mkdir(exist_ok=True)
dpr_state = DPRState.from_type(comp_type, src_file=src_file)
model = dpr_state.load_dpr_model()
model.save_pretrained(dest_dir)
model.from_pretrained(dest_dir) |
class TestExitCode(unittest.TestCase):
def setUp(self):
sys.path.append('.')
from mprof import run_action
self.run_action = run_action
def test_exit_code_success(self):
s = '1+1'
tmpfile = tempfile.NamedTemporaryFile('w', suffix='.py')
with tmpfile as ofile:
... |
def decode_onion_error(error_packet: bytes, payment_path_pubkeys: Sequence[bytes], session_key: bytes) -> (OnionRoutingFailureMessage, int):
(decrypted_error, sender_index) = _decode_onion_error(error_packet, payment_path_pubkeys, session_key)
failure_msg = get_failure_msg_from_onion_error(decrypted_error)
... |
def handle_style(book, data):
if (not book.formatting_info):
return
blah = (DEBUG or (book.verbosity >= 2))
bv = book.biff_version
(flag_and_xfx, built_in_id, level) = unpack('<HBB', data[:4])
xf_index = (flag_and_xfx & 4095)
if ((data == b'\x00\x00\x00\x00') and ('Normal' not in book.st... |
class TestCDPSession(BaseTestCase):
async def test_create_session(self):
client = (await self.page.target.createCDPSession())
(await client.send('Runtime.enable'))
(await client.send('Runtime.evaluate', {'expression': 'window.foo = "bar"'}))
foo = (await self.page.evaluate('window.fo... |
(st.sets(text))
def test_map(tmpdir_factory, keys):
trie = marisa_trie.Trie(keys)
dirname = f'{str(uuid4())}_'
path = str(tmpdir_factory.mktemp(dirname).join('trie.bin'))
trie.save(path)
data = open(path, 'rb').read()
trie2 = marisa_trie.Trie()
trie2.map(data)
for key in keys:
as... |
class MedrxivClusteringP2P(AbsTaskClustering):
def description(self):
return {'name': 'MedrxivClusteringP2P', 'hf_hub_name': 'mteb/medrxiv-clustering-p2p', 'description': 'Clustering of titles+abstract from medrxiv. Clustering of 10 sets, based on the main category.', 'reference': ' 'type': 'Clustering', 'c... |
def test_in_solver():
opt = {'method': 'adams', 'store_states': True, 'atol': 1}
solver = qutip.SESolver(qutip.qeye(1), options=opt)
adams = qutip.integrator.IntegratorScipyAdams
lsoda = qutip.integrator.IntegratorScipylsoda
bdf = qutip.integrator.IntegratorScipyBDF
assert (solver.options['store... |
def test_rebuild_system_tpm(s):
node0_tpm = ExplicitTPM(np.array([[0, 1], [0, 0]]))
node1_tpm = ExplicitTPM(np.array([[0, 1]]))
node_tpms = [node0_tpm, node1_tpm]
answer = ExplicitTPM(np.array([[[0, 0], [1, 1]], [[0, 0], [0, 1]]]))
assert macro.rebuild_system_tpm(node_tpms).array_equal(answer)
n... |
class Optimizer(object):
def __init__(self, optimizer, learning_rate, learning_rate_decay_fn=None, max_grad_norm=None):
self._optimizer = optimizer
self._learning_rate = learning_rate
self._learning_rate_decay_fn = learning_rate_decay_fn
self._max_grad_norm = (max_grad_norm or 0)
... |
def get_valid_dataloader(musdb_root, is_wav, filed_mode, n_fft, hop_length, num_frame, batch_size=4, num_workers=1, pin_memory=True, target_names=None, cache_mode=True, dev_mode=False) -> DataLoader:
if filed_mode:
musdb_valid = FiledMusdbValidSet(musdb_root, is_wav, n_fft=n_fft, hop_length=hop_length, num_... |
class MockReadline():
def __init__(self):
self.l_buffer = lineobj.ReadLineTextBuffer('')
self._history = history.LineHistory()
def add_history(self, line):
self._history.add_history(lineobj.TextLine(line))
def _print_prompt(self):
pass
def _bell(self):
pass
de... |
class TestGenericReporting():
def test_collect_fail(self, pytester: Pytester, option) -> None:
pytester.makepyfile('import xyz\n')
result = pytester.runpytest(*option.args)
result.stdout.fnmatch_lines(['ImportError while importing*', '*No module named *xyz*', '*1 error*'])
def test_maxfa... |
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