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class RegNetEncoder(nn.Module):
def __init__(self, config: RegNetConfig):
super().__init__()
self.stages = nn.ModuleList([])
self.stages.append(RegNetStage(config, config.embedding_size, config.hidden_sizes[0], stride=(2 if config.downsample_in_first_stage else 1), depth=config.depths[0]))
... |
class AugAssign(_base_nodes.AssignTypeNode, _base_nodes.OperatorNode, _base_nodes.Statement):
_astroid_fields = ('target', 'value')
_other_fields = ('op',)
target: ((Name | Attribute) | Subscript)
value: NodeNG
def __init__(self, op: str, lineno: int, col_offset: int, parent: NodeNG, *, end_lineno: ... |
def test_update_none_param(tmpfolder):
invalid = ' [metadata]\n [pyscaffold]\n version = 4\n '
Path(tmpfolder, 'setup.cfg').write_text(dedent(invalid))
extensions = [Object(name='x_foo_bar_x', persist=True)]
(_, opts) = actions.get_default_options({}, {'extensions': extensions})
opts['x_... |
def deploy_one_to_n(user_deposit_deploy_result: Callable[([], UserDeposit)], service_registry_deploy_result: Callable[([], ServiceRegistry)], deploy_client: JSONRPCClient, contract_manager: ContractManager, proxy_manager: ProxyManager, chain_id: ChainID) -> OneToN:
user_deposit_proxy = user_deposit_deploy_result()
... |
class Effect91(BaseEffect):
type = 'passive'
def handler(fit, module, context, projectionRange, **kwargs):
fit.modules.filteredItemMultiply((lambda mod: (mod.item.group.name == 'Energy Weapon')), 'damageMultiplier', module.getModifiedItemAttr('damageMultiplier'), stackingPenalties=True, **kwargs) |
class GhauriExtractor():
def __init__(self, vectors='', is_string=False, skip_urlencoding=False, filepaths=None):
self.vectors = vectors
self.is_string = is_string
self.skip_urlencoding = skip_urlencoding
self.filepaths = filepaths
def _check_operator(self, url, data, vector, par... |
def render_pdffile_topil(multipage_doc):
renderer = multipage_doc.render(pdfium.PdfBitmap.to_pil, scale=0.5)
imgs = []
for image in renderer:
assert isinstance(image, PIL.Image.Image)
assert (image.mode == 'RGB')
imgs.append(image)
assert (len(imgs) == 3)
(yield imgs) |
class LinksnappyCom(MultiAccount):
__name__ = 'LinksnappyCom'
__type__ = 'account'
__version__ = '0.22'
__status__ = 'testing'
__config__ = [('mh_mode', 'all;listed;unlisted', 'Filter downloaders to use', 'all'), ('mh_list', 'str', 'Downloader list (comma separated)', ''), ('mh_interval', 'int', 'Re... |
def setUpModule():
global mol, m, h1e, g2e, ci0, cis
global norb, nelec, orbsym
mol = gto.Mole()
mol.verbose = 0
mol.atom = '\n O 0. 0. 0.\n H 0. -0.757 0.587\n H 0. 0.757 0.587'
mol.basis = 'sto-3g'
mol.symmetry = 'c2v'
mol.build()
m = scf.RH... |
class FilerNetFolder(SimpleDecrypter):
__name__ = 'FilerNetFolder'
__type__ = 'decrypter'
__version__ = '0.48'
__status__ = 'testing'
__pattern__ = '
__config__ = [('enabled', 'bool', 'Activated', True), ('use_premium', 'bool', 'Use premium account if available', True), ('folder_per_package', 'D... |
def test_wr_As_wr_A_conflict():
class Top(ComponentLevel3):
def construct(s):
s.A = Wire(Bits32)
def up_wr_As():
s.A[1:3] = Bits2(2)
def up_wr_A():
s.A = Bits32(123)
try:
_test_model(Top)
except MultiWriterError as e:
... |
class GPTNeoXConfig(PretrainedConfig):
model_type = 'gpt_neox'
def __init__(self, vocab_size=50432, hidden_size=6144, num_hidden_layers=44, num_attention_heads=64, intermediate_size=24576, hidden_act='gelu', rotary_pct=0.25, rotary_emb_base=10000, max_position_embeddings=2048, initializer_range=0.02, layer_norm... |
class Groups(object):
def init_groups(self):
layout = Layouts()
return [Group('SYS', layouts=[layout.max(), layout.two_stackWide(), layout.two_stackTall()]), Group('CLI', layouts=[layout.two_stackTall(), layout.monadTall(), layout.ten_monadWide()], matches=[Match(title=['Irssi', 'Mpsyt'])]), Group('... |
def create_bottom_up_layers(input_mlp_out: Tensor, num_layers: int, base_num_filters: int, max_num_filters: int, bottom_up_stack: BottomUpStackInterface) -> List[BottomUpLayer]:
bottom_up_layers = []
num_filters_out = min(max_num_filters, base_num_filters)
x = bottom_up_stack.convolve(input_mlp_out, num_fil... |
def main():
parser = argparse.ArgumentParser(description='Train Blending GAN')
parser.add_argument('--nef', type=int, default=64, help='# of base filters in encoder')
parser.add_argument('--ngf', type=int, default=64, help='# of base filters in decoder')
parser.add_argument('--nc', type=int, default=3, ... |
def test_compare_DA_pn():
from solcore import material, si
from solcore.structure import Junction, Layer
from solcore.solar_cell_solver import solar_cell_solver, SolarCell
from solcore.analytic_solar_cells import iv_depletion
from solcore.sesame_drift_diffusion.solve_pdd import iv_sesame
from so... |
def compute_cost(num_spin_orbs: int, lambda_tot: float, num_sym_unique: int, kmesh: list[int], dE_for_qpe: float=0.0016, chi: int=10) -> ResourceEstimates:
init_cost = _compute_cost(num_spin_orbs, lambda_tot, num_sym_unique, dE_for_qpe, chi, 20000, *kmesh)
steps = init_cost[0]
final_cost = _compute_cost(num... |
def test_none_crown_at_list_crown(debug_ctx, debug_trail, acc_schema):
dumper_getter = make_dumper_getter(shape=shape(TestField('a', acc_schema.accessor_maker('a', True))), name_layout=OutputNameLayout(crown=OutListCrown([OutNoneCrown(placeholder=DefaultValue(None)), OutNoneCrown(placeholder=DefaultValue(SomeClass(... |
def postprocess_args(args):
ROOTDIR = args.root_dir
ft_file_map = {'vitbase': 'pth_vit_base_patch16_224_imagenet.hdf5', 'vitbase_r2rfte2e': 'pth_vit_base_patch16_224_imagenet_r2r.e2e.ft.22k.hdf5', 'vitbase_clip': 'pth_vit_base_patch32_224_clip.hdf5', 'clip16': 'CLIP-ViT-B-16-views.tsv'}
args.img_ft_file = o... |
def l2_lgr_schema(settings=None):
settings = (settings or {})
ngrps = settings.get('num_groups', 120)
return {'providers': settings.get('providers', {}), 'variable_path': settings.get('variable_path', ''), 'dimensions': {'groups': ngrps}, 'variables': {'latitude': {'format': 'f4', 'shape': ('groups',), 'lon... |
def read_emc(root_path):
emc = {}
if os.path.isdir((root_path + '/debug/bpmp/debug/clk/emc')):
path = (root_path + '/debug/bpmp/debug/clk/emc')
if os.access((path + '/rate'), os.R_OK):
with open((path + '/rate'), 'r') as f:
emc['cur'] = (int(f.read()) // 1000)
... |
_config
def test_select_group(manager):
group = manager.c.group
assert (group.layout.info()['group'] == 'a')
assert (len(group.layout.info()['stacks']) == 1)
assert (len(group.layout[2].info()['stacks']) == 3)
with pytest.raises(CommandError):
manager.c.group.window.info()
manager.test_w... |
class Migration(migrations.Migration):
dependencies = [('accounts', '0002_move_defaults')]
operations = [migrations.CreateModel(name='DefaultAccount', fields=[], options={'proxy': True}, bases=('accounts.accountdb',)), migrations.CreateModel(name='DefaultGuest', fields=[], options={'proxy': True}, bases=('accou... |
def testActiveComps(run_cli, backends):
bz = _open_bz(REDHAT_URL, **backends)
out = run_cli("bugzilla info --components 'Virtualization Tools' --active-components", bz)
assert ('virtinst' not in out)
out = run_cli("bugzilla info --component_owners 'Virtualization Tools' --active-components", bz)
ass... |
def gen_seq_masks(seq_lens, max_len=None):
if (max_len is None):
max_len = max(seq_lens)
batch_size = len(seq_lens)
device = seq_lens.device
masks = torch.arange(max_len).unsqueeze(0).repeat(batch_size, 1).to(device)
masks = (masks < seq_lens.unsqueeze(1))
return masks |
class Wav2Vec2PhonemeCTCTokenizer(PreTrainedTokenizer):
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
model_input_names = ['input_ids', 'attention_mask']
def __init__(self, vocab_file, bos_... |
.parametrize('v', [set_test_value(ps.float64(), np.array(1.0, dtype='float64'))])
def test_TensorFromScalar(v):
g = ptb.TensorFromScalar()(v)
g_fg = FunctionGraph(outputs=[g])
compare_numba_and_py(g_fg, [i.tag.test_value for i in g_fg.inputs if (not isinstance(i, (SharedVariable, Constant)))]) |
class BehavioralRTLIRGeneratorL3(BehavioralRTLIRGeneratorL2):
def visit_Call(s, node):
obj = s.get_call_obj(node)
if is_bitstruct_class(obj):
fields = obj.__bitstruct_fields__
nargs = len(node.args)
nfields = len(fields.keys())
if (nargs == 0):
... |
def discriminator_loss_func(real_pred, fake_pred, real_pred_edge, fake_pred_edge, edge):
criterion = nn.BCELoss()
real_target = torch.tensor(1.0).expand_as(real_pred)
fake_target = torch.tensor(0.0).expand_as(fake_pred)
if torch.cuda.is_available():
real_target = real_target.cuda()
fake_... |
def _gen_docx_contract(output, contract, **context):
context = _contract_context(contract, **context)
renewal = context['renewal']
if renewal:
template = os.path.join(settings.TEMPLATES_DIR, 'sponsors', 'admin', 'renewal-contract-template.docx')
else:
template = os.path.join(settings.TEM... |
def _afd_helper_handle() -> Handle:
rawname = ('\\\\.\\GLOBALROOT\\Device\\Afd\\Trio'.encode('utf-16le') + b'\x00\x00')
rawname_buf = ffi.from_buffer(rawname)
handle = kernel32.CreateFileW(ffi.cast('LPCWSTR', rawname_buf), FileFlags.SYNCHRONIZE, (FileFlags.FILE_SHARE_READ | FileFlags.FILE_SHARE_WRITE), ffi.... |
def print_commands(prefix: str, obj: CommandClient) -> None:
prefix += ' -f '
cmds = obj.call('commands')
output = []
for cmd in cmds:
doc_args = get_formated_info(obj, cmd)
pcmd = (prefix + cmd)
output.append([pcmd, doc_args])
max_cmd = max((len(pcmd) for (pcmd, _) in output... |
class CoordConv(nn.Module):
def __init__(self, input_nc, output_nc, with_r=False, use_spect=False, **kwargs):
super(CoordConv, self).__init__()
self.addcoords = AddCoords(with_r=with_r)
input_nc = (input_nc + 2)
if with_r:
input_nc = (input_nc + 1)
self.conv = spe... |
def compressed_all_to_all(output, input, group=None):
world_size = dist.get_world_size(group)
rank = torch.distributed.get_rank(group)
ts_in = torch.tensor_split(input, world_size)
(compressed_a2a_input, _) = dg_compress(ts_in)
ts_out = torch.tensor_split(output, world_size)
for i in range(world... |
class ClusterNet5gTrunk(ResNetTrunk):
def __init__(self, config):
super(ClusterNet5gTrunk, self).__init__()
self.batchnorm_track = config.batchnorm_track
block = BasicBlock
layers = [3, 4, 6, 3]
in_channels = config.in_channels
self.inplanes = 64
self.conv1 = ... |
class NormalResnetBackbone(nn.Module):
def __init__(self, orig_resnet):
super(NormalResnetBackbone, self).__init__()
self.num_features = 2048
self.prefix = orig_resnet.prefix
self.maxpool = orig_resnet.maxpool
self.layer1 = orig_resnet.layer1
self.layer2 = orig_resnet... |
class Files(object):
def __init__(self, inst, data_dir=None, directory_format=None, update_files=False, file_format=None, write_to_disk=True, ignore_empty_files=False):
self.update_files = update_files
self.home_path = os.path.join(pysat.pysat_dir, 'instruments')
self.start_date = None
... |
def normalize_intersec(i, j, h, w, intersec):
box_num = (len(intersec) // 4)
for x in range(box_num):
intersec[(0 + (4 * x))] = ((intersec[(0 + (4 * x))] - j) / w)
intersec[(2 + (4 * x))] = ((intersec[(2 + (4 * x))] - j) / w)
intersec[(1 + (4 * x))] = ((intersec[(1 + (4 * x))] - i) / h)
... |
class F28_Authconfig(FC3_Authconfig):
removedKeywords = FC3_Authconfig.removedKeywords
removedAttrs = FC3_Authconfig.removedAttrs
def parse(self, args):
warnings.warn('The authconfig command will be deprecated, use authselect instead.', KickstartDeprecationWarning)
return super(F28_Authconfi... |
class Effect11432(BaseEffect):
type = 'passive'
def handler(fit, ship, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Repair Systems')), 'armorDamageAmount', ship.getModifiedItemAttr('eliteBonusGunship2'), skill='Assault Frigates', **kwargs) |
def test_player_play_multiple(player):
sources = (SilentTestSource(0.1), SilentTestSource(0.1))
for source in sources:
player.queue(source)
player.play()
player.wait_for_all_events(1.0, 'on_eos', 'on_player_next_source', 'on_eos', 'on_player_eos')
for source in sources:
assert (sourc... |
class P2PModel(nn.Module):
def __init__(self, batch_size=100, channels=1, g_dim=128, z_dim=10, rnn_size=256, prior_rnn_layers=1, posterior_rnn_layers=1, predictor_rnn_layers=2, opt=None):
super().__init__()
self.batch_size = batch_size
self.channels = channels
self.g_dim = g_dim
... |
class Link():
__slots__ = ('prev', 'next', 'key', '__weakref__')
def __getstate__(self):
ret = [self.prev(), self.next()]
try:
ret.append(self.key)
except AttributeError:
pass
return ret
def __setstate__(self, state):
self.prev = weakref.ref(st... |
def test_setting_logging():
apply_patch_if_needed_and_test_it()
args = Args(logging_verbose=False, logging_debug=False)
run_logging_basic_config(args, {'level': logging.DEBUG})
assert (logging.root.getEffectiveLevel() == logging.DEBUG)
run_logging_basic_config(args, {'level': 'error'})
assert (l... |
class HostedGraphiteHandler(Handler):
def __init__(self, config=None):
Handler.__init__(self, config)
self.key = self.config['apikey'].lower().strip()
self.graphite = GraphiteHandler(self.config)
def get_default_config_help(self):
config = super(HostedGraphiteHandler, self).get_d... |
class AmpCalFitter(BaseGateFitter):
def __init__(self, backend_result, xdata, qubits, fit_p0, fit_bounds):
circuit_names = []
for (cind, _) in enumerate(xdata):
circuit_names.append(('ampcal1Qcircuit_%d_' % cind))
BaseGateFitter.__init__(self, '$AmpCal1Q$', backend_result, xdata,... |
def test_update_optionset_error(db):
optionset = OptionSet.objects.first()
optionset.locked = True
optionset.save()
option = Option.objects.exclude(optionsets=optionset).first()
with pytest.raises(ValidationError):
OptionLockedValidator(option)({'optionsets': [optionset], 'locked': False}) |
class ChatMemberUpdated(Object, Update):
def __init__(self, *, client: 'pyrogram.Client'=None, chat: 'types.Chat', from_user: 'types.User', date: datetime, old_chat_member: 'types.ChatMember', new_chat_member: 'types.ChatMember', invite_link: 'types.ChatInviteLink'=None):
super().__init__(client)
se... |
class Temporal(object):
format_sandbox_id = staticmethod('sandbox{0}_{1}'.format)
cluster_dirname = staticmethod('pg_tmp_{0}_{1}'.format)
cluster = None
_init_pid_ = None
_local_id_ = 0
builtins_keys = {'connector', 'db', 'do', 'xact', 'proc', 'settings', 'prepare', 'sqlexec', 'newdb'}
def _... |
def test_setitem(stream):
df = pd.DataFrame({'x': list(range(10)), 'y': ([1] * 10)})
sdf = DataFrame(example=df.iloc[:0], stream=stream)
stream = sdf.stream
sdf['z'] = (sdf['x'] * 2)
sdf['a'] = 10
sdf[['c', 'd']] = sdf[['x', 'y']]
L = sdf.mean().stream.gather().sink_to_list()
stream.emit... |
_benchmark.command(name='analyze')
_option
_range_option
('--datetime', '-d', 'datetime_range', help="Filter execution progress plot to contain data within the specified datetime range, e.g '2021-11-16T10:00:00-2021-11-16T11:00:00'", type=str, callback=(lambda c, p, v: _to_datetime_range(v)))
('--title', '-t', help='Ti... |
_if_fails
def test_parameter_generators(n_evaluations=100):
for generator_type in [RandomParameterOptimizer, RegressionParameterOptimizer, SubgridParameterOptimizer, AnnealingParameterOptimizer]:
for maximize in [True, False]:
(yield (check_optimizer, generator_type, maximize, n_evaluations)) |
('pypyr.moduleloader.get_module')
(Step, 'invoke_step')
def test_run_pipeline_steps_complex_swallow_false(mock_invoke_step, mock_get_module):
step = Step({'name': 'step1', 'swallow': False})
context = get_test_context()
original_len = len(context)
with patch_logger('pypyr.dsl', logging.DEBUG) as mock_lo... |
def configureLogging():
logformatNoColor = '%(levelname)-3s -: %(message)s'
level = logging.WARNING
formatter = logging.Formatter(logformatNoColor, datefmt=None)
stream = logging.StreamHandler()
stream.setFormatter(formatter)
root = logging.getLogger()
root.setLevel(level)
root.addHandle... |
def sharp_expr(extr, expr):
try:
expr = extr.expand(expr)
expr = re.sub('(?<![!<>])=', '==', expr)
expr = re.sub('mod', '%', expr)
expr = re.sub('\x08div\x08', '/', expr)
expr = re.sub('\x08round\x08', '|ROUND|', expr)
return text_type(eval(expr))
except:
... |
class ScheduleItemAttendee(TimeStampedModel):
schedule_item = models.ForeignKey(ScheduleItem, on_delete=models.CASCADE, verbose_name=_('schedule item'), related_name='attendees')
user = models.ForeignKey('users.User', on_delete=models.CASCADE, null=False, blank=False, verbose_name=_('user'), related_name='+')
... |
def make_mating_pool(population_mol: List[Mol], population_scores, offspring_size: int):
sum_scores = sum(population_scores)
population_probs = [(p / sum_scores) for p in population_scores]
mating_pool = np.random.choice(population_mol, p=population_probs, size=offspring_size, replace=True)
return matin... |
class ProbabilisticFlightBackend(AdvertisingEnabledBackend):
def select_flight(self):
flights = self.get_candidate_flights()
paid_flights = []
affiliate_flights = []
community_flights = []
publisher_house_flights = []
house_flights = []
for flight in flights:
... |
def add_bb_into_image(image, bb, color=(255, 0, 0), thickness=2, label=None):
r = int(color[0])
g = int(color[1])
b = int(color[2])
font = cv2.FONT_HERSHEY_SIMPLEX
fontScale = 0.5
fontThickness = 1
(x1, y1, x2, y2) = bb.getAbsoluteBoundingBox(BBFormat.XYX2Y2)
x1 = int(x1)
y1 = int(y1... |
class Space(metaclass=MetaSpace):
_stored_dims = {}
def __init__(self, dims):
idims = int(dims)
if ((idims <= 0) or (idims != dims)):
raise ValueError('Dimensions must be integers > 0')
self.size = dims
self.issuper = False
self.superrep = None
self._p... |
def test_fileinrewriterstep_in_and_out_with_formatting():
context = Context({'k1': 'v1', 'root': {'in': 'inpath{k1}here', 'out': 'outpath{k1}here'}})
obj = FileInRewriterStep('blah.name', 'root', context)
assert (obj.path_in == 'inpathv1here')
assert (obj.path_out == 'outpathv1here')
assert (obj.con... |
class Response_Aggregator(nn.Module):
def __init__(self, num_class, W=256, input_class=None):
super(Response_Aggregator, self).__init__()
self.num_class = num_class
self.W = W
if (input_class is not None):
self.input_linear = nn.Sequential(fc_block(input_class, W), fc_blo... |
class MathUtilsTestCase(TestCase):
def test_number_of_decimal_places(self):
self.assertEqual(number_of_decimal_places(1), 0)
self.assertEqual(number_of_decimal_places(3.14), 2)
self.assertEqual(number_of_decimal_places('3.14'), 2)
self.assertEqual(number_of_decimal_places((- 3.14)), ... |
def recursively_load_weights(fairseq_model, hf_model, is_headless):
unused_weights = []
fairseq_dict = fairseq_model.state_dict()
feature_extractor = hf_model.wav2vec2_conformer.feature_extractor
for (name, value) in fairseq_dict.items():
is_used = False
if ('conv_layers' in name):
... |
class LongitudinalDistanceAction(_PrivateActionType):
def __init__(self, entity, freespace=True, continuous=True, max_acceleration=None, max_deceleration=None, max_speed=None, distance=None, timeGap=None, coordinate_system=CoordinateSystem.entity, displacement=LongitudinalDisplacement.any):
self.target = en... |
class InstagramOAuth2Test(OAuth2Test):
backend_path = 'social_core.backends.instagram.InstagramOAuth2'
user_data_url = '
expected_username = 'foobar'
access_token_body = json.dumps({'access_token': 'foobar', 'token_type': 'bearer', 'meta': {'code': 200}, 'user': {'username': 'foobar', 'id': ''}})
us... |
def test_IterativeImputer_params_vs_sklearn():
from sklearn.experimental import enable_iterative_imputer
result = sorted(impute.IterativeImputer._skcriteria_parameters)
ignore = ['add_indicator', 'skip_complete']
alias = {'n_nearest_features': 'n_nearest_criteria', 'keep_empty_features': 'keep_empty_cri... |
.parametrize('order', [20, 25, 30])
.parametrize('alpha', [0.0, 0.35, 0.5])
.parametrize('stage', [1, 2, 3, 4, 5, 6])
def test_mglsadf(order, alpha, stage):
delay = pysptk.mglsadf_delay(order, stage)
__test_filt_base(pysptk.mglsadf, order, delay, alpha, stage)
__test_filt_base(pysptk.mglsadft, order, delay,... |
def get_tiny_config(config_class, model_class=None, **model_tester_kwargs):
model_type = config_class.model_type
config_source_file = inspect.getsourcefile(config_class)
modeling_name = config_source_file.split(os.path.sep)[(- 1)].replace('configuration_', '').replace('.py', '')
try:
print('Impo... |
class Division(BinaryOperator):
def __init__(self, left, right):
super().__init__('/', left, right)
def _diff(self, variable):
(top, bottom) = self.orphans
return (((top.diff(variable) * bottom) - (top * bottom.diff(variable))) / (bottom ** 2))
def _binary_jac(self, left_jac, right_j... |
def compile_forward_sampling_function(outputs: List[Variable], vars_in_trace: List[Variable], basic_rvs: Optional[List[Variable]]=None, givens_dict: Optional[Dict[(Variable, Any)]]=None, constant_data: Optional[Dict[(str, np.ndarray)]]=None, constant_coords: Optional[Set[str]]=None, **kwargs) -> Tuple[(Callable[(..., U... |
class PipSource(DependencySource):
def __init__(self, *, local: bool=False, paths: Sequence[Path]=[], skip_editable: bool=False, state: AuditState=AuditState()) -> None:
self._local = local
self._paths = paths
self._skip_editable = skip_editable
self.state = state
effective_p... |
class IE9(Library):
def __init__(self):
super().__init__('IE9')
self.shipped_in_package = 'reahl.web.static'
self.files = ['IE9.js']
def footer_only_material(self, rendered_page):
result = '\n<!--[if lte IE 9]>'
result += super().footer_only_material(rendered_page)
... |
class TestIOPath(unittest.TestCase):
def test_no_iopath(self):
from .test_reproducibility import TestReproducibility
with mock.patch.dict('sys.modules', {'iopath': None}):
TestReproducibility._test_reproducibility(self, 'test_reproducibility')
def test_no_supports_rename(self):
... |
class ResNetV1(HybridBlock):
def __init__(self, block, layers, channels, classes=1000, thumbnail=False, last_gamma=False, norm_layer=BatchNorm, norm_kwargs=None, **kwargs):
super(ResNetV1, self).__init__()
assert ('fw' in kwargs.keys()), 'no_fw'
self.fw = kwargs['fw']
assert (len(lay... |
class SFT_Net(nn.Module):
def __init__(self):
super(SFT_Net, self).__init__()
self.conv0 = nn.Conv2d(3, 64, 3, 1, 1)
sft_branch = []
for i in range(16):
sft_branch.append(ResBlock_SFT())
sft_branch.append(SFTLayer())
sft_branch.append(nn.Conv2d(64, 64, 3, ... |
def format_func(fn: FuncIR, errors: Sequence[tuple[(ErrorSource, str)]]=()) -> list[str]:
lines = []
cls_prefix = ((fn.class_name + '.') if fn.class_name else '')
lines.append('def {}{}({}):'.format(cls_prefix, fn.name, ', '.join((arg.name for arg in fn.args))))
names = generate_names_for_ir(fn.arg_regs... |
class AM2RGameExportDialog(GameExportDialog, Ui_AM2RGameExportDialog):
def game_enum(cls):
return RandovaniaGame.AM2R
def __init__(self, options: Options, patch_data: dict, word_hash: str, spoiler: bool, games: list[RandovaniaGame]):
super().__init__(options, patch_data, word_hash, spoiler, game... |
def setUpModule():
global cell, kmf, kpts, nkpts
cell = gto.Cell()
cell.atom = '\n H 0.0 0.0 0.0\n F 0.9 0.0 0.0\n '
cell.basis = 'sto-3g'
cell.a = [[2.82, 0, 0], [0, 2.82, 0], [0, 0, 2.82]]
cell.dimension = 1
cell.output = '/dev/null'
cell.build()
nk = [2, 1, 1]
kpts ... |
def maybe_create_ambiguous_expander(tree_class, expansion, keep_all_tokens):
to_expand = [i for (i, sym) in enumerate(expansion) if (keep_all_tokens or ((not (sym.is_term and sym.filter_out)) and _should_expand(sym)))]
if to_expand:
return partial(AmbiguousExpander, to_expand, tree_class) |
def test_arrange_horizontal_with_gap(view, settings):
settings.setValue('Items/arrange_gap', 6)
item1 = BeePixmapItem(QtGui.QImage())
view.scene.addItem(item1)
item1.setSelected(True)
item1.setPos(10, (- 100))
item2 = BeePixmapItem(QtGui.QImage())
view.scene.addItem(item2)
item2.setSelec... |
class MyDataset(torch.utils.data.Dataset):
def __init__(self):
super().__init__()
self.length = 100
def __getitem__(self, idx):
assert ((idx >= 0) and (idx < self.length)), 'Provided index {} must be in range [0, {}).'.format(idx, self.length)
return torch.rand(3, 100, 100)
d... |
def set(name, data=None, dbHandle=None):
if (dbHandle is None):
dbHandle = ops.db.Database(db=ops.db.TARGET_DB, isolation_level=None)
with dbHandle as db:
curs = ensureMarkerTable(db)
curs.execute('SELECT name, last_date, extra FROM marker WHERE name = :name', (name,))
if curs.fe... |
class ConvolutionalEncoder(nn.Module):
def __init__(self, n_features_input, num_hidden_features, kernel_size, padding, n_resblocks, dropout_min=0, dropout_max=0.2, blockObject=ResidualBlock, batchNormObject=nn.BatchNorm2d):
super(ConvolutionalEncoder, self).__init__()
self.n_features_input = n_featu... |
_config
def test_matrix_simple(manager):
manager.test_window('one')
assert (manager.c.layout.info()['rows'] == [['one']])
manager.test_window('two')
assert (manager.c.layout.info()['rows'] == [['one', 'two']])
manager.test_window('three')
assert (manager.c.layout.info()['rows'] == [['one', 'two'... |
def get_configs_from_multiple_files():
train_config = train_pb2.TrainConfig()
with tf.gfile.GFile(FLAGS.train_config_path, 'r') as f:
text_format.Merge(f.read(), train_config)
model_config = model_pb2.DetectionModel()
with tf.gfile.GFile(FLAGS.model_config_path, 'r') as f:
text_format.Me... |
def kana2alphabet(text):
text = text.replace('', 'kya').replace('', 'kyu').replace('', 'kyo')
text = text.replace('', 'gya').replace('', 'gyu').replace('', 'gyo')
text = text.replace('', 'sha').replace('', 'shu').replace('', 'sho')
text = text.replace('', 'ja').replace('', 'ju').replace('', 'jo')
te... |
def pytest_addoption(parser):
group = parser.getgroup('timeout', 'Interrupt test run and dump stacks of all threads after a test times out')
group.addoption('--timeout', type=float, help=TIMEOUT_DESC)
group.addoption('--timeout_method', action='store', choices=['signal', 'thread'], help='Deprecated, use --t... |
def test_show_different_scopes(pytester: Pytester, mode) -> None:
p = pytester.makepyfile('\n import pytest\n \n def arg_function():\n """function scoped fixture"""\n (scope=\'session\')\n def arg_session():\n """session scoped fixture"""\n def test_ar... |
.skipif((K.backend() != 'tensorflow'), reason='Requires TF backend')
_test
def test_model_with_input_feed_tensor():
import tensorflow as tf
input_a_np = np.random.random((10, 3))
input_b_np = np.random.random((10, 3))
output_a_np = np.random.random((10, 4))
output_b_np = np.random.random((10, 3))
... |
def _get_number_symbols(locale: ((Locale | str) | None), *, numbering_system: (Literal['default'] | str)='latn') -> LocaleDataDict:
parsed_locale = Locale.parse(locale)
numbering_system = _get_numbering_system(parsed_locale, numbering_system)
try:
return parsed_locale.number_symbols[numbering_system... |
class TagTreeModelManager(TagModelManager):
def get_queryset(self):
return TagTreeModelQuerySet(self.model, using=self._db)
get_query_set = get_queryset
def rebuild(self):
for tag in self.all():
tag.slug = None
tag.save()
rebuild.alters_data = True
def as_nest... |
class GameOneHotSpottingLabelReader(GameOneHotLabelReaderInterface):
def __init__(self, soccernet_type: str, frame_rate: float, num_classes: int) -> None:
self._frame_rate = frame_rate
self._num_classes = num_classes
self._event_dictionary = choose_spotting_event_dictionary(soccernet_type)
... |
def calculate_fid_folder():
device = torch.device(('cuda' if torch.cuda.is_available() else 'cpu'))
parser = argparse.ArgumentParser()
parser.add_argument('folder', type=str, help='Path to the folder.')
parser.add_argument('--fid_stats', type=str, help='Path to the dataset fid statistics.')
parser.a... |
class ManifestEntryList(List[ManifestEntry]):
def of(entries: List[ManifestEntry]) -> ManifestEntryList:
manifest_entries = ManifestEntryList()
for entry in entries:
if ((entry is not None) and (not isinstance(entry, ManifestEntry))):
entry = ManifestEntry(entry)
... |
class GeneratorModel(FunctionModel, ContextManagerModel):
def __new__(cls, *args, **kwargs):
ret = super().__new__(cls, *args, **kwargs)
generator = AstroidManager().builtins_module['generator']
for (name, values) in generator.locals.items():
method = values[0]
def pa... |
def _backend() -> str:
if (objects.backend == usertypes.Backend.QtWebKit):
return 'new QtWebKit (WebKit {})'.format(qWebKitVersion())
elif (objects.backend == usertypes.Backend.QtWebEngine):
return str(qtwebengine_versions(avoid_init=('avoid-chromium-init' in objects.debug_flags)))
raise uti... |
def calculate_metrics(correct, guessed, total):
(tp, fp, fn) = (correct, (guessed - correct), (total - correct))
p = (0 if ((tp + fp) == 0) else ((1.0 * tp) / (tp + fp)))
r = (0 if ((tp + fn) == 0) else ((1.0 * tp) / (tp + fn)))
f = (0 if ((p + r) == 0) else (((2 * p) * r) / (p + r)))
return Metrics... |
class AddressBookUI(UserInterface):
def assemble(self):
add = self.define_view('/add', title='Add an address')
add.set_slot('main', AddAddressForm.factory())
self.edit = self.define_view('/edit', view_class=EditView, address_id=IntegerField())
addresses = self.define_view('/', title=... |
class TestTruncateExplanation():
LINES_IN_TRUNCATION_MSG = 2
def test_doesnt_truncate_when_input_is_empty_list(self) -> None:
expl: List[str] = []
result = truncate._truncate_explanation(expl, max_lines=8, max_chars=100)
assert (result == expl)
def test_doesnt_truncate_at_when_input_... |
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