code stringlengths 281 23.7M |
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def test_project_only(hatch, helpers, temp_dir, config_file):
config_file.model.template.plugins['default']['tests'] = False
config_file.save()
project_name = 'My.App'
with temp_dir.as_cwd():
result = hatch('new', project_name)
assert (result.exit_code == 0), result.output
project_path =... |
def _purview_inclusion(distinction_attr, distinctions, min_order, max_order):
purview_inclusion_by_order = defaultdict(defaultdict_set)
for distinction in distinctions:
for subset in map(frozenset, utils.powerset(getattr(distinction, distinction_attr), nonempty=True, min_size=min_order, max_size=max_ord... |
def check_internal_api_for_subscription(namespace_user):
plans = []
if namespace_user.organization:
query = organization_skus.get_org_subscriptions(namespace_user.id)
org_subscriptions = (list(query.dicts()) if (query is not None) else [])
for subscription in org_subscriptions:
... |
class RegExpSub(Gtk.HBox, RenameFilesPlugin, TagsFromPathPlugin):
PLUGIN_ID = 'Regex Substitution'
PLUGIN_NAME = _('Regex Substitution')
PLUGIN_DESC_MARKUP = _('Allows arbitrary regex substitutions (<tt>s/from/to/</tt>) when tagging or renaming files.')
PLUGIN_ICON = Icons.EDIT_FIND_REPLACE
__gsigna... |
def run_meteor(ref_path, mt_path, metric_path, lang='en'):
(_, out_path) = tempfile.mkstemp()
subprocess.call(['java', '-Xmx2G', '-jar', metric_path, mt_path, ref_path, '-p', '0.5 0.2 0.6 0.75', '-norm', '-l', lang], stdout=open(out_path, 'w'))
os.remove(ref_path)
os.remove(mt_path)
sys.stderr.write... |
def test_config_parse_error(capsys) -> None:
curr_dir = os.path.dirname(__file__)
config = os.path.join(curr_dir, 'file_fixtures', 'test_f0011.pylintrc')
reporter = python_ta.check_all(module_name='examples/nodes/name.py', config=config)
msg_id = reporter.messages[config][0].msg_id
assert (msg_id ==... |
class JsonReaderStringsTest(Json, ReaderTest, TestCase):
input_data = (('[' + ',\n'.join(map(json.dumps, ('foo', 'bar', 'baz')))) + ']')
()
def test_nofields(self, context):
context.write_sync(EMPTY)
context.stop()
assert (context.get_buffer() == [('foo',), ('bar',), ('baz',)])
(... |
def isolated_environment(environ: (dict[(str, Any)] | None)=None, clear: bool=False) -> Iterator[None]:
original_environ = dict(os.environ)
if clear:
os.environ.clear()
if environ:
os.environ.update(environ)
(yield)
os.environ.clear()
os.environ.update(original_environ) |
def recursive_update(directory, text_to_search, replacement_text):
filenames = glob.glob(osp.join(directory, '*'))
for filename in filenames:
if osp.isfile(filename):
if (not is_python_file(filename)):
continue
update_file(filename, text_to_search, replacement_tex... |
def test_binary(hatch, helpers, temp_dir_data, dist_name):
install_dir = ((temp_dir_data / 'data') / 'pythons')
dist = helpers.write_distribution(install_dir, dist_name)
result = hatch('python', 'find', dist_name)
assert (result.exit_code == 0), result.output
assert (result.output == helpers.dedent(... |
def get_registrykey(hive, keyname, cache_tag='', cache_size=2, maxage=timedelta(seconds=0), targetID=None, use_volatile=False, **cmdargs):
reg_cmd = ops.cmd.getDszCommand('registryquery', hive=hive, key=keyname, **cmdargs)
return ops.project.generic_cache_get(reg_cmd, cache_tag=cache_tag, cache_size=cache_size,... |
def test_add_sphinx_deprecated_directive_whit_titles():
original = 'foo\n\n Introduction\n \n\n something foo del baz ham eggs'
with_directive = deprecate.add_sphinx_deprecated_directive(original, reason='yes', version=0.9)
expected = 'foo\n\n .. deprecated:: 0.9\n yes\n\n\n Introduction\n \n\n somethin... |
('evaluation', blacklist=['model_dir', 'output_dir', 'overwrite'])
def evaluate(model_dir, output_dir, overwrite=False, evaluation_fn=gin.REQUIRED, random_seed=gin.REQUIRED, name=''):
del name
if tf.gfile.IsDirectory(output_dir):
if overwrite:
tf.gfile.DeleteRecursively(output_dir)
e... |
class TrainerBase():
def __init__(self):
self._models = OrderedDict()
self._optims = OrderedDict()
self._scheds = OrderedDict()
self._writer = None
def register_model(self, name='model', model=None, optim=None, sched=None):
if (self.__dict__.get('_models') is None):
... |
.slow
def test_conversions():
data_paths = pymedphys.zip_data_paths('trf-references-and-baselines.zip')
files_with_references = [path for path in data_paths if ((path.parent.name == 'with_reference') and (path.suffix == '.trf'))]
assert (len(files_with_references) >= 5)
files_without_references = [path ... |
def pointwise_loss(loss_function, y_rea, y_pre):
loss = None
if (loss_function.lower() == 'cross_entropy'):
loss = tf.losses.sigmoid_cross_entropy(y_rea, y_pre)
elif (loss_function.lower() == 'square'):
loss = tf.reduce_sum(tf.square((y_rea - y_pre)))
else:
raise Exception('pleas... |
def run(config):
config['drop_last'] = False
loaders = utils.get_data_loaders(**config)
net = inception_utils.load_inception_net(parallel=config['parallel'])
(pool, logits, labels) = ([], [], [])
device = 'cuda'
for (i, (x, y)) in enumerate(tqdm(loaders[0])):
x = x.to(device)
wit... |
def _qcore_assert_impl(ctx: CallContext, constraint_type: ConstraintType, positive: bool) -> ImplReturn:
left_varname = ctx.varname_for_arg('expected')
right_varname = ctx.varname_for_arg('actual')
if ((left_varname is not None) and isinstance(ctx.vars['actual'], KnownValue)):
varname = left_varname... |
def _evp_aead_encrypt(backend: Backend, cipher: _AEADTypes, nonce: bytes, data: bytes, associated_data: list[bytes], tag_length: int, ctx: typing.Any) -> bytes:
assert (ctx is not None)
aead_cipher = _evp_aead_get_cipher(backend, cipher)
assert (aead_cipher is not None)
out_len = backend._ffi.new('size_... |
.slow
.pydicom
def test_round_trip_dd2dcm2dd(loaded_dicom_dataset, logfile_delivery_data: Delivery):
original = logfile_delivery_data._filter_cps()
template = loaded_dicom_dataset
dicom = original.to_dicom(template)
processed = Delivery.from_dicom(dicom, FRACTION_GROUP)
assert np.all((np.around(orig... |
def __batch_normalization(input, is_training, decay=0.999, eps=0.001):
shape = input.get_shape().as_list()[(- 1)]
beta = tf.Variable(tf.zeros(shape), name='beta')
gamma = tf.Variable(tf.ones(shape), name='gamma')
population_mean = tf.Variable(tf.zeros(shape))
population_var = tf.Variable(tf.ones(sha... |
.parametrize('return_index', [False])
.parametrize('return_counts', [False])
.parametrize('return_inverse', [False])
def test_local_Unique_scalar(return_index, return_counts, return_inverse):
x = dscalar()
y = unique(x, return_index=return_index, return_counts=return_counts, return_inverse=return_inverse, axis=... |
def test_context_raw_positive(local_client, grpc_client):
random_image_vector = random_vector(image_vector_size)
def f(client: QdrantBase, **kwargs: Dict[(str, Any)]) -> List[models.ScoredPoint]:
return client.discover(collection_name=COLLECTION_NAME, target=10, context=[models.ContextExamplePair(posit... |
class AsyncSchemaGenerator(AsyncVisitor, SchemaGenerator):
async def _can_create_table(self, table):
self.dialect.validate_identifier(table.name)
effective_schema = self.connection.schema_for_object(table)
if effective_schema:
self.dialect.validate_identifier(effective_schema)
... |
class DatetimeFormatter(logging.Formatter):
def formatTime(self, record: LogRecord, datefmt: Optional[str]=None) -> str:
if (datefmt and ('%f' in datefmt)):
ct = self.converter(record.created)
tz = timezone(timedelta(seconds=ct.tm_gmtoff), ct.tm_zone)
dt = datetime(*ct[0:... |
class Grower(Processor):
def __init__(self, tflush=None):
Processor.__init__(self)
self._tflush = tflush
def process(self, trace):
buffer = self.get_buffer(trace)
if (buffer is None):
buffer = trace
self.set_buffer(buffer)
else:
buffer.... |
def appendIncompleteTraceLog(testruns):
testcnt = len(testruns)
testidx = 0
testrun = []
for data in testruns:
testrun.append(TestRun(data))
sysvals.vprint(('Analyzing the ftrace data (%s)...' % os.path.basename(sysvals.ftracefile)))
tp = TestProps()
tf = sysvals.openlog(sysvals.ftra... |
.parametrize('x, axis, return_index, return_inverse, return_counts, exc', [(set_test_value(pt.lscalar(), np.array(1, dtype='int64')), None, False, False, False, None), (set_test_value(pt.lvector(), np.array([1, 1, 2], dtype='int64')), None, False, False, False, None), (set_test_value(pt.lmatrix(), np.array([[1, 1], [2,... |
class ResourceBaseUnapprovedListView(LoginRequiredMixin, ResourceBaseListView, ResourceSearchMixin):
def get_queryset(self):
qs = self.model.unapproved_objects.all()
qs = self.get_queryset_search_and_is_creator(qs)
return qs
def get_context_data(self, **kwargs):
context = super()... |
def test_py_with_closure_scope():
pycode = "list1.append(1)\nlist2 = ['a', 'b', 'c']\nout = [(x, y) for x in list1 for y in list2]\nsave('out')\n"
context = Context({'list1': [0], 'list2': ['a', 'b'], 'py': pycode})
pypyr.steps.py.run_step(context)
assert (context == {'list1': [0, 1], 'list2': ['a', 'b'... |
def fcn(split):
n = caffe.NetSpec()
pydata_params = dict(split=split, mean=(104.00699, 116.66877, 122.67892), seed=1337)
if (split == 'train'):
pydata_params['sbdd_dir'] = '../data/sbdd/dataset'
pylayer = 'SBDDSegDataLayer'
else:
pydata_params['voc_dir'] = '../data/pascal/VOC2011... |
class SawyerDoorLockV2Policy(Policy):
_fully_parsed
def _parse_obs(obs):
return {'hand_pos': obs[:3], 'gripper': obs[3], 'lock_pos': obs[4:7], 'unused_info': obs[7:]}
def get_action(self, obs):
o_d = self._parse_obs(obs)
action = Action({'delta_pos': np.arange(3), 'grab_effort': 3})
... |
def test_postcmd_exception_first(capsys):
app = PluggedApp()
app.register_postcmd_hook(app.postcmd_hook_exception)
stop = app.onecmd_plus_hooks('say hello')
(out, err) = capsys.readouterr()
assert (not stop)
assert (out == 'hello\n')
assert err
assert (app.called_postcmd == 1)
app.re... |
def bn_reestimation_example():
(model, use_cuda) = load_fp32_model()
if use_cuda:
device = torch.device('cuda')
else:
device = torch.device('cpu')
dummy_input = torch.rand(1, 3, 224, 224, device=device)
quant_sim = create_quant_sim(model, dummy_input, use_cuda)
perform_qat(quant_... |
class LayoutLMv2TokenizerFast(PreTrainedTokenizerFast):
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION
max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
slow_tokenizer_class = La... |
class MathQA(MultipleChoiceTask):
VERSION = 0
DATASET_PATH = 'math_qa'
DATASET_NAME = None
def has_training_docs(self):
return True
def has_validation_docs(self):
return True
def has_test_docs(self):
return True
def training_docs(self):
if (self._training_docs... |
_on_failure
.parametrize('number_of_nodes', [2])
.parametrize('resolver_ports', [[None, 8000]])
.parametrize('enable_rest_api', [True])
.usefixtures('resolvers')
def test_api_payments_with_resolver(api_server_test_instance: APIServer, raiden_network: List[RaidenService], token_addresses, pfs_mock):
(_, app1) = raid... |
def basic_validate(net, criterion, val_batches):
print('running validation ... ', end='')
net.eval()
start = time()
with torch.no_grad():
validate_fn = val_step(compute_loss(net, criterion))
(n_data, tot_loss) = reduce((lambda a, b: ((a[0] + b[0]), (a[1] + b[1]))), starmap(validate_fn, v... |
class InfluenceMartingale():
def __init__(self, nm_solver, a_parameter, quad_limit):
self._nm_solver = nm_solver
self._quad_limit = quad_limit
self._a_parameter = a_parameter
self.reset()
def reset(self):
self._t_prev = None
self._continuous_martingale_at_t_prev =... |
def optimization_step(A, Y, Z, beta, apply_cg, mode='prox_cg1'):
apply_A = partial(apply_cg, A)
if (mode == 'prox_exact'):
AA = A.t().mm(A)
I = torch.eye(A.size(1)).type_as(A)
A_tilde = (AA + (beta * I))
b_tilde = (A.t().mm(Y) + (beta * Z))
(X, _) = torch.gesv(b_tilde, A_... |
class BuiltinExtraMoveAndPoliciesMaker(ExtraMoveMaker, ExtraPoliciesMaker):
def _create_extra_targets(self, extra: Union[(str, Sequence[str])]) -> ExtraTargets:
if isinstance(extra, str):
return ExtraTargets((extra,))
return ExtraTargets(tuple(extra))
def make_inp_extra_move(self, me... |
class GithubOrganizationOAuth2FailTest(GithubOAuth2Test):
backend_path = 'social_core.backends.github.GithubOrganizationOAuth2'
def auth_handlers(self, start_url):
url = '
HTTPretty.register_uri(HTTPretty.GET, url, status=404, body='{"message": "Not Found"}', content_type='application/json')
... |
def icon_from_app(app_path):
plist_path = os.path.join(app_path, 'Contents', 'Info.plist')
with open(plist_path, 'rb') as h:
plist = plistlib.load(h)
icon_name = plist['CFBundleIconFile']
(icon_root, icon_ext) = os.path.splitext(icon_name)
if (not icon_ext):
icon_ext = '.icns'
ic... |
class TestConfigureWindow(EndianTest):
def setUp(self):
self.req_args_0 = {'attrs': {'width': 39387, 'stack_mode': 2, 'height': 57679, 'sibling': , 'y': (- 17512), 'x': (- 27539), 'border_width': (- 14551)}, 'window': }
self.req_bin_0 = b'\x0c\x00\x00\n\x14\xd2\xd9t\x00\x7f\x00\x00\x94m\x00\x00\xbb\... |
def test_infer_model_family():
assert (_infer_model_family('facebook/mbart-large-50-many-to-many-mmt') == 'mbart50')
assert (_infer_model_family('facebook/m2m100_418M') == 'm2m100')
assert (_infer_model_family('facebook/m2m100_1.2B') == 'm2m100')
with pytest.raises(ValueError):
_infer_model_fami... |
def get_seq(dname):
data_dir = ('%s/softmotion30_44k/%s' % (opt.data_dir, dname))
filenames = gfile.Glob(os.path.join(data_dir, '*'))
if (not filenames):
raise RuntimeError('No data files found.')
for f in filenames:
k = 0
for serialized_example in tf.python_io.tf_record_iterator... |
def _format_to_bert(params):
(_, json_file, args, file_counter, save_file) = params
if os.path.exists(save_file):
logger.info(('Ignore %s' % save_file))
return
bert = BertData(args)
logger.info(('Processing %s' % json_file))
jobs = json.load(open(json_file))
if args.tokenize:
... |
def create_split(data, split_size):
random.seed(SEED)
(inputs, outputs) = data
assert (len(inputs) == len(outputs))
indices = random.sample(range(len(inputs)), split_size)
inputs1 = [inputs[i] for i in indices]
outputs1 = [outputs[i] for i in indices]
inputs2 = [inputs[i] for i in range(len(... |
class ubmark_vvadd_opt():
def verify(memory):
is_pass = True
first_failed = (- 1)
for i in range(c_vvadd_size):
x = struct.unpack('i', memory[(c_vvadd_dest_ptr + (i * 4)):(c_vvadd_dest_ptr + ((i + 1) * 4))])[0]
if (not (x == ref[i])):
is_pass = False
... |
def test_nested_struct_record_types(client):
client = BigQueryClient(client)
recap_schema = client.schema('test_project', 'test_dataset', 'test_table_struct')
recap_fields = recap_schema.fields
assert (recap_fields[0] == UnionType(types=[NullType(), StructType(fields=[UnionType(types=[NullType(), BoolTy... |
def getConcentrableEntanglementStateSet(num_qubits, num_states, ce_mean, ce_variance=0.05):
training_set = []
for _ in range(num_states):
state_accepted = False
while (not state_accepted):
state = randomQubitState(num_qubits)
ce = getConcentrableEntanglementState(state)
... |
def test_mediator_lock_expired_with_new_block():
block_number = BlockNumber(5)
pseudo_random_generator = random.Random()
channels = mediator_make_channel_pair()
payer_transfer = factories.make_signed_transfer_for(channels[0], LockedTransferSignedStateProperties(initiator=HOP1, expiration=BlockExpiration... |
class Attribute():
__slots__ = ('name', 'default', 'validator', 'repr', 'eq', 'eq_key', 'order', 'order_key', 'hash', 'init', 'metadata', 'type', 'converter', 'kw_only', 'inherited', 'on_setattr', 'alias')
def __init__(self, name, default, validator, repr, cmp, hash, init, inherited, metadata=None, type=None, c... |
def test_send_mail_cc(db):
send_mail('Subject', 'Message', to=[''], cc=[''])
assert (len(mail.outbox) == 1)
assert (mail.outbox[0].subject == '[example.com] Subject')
assert (mail.outbox[0].body == 'Message')
assert (mail.outbox[0].from_email == settings.DEFAULT_FROM_EMAIL)
assert (mail.outbox[0... |
class SecurityCheck(AuthError):
def __init__(self, phone_prefix=None, phone_postfix=None, response=None):
super(SecurityCheck, self).__init__()
self.phone_prefix = phone_prefix
self.phone_postfix = phone_postfix
self.response = response
def __str__(self):
if (self.phone_p... |
class TestTreeSelectFunc(EvenniaTest):
def test_tree_functions(self):
self.assertTrue((tree_select.dashcount('--test') == 2))
self.assertTrue((tree_select.is_category(TREE_MENU_TESTSTR, 1) == True))
self.assertTrue((tree_select.parse_opts(TREE_MENU_TESTSTR, category_index=2) == [(3, 'Baz 1')... |
()
('-D', '--debug', is_flag=True, help='Set logging level to DEBUG to print verbose messages.')
('-q', '--quiet', is_flag=True, help='Silence all messages, this option has higher priority to `-D/--debug`.')
('images', type=click.Path(exists=True, file_okay=False, resolve_path=True, path_type=pathlib.Path), required=Tr... |
class RFCNMetaArchTest(faster_rcnn_meta_arch_test_lib.FasterRCNNMetaArchTestBase):
def _get_second_stage_box_predictor_text_proto(self):
box_predictor_text_proto = '\n rfcn_box_predictor {\n conv_hyperparams {\n op: CONV\n activation: NONE\n regularizer {\n ... |
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('in_file', help='Annotation file for closeset.')
parser.add_argument('out_file', help='Annotation file for openset.')
parser.add_argument('--merge', action='store_true', help='Merge two classes: "background" and "others" in closese... |
def test_SingleAxisTrackerMount_get_orientation(single_axis_tracker_mount):
expected = {'surface_tilt': 19., 'surface_azimuth': }
actual = single_axis_tracker_mount.get_orientation(45, 190)
for (key, expected_value) in expected.items():
err_msg = f'{key} value incorrect'
assert (actual[key] ... |
def main():
args = create_argparser().parse_args()
dist_util.setup_dist()
logger.configure(dir=args.save_dir)
logger.log('creating model and diffusion...')
(model, diffusion) = create_model_and_diffusion(image_size=args.img_size, model_name=args.model_name, dataset=args.dataset, **args_to_dict(args,... |
def get_training_set(upscale_factor):
root_dir = download_bsd300()
train_dir = join(root_dir, 'train')
crop_size = calculate_valid_crop_size(256, upscale_factor)
return DatasetFromFolder(train_dir, input_transform=input_transform(crop_size, upscale_factor), target_transform=target_transform(crop_size)) |
_module()
class DvcliveLoggerHook(LoggerHook):
def __init__(self, path, interval=10, ignore_last=True, reset_flag=True, by_epoch=True):
super(DvcliveLoggerHook, self).__init__(interval, ignore_last, reset_flag, by_epoch)
self.path = path
self.import_dvclive()
def import_dvclive(self):
... |
def printsystemtokens(args):
printT('All nt authority\\system tokens which are accessible from current thread:')
imp = Impersonate()
imp.printSystemTokensAccessible(targetPID=args['pid'], oneMaxByPid=args['oneMaxByPid'], impersonationPossibleOnly=args['impPossibleOnly'], printFull=args['printFull']) |
def segment_buffer_line(buffer_line):
is_wide_char = False
text = ''
start = 0
counter = 0
fg = 'default'
bg = 'default'
bold = False
reverse = False
if buffer_line:
last_index = (max(buffer_line.keys()) + 1)
else:
last_index = 0
for i in range(last_index):
... |
class JSONCacheHelper():
def __init__(self, func: Callable, cache_config_key: str, cache_version: int=1):
self._callable = func
self._cache_config_key = cache_config_key
self._cache_version = cache_version
self._uncacheable_arg_type_names = ('',)
def cache_clear(cache_dir: (str |... |
def get_image_info(databytes):
head = databytes[0:32]
if (len(head) != 32):
return
what = imghdr.what(None, head)
if (what == 'png'):
check = struct.unpack('>i', head[4:8])[0]
if (check != ):
return
(width, height) = struct.unpack('>ii', head[16:24])
elif ... |
class Question(Factory.Popup):
def __init__(self, msg, callback, *, yes_str: str=None, no_str: str=None, title: str=None):
Factory.Popup.__init__(self)
self.yes_str = (yes_str or _('Yes'))
self.no_str = (no_str or _('No'))
self.title = (title or _('Question'))
self.message = ... |
class PostgresBase():
def get_tokens_unprocessed(self, text, *args):
self.text = text
(yield from super().get_tokens_unprocessed(text, *args))
def _get_lexer(self, lang):
if (lang.lower() == 'sql'):
return get_lexer_by_name('postgresql', **self.options)
tries = [lang]... |
def setup(app):
app.setup_extension('sphinx.ext.autodoc')
app.add_config_value('todo_include_todos', False, False)
app.add_node(Todolist)
app.add_node(Todo, html=(visit_todo_node, depart_todo_node), latex=(visit_todo_node, depart_todo_node), text=(visit_todo_node, depart_todo_node))
app.add_directiv... |
def main():
Format()
basic_multivector_operations_3D()
basic_multivector_operations_2D()
basic_multivector_operations_2D_orthogonal()
check_generalized_BAC_CAB_formulas()
rounding_numerical_components()
derivatives_in_rectangular_coordinates()
derivatives_in_spherical_coordinates()
n... |
def create_model(opt):
model_type = opt['model_type']
for module in _model_modules:
model_cls = getattr(module, model_type, None)
if (model_cls is not None):
break
if (model_cls is None):
raise ValueError(f'Model {model_type} is not found.')
model = model_cls(opt)
... |
def _require_equal_type(method):
(method)
def out(self, other):
if (other == 0):
return method(self, other)
if ((self.type in ('oper', 'super')) and (self._dims[0] == self._dims[1]) and isinstance(other, numbers.Number)):
scale = complex(other)
other = Qobj(_d... |
def _setattr_wrapper(setattr_: Callable, expected_keys: set[str]) -> Callable:
(setattr_)
def wrapper(self, key: str, value: Any) -> None:
__dict__ = self.__dict__
if (('_tensordict' not in __dict__) or ('_non_tensordict' not in __dict__) or (key in SET_ATTRIBUTES)):
return setattr_(... |
def test_arguments_contains_all():
def manually_get_args(arg_node) -> set:
names = set()
if arg_node.args.vararg:
names.add(arg_node.args.vararg)
if arg_node.args.kwarg:
names.add(arg_node.args.kwarg)
names.update([x.name for x in arg_node.args.args])
... |
def build_host(host: str, port: int, secure: bool) -> str:
try:
address = ipaddress.ip_address(host)
except ValueError:
pass
else:
if (address.version == 6):
host = f'[{host}]'
if (port != (443 if secure else 80)):
host = f'{host}:{port}'
return host |
class MetafileChecker(ScriptBaseWithConfig):
ARGS_HELP = '<metafile> [<data-dir-or-file>]'
def add_options(self):
super(MetafileChecker, self).add_options()
def mainloop(self):
if (not self.args):
self.parser.print_help()
self.parser.exit()
elif (len(self.args... |
def _extract_expressions(node: nodes.NodeNG) -> Iterator[nodes.NodeNG]:
if (isinstance(node, nodes.Call) and isinstance(node.func, nodes.Name) and (node.func.name == _TRANSIENT_FUNCTION)):
real_expr = node.args[0]
assert node.parent
real_expr.parent = node.parent
for name in node.par... |
def string_cp866_mutator(data: str):
t_data = data.translate(CP866_CHAR_REPLACES)
try:
t_data.encode('cp866', 'strict')
except UnicodeEncodeError as e:
bad_char = e.object[e.start:e.end]
raise ValueLoadError(f'Char {bad_char!r} can not be represented at CP866', data)
return t_dat... |
('meta-baseline')
class MetaBaseline(nn.Module):
def __init__(self, encoder, encoder_args={}, method='cos', temp=10.0, temp_learnable=True):
super().__init__()
self.encoder = models.make(encoder, **encoder_args)
self.method = method
if temp_learnable:
self.temp = nn.Param... |
class VerticalFlip(DualTransform):
identity_param = False
def __init__(self):
super().__init__('apply', [False, True])
def apply_aug_image(self, image, apply=False, **kwargs):
if apply:
image = F.vflip(image)
return image
def apply_deaug_mask(self, mask, apply=False, ... |
def gather_embeddings(input_dir: Path, output_path: Optional[Path]=None, glob_pattern: Optional[str]=None, verbose: bool=False) -> None:
if (glob_pattern is None):
glob_pattern = '*.h5'
if (output_path is None):
output_path = (input_dir / 'embeddings_gathered.h5')
input_files = list(input_di... |
.parametrize('new_state', [False, True])
.parametrize('old_state', [False, True])
def test_admin_set_allow_everyone_claim(flask_app, two_player_session, mock_audit, mock_emit_session_update, old_state, new_state):
sa = MagicMock()
sa.get_current_user.return_value = database.User.get_by_id(1234)
two_player_s... |
def G_logistic_ns_pathreg(G, D, latents, pl_avg, latent_labels=None, pl_decay=0.01, gamma=2, *args, **kwargs):
(fakes, dlatents) = G(latents, labels=latent_labels, return_dlatents=True)
fake_scores = D(fakes, labels=latent_labels).float()
loss = F.binary_cross_entropy_with_logits(fake_scores, torch.ones_lik... |
def trybaseget(targetfilename, start=(- 1), end=(- 1), tail=(- 1), name=''):
if (targetfilename[0] == '"'):
targetfilename = targetfilename[1:(- 1)]
cmd = ('get "%s" ' % targetfilename)
if (name != ''):
cmd += ('-name %s ' % name)
if ((start > (- 1)) and (end == (- 1))):
cmd += (... |
def train(args, trainer, task, epoch_itr):
update_freq = (args.update_freq[(epoch_itr.epoch - 1)] if (epoch_itr.epoch <= len(args.update_freq)) else args.update_freq[(- 1)])
itr = epoch_itr.next_epoch_itr(fix_batches_to_gpus=args.fix_batches_to_gpus, shuffle=(epoch_itr.epoch >= args.curriculum))
itr = itera... |
class BaseReader(object):
def open(path):
raise NotImplementedError('Should be implemented in derived class!')
def close(path):
raise NotImplementedError('Should be implemented in derived class!')
def open_anno_file(path, anno_filename=None):
raise NotImplementedError('Should be impl... |
class UdataBaseOAuth2(BaseOAuth2):
SCOPE_SEPARATOR = ','
REDIRECT_STATE = False
DEFAULT_SCOPE = ['default']
ACCESS_TOKEN_METHOD = 'POST'
def get_user_details(self, response):
return {'username': response.get('first_name'), 'email': (response.get('email') or ''), 'first_name': response.get('f... |
def assert_module_equivalence(name: str, expected: Iterable[str], actual: Iterable[str]) -> None:
expected_normalized = sorted(expected)
actual_normalized = sorted(set(actual).difference({'__main__'}))
assert_string_arrays_equal(expected_normalized, actual_normalized, 'Actual modules ({}) do not match expec... |
def get_Nash_equilibrium(alphas):
a = alphas[0]
b = alphas[1]
if (((a + b) > 1.0) or ((a < eps) and (b < eps))):
return (0.0, 0.0, 1.0, 1.0)
x = 0.0
y = 0.0
while True:
(X, R1) = get_optimal_strategy(a, b, y)
(Y, R2) = get_optimal_strategy(b, a, x)
if ((abs((X - x... |
def test_local_filename_installed_malformed(tmpdir, monkeypatch, caplog):
monkeypatch.setattr(spell, 'dictionary_dir', (lambda : str(tmpdir)))
for lang_file in ['en-US-11-0.bdic', 'en-US-7-1.bdic', 'en-US.bdic']:
(tmpdir / lang_file).ensure()
with caplog.at_level(logging.WARNING):
assert (sp... |
def test_ls(client):
client = BigQueryClient(client)
assert (client.ls('test_project') == ['test_dataset'])
assert (client.ls('test_project', 'test_dataset') == ['test_table', 'test_table_required', 'test_table_struct', 'test_table_repeated', 'test_table_repeated_records', 'test_table_description']) |
def save_snapshot(model, dataset_name, uid, typ, optimizer=None, root='models_checkpoints'):
snapshot_path = os.path.join(root, dataset_name, model.name, ('%s_%s_%s' % (dataset_name, model.name, uid)))
fname = ('%s_%s_%s_%%s.pth.tar' % (dataset_name, model.name, uid))
save_path = os.path.join(snapshot_path,... |
class _FunctionType(PySMTType):
_instances = {}
def __init__(self, return_type, param_types):
PySMTType.__init__(self)
self._return_type = return_type
self._param_types = tuple(param_types)
self._hash = (hash(return_type) + sum((hash(p) for p in param_types)))
self.args =... |
def translate(opt):
ArgumentParser.validate_translate_opts(opt)
logger = init_logger(opt.log_file)
translator = build_translator(opt, report_score=True)
src_shards = split_corpus(opt.src, opt.shard_size)
edge_index_shards = split_corpus(opt.edge_index, opt.shard_size)
edge_type_shards = split_co... |
def batch_ber(output, target, class_ids=[1, 2]):
predict = torch.argmax(output.long(), 1)
target = target.long()
bers = torch.zeros(3)
bers_count = torch.zeros(3)
bers_count[0] = 1
for class_id in class_ids:
valid = (target == class_id)
if (valid.sum() == 0):
continue... |
class MHTMLWriter():
def __init__(self, root_content, content_location, content_type):
self.root_content = root_content
self.content_location = content_location
self.content_type = content_type
self._files: MutableMapping[(QUrl, _File)] = {}
def add_file(self, location, content, ... |
def get_scene_graphs(start_index=0, end_index=(- 1), data_dir='data/', image_data_dir='data/by-id/', min_rels=0, max_rels=100):
images = {img.id: img for img in get_all_image_data(data_dir)}
scene_graphs = []
img_fnames = os.listdir(image_data_dir)
if (end_index < 1):
end_index = len(img_fnames)... |
def _dir2(obj, pref=_NN, excl=(), slots=None, itor=_NN):
if slots:
if hasattr(obj, slots):
s = {}
for c in type(obj).mro():
n = _nameof(c)
for a in getattr(c, slots, ()):
if a.startswith('__'):
a = (('_' + n)... |
class CriterionAdv(nn.Module):
def __init__(self, adv_type):
super(CriterionAdv, self).__init__()
if ((adv_type != 'wgan-gp') and (adv_type != 'hinge')):
raise ValueError('adv_type should be wgan-gp or hinge')
self.adv_loss = adv_type
def forward(self, d_out_S, d_out_T):
... |
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