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def _row_column_layout(content, flow, size, scope=None, position=OutputPosition.BOTTOM) -> Output:
if (not isinstance(content, (list, tuple, OutputList))):
content = [content]
if (not size):
size = ' '.join((('1fr' if (c is not None) else '10px') for c in content))
content = [(c if (c is not... |
class Vector(QtWidgets.QGraphicsItem):
arrow_color = QtGui.QColor(*getConfig().vector_color)
arrow_brush = QtGui.QBrush(arrow_color, QtCore.Qt.SolidPattern)
arrow_pen = QtGui.QPen(arrow_brush, 1, QtCore.Qt.SolidLine, QtCore.Qt.RoundCap, QtCore.Qt.RoundJoin)
relative_length = getConfig().vector_relative_... |
def pytest_runtest_setup(item):
sanity = item.config.getoption('--sanity', False)
non_interactive = item.config.getoption('--non-interactive', False)
interactive = ((not sanity) and (not non_interactive))
if interactive:
_show_test_header(item)
_try_set_class_attribute(item, 'interactive', i... |
def test_monkeypatch_ini(testdir: Any, mocker: MockerFixture) -> None:
stub = mocker.stub()
assert (stub.assert_called_with.__module__ != stub.__module__)
testdir.makepyfile('\n def test_foo(mocker):\n stub = mocker.stub()\n assert stub.assert_called_with.__module__ == stub.__mo... |
def test_initialization():
x = np.random.normal(size=(13, 5))
y = np.random.randint(2, size=(13, 3))
model = MultiLabelClf()
model.initialize(x, y)
assert_equal(model.n_states, 2)
assert_equal(model.n_labels, 3)
assert_equal(model.n_features, 5)
assert_equal(model.size_joint_feature, (5 ... |
class Blip2Config(PretrainedConfig):
model_type = 'blip-2'
is_composition = True
def __init__(self, vision_config=None, qformer_config=None, text_config=None, num_query_tokens=32, **kwargs):
super().__init__(**kwargs)
if (vision_config is None):
vision_config = {}
log... |
def test_save_unequal_chunks_error():
ds = simulate_genotype_call_dataset(n_variant=10, n_sample=10, n_ploidy=10, n_allele=10, n_contig=10)
with pytest.raises(ValueError, match="path '' contains an array"):
save_dataset(ds, {'.zarray': ''})
ds = ds.chunk({dim: (1, 3, 5, 1) for dim in ds.sizes})
... |
def test_links_1():
with Simulation(MODEL_WEIR_SETTING_PATH) as sim:
print('\n\n\nLINKS\n')
c1c2 = Links(sim)['C1:C2']
assert (c1c2.linkid == 'C1:C2')
assert (c1c2.is_conduit() == True)
assert (c1c2.is_pump() == False)
assert (c1c2.is_orifice() == False)
asser... |
class AppDefStatusTest(unittest.TestCase):
def test_is_terminal(self) -> None:
for s in AppState:
is_terminal = AppStatus(state=s).is_terminal()
if (s in _TERMINAL_STATES):
self.assertTrue(is_terminal)
else:
self.assertFalse(is_terminal)
... |
.skipif(IS_PYPY, reason='Test run with coverage on PyPy sometimes raises a RecursionError')
def test_recursion_on_inference_tip() -> None:
code = '\n class MyInnerClass:\n ...\n\n\n class MySubClass:\n inner_class = MyInnerClass\n\n\n class MyClass:\n sub_class = MySubClass()\n\n\n ... |
class DistributedGroupSampler(Sampler):
def __init__(self, dataset, samples_per_gpu=1, num_replicas=None, rank=None):
(_rank, _num_replicas) = get_dist_info()
if (num_replicas is None):
num_replicas = _num_replicas
if (rank is None):
rank = _rank
self.dataset ... |
_LOSSES.register_module()
class SmoothFocalLoss(nn.Module):
def __init__(self, gamma=2.0, alpha=0.25, reduction='mean', loss_weight=1.0):
super(SmoothFocalLoss, self).__init__()
self.gamma = gamma
self.alpha = alpha
self.reduction = reduction
self.loss_weight = loss_weight
... |
class Transparent(BaseProtocol):
async def guess(self, reader, sock, **kw):
remote = self.query_remote(sock)
return ((remote is not None) and ((sock is None) or (sock.getsockname() != remote)))
async def accept(self, reader, user, sock, **kw):
remote = self.query_remote(sock)
ret... |
def print_loaded_dict_info(model_state_dict: Dict[(str, Any)], state_dict: Dict[(str, Any)], skip_layers: List[str], model_config: AttrDict):
extra_layers = []
max_len_model = max((len(key) for key in model_state_dict.keys()))
for layername in model_state_dict.keys():
if ((len(skip_layers) > 0) and ... |
def get_value_counts(values: List[Any]) -> List[int]:
counts = []
if all(((value is None) for value in values)):
counts.append(0)
else:
for value in values:
if (value is None):
counts.append(0)
elif (hasattr(value, '__len__') and (not isinstance(value,... |
class NIREmissivePartFromReflectance(NIRReflectance):
def __init__(self, sunz_threshold=None, **kwargs):
self.sunz_threshold = sunz_threshold
super(NIREmissivePartFromReflectance, self).__init__(sunz_threshold=sunz_threshold, **kwargs)
def __call__(self, projectables, optional_datasets=None, **i... |
def ssl_server(request, qapp):
server = WebserverProcess(request, 'webserver_sub_ssl')
if (not hasattr(request.node, '_server_logs')):
request.node._server_logs = []
request.node._server_logs.append(('SSL server', server.captured_log))
server.start()
(yield server)
server.after_test()
... |
class main(list):
def __init__(self, campaign, domains, mod, project_id):
global campaign_list
campaign_list = campaign
global domain_list
domain_list = domains
if (mod is not None):
global module
module = mod
i = cmd_main()
i.prompt = ... |
class Effect6404(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: (mod.item.group.name == 'Structure Energy Neutralizer')), 'maxRange', src.getModifiedItemAttr('structureRigEwarOptimalBonus'), stackingPenalties=True, **kw... |
def test_find_files_to_add() -> None:
poetry = Factory().create_poetry(project('complete'))
builder = SdistBuilder(poetry)
result = {f.relative_to_source_root() for f in builder.find_files_to_add()}
assert (result == {Path('AUTHORS'), Path('COPYING'), Path('LICENCE'), Path('LICENSE'), Path('README.rst')... |
def _fallback_property(func):
name = func.__name__
(func)
def new_func(self):
out = getattr(self._param_td, name)
if (out is self._param_td):
return self
return out
def setter(self, value):
return getattr(type(self._param_td), name).fset(self._param_td, value)... |
class TestTotalVariationLoss():
def test_call(self):
torch.manual_seed(0)
image = torch.rand(1, 3, 128, 128)
exponent = 3.0
op = loss.TotalVariationLoss(exponent=exponent)
actual = op(image)
desired = F.total_variation_loss(image, exponent=exponent)
ptu.assert... |
def get_optim_and_schedulers(model, args):
if (args.base_opt == 'SGD'):
base_optimizer = optim.SGD(model.parameters(), lr=args.lr, momentum=args.momentum, weight_decay=args.weight_decay)
elif (args.base_opt == 'Adam'):
base_optimizer = optim.Adam(model.parameters(), lr=args.lr, weight_decay=args... |
_response(prefix='')
def request_word(word):
url = URL_FORM.format(word=word)
try:
response = requests.get(url, timeout=DEFAULT_TIMEOUT)
except requests.exceptions.ConnectionError as exc:
raise Exception(_('Connection could not be established. Check your internet connection.')) from exc
... |
def main(opts):
(default_gpu, n_gpu, device) = set_cuda(opts)
if default_gpu:
LOGGER.info('device: {} n_gpu: {}, distributed training: {}, 16-bits training: {}'.format(device, n_gpu, bool((opts.local_rank != (- 1))), opts.fp16))
seed = opts.seed
if (opts.local_rank != (- 1)):
seed += opt... |
def test_generate_system_pyproject_carriage_returns(example_system_pyproject: str) -> None:
cmd = SelfCommand()
cmd.system_pyproject.write_text((example_system_pyproject + '\n'))
cmd.generate_system_pyproject()
with open(cmd.system_pyproject, newline='') as f:
generated = f.read()
assert ('\... |
class ResultsTable(QtCore.QObject):
data_changed = QtCore.Signal(int, int, int, int)
def __init__(self, results, color, column_index=None, force_reload=False, wdg=None, **kwargs):
super().__init__()
self.results = results
self.color = color
self.force_reload = force_reload
... |
class SourceGenerator(LocationGenerator):
nevents = Int.T(default=2)
avoid_water = Bool.T(default=False, help='Avoid sources offshore under the ocean / lakes.')
time_min = Timestamp.T(default=Timestamp.D('2017-01-01 00:00:00'))
time_max = Timestamp.T(default=Timestamp.D('2017-01-03 00:00:00'))
magni... |
class Meteor(object):
def __init__(self):
assert (_METEOR_PATH is not None)
cmd = 'java -Xmx2G -jar {} - - -l en -norm -stdio'.format(_METEOR_PATH)
self._meteor_proc = sp.Popen(cmd.split(), stdin=sp.PIPE, stdout=sp.PIPE, stderr=sp.PIPE, universal_newlines=True, encoding='utf-8', bufsize=1)
... |
class BertPredictionHeadTransform(nn.Module):
def __init__(self, config):
super().__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
if isinstance(config.hidden_act, str):
self.transform_act_fn = ACT2FN[config.hidden_act]
else:
self.tran... |
class Effect6559(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.fighters.filteredItemBoost((lambda mod: mod.item.requiresSkill('Fighters')), 'fighterAbilityAttackMissileExplosionRadius', src.getModifiedItemAttr('aoeCloudSizeBonus'), stackingPenalties=True, *... |
class WordInformationPreserved(Metric[torch.Tensor]):
def __init__(self: TWordInformationPreserved, *, device: Optional[torch.device]=None) -> None:
super().__init__(device=device)
self._add_state('correct_total', torch.tensor(0, dtype=torch.float64, device=self.device))
self._add_state('inp... |
(python=PYTHON_ALL_VERSIONS)
def tests(session: nox.Session) -> None:
posargs = session.posargs
extras = ('coverage' if RUNNING_CI else 'test')
session.install('-e', f'.[{extras}]')
if RUNNING_CI:
posargs.extend(['--cov', 'auditwheel', '--cov-branch'])
for image in _docker_images(session... |
class TestAppConfig(AppConfig):
name = 'test_app'
def ready(self):
register_iframe('test_app.views.view_to_component_sync_func_compatibility')
register_iframe(views.view_to_component_async_func_compatibility)
register_iframe(views.ViewToComponentSyncClassCompatibility)
register_i... |
def generate_meas_calibration(results_file_path: str, runs: int):
results = []
for run in range(runs):
(cal_results, state_labels, circuit_results) = meas_calibration_circ_execution(1000, (SEED + run))
meas_cal = CompleteMeasFitter(cal_results, state_labels)
meas_filter = MeasurementFilt... |
class ViewProviderAsmElementGroup(ViewProviderAsmGroup):
_iconName = 'Assembly_Assembly_Element_Tree.svg'
def setupContextMenu(self, vobj, menu):
setupSortMenu(menu, self.sort, self.sortReverse)
ViewProviderAsmElement.setupSyncNameMenu('Sync elements names', menu, vobj)
def syncElementName(s... |
class Disc_feat(nn.Module):
def __init__(self):
super(Disc_feat, self).__init__()
self.fc11 = nn.Linear(10240, 4096)
self.fc12 = nn.Linear(4096, 4096)
self.fc13 = nn.Linear(4096, 1)
self.d = nn.Dropout(0.5)
def forward(self, x_feat):
x = self.fc13(self.d(F.relu(se... |
def create_sweeptx_for_their_revoked_htlc(chan: 'Channel', ctx: Transaction, htlc_tx: Transaction, sweep_address: str) -> Optional[SweepInfo]:
x = analyze_ctx(chan, ctx)
if (not x):
return
(ctn, their_pcp, is_revocation, per_commitment_secret) = x
if (not is_revocation):
return
pcp =... |
class ParentProperty():
def __get__(self, inst, owner):
return getattr(inst, '_parent', None)
def __set__(self, inst, value):
if ((getattr(inst, '_parent', None) is not None) and (value is not None)):
raise ValueError("Cannot set parent property without first setting it to 'None'.")
... |
def clean_value(val: Any) -> str:
if isinstance(val, (Mapping, list, set, tuple)):
raise ValueError(('Cannot clean parameter value of type %s' % str(type(val))))
if isinstance(val, (datetime.datetime, datetime.date)):
return clean_date(val)
if isinstance(val, bool):
return clean_bool... |
def _add_encryption(field_class, requires_length_check=True):
class indexed_class(field_class):
def __init__(self, default_token_length=None, *args, **kwargs):
def _generate_default():
return DecryptedValue(random_string(default_token_length))
if (default_token_length... |
def _generate_WS_to_parallel(i, num_nodes, num_signals, graph_hyper, weighted, weight_scale=False):
G = nx.watts_strogatz_graph(num_nodes, k=graph_hyper['k'], p=graph_hyper['p'])
W_GT = nx.adjacency_matrix(G).A
if (weighted == 'uniform'):
weights = np.random.uniform(0, 2, (num_nodes, num_nodes))
... |
def annotate_pymodbus_logs(file: (str | os.PathLike)) -> None:
with open(file, encoding='utf-8') as in_file, tempfile.NamedTemporaryFile(mode='w', encoding='utf-8', delete=False) as out_file:
for (i, line) in enumerate(in_file):
if (('Running transaction' in line) and (i > 0)):
o... |
.parametrize('environment', [{}, {'something': 'value'}, {'something': 'value', 'something_else': 'other_value'}])
.parametrize('platform_specific', [False, True])
def test_environment(environment, platform_specific, platform, intercepted_build_args, monkeypatch):
env_string = ' '.join((f'{k}={v}' for (k, v) in env... |
def test_pass_through_equal_m_constraint():
class Top(Component):
def construct(s):
s.push = CalleeIfcCL()
s.pull = CalleeIfcCL()
s.pass1 = PassThroughPlus100()
s.pass1.push //= s.push
s.inner = TestModuleNonBlockingIfc()
s.inner.push /... |
class ParallelLinearQubitOperatorTest(unittest.TestCase):
def setUp(self):
self.qubit_operator = ((QubitOperator('Z3') + QubitOperator('Y0')) + QubitOperator('X1'))
self.n_qubits = 4
self.linear_operator = ParallelLinearQubitOperator(self.qubit_operator)
self.vec = numpy.array(range(... |
def test_is_generator_for_yield_in_while() -> None:
code = '\n def paused_iter(iterable):\n while True:\n # Continue to yield the same item until `next(i)` or `i.send(False)`\n while (yield value):\n pass\n '
node = astroid.extract_node(code)
assert bool(nod... |
class LazyFrames(object):
def __init__(self, frames):
self._frames = frames
self._out = None
def _force(self):
if (self._out is None):
self._out = np.concatenate(self._frames, axis=0)
self._frames = None
return self._out
def __array__(self, dtype=None)... |
def _create_or_update_runtime(task_signature: str, start: float, end: float) -> None:
with DatabaseSession() as session:
runtime = session.get(Runtime, task_signature)
if (not runtime):
session.add(Runtime(task=task_signature, date=start, duration=(end - start)))
else:
... |
class RoIAlignFunction(Function):
def forward(ctx, features, rois, out_size, spatial_scale, sample_num=0):
(out_h, out_w) = _pair(out_size)
assert (isinstance(out_h, int) and isinstance(out_w, int))
ctx.spatial_scale = spatial_scale
ctx.sample_num = sample_num
ctx.save_for_ba... |
def create_line_trotter_step_circuit(parameters: FermiHubbardParameters) -> cirq.Circuit:
layout = parameters.layout
hamiltonian = parameters.hamiltonian
dt = parameters.dt
j_theta = (dt * hamiltonian.j_array)
(j_theta_even, j_theta_odd) = (j_theta[0::2], j_theta[1::2])
u_phi = ((- dt) * hamilto... |
class SerializerTests(AuthenticatedAPITestCase):
def setUpTestData(cls):
cls.user = User.objects.create(id=5, name='james', discriminator=1)
def create_infraction(self, _type: str, active: bool):
return Infraction.objects.create(user_id=self.user.id, actor_id=self.user.id, type=_type, reason='A ... |
class PickupObjectAction(BaseAction):
valid_actions = {'PickupObject', 'OpenObject', 'CloseObject'}
def get_reward(self, state, prev_state, expert_plan, goal_idx, low_idx=None):
if (low_idx is None):
subgoal = expert_plan[goal_idx]['planner_action']
else:
subgoal = expert... |
class BareReport(FormatterAPI):
def render_vulnerabilities(self, announcements, vulnerabilities, remediations, full, packages, fixes=()):
parsed_announcements = []
Announcement = namedtuple('Announcement', ['name'])
for announcement in get_basic_announcements(announcements, include_local=Fal... |
class KnownValues(unittest.TestCase):
def test_nosymm_sa4_newton(self):
mc = mcscf.CASSCF(m, 4, 4).state_average_(([0.25] * 4)).newton()
mo = mc.sort_mo([4, 5, 6, 10], base=1)
mc.kernel(mo)
self.assertAlmostEqual(mc.e_tot, mc_ref.e_tot, 8)
for (e1, e0) in zip(mc.e_states, mc_... |
class ins(object):
def localin(self):
Mylogo()
print('\n\x1b[01;32mInstalling Localtunnel .......\x1b[00m\n')
if (system == 'termux'):
lt().notinl()
elif (system == 'ubuntu'):
os.system((pac + ' update'))
os.system((pac + ' upgrade -y'))
... |
class ImageNetConverter(DatasetConverter):
def _create_data_spec(self):
self.files_to_skip = set()
for other_dataset in ('Caltech101', 'Caltech256', 'CUBirds'):
duplicates_file = os.path.join(AUX_DATA_PATH, 'ImageNet_{}_duplicates.txt'.format(other_dataset))
with tf.io.gfile.... |
(kw_only=True)
class Session():
config: dict[(str, Any)] = field(factory=dict)
collection_reports: list[CollectionReport] = field(factory=list)
dag: nx.DiGraph = field(factory=nx.DiGraph)
hook: HookRelay = field(factory=HookRelay)
tasks: list[PTask] = field(factory=list)
dag_report: (DagReport |... |
class TestUserAgent(BaseTestCase):
async def test_user_agent(self):
self.assertIn('Mozilla', (await self.page.evaluate('() => navigator.userAgent')))
(await self.page.setUserAgent('foobar'))
(await self.page.goto(self.url))
self.assertEqual('foobar', (await self.page.evaluate('() => ... |
def sort_by_keywords(keywords, args):
flat = []
res = {}
cur_key = None
limit = (- 1)
for arg in args:
if (arg in keywords):
limit = keywords[arg]
if (limit == 0):
res[arg] = True
cur_key = None
limit = (- 1)
... |
class CLIPFeatureExtractor(FeatureExtractionMixin, ImageFeatureExtractionMixin):
model_input_names = ['pixel_values']
def __init__(self, do_resize=True, size=224, resample=Image.BICUBIC, do_center_crop=True, crop_size=224, do_normalize=True, image_mean=None, image_std=None, do_convert_rgb=True, **kwargs):
... |
class EntryChangeNotificationControl(ResponseControl):
controlType = '2.16.840.1.113730.3.4.7'
def decodeControlValue(self, encodedControlValue):
(ecncValue, _) = decoder.decode(encodedControlValue, asn1Spec=EntryChangeNotificationValue())
self.changeType = int(ecncValue.getComponentByName('chan... |
def test_index_report(api, initialized_db):
with fake_security_scanner() as security_scanner:
manifest = manifest_for('devtable', 'simple', 'latest')
layers = registry_model.list_manifest_layers(manifest, storage, True)
assert (manifest.digest not in security_scanner.index_reports.keys())
... |
def test_TrioToken_run_sync_soon_idempotent_requeue() -> None:
record: list[None] = []
def redo(token: _core.TrioToken) -> None:
record.append(None)
with suppress(_core.RunFinishedError):
token.run_sync_soon(redo, token, idempotent=True)
async def main() -> None:
token = ... |
class XDistanceMixin(SmoothPointGetter):
_baseResolution = 50
_extraDepth = 2
def _getCommonData(self, miscParams, src, tgt):
self._prepareTimeCache(src=src, ancReload=miscParams['ancReload'], maxTime=miscParams['time'])
return {'rrMap': self._getRepsPerKey(src=src, ancReload=miscParams['anc... |
class SpatialDropout2D(Dropout):
_spatialdropoutNd_support
def __init__(self, rate, data_format=None, **kwargs):
super(SpatialDropout2D, self).__init__(rate, **kwargs)
if (data_format is None):
data_format = K.image_data_format()
if (data_format not in {'channels_last', 'chan... |
class ConvNextOnnxConfig(OnnxConfig):
torch_onnx_minimum_version = version.parse('1.11')
def inputs(self) -> Mapping[(str, Mapping[(int, str)])]:
return OrderedDict([('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'})])
def atol_for_validation(self) -> float:
return 1e... |
def require_digest_auth(resource):
p = portal.Portal(TestAuthRealm(DIGEST_AUTH_PAGE))
c = checkers.InMemoryUsernamePasswordDatabaseDontUse(digestuser=b'digestuser')
p.registerChecker(c)
cred_factory = DigestCredentialFactory('md5', b'Digest Auth protected area')
return HTTPAuthSessionWrapper(p, [cre... |
class Bottleneck(nn.Module):
expansion = 2
def __init__(self, inplanes, planes, stride=1, dilation=1):
super(Bottleneck, self).__init__()
expansion = Bottleneck.expansion
bottle_planes = (planes // expansion)
self.conv1 = nn.Conv2d(inplanes, bottle_planes, kernel_size=1, bias=Fal... |
def test_jsonparse_scalar_with_key_empty():
context = Context({'ok1': 'ov1', 'jsonParse': {'json': '', 'key': 'out'}})
with pytest.raises(KeyInContextHasNoValueError) as err_info:
jsonparse.run_step(context)
assert (str(err_info.value) == 'jsonParse.json exists but is empty. It should be a valid jso... |
class RegNetCfg():
depth: int = 21
w0: int = 80
wa: float = 42.63
wm: float = 2.66
group_size: int = 24
bottle_ratio: float = 1.0
se_ratio: float = 0.0
stem_width: int = 32
downsample: Optional[str] = 'conv1x1'
linear_out: bool = False
preact: bool = False
num_features: i... |
def _test():
import torch
pretrained = False
models = [sharesnet18, sharesnet34, sharesnet50, sharesnet50b, sharesnet101, sharesnet101b, sharesnet152, sharesnet152b]
for model in models:
net = model(pretrained=pretrained)
net.eval()
weight_count = _calc_width(net)
print('... |
class LinearAttention(nn.Module):
def __init__(self, dim, heads=4, dim_head=32):
super().__init__()
self.heads = heads
hidden_dim = (dim_head * heads)
self.to_qkv = nn.Conv2d(dim, (hidden_dim * 3), 1, bias=False)
self.to_out = nn.Conv2d(hidden_dim, dim, 1)
def forward(sel... |
class BoundMethod(UnboundMethod):
special_attributes = objectmodel.BoundMethodModel()
def __init__(self, proxy: ((nodes.FunctionDef | nodes.Lambda) | UnboundMethod), bound: SuccessfulInferenceResult) -> None:
super().__init__(proxy)
self.bound = bound
def implicit_parameters(self) -> Literal... |
class LoopNonlocalControl(NonlocalControl):
def __init__(self, outer: NonlocalControl, continue_block: BasicBlock, break_block: BasicBlock) -> None:
self.outer = outer
self.continue_block = continue_block
self.break_block = break_block
def gen_break(self, builder: IRBuilder, line: int) -... |
def test_verbose_output(testdir):
testdir.makepyfile('\n def describe_something():\n def describe_nested_ok():\n def passes():\n assert True\n def describe_nested_bad():\n def fails():\n assert False\n ')
res... |
class TestDicke():
def test_num_dicke_states(self):
N_list = [1, 2, 3, 4, 5, 6, 9, 10, 20, 100, 123]
dicke_states = [num_dicke_states(i) for i in N_list]
assert_array_equal(dicke_states, [2, 4, 6, 9, 12, 16, 30, 36, 121, 2601, 3906])
N = (- 1)
assert_raises(ValueError, num_di... |
def get_train_features(cfg, temp_dir, train_dataset_name, resize_img, spatial_levels, image_helper, train_dataset, model):
train_features = []
def process_train_image(i, out_dir):
if ((i % LOG_FREQUENCY) == 0):
(logging.info(f'Train Image: {i}'),)
fname_out = f'{out_dir}/{i}.npy'
... |
class MemcacheContextFactory(ContextFactory):
PROM_PREFIX = 'memcached_client_pool'
PROM_LABELS = ['memcached_pool']
pool_size_gauge = Gauge(f'{PROM_PREFIX}_max_size', 'Maximum number of connections allowed in this pool', PROM_LABELS)
used_connections_gauge = Gauge(f'{PROM_PREFIX}_active_connections', '... |
class STFTLoss(torch.nn.Module):
def __init__(self, fft_size=1024, shift_size=120, win_length=600, window='hann_window'):
super(STFTLoss, self).__init__()
self.fft_size = fft_size
self.shift_size = shift_size
self.win_length = win_length
window = getattr(torch, window)(win_le... |
class SentimentTriple(BaseModel):
aspect: List
opinion: List
sentiment: Text
def from_sentiment_triple(cls, labels: Tuple[(List, List, Text)]):
relation = {'': 'POS', '': 'NEG', '': 'NEU'}
assert (len(labels) == 3)
return cls(aspect=labels[0], opinion=labels[1], sentiment=(relati... |
class LilyPondStyle(Style):
name = 'lilypond'
web_style_gallery_exclude = True
styles = {Token.Text: '', Token.Keyword: 'bold', Token.Comment: 'italic #A3AAB2', Token.String: '#AB0909', Token.String.Escape: '#C46C6C', Token.String.Symbol: 'noinherit', Token.Pitch: '', Token.Number: '#976806', Token.ChordMod... |
class ResourceRequirementEditor():
def __init__(self, parent: QWidget, layout: QHBoxLayout, resource_database: ResourceDatabase, item: ResourceRequirement):
self.parent = parent
self.layout = layout
self.resource_database = resource_database
self.resource_type_combo = _create_resourc... |
class Decoderv2(nn.Module):
def __init__(self, up_in, x_in, n_out):
super(Decoderv2, self).__init__()
up_out = x_out = (n_out // 2)
self.x_conv = nn.Conv2d(x_in, x_out, 1, bias=False)
self.tr_conv = nn.ConvTranspose2d(up_in, up_out, 2, stride=2)
self.bn = nn.BatchNorm2d(n_out... |
_fixtures(SqlAlchemyFixture, DeferredActionFixture)
def test_deferred_action_times_out_with_shared_requirements(sql_alchemy_fixture, deferred_action_fixture):
fixture = deferred_action_fixture
with sql_alchemy_fixture.persistent_test_classes(fixture.MyDeferredAction, fixture.SomeObject):
requirements1 =... |
def get_datasets(data_cfg: DataConfig) -> Tuple[(Subset[CharDataset], Subset[CharDataset], CharDataset)]:
dataset = CharDataset(data_cfg)
train_len = int((len(dataset) * data_cfg.train_split))
(train_set, eval_set) = random_split(dataset, [train_len, (len(dataset) - train_len)])
return (train_set, eval_... |
class ApacheRole(Role):
def __available_site_for(self, name):
return ('/etc/apache2/sites-available/%s' % name)
def __enabled_site_for(self, name):
return ('/etc/apache2/sites-enabled/%s' % name)
def __init__(self, prov, context):
super(ApacheRole, self).__init__(prov, context)
... |
class HeaderChecker():
def __init__(self, caplog, stubs):
self.caplog = caplog
self.stubs = stubs
def check_filename(self, header, filename, expected_inline=False):
reply = self.stubs.FakeNetworkReply(headers={'Content-Disposition': header})
(cd_inline, cd_filename) =
as... |
class PosTransformerEncoderLayerNoFFN(TransformerEncoderLayerNoFFN):
def __init__(self, d_model, nhead, dropout):
super().__init__(d_model, nhead, dropout)
def forward(self, src, pos, src_mask=None, src_key_padding_mask=None):
src2 = self.self_attn((src + pos), (src + pos), src, attn_mask=src_ma... |
def test_basename_natural2():
fsos = [create_filesystem_object(path) for path in ('hello', 'hello.txt', 'hello0.txt', 'hello1.txt', 'hello2.txt', 'hello3.txthello10.txt', 'hello11.txt', 'hello12.txt', 'hello13.txthello100.txt', 'hello101.txt', 'hello102.txt', 'hello103.txthello110.txt', 'hello111.txt', 'hello112.tx... |
class BeachballView(qw.QWidget):
def __init__(self, *args):
qw.QWidget.__init__(self, *args)
mt = mtm.MomentTensor(m=mtm.symmat6(1.0, (- 1.0), 2.0, 0.0, (- 2.0), 1.0))
self._mt = mt
self.set_moment_tensor(mt)
def set_moment_tensor(self, mt):
self._mt = mt
self.upd... |
class Xception65(nn.Module):
def __init__(self, norm_layer=nn.BatchNorm2d):
super().__init__()
output_stride = cfg.MODEL.OUTPUT_STRIDE
if (output_stride == 32):
entry_block3_stride = 2
middle_block_dilation = 1
exit_block_dilations = (1, 1)
exi... |
class WBLogger():
def __init__(self, opts):
wandb_run_name = os.path.basename(opts.exp_dir)
wandb.init(project='pixel2style2pixel', config=vars(opts), name=wandb_run_name)
def log_best_model():
wandb.run.summary['best-model-save-time'] = datetime.datetime.now()
def log(prefix, metric... |
class DevhostSt(SimpleDownloader):
__name__ = 'DevhostSt'
__type__ = 'downloader'
__version__ = '0.11'
__status__ = 'testing'
__pattern__ = '
__config__ = [('enabled', 'bool', 'Activated', True), ('use_premium', 'bool', 'Use premium account if available', True), ('fallback', 'bool', 'Fallback to... |
_config
def test_fullscreen_on_top(xmanager):
conn = xcbq.Connection(xmanager.display)
def _wnd(name):
return xmanager.c.window[{w['name']: w['id'] for w in xmanager.c.windows()}[name]]
def _clients():
root = conn.default_screen.root.wid
q = conn.conn.core.QueryTree(root).reply()
... |
class KTZ1(DataElementGroup):
is_sepa = DataElementField(type='jn', _d='Kontoverwendung SEPA')
iban = DataElementField(type='an', max_length=34, _d='IBAN')
bic = DataElementField(type='an', max_length=11, _d='BIC')
account_number = DataElementField(type='id', _d='Konto-/Depotnummer')
subaccount_numb... |
class random_crystal():
def __init__(self, dim=3, group=227, species=['C'], numIons=8, factor=1.1, thickness=None, area=None, lattice=None, sites=None, conventional=True, tm=Tol_matrix(prototype='atomic'), use_hall=False):
self.source = 'Random'
self.valid = False
self.factor = factor
... |
def system_details_to_str(d: Dict[(str, Union[(str, Dict[(str, DebugInfo)])])], indent: str='') -> str:
details = ['Machine Details:', (' Platform ID: %s' % d.get('platform', 'n/a')), (' Processor: %s' % d.get('processor', 'n/a')), '', 'Python:', (' Implementation: %s' % d.get('implementation', 'n/a')... |
def test_notify_exception(pytester: Pytester, capfd) -> None:
config = pytester.parseconfig()
with pytest.raises(ValueError) as excinfo:
raise ValueError(1)
config.notify_exception(excinfo, config.option)
(_, err) = capfd.readouterr()
assert ('ValueError' in err)
class A():
def p... |
class ShardedIterator(CountingIterator):
def __init__(self, iterable, num_shards, shard_id, fill_value=None):
if ((shard_id < 0) or (shard_id >= num_shards)):
raise ValueError('shard_id must be between 0 and num_shards')
sharded_len = int(math.ceil((len(iterable) / float(num_shards))))
... |
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