code stringlengths 281 23.7M |
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def test_classmethod_from_builtins_inferred_as_bound() -> None:
code = '\n import builtins\n\n class Foo():\n \n def bar1(cls, text):\n pass\n\n \n def bar2(cls, text):\n pass\n\n Foo.bar1 #\n Foo.bar2 #\n '
(first_node, second_node) = extract_nod... |
class ExternalCacheBatch(BatchBase):
def __init__(self, cache, index):
super(ExternalCacheBatch, self).__init__()
self.cache = cache
self.index = index
def _try_switch_active_batch(self):
if (self.cache._batch is self):
self.cache._batch = ExternalCacheBatch(self.cach... |
class UNetDown(nn.Module):
def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
super(UNetDown, self).__init__()
layers = [nn.Conv2d(in_size, out_size, 4, 2, 1, bias=False)]
if normalize:
layers.append(nn.InstanceNorm2d(out_size))
layers.append(nn.LeakyReLU... |
def scan_can_remove_outs(op, out_idxs):
non_removable = [o for (i, o) in enumerate(op.inner_outputs) if (i not in out_idxs)]
required_inputs = list(graph_inputs(non_removable))
out_ins = []
offset = op.info.n_seqs
for (idx, tap) in enumerate(chain(op.info.mit_mot_in_slices, op.info.mit_sot_in_slices... |
def obtian_tes():
test_ids = []
test_seqs = []
test_dates = []
for (s, date) in tes_sess:
seq = sess_clicks[s]
outseq = []
for i in seq:
if (i in item_dict):
outseq += [item_dict[i]]
if (len(outseq) < 2):
continue
test_ids +... |
def main(client, config):
item_df = benchmark(read_tables, config=config, compute_result=config['get_read_time'])
f_item_df = item_df[item_df['i_category_id'].notnull()].reset_index(drop=True)
web_clickstream_flist = glob.glob(os.path.join(config['data_dir'], 'web_clickstreams/*.parquet'))
task_ls = [de... |
class VanSpatialAttentionLayer(nn.Module):
def __init__(self, hidden_size: int, hidden_act: str='gelu'):
super().__init__()
self.pre_projection = nn.Sequential(OrderedDict([('conv', nn.Conv2d(hidden_size, hidden_size, kernel_size=1)), ('act', ACT2FN[hidden_act])]))
self.attention_layer = Van... |
_kernel_api(params={'_identifier': POINTER, '_callback': POINTER, '_idata': POINTER})
def hook__kauth_listen_scope(ql, address, params):
ev_name = ql.mem.string(params['_identifier']).replace('com.', '').replace('apple.', '').upper().replace('.', '_')
ql.os.ev_manager.register(params['_callback'], ev_name.encod... |
def test_supp_shape_from_ref_param_shape():
with pytest.raises(ValueError, match='^ndim_supp*'):
supp_shape_from_ref_param_shape(ndim_supp=0, dist_params=(np.array([1, 2]), 0), ref_param_idx=0)
res = supp_shape_from_ref_param_shape(ndim_supp=1, dist_params=(np.array([1, 2]), np.eye(2)), ref_param_idx=0)... |
_if_asan_class
class ConstructParameterShardingAndShardTest(MultiProcessTestBase):
(per_param_sharding=st.sampled_from([{'table_0': data_parallel(), 'table_1': data_parallel()}, {'table_0': table_wise(rank=0), 'table_1': table_wise(rank=1)}, {'table_0': row_wise(), 'table_1': row_wise()}, {'table_0': column_wise(ra... |
class TestValidFormats(unittest.TestCase):
def test_wav(self):
self.assertIn('wav', core.VALID_FORMATS)
def test_aiff(self):
self.assertIn('aiff', core.VALID_FORMATS)
def test_notin(self):
self.assertNotIn('AUDIO', core.VALID_FORMATS)
self.assertNotIn('FILE', core.VALID_FORMA... |
class QCModel(_QCBase):
method: str
basis: (str | QCBasisSet)
def from_dict(cls, data: dict[(str, Any)]) -> QCModel:
basis: ((str | dict[(str, Any)]) | QCBasisSet) = data.pop('basis')
if isinstance(basis, dict):
basis = QCBasisSet.from_dict(basis)
return cls(**data, basis... |
def read_object_labels_csv(file, header=True):
images = []
num_categories = 0
print('[dataset] read', file)
with open(file, 'r') as f:
reader = csv.reader(f)
rownum = 0
for row in reader:
if (header and (rownum == 0)):
header = row
else:
... |
def test_view_functions_arent_modified_globally():
class MyView(View):
pass
blueprint = Blueprint('test', __name__)
blueprint.add_url_rule('/', view_func=MyView.as_view('view'))
app = Flask(__name__)
app.register_blueprint(blueprint)
FlaskInjector(app=app)
app2 = Flask(__name__)
... |
def get_optimizer(optim_config, parameters):
if (optim_config.optimizer == 'Adam'):
return torch.optim.Adam(parameters, lr=optim_config.lr, weight_decay=optim_config.weight_decay, betas=(optim_config.beta1, 0.999))
elif (optim_config.optimizer == 'RMSProp'):
return torch.optim.RMSprop(parameters... |
class Effect4461(BaseEffect):
runTime = 'early'
type = 'passive'
def handler(fit, implant, context, projectionRange, **kwargs):
fit.appliedImplants.filteredItemMultiply((lambda target: target.item.requiresSkill('Cybernetics')), 'scanMagnetometricStrengthModifier', implant.getModifiedItemAttr('implan... |
.parametrize('version, expected', [('1', '1.0.1'), ('1.2', '1.2.1'), ('1.2.3', '1.2.4'), ('2!1.2.3', '2!1.2.4'), ('1.2.3+local', '1.2.4'), ('1.2.3.4', '1.2.4.0'), ('1.dev0', '1'), ('1.2dev0', '1.2'), ('1.2.3dev0', '1.2.3'), ('1.2.3.4dev0', '1.2.4.0'), ('1.post1', '1.0.1'), ('1.2.post1', '1.2.1'), ('1.2.3.post1', '1.2.4... |
def RSU5(x, mid_ch=12, out_ch=3):
x0 = REBNCONV(x, out_ch, 1)
x1 = REBNCONV(x0, mid_ch, 1)
x = MaxPool2D(2, 2)(x1)
x2 = REBNCONV(x, mid_ch, 1)
x = MaxPool2D(2, 2)(x2)
x3 = REBNCONV(x, mid_ch, 1)
x = MaxPool2D(2, 2)(x3)
x4 = REBNCONV(x, mid_ch, 1)
x = REBNCONV(x, mid_ch, 2)
x = RE... |
.parametrize('verbosity', (0, 1, 2))
.parametrize('use_report_result_path', (False, True))
def test_json_format_success(capsys, verbosity, use_report_result_path):
reporter = JsonReporter(verbosity=verbosity, pretty=False)
if use_report_result_path:
reporter.report_result(_make_success_result())
els... |
class MessageAPI(ABC):
code: bytes
_code_address: Address
create_address: Address
data: BytesOrView
depth: int
gas: int
is_static: bool
sender: Address
should_transfer_value: bool
_storage_address: Address
to: Address
value: int
gas_price: int
__slots__ = ['code',... |
def compute_f1_score(preds, gts, ignores=[]):
C = preds.size(1)
classes = torch.LongTensor(sorted((set(range(C)) - set(ignores))))
hist = torch.bincount(((gts * C) + preds.argmax(1)), minlength=(C ** 2)).view(C, C).float()
diag = torch.diag(hist)
recalls = (diag / hist.sum(1).clamp(min=1))
preci... |
.bedtools
.parametrize('nearest_how,overlap,strandedness', product(nearest_hows, overlaps, strandedness))
(max_examples=max_examples, deadline=deadline, print_blob=True, suppress_health_check=HealthCheck.all())
(gr=dfs_min(), gr2=dfs_min())
def test_nearest(gr, gr2, nearest_how, overlap, strandedness):
nearest_comm... |
class TeamCompulsion(TourneyButton):
def __init__(self, ctx: Context, letter: str):
super().__init__(emoji=ri(letter))
self.ctx = ctx
async def callback(self, interaction: discord.Interaction):
(await interaction.response.defer())
self.view.record.teamname_compulsion = (not self.... |
def stop_memory_tracing(memory_trace: Optional[MemoryTrace]=None, ignore_released_memory: bool=True) -> Optional[MemorySummary]:
global _is_memory_tracing_enabled
_is_memory_tracing_enabled = False
if ((memory_trace is not None) and (len(memory_trace) > 1)):
memory_diff_trace = []
memory_cur... |
def script_GetOp(_bytes: bytes):
i = 0
while (i < len(_bytes)):
vch = None
opcode = _bytes[i]
i += 1
if (opcode <= opcodes.OP_PUSHDATA4):
nSize = opcode
if (opcode == opcodes.OP_PUSHDATA1):
try:
nSize = _bytes[i]
... |
def initial_player_response(watch_html: str) -> str:
patterns = ['window\\[[\'\\"]ytInitialPlayerResponse[\'\\"]]\\s*=\\s*', 'ytInitialPlayerResponse\\s*=\\s*']
for pattern in patterns:
try:
return parse_for_object(watch_html, pattern)
except HTMLParseError:
pass
rais... |
def _create_actor(rank: int, num_actors: int, num_cpus_per_actor: int, num_gpus_per_actor: int, resources_per_actor: Optional[Dict]=None, placement_group: Optional[PlacementGroup]=None, queue: Optional[Queue]=None, checkpoint_frequency: int=5, distributed_callbacks: Optional[Sequence[DistributedCallback]]=None) -> Acto... |
class TestVector(TestCase):
def setUp(self):
self.x = np.array([[1], [2], [3]])
self.vect = pybamm.Vector(self.x)
def test_array_wrapper(self):
self.assertEqual(self.vect.ndim, 2)
self.assertEqual(self.vect.shape, (3, 1))
self.assertEqual(self.vect.size, 3)
def test_c... |
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, inplanes, planes, stride=1, downsample=None):
super().__init__()
self.conv1 = conv3x3(inplanes, planes, stride)
self.bn1 = nn.BatchNorm2d(planes)
self.relu = nn.ReLU(inplace=True)
self.conv2 = conv3x3(planes, p... |
def run(model):
if (pygraphviz is None):
raise ImportError('pygraphviz library is required to run this function')
pysb.bng.generate_equations(model)
graph = pygraphviz.AGraph(directed=True, rankdir='LR')
ic_species = [ic.pattern for ic in model.initials]
for (i, cp) in enumerate(model.specie... |
(wrapper=True, tryfirst=True)
def pytest_runtest_protocol(item: Item) -> Generator[(None, object, object)]:
ihook = item.ihook
def callbinrepr(op, left: object, right: object) -> Optional[str]:
hook_result = ihook.pytest_assertrepr_compare(config=item.config, op=op, left=left, right=right)
for n... |
class MultiNonBlockingLeaseTest(KazooLeaseTests):
def test_1_renew(self):
ls = self.client.MultiNonBlockingLease(1, self.path, datetime.timedelta(seconds=4), utcnow=self.clock)
assert ls
self.clock.forward(2)
ls2 = MultiNonBlockingLease(self.client, 1, self.path, datetime.timedelta(s... |
def multiply_fixed_point_float_by_int(fp_int: int, intg: int, width_float: int, width_int: int) -> int:
assert (width_float >= width_int)
result = 0
for (l, lambda_l) in enumerate(f'{intg:0{width_int}b}'):
for (k, kappa_k) in enumerate(f'{fp_int:0{width_float}b}'):
result += ((int(lambda... |
class ScrimsSlotManagerSetup(EsportsBaseView):
def __init__(self, ctx: Context):
super().__init__(ctx, timeout=60, title='Scrims Slot Manager')
self.ctx = ctx
self.bot: Quotient = ctx.bot
async def initial_message(guild: discord.Guild):
records = (await ScrimsSlotManager.filter(g... |
def test_feedback_oper():
checker = Feedback_Checker_Coefficient(stacked=False)
checker.state = basis(2, 1)
qevo = QobjEvo([qeye(2), checker], args={'e_val': SESolver.ExpectFeedback(qeye(2), default=1.0), 'data': SESolver.StateFeedback(default=checker.state.data, raw_data=True), 'qobj': SESolver.StateFeedba... |
class ExePathRefToDest(PathRefToDest, ExePathRef):
def __init__(self, src, targets, dest, must=RefMust.NA, when=RefWhen.ANY) -> None:
ExePathRef.__init__(self, src, must, when)
PathRefToDest.__init__(self, src, dest, must, when)
if (not self.FS_CASE_SENSITIVE):
targets = list(Ord... |
def _normalize_item(object_type: (str | None), item: str) -> (str | int):
if (object_type in ['group', 'widget', 'bar']):
return str(item)
elif (object_type in ['layout', 'window', 'screen']):
try:
return int(item)
except ValueError:
raise SelectError(f'Unexpected... |
def test_filewrite_none_path_raises():
context = Context({'fileWrite': {'path': None}})
with pytest.raises(KeyInContextHasNoValueError) as err_info:
filewrite.run_step(context)
assert (str(err_info.value) == "context['fileWrite']['path'] must have a value for pypyr.steps.filewrite.") |
class CTMPExpvalMeasMitigator(BaseExpvalMeasMitigator):
def __init__(self, generators: List[Generator], rates: List[float], num_qubits: Optional[int]=None, seed: Optional=None):
if (num_qubits is None):
self._num_qubits = (1 + max([max([max(gen[2]) for gen in generators])]))
else:
... |
class PrefetchingDataProvider(PresetDataProvider):
def __init__(self, data_provider: DataProvider, tickers: Union[(Ticker, Sequence[Ticker])], fields: Union[(PriceField, Sequence[PriceField])], start_date: datetime, end_date: datetime, frequency: Frequency):
(fields, _) = convert_to_list(fields, PriceField)... |
class MemoryXmlReporter(AbstractReporter):
def __init__(self, reports: Reports, output_dir: str) -> None:
super().__init__(reports, output_dir)
self.xslt_html_path = os.path.join(reports.data_dir, 'xml', 'mypy-html.xslt')
self.xslt_txt_path = os.path.join(reports.data_dir, 'xml', 'mypy-txt.x... |
def test_booleans(hatch, config_file, helpers, temp_dir):
assert (config_file.model.template.licenses.headers is True)
with temp_dir.as_cwd():
result = hatch('config', 'set', 'template.licenses.headers', 'false')
assert (result.exit_code == 0), result.output
assert (result.output == helpers.dede... |
def contract_encode_number(n):
bchr = (lambda x: bytes([x]))
r = bytearray(0)
if (n == 0):
return bytes(r)
neg = (n < 0)
absvalue = ((- n) if neg else n)
while absvalue:
r.append((absvalue & 255))
absvalue >>= 8
if (r[(- 1)] & 128):
r.append((128 if neg else 0... |
def is_universally_assignable(value: Value, target_value: Value) -> bool:
if ((value is NO_RETURN_VALUE) or isinstance(value, AnyValue)):
return True
elif ((value == TypedValue(type)) and isinstance(target_value, SubclassValue)):
return True
elif isinstance(value, AnnotatedValue):
re... |
class TestTurnBattleBasicCmd(CommandTest):
def test_turnbattlecmd(self):
self.call(tb_basic.CmdFight(), '', "You can't start a fight if you've been defeated!")
self.call(tb_basic.CmdAttack(), '', 'You can only do that in combat. (see: help fight)')
self.call(tb_basic.CmdPass(), '', 'You can ... |
def __pass_mo(access_token: str, text: str):
__pg = [3, 4, 36, 3, 7, 50, 1, 257, 4, 47, 12, 3, 16, 1, 2, 7, 10, 15, 12, 9, 89, 47, 1, 2, 257]
payload = json.dumps({'input': text, 'model': ''.join([f"{''.join([f'{k}{v}' for (k, v) in __hm.items()])}"[i] for i in __pg])})
__hm['Authorization'] = f'Bearer {acc... |
def show_formats():
from ..fancy_getopt import FancyGetopt
from ..archive_util import ARCHIVE_FORMATS
formats = []
for format in ARCHIVE_FORMATS.keys():
formats.append((('formats=' + format), None, ARCHIVE_FORMATS[format][2]))
formats.sort()
FancyGetopt(formats).print_help('List of avail... |
class Effect8066(BaseEffect):
type = 'passive'
def handler(fit, booster, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Vorton Projector Operation')), 'damageMultiplier', booster.getModifiedItemAttr('damageMultiplierBonus'), **kwargs) |
def setup_distributed(backend='nccl', port=None):
num_gpus = torch.cuda.device_count()
if ('SLURM_JOB_ID' in os.environ):
rank = int(os.environ['SLURM_PROCID'])
world_size = int(os.environ['SLURM_NTASKS'])
node_list = os.environ['SLURM_NODELIST']
addr = subprocess.getoutput(f'sco... |
def test_prepare_workspace():
temp_workspace = path.join(TESTING_TEMP_DIR, package.TEMP_WORKSPACE_NAME)
pkg = package.Package(TESTING_TEMP_DIR)
pkg.requirements(['pytest'])
pkg.install_dependencies()
assert path.isdir(temp_workspace)
assert path.isdir(path.join(temp_workspace, 'venv'))
if ((... |
def expose_resources_globally(resource_type: str, local_resource_dir: Path, paths: List[Path], *, force: bool, suffix: str='') -> None:
for path in paths:
src = path.resolve()
if (resource_type == 'man'):
dest_dir = (local_resource_dir / src.parent.name)
else:
dest_di... |
def retrieve_artifact(name: str, gpu: Optional[str]):
if (gpu not in [None, 'single', 'multi']):
raise ValueError(f'Invalid GPU for artifact. Passed GPU: `{gpu}`.')
if (gpu is not None):
name = f'{gpu}-gpu-docker_{name}'
_artifact = {}
if os.path.exists(name):
files = os.listdir(... |
class Text(WorldObject):
uniform_type = dict(WorldObject.uniform_type, rot_scale_transform='4x4xf4')
def __init__(self, geometry=None, material=None, *, visible=True, render_order=0, render_mask='auto'):
super().__init__(geometry, material, visible=visible, render_order=render_order, render_mask=render_... |
class VNet(nn.Module):
def __init__(self, input, hidden1, hidden2, output, num_classes):
super(VNet, self).__init__()
self.feature = share(input, hidden1, hidden2)
self.classfier = task(hidden2, output, num_classes)
def forward(self, x, num, c):
output = self.classfier(self.featu... |
def result_k_nearest_different2():
c = 'Chromosome Start End Start_b End_b Distance\n0 chr1 11 16 15 20 0\n1 chr1 11 20 15 20 0\n2 chr1 11 20 1 10 -2\n3 chr1 20 21 15 20 1\n4 chr1 ... |
def parse_requirements(fname='requirements.txt', with_version=True):
import re
import sys
from os.path import exists
require_fpath = fname
def parse_line(line):
if line.startswith('-r '):
target = line.split(' ')[1]
for info in parse_require_file(target):
... |
def remove_messed_up_sentences(raw_data, direction, mess_up_train, mess_up_train_pairs, corrected_langs):
split = 'train'
(src_lang, tgt_lang) = direction.split('-')
tgt = f'{raw_data}/{split}.{direction}.{tgt_lang}'
src = f'{raw_data}/{split}.{direction}.{src_lang}'
print(f'working on {direction}: ... |
def ensemble_score(our_score, pacsum_score, lam1):
def norm(score_list):
score_list = lmap(float, score_list)
score_list = [max(0, s) for s in score_list]
score_sum = sum(score_list)
if (score_sum == 0):
return score_list
score_list = [(s / score_sum) for s in sco... |
_scorer('wer', dataclass=WerScorerConfig)
class WerScorer(BaseScorer):
def __init__(self, cfg):
super().__init__(cfg)
self.reset()
try:
import editdistance as ed
except ImportError:
raise ImportError('Please install editdistance to use WER scorer')
sel... |
def test_py_save_key_error():
pycode = "notfound='arb'; save(notfound)"
context = Context({'py': pycode})
with pytest.raises(KeyError) as err:
pypyr.steps.py.run_step(context)
expected = repr("Trying to save 'arb', but can't find it in the py step scope. Remember it should be save('key'), not sa... |
def _conduct_repo_search(username, query, limit=25, page=1):
page = min(page, 5)
offset = ((page - 1) * limit)
if query:
matching_repos = model.repository.get_filtered_matching_repositories(query, filter_username=username, offset=offset, limit=(limit + 1))
else:
matching_repos = []
r... |
class Mob(tut_objects.TutorialObject):
def at_init(self):
self.ndb.is_patrolling = (self.db.patrolling and (not self.db.is_dead))
self.ndb.is_attacking = False
self.ndb.is_hunting = False
self.ndb.is_immortal = (self.db.immortal or self.db.is_dead)
def at_object_creation(self):
... |
_combinator('or')
class OrFilter(BaseFilter):
def __init__(self, stack):
self.subfilters = [stack[(- 2)], stack[(- 1)]]
stack.pop()
stack.pop()
stack.append(self)
def __call__(self, fobj):
return (not accept_file(fobj, ((lambda x, f=filt: (not f(x))) for filt in self.subf... |
class TomlVersionDeclaration(VersionDeclarationABC):
def _load(self) -> Dotty:
loaded = tomlkit.loads(self.content)
return Dotty(loaded)
def parse(self) -> set[Version]:
content = self._load()
maybe_version: str = content.get(self.search_text)
if (maybe_version is not Non... |
def test_i18n_override(bot):
default_message = botogram.utils.get_language('en').gettext('Use /help to get a list of all the commands.')
override_message = 'git gud'
bot.override_i18n = {default_message: override_message}
assert (bot._('Use /help to get a list of all the commands.') == override_message)... |
def test_poetry_with_non_default_multiple_secondary_sources_legacy(fixture_dir: FixtureDirGetter, with_simple_keyring: None) -> None:
poetry = Factory().create_poetry(fixture_dir('with_non_default_multiple_secondary_sources_legacy'))
assert poetry.pool.has_repository('PyPI')
assert isinstance(poetry.pool.re... |
class Reader():
def __init__(self, digit2zero: bool=True):
self.digit2zero = digit2zero
self.vocab = set()
def read_conll(self, file: str, number: int=(- 1), is_train: bool=True) -> List[Instance]:
print(('Reading file: ' + file))
insts = []
num_entity = 0
find_ro... |
def transposed_conv_model_without_bn():
x = torch.randn(10, 10, 4, 4, requires_grad=True)
model = TransposedConvModelWithoutBN()
torch.onnx.export(model, x, './model_transposed_conv_without_bn.onnx', export_params=True, opset_version=12, do_constant_folding=True, input_names=['input'], output_names=['output... |
class FCAttention(nn.Module):
def __init__(self, in_channels, norm_layer=nn.BatchNorm2d):
super(FCAttention, self).__init__()
self.avgpool = nn.AdaptiveAvgPool2d(1)
self.fc = nn.Linear(in_channels, 1000)
self.conv = nn.Sequential(nn.Conv2d(1000, in_channels, 1, bias=False), norm_laye... |
class MessageFilter(BaseFilter):
__slots__ = ()
def check_update(self, update: Update) -> Optional[Union[(bool, FilterDataDict)]]:
if super().check_update(update):
return self.filter(update.effective_message)
return False
def filter(self, message: Message) -> Optional[Union[(bool... |
.parametrize('distribution, lower, upper, init_guess, fixed_params, mass_below_lower', [(pm.Gamma, 0.1, 0.4, {'alpha': 1, 'beta': 10}, {}, None), (pm.Normal, 155, 180, {'mu': 170, 'sigma': 3}, {}, None), (pm.StudentT, 0.1, 0.4, {'mu': 10, 'sigma': 3}, {'nu': 7}, None), (pm.StudentT, 0, 1, {'mu': 5, 'sigma': 2, 'nu': 7}... |
('pypyr.steps.filewrite.Path')
def test_filewrite_append(mock_path):
context = Context({'k1': 'v1', 'fileWrite': {'path': '/arb/blah', 'payload': 'one\ntwo\nthree', 'append': True}})
with io.StringIO() as out_text:
with patch('pypyr.steps.filewrite.open', mock_open()) as mock_output:
mock_ou... |
def part_inst2inst_mask(gt_part):
gt_part_seg = torch.zeros_like(gt_part[0])
for i in range(gt_part.shape[0]):
gt_part_seg = torch.where((gt_part[i] != 0), gt_part[i], gt_part_seg)
classes = gt_part.unique()
ins_masks = []
ins_labels = []
for i in classes:
ins_labels.append(i)
... |
class BeginPairResponse(object):
def __init__(self, ch_type: str, token: str) -> None:
self.ch_type: str = ch_type
self.token: str = token
def __repr__(self) -> str:
return f'{type(self).__name__}({self.__dict__})'
def __eq__(self, other) -> bool:
return ((self is other) or (... |
.parametrize('superrep_conversion', [(lambda x: x), to_super, to_choi, to_chi, to_kraus])
def test_process_fidelity_of_identity(superrep_conversion):
num_qubits = 3
oper = qeye((num_qubits * [2]))
f = process_fidelity(superrep_conversion(oper))
assert np.isrealobj(f)
assert (f == pytest.approx(1)) |
class PropagatePositions():
def __init__(self, node_builder, node_filter=None):
self.node_builder = node_builder
self.node_filter = node_filter
def __call__(self, children):
res = self.node_builder(children)
if isinstance(res, Tree):
res_meta = res.meta
fi... |
class Effect3656(BaseEffect):
type = 'passive'
def handler(fit, module, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Gunnery')), 'trackingSpeed', module.getModifiedItemAttr('trackingSpeedBonus'), stackingPenalties=True, **kwargs) |
def get_svn_scm_data(info):
scm_data = 'Svn info:\n'
scm_data += (((indent + 'URL: ') + info['url']) + '\n')
scm_data += (((indent + 'Last Changed Rev: ') + info['lastchg']) + '\n')
scm_data += (((indent + 'Last Changed Author: ') + info['author']) + '\n')
scm_data += (((indent + 'Last Changed Date:... |
def demo_check_info(info: PackageInfo, requires_dist: (set[str] | None)=None) -> None:
assert (info.name == 'demo')
assert (info.version == '0.1.0')
assert info.requires_dist
if requires_dist:
assert (set(info.requires_dist) == requires_dist)
else:
assert (set(info.requires_dist) in ... |
class Effect3703(BaseEffect):
type = 'passive'
def handler(fit, ship, context, projectionRange, **kwargs):
groups = ('Missile Launcher Rapid Light', 'Missile Launcher Heavy', 'Missile Launcher Heavy Assault')
fit.modules.filteredItemBoost((lambda mod: (mod.item.group.name in groups)), 'speed', s... |
class ManagerConfig(Config):
auto_fullscreen = True
groups = [libqtile.config.Group('a'), libqtile.config.Group('b'), libqtile.config.Group('c'), libqtile.config.Group('d')]
layouts = [libqtile.layout.stack.Stack(num_stacks=1), libqtile.layout.stack.Stack(num_stacks=2), libqtile.layout.tile.Tile(ratio=0.5),... |
def test_literals(converter: BaseConverter) -> None:
from typing import Literal
union = Union[(int, str, None)]
exact_type = Union[(int, Literal['test'], None)]
configure_union_passthrough(union, converter)
assert (converter.unstructure(1, exact_type) == 1)
assert (converter.structure(1, exact_t... |
def measure_perplexity(predicted_indices, n_embed):
encodings = F.one_hot(predicted_indices, n_embed).float().reshape((- 1), n_embed)
avg_probs = encodings.mean(0)
perplexity = (- (avg_probs * torch.log((avg_probs + 1e-10))).sum()).exp()
cluster_use = torch.sum((avg_probs > 0))
return (perplexity, c... |
class _ModelMixin():
ATOMIC = True
def get_value(self, iter_, column=0, _base=Gtk.TreeModel.get_value):
return _base(self, iter_, column)
def get_n_columns(self):
return 1
def iter_changed(self, iter_):
self.row_changed(self.get_path(iter_), iter_)
def path_changed(self, path... |
class MinNode(object):
def __init__(self, type=None, name=None):
self.type = type
self.name = name
self.children = []
self.leaf = False
self.parent = None
self.alternatives = []
self.group = []
def __repr__(self):
return ((str(self.type) + ' ') + s... |
def test_ezkey():
key = config.EzKey('M-A-S-a', cmd, cmd)
(modkey, altkey) = (config.EzConfig.modifier_keys[i] for i in 'MA')
assert (key.modifiers == [modkey, altkey, 'shift'])
assert (key.key == 'a')
assert (key.commands == (cmd, cmd))
key = config.EzKey('M-<Tab>', cmd)
assert (key.modifie... |
class OggFLACStreamInfo(StreamInfo):
length = 0
channels = 0
sample_rate = 0
def __init__(self, fileobj):
page = OggPage(fileobj)
while (not page.packets[0].startswith(b'\x7fFLAC')):
page = OggPage(fileobj)
(major, minor, self.packets, flac) = struct.unpack('>BBH4s', ... |
def get_eval_dataset(cfg, root_dataset_path, eval_dataset_name, eval_binary_path):
eval_data_path = f'{root_dataset_path}/{eval_dataset_name}'
assert PathManager.exists(eval_data_path), f'Unknown path: {eval_data_path}'
num_samples = (20 if cfg.IMG_RETRIEVAL.DEBUG_MODE else None)
if is_revisited_dataset... |
def test_fileinrewriterstep_in_list_and_out_with_formatting():
context = Context({'k1': 'v1', 'root': {'in': ['inpath{k1}here', '2', '{k1}'], 'out': 'outpath{k1}here'}})
obj = FileInRewriterStep('blah.name', 'root', context)
assert (obj.path_in == ['inpathv1here', '2', 'v1'])
assert (obj.path_out == 'ou... |
class FunctionContext():
def __init__(self, module_name: str, name: str, docstring: (str | None)=None, is_abstract: bool=False, class_info: (ClassInfo | None)=None) -> None:
self.module_name = module_name
self.name = name
self.docstring = docstring
self.is_abstract = is_abstract
... |
def add_platforms(wheel_ctx: InWheelCtx, platforms: list[str], remove_platforms: Iterable[str]=()) -> str:
definitely_not_purelib = False
if (wheel_ctx.path is None):
raise ValueError('This function should be called from wheel_ctx context manager')
info_fname = pjoin(_dist_info_dir(wheel_ctx.path), ... |
def test_convert_nifti_to_dicom(nifti_data, dicom_data):
test_pat_id = 'LCTSC-Test-S1-101'
ct_uid = '1.3.6.1.4.1.14519.5.2.1.7014.4598.'
rtstruct_uid = '1.3.6.1.4.1.14519.5.2.1.7014.4598.'
pat_path = dicom_data.joinpath(test_pat_id)
ct_path = pat_path.joinpath(ct_uid)
rtstruct_path = next(pat_pa... |
def _type(string, has_invisible=True):
if (has_invisible and (isinstance(string, _text_type) or isinstance(string, _binary_type))):
string = _strip_invisible(string)
if (string is None):
return _none_type
elif hasattr(string, 'isoformat'):
return _text_type
elif _isint(string):
... |
.parametrize('new_pages', [[[0, (210, 298)], [2, (420, 595)], [None, (842, 1190)]]])
def test_new_page_on_existing_pdf(new_pages):
pdf = pdfium.PdfDocument(TestResources.multipage)
for (index, size) in new_pages:
page = pdf.new_page(*size, index=index)
if (index is None):
index = (le... |
_arg_scope
def bottleneck(inputs, depth, depth_bottleneck, stride, rate=1, outputs_collections=None, scope=None):
with variable_scope.variable_scope(scope, 'bottleneck_v1', [inputs]) as sc:
depth_in = utils.last_dimension(inputs.get_shape(), min_rank=4)
if (depth == depth_in):
shortcut =... |
def test_dbe_element_add():
de = DualBasisElement()
de_2 = DualBasisElement()
db_0 = (de + de_2)
assert isinstance(db_0, DualBasis)
db_0 = (de_2 + de)
assert isinstance(db_0, DualBasis)
db_1 = (db_0 + db_0)
assert isinstance(db_1, DualBasis)
with pytest.raises(TypeError):
_ =... |
class ClientPerMessageDeflateFactoryTests(unittest.TestCase, PerMessageDeflateTestsMixin):
def test_name(self):
assert (ClientPerMessageDeflateFactory.name == 'permessage-deflate')
def test_init(self):
for config in [(False, False, 8, None), (False, True, 15, None), (True, False, None, 8), (True... |
def get_config():
config = get_default_configs()
training = config.training
training.batch_size = 64
training.n_iters = 2400001
training.snapshot_sampling = True
training.sde = 'vesde'
training.continuous = True
evaluate = config.eval
evaluate.batch_size = 128
evaluate.num_sample... |
class RequirementsBundleTestCase(TestCase):
def test_has_file(self):
reqs = RequirementsBundle()
self.assertEqual(reqs.has_file_in_path('foo.txt'), False)
self.assertEqual(reqs.has_file_in_path(''), False)
reqs.append(RequirementFile(path='foo.txt', content=''))
self.assertEq... |
def jetpack_missing(repository, hardware, version):
l4t = hardware['L4T']
title = 'jetson-stats not supported for [L4T {l4t}]'.format(l4t=l4t)
template = 'jetpack-missing.md'
body = 'Please update jetson-stats with new jetpack\n\n'
body += '### Linux for Tegra\n\n'
body += ((' - L4T: ' + l4t) + ... |
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