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def test_control_check_get_errors(fake, caplog):
def checking():
fake.error = True
return [(7, 'some error')]
fake.check_get_errors = checking
fake.fake_ctrl_errors
assert (fake.error is True)
assert (caplog.record_tuples[(- 1)] == ('pymeasure.instruments.common_base', logging.ERROR,... |
def read_data(train_data_dir, test_data_dir):
clients = []
groups = []
train_data = {}
test_data = {}
train_files = os.listdir(train_data_dir)
train_files = [f for f in train_files if f.endswith('.json')]
for f in train_files:
file_path = os.path.join(train_data_dir, f)
with ... |
def test_old_style():
assert (get_attrs_shape(OldStyle) == Shape(input=InputShape(constructor=OldStyle, kwargs=None, fields=(InputField(type=Any, id='a', default=NoDefault(), is_required=True, metadata=MappingProxyType({}), original=ANY), InputField(type=int, id='b', default=NoDefault(), is_required=True, metadata=... |
def compute_cost(num_spin_orbs: int, lambda_tot: float, thc_dim: int, kmesh: list[int], dE_for_qpe: float=0.0016, chi: int=10, beta: Union[(int, None)]=None) -> ResourceEstimates:
thc_costs = _compute_cost(n=num_spin_orbs, lam=lambda_tot, dE=dE_for_qpe, chi=chi, beta=beta, M=thc_dim, Nkx=kmesh[0], Nky=kmesh[1], Nkz... |
def test():
input_time = np.linspace(0, 4, 400)
input_signal = (np.sin((((input_time * 40) * np.pi) * 2)) + np.sin((((input_time * 20) * np.pi) * 2)))
filter1 = LPFilter(100, 40)
filter2 = LPFilter(100, 10)
y1 = [filter1.next(x) for x in input_signal]
y2 = [filter2.next(x) for x in input_signal]... |
def open_file(path, sep=' ', mode='train'):
src = []
tgt = []
with open(path, 'r', encoding='utf8') as f:
content = f.readlines()
tmp_src = []
tmp_tgt = []
for (i, line) in enumerate(content):
line = line.strip().split(sep)
if (len(line) == 2):
... |
class ProjectViewSet(ModelViewSet):
permission_classes = ((HasModelPermission | HasProjectsPermission),)
serializer_class = ProjectSerializer
filter_backends = (DjangoFilterBackend,)
filterset_fields = ('title', 'user', 'user__username', 'catalog', 'catalog__uri')
def get_queryset(self):
ret... |
class CredentialField(CharField):
def __init__(self, *args, **kwargs):
CharField.__init__(self, *args, **kwargs)
assert ('default' not in kwargs)
assert (not self.index)
def db_value(self, value):
if (value is None):
return None
if isinstance(value, str):
... |
def train_lm(args, gpu_id, rank, loader, model, optimizer, scheduler):
model.train()
start_time = time.time()
total_loss = 0.0
(total_correct, total_denominator) = (0.0, 0.0)
steps = 1
total_steps = args.total_steps
loader_iter = iter(loader)
while True:
if (steps == (total_steps... |
def get_args():
parser = argparse.ArgumentParser(description='This script augments a phones.txt\n file (a phone-level symbol table) by adding certain special symbols\n relating to grammar support. See ../add_nonterminals.sh for context.')
parser.add_argument('input_phones_txt', type=str, help='File... |
class GPUSchema(Schema):
class Meta():
unknown = RAISE
gpus = fields.Int(required=True, description='Number of gpus for training. This affects the `world size` of PyTorch DDP.', exclusiveMinimum=0)
vRam = fields.Int(required=True, description='Minimum VRam required for each gpu. Set it to `-1` to us... |
class GripperController():
def __init__(self, robot_name, create_node=False, upper_limit=0.035, lower_limit=0.01, des_pos_max=1, des_pos_min=0):
if create_node:
rospy.init_node('gripper_controller')
assert (des_pos_max >= des_pos_min), 'gripper des_pos_max has to be >= des_pos_min'
... |
.parametrize('package_spec_in,package_or_url_correct,valid_spec', [('pipx', 'pipx', True), ('PiPx_stylized.name', 'pipx-stylized-name', True), ('pipx==0.15.0', 'pipx==0.15.0', True), ('pipx>=0.15.0', 'pipx>=0.15.0', True), ('pipx<=0.15.0', 'pipx<=0.15.0', True), ('pipx;python_version>="3.6"', 'pipx', True), ('pipx==0.1... |
def _get_version_tag(tag):
version_re = re.compile('\n (?P<package>qt|pyqt|pyqtwebengine|python)\n (?P<operator>==|>=|!=|<)\n (?P<version>\\d+\\.\\d+(\\.\\d+)?)\n ', re.VERBOSE)
match = version_re.fullmatch(tag)
if (not match):
return None
package = match.group('package')... |
def test_build_schema1():
manifest = DockerSchema2Manifest(Bytes.for_string_or_unicode(MANIFEST_BYTES))
assert (not manifest.has_remote_layer)
retriever = ContentRetrieverForTesting({CONFIG_DIGEST: CONFIG_BYTES})
builder = DockerSchema1ManifestBuilder('somenamespace', 'somename', 'sometag')
manifest... |
class DBAPICursor():
def execute(self, statement, parameters):
pass
def executemany(self, statement, parameters):
pass
def description(self):
raise NotImplementedError
async def prepare(self, context, clause=None):
raise NotImplementedError
async def async_execute(sel... |
class Channel():
BOOLS = {True: 1, False: 0}
bwlimit = Instrument.control('BWLimit?', 'BWLimit %d', ' A boolean parameter that toggles 25 MHz internal low-pass filter.', validator=strict_discrete_set, values=BOOLS, map_values=True)
coupling = Instrument.control('COUPling?', 'COUPling %s', ' A string paramet... |
def test_dsl_async_cmd_run_has_list_input_save_dev_null():
cmd1 = get_cmd('echo one', 'tests\\testfiles\\cmds\\echo.bat one')
cmd2 = get_cmd('echo two three', 'tests\\testfiles\\cmds\\echo.bat "two three"')
context = Context({'cmds': {'run': [cmd1, cmd2], 'stdout': '/dev/null', 'stderr': '/dev/null'}})
... |
_torch
_vision
class ViltImageProcessingTest(ImageProcessingSavingTestMixin, unittest.TestCase):
image_processing_class = (ViltImageProcessor if is_vision_available() else None)
def setUp(self):
self.image_processor_tester = ViltImageProcessingTester(self)
def image_processor_dict(self):
ret... |
def test_order_vertex():
dummy_points_x = [20, 20, 120, 120]
dummy_points_y = [20, 40, 40, 20]
expect_points_x = [20, 120, 120, 20]
expect_points_y = [20, 20, 40, 40]
with pytest.raises(AssertionError):
sort_vertex([], dummy_points_y)
with pytest.raises(AssertionError):
sort_vert... |
def locate_cuda():
if ('CUDAHOME' in os.environ):
home = os.environ['CUDAHOME']
nvcc = pjoin(home, 'bin', 'nvcc')
else:
default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
nvcc = find_in_path('nvcc', ((os.environ['PATH'] + os.pathsep) + default_path))
if (nvcc is ... |
def get_stale_team(stale_timespan):
stale_at = (datetime.now() - stale_timespan)
try:
candidates = TeamSync.select(TeamSync.id).where(((TeamSync.last_updated <= stale_at) | (TeamSync.last_updated >> None))).limit(500).alias('candidates')
found = TeamSync.select(candidates.c.id).from_(candidates)... |
def get_cadidate_embeddings(json_list, document_embeddings):
document_feats = []
for (document, document_emb) in tqdm(zip(json_list, document_embeddings), total=len(json_list)):
assert (document['document_id'] == document_emb['document_id'])
sentence = flat_list(document['tokens'])
sente... |
class TrezorClientBase(HardwareClientBase, Logger):
def __init__(self, transport, handler, plugin):
HardwareClientBase.__init__(self, plugin=plugin)
if plugin.is_outdated_fw_ignored():
TrezorClient.is_outdated = (lambda *args, **kwargs: False)
self.client = TrezorClient(transport... |
class BasicBlock(nn.Module):
def __init__(self, in_planes, planes, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, ker... |
def test_upload_mixin_with_filepath(gl):
class TestClass(UploadMixin, FakeObject):
_upload_path = '/tests/{id}/uploads'
url = '
responses.add(method=responses.POST, url=url, json={'id': 42, 'file_name': 'test.txt', 'file_content': 'testing contents'}, status=200, match=[responses.matchers.query_para... |
class PresetAM2RHints(PresetTab, Ui_PresetAM2RHints):
def __init__(self, editor: PresetEditor, game_description: GameDescription, window_manager: WindowManager):
super().__init__(editor, game_description, window_manager)
self.setupUi(self)
self.hint_layout.setAlignment(QtCore.Qt.AlignmentFla... |
class TestRiskParityBoxesFactory(TestCase):
def setUpClass(cls):
cls.start_date = str_to_date('2022-10-01')
cls.end_date = str_to_date('2022-11-01')
cls.frequency = Frequency.DAILY
datetime_index = pd.DatetimeIndex(['2022-10-02', '2022-10-03', '2022-10-04', '2022-10-05', '2022-10-06'... |
(scope='function')
def simulation_evaluator() -> ClosedLoopEvaluator:
metrics = [DisplacementErrorL2Metric(), DistanceToRefTrajectoryMetric(), CollisionFrontMetric(), CollisionRearMetric(), CollisionSideMetric()]
validators = [RangeValidator('displacement_error_l2_validator', DisplacementErrorL2Metric, max_valu... |
class TearDownConvenience(object):
def __init__(self, setup_stack=None):
self._own_setup_stack = (setup_stack is None)
if (setup_stack is None):
setup_stack = SetupStack()
self._setup_stack = setup_stack
def tear_down(self):
assert self._own_setup_stack
self._... |
class CAM(Net):
def __init__(self):
super(CAM, self).__init__()
def forward(self, x):
x = self.stage1(x)
x = self.stage2(x)
x = self.stage3(x)
x = self.stage4(x)
x = F.conv2d(x, self.classifier.weight)
x = F.relu(x)
x = (x[0] + x[1].flip((- 1)))
... |
def _get_in_vals(binst: BloqInstance, reg: Register, soq_assign: Dict[(Soquet, ClassicalValT)]) -> ClassicalValT:
if (not reg.shape):
return soq_assign[Soquet(binst, reg)]
if (reg.bitsize <= 8):
dtype = np.uint8
elif (reg.bitsize <= 16):
dtype = np.uint16
elif (reg.bitsize <= 32)... |
.parametrize('metric', ['euclidean', 'minkowski', 'cityblock', 'chebyshev', 'haversine'])
def test_metric(metric):
data = (grocs.to_crs(4326) if (metric == 'haversine') else grocs)
if ((not HAS_SKLEARN) and (metric in ['chebyshev', 'haversine'])):
pytest.skip('metric not supported by scipy')
(head, ... |
class EmbedSend(discord.ui.Button):
view: EmbedBuilder
def __init__(self, channel: discord.TextChannel):
self.channel = channel
super().__init__(label='Send to #{0}'.format(channel.name), style=discord.ButtonStyle.green)
async def callback(self, interaction: discord.Interaction) -> T.Any:
... |
def initialise_colour_map(book):
book.colour_map = {}
book.colour_indexes_used = {}
if (not book.formatting_info):
return
for i in xrange(8):
book.colour_map[i] = excel_default_palette_b8[i]
dpal = default_palette[book.biff_version]
ndpal = len(dpal)
for i in xrange(ndpal):
... |
def test_environment_pass_references():
options = Options(platform='linux', command_line_arguments=CommandLineArguments.defaults(), env={'CIBW_ENVIRONMENT_PASS_LINUX': 'STARTER MAIN_COURSE', 'STARTER': 'green eggs', 'MAIN_COURSE': 'ham', 'CIBW_ENVIRONMENT': 'MEAL="$STARTER and $MAIN_COURSE"'})
parsed_environmen... |
class Effect6796(BaseEffect):
type = 'passive'
def handler(fit, module, context, projectionRange, **kwargs):
fit.modules.filteredItemMultiply((lambda mod: mod.item.requiresSkill('Small Hybrid Turret')), 'damageMultiplier', (1 / module.getModifiedItemAttr('modeDamageBonusPostDiv')), stackingPenalties=Tru... |
_module()
class FooLinearConv1d(BaseModule):
def __init__(self, linear=None, conv1d=None, init_cfg=None):
super().__init__(init_cfg)
if (linear is not None):
self.linear = build_from_cfg(linear, COMPONENTS)
if (conv1d is not None):
self.conv1d = build_from_cfg(conv1d,... |
def build_dataset_ccrop(cfg):
args = cfg.copy()
transform_rcrop = build_transform(args.rcrop_dict)
transform_ccrop = build_transform(args.ccrop_dict)
ds_dict = args.ds_dict
ds_name = ds_dict.pop('type')
ds_dict['transform_rcrop'] = transform_rcrop
ds_dict['transform_ccrop'] = transform_ccrop... |
class Hook():
stages = ('before_run', 'before_train_epoch', 'before_train_iter', 'after_train_iter', 'after_train_epoch', 'before_val_epoch', 'before_val_iter', 'after_val_iter', 'after_val_epoch', 'after_run')
def before_run(self, runner):
pass
def after_run(self, runner):
pass
def befo... |
def wrap_model(opt, modelG, modelD, flowNet):
if (opt.n_gpus_gen == len(opt.gpu_ids)):
modelG = myModel(opt, modelG)
modelD = myModel(opt, modelD)
flowNet = myModel(opt, flowNet)
else:
if (opt.batchSize == 1):
gpu_split_id = (opt.n_gpus_gen + 1)
modelG = n... |
def apply_definition(words, args, raw_expansion, def_name):
global valid_prefixes
arg_dict = {}
num_words_left = len(words)
for i in range((len(args) - 1), (- 1), (- 1)):
arg_start = (num_words_left - 1)
while ((arg_start > 1) and (words[(arg_start - 1)] == ':')):
arg_start -... |
class MLPNet(nn.Module):
def __init__(self):
super(MLPNet, self).__init__()
self.fc1 = nn.Linear((28 * 28), 256)
self.fc2 = nn.Linear(256, 10)
def forward(self, x):
x = x.view((- 1), (28 * 28))
x = F.relu(self.fc1(x))
x = self.fc2(x)
return x |
class TotalGraph(TimeGraph):
value_params = [(_('year'), _('Distance (km)'), _('Annual Distance'), 'y'), (_('year'), _('Time (hours)'), _('Annual Time'), 'b'), (_('year'), _('Average Heart Rate (bpm)'), _('Annual Average Heart Rate'), 'r'), (_('year'), _('Average Speed (km/h)'), _('Annual Average Speed'), 'g'), (_(... |
def test_wrap_long_word_max_data_lines():
column_1 = Column('Col 1', width=10, max_data_lines=2)
column_2 = Column('Col 2', width=10, max_data_lines=2)
column_3 = Column('Col 3', width=10, max_data_lines=2)
column_4 = Column('Col 4', width=10, max_data_lines=1)
columns = [column_1, column_2, column_... |
.issue(86)
.parametrize('today', [False, True])
def test_git_dirty_notag(today: bool, wd: WorkDir, monkeypatch: pytest.MonkeyPatch) -> None:
if today:
monkeypatch.delenv('SOURCE_DATE_EPOCH', raising=False)
wd.commit_testfile()
wd.write('test.txt', 'test2')
wd('git add test.txt')
version = wd... |
class NitroMessageLengthTest(TestCase):
def setUp(self):
self.user = User.objects.create(id=50, name='bill', discriminator=5)
self.context = MessageDeletionContext.objects.create(id=50, actor=self.user, creation=dt.now(UTC))
def test_create(self):
message = DeletedMessage(id=46, author=s... |
class KeynoteSpeaker(TimeStampedModel, OrderedModel):
keynote = models.ForeignKey('conferences.Keynote', on_delete=models.CASCADE, verbose_name=_('keynote'), related_name='speakers', null=False)
user = models.ForeignKey('users.User', on_delete=models.CASCADE, null=True, blank=True, verbose_name=_('user'), relat... |
class ListParameterItem(WidgetParameterItem):
def __init__(self, param, depth):
self.targetValue = None
WidgetParameterItem.__init__(self, param, depth)
def makeWidget(self):
w = QtWidgets.QComboBox()
w.setMaximumHeight(20)
w.sigChanged = w.currentIndexChanged
w.v... |
class read_file():
def GeoTIFF(path_or_dataset, crs_key=None, data_crs=None, sel=None, isel=None, set_data=None, mask_and_scale=False, fill_values='mask'):
(xar, rioxarray) = register_modules('xarray', 'rioxarray')
if ((isel is None) and (sel is None)):
isel = {'band': 0}
opened ... |
.parametrize('\n start_datetime, end_datetime,\n repository_id, namespace_id,\n max_query_time, scroll_responses, expected_requests, expected_logs, throws\n ', [pytest.param(parse('2018-03-08'), parse('2018-04-02'), 1, 1, timedelta(seconds=10), SCROLL_RESPONSES, SCROLL_REQUESTS, SCROLL_LOGS, False, id='Scroll 3 pag... |
class AdaroundAcceptanceTests(unittest.TestCase):
.cuda
def test_adaround_resnet18_only_weights(self):
AimetLogger.set_level_for_all_areas(logging.DEBUG)
torch.cuda.empty_cache()
seed_all(1000)
model = models.resnet18().eval()
model = model.to(torch.device('cuda'))
... |
class TopicEntryList(EntryCreateMixin, IntegratedFormMixin, ListView):
context_object_name = 'entries'
template_name = 'dictionary/list/entry_list.html'
paginator_class = SafePaginator
topic = None
entry = None
view_mode = None
modes = ('regular', 'today', 'popular', 'history', 'nice', 'nice... |
def read_regression_classification(db_loc, fs, models_names, datasets, task):
fields = (['dataset', 'N', 'D'] + [m[1] for m in models_names])
results = {}
for f in fs:
results[f] = {'table': {f: [] for f in fields}, 'vals': []}
with Database(db_loc) as db:
for dataset in datasets:
... |
_dtype_float_test(only64=True, onlycpu=True)
def test_equil_mem(dtype, device):
def _test_equil():
clss = DummyModule
torch.manual_seed(100)
random.seed(100)
nbatch = 2000
fwd_options = {'method': 'broyden1', 'f_tol': 1e-09, 'alpha': (- 0.5)}
a = (torch.ones((nbatch,)... |
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--input_file', default=None, type=str, required=True)
parser.add_argument('--vocab_file', default=None, type=str, required=True, help='The vocabulary file that the BERT model was trained on.')
parser.add_argument('--output_file', defaul... |
class BidirectionalLSTM(nn.Module):
def __init__(self, nIn, nHidden, nOut, ngpu):
super(BidirectionalLSTM, self).__init__()
self.ngpu = ngpu
self.rnn = nn.LSTM(nIn, nHidden, bidirectional=True)
self.embedding = nn.Linear((nHidden * 2), nOut)
def forward(self, input):
(rec... |
class WebsocketClient():
def __init__(self, symbol, expiry, api_key, acess_token, underlying):
self.kws = KiteTicker(api_key, acess_token, debug=True)
self.symbol = symbol
self.expiry = expiry
self.underlying = underlying
self.instrumentClass = InstrumentMaster(api_key)
... |
def passive_grab_device(self, deviceid, time, detail, grab_type, grab_mode, paired_device_mode, owner_events, event_mask, modifiers):
return XIPassiveGrabDevice(display=self.display, opcode=self.display.get_extension_major(extname), deviceid=deviceid, grab_window=self, time=time, cursor=X.NONE, detail=detail, grab_... |
def parse_args():
parser = argparse.ArgumentParser(description='Finetune a transformers model on a multiple choice task')
parser.add_argument('--dataset_name', type=str, default=None, help='The name of the dataset to use (via the datasets library).')
parser.add_argument('--dataset_config_name', type=str, de... |
class TestAssertLess(TestCase):
def test_you(self):
self.assertLess(abc, 'xxx')
def test_me(self):
self.assertLess(123, (xxx + y))
self.assertLess(456, (aaa and bbb))
self.assertLess(789, (ccc or ddd))
self.assertLess(123, (True if You else False))
def test_everybody(... |
def train(args, model, device, train_loader, optimizer, scheduler, epoch):
model.train()
for (batch_idx, (input_ids, attention_mask, token_type_ids, cate)) in enumerate(train_loader):
input_ids = input_ids.to(device)
attention_mask = attention_mask.to(device)
token_type_ids = token_type_... |
class ViewProviderAsmRelation(ViewProviderAsmBase):
def canDropObjects(self):
return False
def canDelete(self, _obj):
return True
def claimChildren(self):
return self.ViewObject.Object.Group
def getDetailPath(self, subname, path, append):
vobj = self.ViewObject
id... |
def coco_score(refs, pred, scorer):
if (scorer.method() == 'Bleu'):
scores = np.array([0.0 for n in range(4)])
else:
scores = 0
num_cap_per_audio = len(refs[list(refs.keys())[0]])
for i in range(num_cap_per_audio):
if (i > 0):
for key in refs:
refs[key... |
class EditableModule(object):
def getparams(self, methodname: str) -> Sequence[torch.Tensor]:
paramnames = self.cached_getparamnames(methodname)
return [get_attr(self, name) for name in paramnames]
def setparams(self, methodname: str, *params) -> int:
paramnames = self.cached_getparamnam... |
class Migration(migrations.Migration):
dependencies = [('conferences', '0004_remove_conference_vote_range'), ('submissions', '0002_auto__0954'), migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('voting', '0004_auto__1733')]
operations = [migrations.DeleteModel(name='VoteRange'), migrations.AlterModel... |
def _adjoint_final_soqs(cbloq: 'CompositeBloq', new_signature: Signature) -> Dict[(str, 'SoquetT')]:
if (LeftDangle not in cbloq._binst_graph):
return {}
(_, init_succs) = _binst_to_cxns(LeftDangle, binst_graph=cbloq._binst_graph)
return _cxn_to_soq_dict(new_signature.rights(), init_succs, get_me=(l... |
class webvision_dataloader():
def __init__(self, batch_size, num_batches, num_class, num_workers, root_dir, root_imagenet_dir, log):
self.batch_size = batch_size
self.num_class = num_class
self.num_samples = (None if (num_batches is None) else (self.batch_size * num_batches))
self.nu... |
class AccountSupportView(LoginRequiredMixin, FormView):
form_class = SupportForm
template_name = 'adserver/accounts/support.html'
success_url = reverse_lazy('dashboard-home')
message_success = _('Thanks, we got your message and we will get back to you as soon as we can.')
message_error = _('There wa... |
def get_parser():
parser = argparse.ArgumentParser(description='Revise the spk2utt file: it only contans a subset of the utts', formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--in-spk2utt', type=str, help='original spk2utt file')
parser.add_argument('--out-spk2utt', type=str, h... |
class SQL2Text(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(description=_DESCRIPTION, features=datasets.Features({'question': datasets.Value('string'), 'query': datasets.Value('string')}), supervised_keys=None, homepage=' citation=_CITATION)
def _split_generators(self, d... |
def main(args):
seed_init()
if ('base' in args.model_name):
model = MANNER_BASE(in_channels=1, out_channels=1, hidden=60, depth=4, kernel_size=8, stride=4, growth=2, head=1, segment_len=64).to(args.device)
elif ('large' in args.model_name):
model = MANNER_BASE(in_channels=1, out_channels=1, ... |
class RegNet(nn.Module):
def __init__(self, cfg, in_chans=3, num_classes=1000, output_stride=32, global_pool='avg', drop_rate=0.0, drop_path_rate=0.0, zero_init_last_bn=True):
super().__init__()
self.num_classes = num_classes
self.drop_rate = drop_rate
assert (output_stride in (8, 16... |
(frozen=True)
class GenericParamRC(LocatedRequestChecker):
LOCATION = GenericParamLoc
pos: int
def _check_location(self, mediator: DirectMediator, loc: GenericParamLoc) -> None:
if (loc.generic_pos == self.pos):
return
raise CannotProvide(f'Generic param position {loc.generic_pos... |
def test_flops_counter():
with pytest.raises(AssertionError):
model = nn.Conv2d(3, 8, 3)
input_res = [1, 3, 16, 16]
get_model_complexity_info(model, input_res)
with pytest.raises(AssertionError):
model = nn.Conv2d(3, 8, 3)
input_res = tuple()
get_model_complexity_... |
class NERModel(nn.Module):
def __init__(self, args):
super().__init__()
self.args = args
config = AutoConfig.from_pretrained(args.model_name_or_path, num_labels=args.num_class)
self.model = AutoModel.from_pretrained(args.model_name_or_path)
self.dropout = nn.Dropout(args.drop... |
def test_switch_case_all_call_inputs():
with pytest.raises(Call) as err:
switch(context=Context({'list': 'sg1', 'def': 'sg3', 'sg2_input': 'sg2', 'case1': False, 'case2': True, 'sg': 'sgv', 'fg': 'fgv', 'switch': [{'case': '{case1}', 'call': '{list}'}, {'case': '{case2}', 'call': {'groups': '{sg2_input}', '... |
def find_similar_names(name: str, names: list[str]) -> list[str]:
threshold = 1000.0
distance_by_name = {}
for actual_name in names:
distance = Levenshtein.distance(name, actual_name)
is_similar = (distance <= (len(name) / 3))
substring_index = actual_name.find(name)
is_subst... |
.unit()
.parametrize(('path_1', 'path_2', 'expectation', 'expected'), [pytest.param(PurePosixPath('relative_1'), PurePosixPath('/home/relative_2'), pytest.raises(ValueError, match="Can't mix absolute and relative paths"), None, id='test path 1 is relative'), pytest.param(PureWindowsPath('C:/home/relative_1'), PureWindo... |
class AudioFile(dict, ImageContainer, HasKey):
fill_metadata = False
fill_length = False
multisong = False
streamsong = False
can_add = True
is_file = True
format = 'Unknown Audio File'
supports_rating_and_play_count_in_file = False
mimes: list[str] = []
_property
def _date_f... |
def multiple_input_model():
input1 = tf.keras.Input(name='input1', shape=(10, 10, 3))
input2 = tf.keras.Input(name='input2', shape=(12, 12, 3))
x1 = tf.keras.layers.Conv2D(8, (1, 1), name='conv1a')(input1)
x2 = tf.keras.layers.Conv2D(8, (3, 3), name='conv1b')(input2)
x = tf.keras.layers.add([x1, x2]... |
class Migration(migrations.Migration):
dependencies = [('projects', '0039_integrationoption_secret')]
operations = [migrations.CreateModel(name='IssueResource', fields=[('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('url', models.URLField(help_text='The URL o... |
class CurrentTests(BaseOutputTest):
def __init__(self, model, param, disc, solution, operating_condition):
super().__init__(model, param, disc, solution, operating_condition)
self.a_j_n = solution['Negative electrode volumetric interfacial current density [A.m-3]']
self.a_j_p = solution['Pos... |
_dataframe_method
def separate_rows(df, column_name: str, sep: str=''):
columns_original = list(df.columns)
df['id'] = df.index
wdf = pd.DataFrame(df[column_name].str.split(sep).tolist()).stack().reset_index()
wdf.rename(columns={'level_0': 'id', 0: 'revenue_items'}, inplace=True)
wdf.drop(columns=[... |
def _transform_electronic_energy(hamiltonian: ElectronicEnergy, density_total: ElectronicIntegrals, density_active: ElectronicIntegrals, active_basis: BasisTransformer, offset_name: str, *, reference_inactive_fock: (ElectronicIntegrals | None)=None, reference_inactive_energy: (float | None)=None) -> ElectronicEnergy:
... |
class PointLineDistance(PointOnLine):
_id = 8
_props = ['Distance']
_iconName = 'Assembly_ConstraintPointLineDistance.svg'
_tooltip = QT_TRANSLATE_NOOP('asm3', 'Add a "{}" to constrain the distance between a point and a linear edge in 2D or 3D')
def init(cls, obj):
infos = obj.Proxy.getEleme... |
class Solution(object):
def oddEvenList(self, head):
odd = head
if (head is None):
return None
if (head.next is None):
return head
even_head = even = head.next
while ((odd.next is not None) and (even.next is not None)):
odd.next = even.next... |
def test_execute_should_show_operation_as_cancelled_on_subprocess_keyboard_interrupt(config: Config, pool: RepositoryPool, mocker: MockerFixture, io: BufferedIO, env: MockEnv) -> None:
executor = Executor(env, pool, config, io)
executor.verbose()
mocker.patch.object(executor, '_install', return_value=(- 2))... |
class SpconvModel(nn.Module):
def __init__(self, in_channels=1, out_channels=10):
super().__init__()
self.conv = spconv.SparseConv2d(in_channels, out_channels, 1)
def forward(self, x):
nhwc_x = x.permute(0, *[i for i in range(2, len(x.shape))], 1)
spconv_input = spconv.SparseConv... |
class ScrimsClaim(discord.ui.Button):
view: ScrimsSlotmPublicView
def __init__(self, **kwargs):
super().__init__(**kwargs)
async def callback(self, interaction: discord.Interaction) -> T.Any:
if (not self.view.claimable):
(await interaction.response.send_message('No slot availabl... |
class AttrVI_ATTR_RSRC_SPEC_VERSION(RangeAttribute):
resources = AllSessionTypes
py_name = 'spec_version'
visa_name = 'VI_ATTR_RSRC_SPEC_VERSION'
visa_type = 'ViVersion'
default = 3145728
(read, write, local) = (True, False, True)
(min_value, max_value, values) = (0, , None) |
def annotation_string(word_annotation):
result = ''
for i in range(len(word_annotation.stresses)):
result += SYLLABLE_SEPARATOR
for j in range(len(word_annotation.syllables)):
if (word_annotation.stresses[i][j] == Stress.primary):
result += ' '
elif (word_... |
class DotOutputFormatter(object):
LOAD_IF = staticmethod((lambda config: (config.formatter == 'dots')))
LOAD_PRIORITY = 30
STATE_SYMBOLS = {Step.State.PASSED: '.', Step.State.PENDING: 'P', Step.State.UNTESTED: 'U', Step.State.SKIPPED: 'S', Step.State.FAILED: 'F'}
def __init__(self):
before.each_... |
class AutoPurgeEvents(Cog):
def __init__(self, bot: Quotient):
self.bot = bot
self.bot.loop.create_task(self.delete_older_snipes())
async def delete_older_snipes(self):
(await self.bot.wait_until_ready())
(await Snipe.filter(delete_time__lte=(datetime.now(tz=IST) - timedelta(days... |
class TestTensorboardPlotHook(HookTestBase):
def setUp(self) -> None:
self.base_dir = tempfile.mkdtemp()
def tearDown(self) -> None:
shutil.rmtree(self.base_dir)
def test_constructors(self) -> None:
config = {'summary_writer': {}, 'log_period': 5}
invalid_config = copy.deepco... |
class Actor(torch.nn.Module):
def __init__(self, device):
super().__init__()
self.device = device
self.mlp_policy = mlp(input_size=128, layer_sizes=[128, 64], output_size=1)
def forward(self, x, action):
logit = self.mlp_policy(torch.concat([x, action], dim=1).to(self.device))
... |
def test_one_pass():
plugin = ConsoleOutputPlugin()
dispatcher = EventDispatcher()
plugin.register(dispatcher)
graph = bonobo.Graph()
context = MagicMock(spec=GraphExecutionContext(graph))
dispatcher.dispatch(events.START, events.ExecutionEvent(context))
dispatcher.dispatch(events.TICK, even... |
class Effect2795(BaseEffect):
type = 'passive'
def handler(fit, module, context, projectionRange, **kwargs):
for type in ('kinetic', 'thermal', 'explosive', 'em'):
fit.ship.boostItemAttr((('shield' + type.capitalize()) + 'DamageResonance'), (module.getModifiedItemAttr((type + 'DamageResistan... |
def load_code_detector(bytecode):
if isinstance(bytecode, bytes):
bytecode = bytecode.hex()
result = list(re.finditer('60.{2}604052', bytecode))
load_bytecode = ''
rtcode_auxdata = bytecode
if (len(result) > 1):
position = result[1].start()
load_bytecode = bytecode[:position]... |
.parametrize(['width', 'height', 'affine_transform', 'expected_bounds'], [pytest.param(2, 2, Affine.identity(), (0.0, 2.0, 2.0, 0.0), id='Identity transform'), pytest.param(2, 2, Affine.scale(1, (- 1)), (0.0, (- 2.0), 2.0, 0.0), id='North-up transform'), pytest.param(2, 2, (Affine.translation(2, 2) * Affine.scale(1, (-... |
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