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def to_py_obj(obj):
if isinstance(obj, (dict, UserDict)):
return {k: to_py_obj(v) for (k, v) in obj.items()}
elif isinstance(obj, (list, tuple)):
return [to_py_obj(o) for o in obj]
elif (is_tf_available() and _is_tensorflow(obj)):
return obj.numpy().tolist()
elif (is_torch_availa... |
_criterion('label_smoothed_cross_entropy')
class LabelSmoothedCrossEntropyCriterion(FairseqCriterion):
def __init__(self, args, task):
super().__init__(args, task)
self.eps = args.label_smoothing
def add_args(parser):
parser.add_argument('--label-smoothing', default=0.0, type=float, meta... |
def test_matchnodes_two_collections_same_file(pytester: Pytester) -> None:
pytester.makeconftest('\n import pytest\n def pytest_configure(config):\n config.pluginmanager.register(Plugin2())\n\n class Plugin2(object):\n def pytest_collect_file(self, file_path, parent):\n ... |
class _ROIAlignRotated(Function):
def forward(ctx, input, roi, output_size, spatial_scale, sampling_ratio):
ctx.save_for_backward(roi)
ctx.output_size = _pair(output_size)
ctx.spatial_scale = spatial_scale
ctx.sampling_ratio = sampling_ratio
ctx.input_shape = input.size()
... |
class DecisionTransformerModelTester():
def __init__(self, parent, batch_size=13, seq_length=7, act_dim=6, state_dim=17, hidden_size=23, max_length=11, is_training=True):
self.parent = parent
self.batch_size = batch_size
self.seq_length = seq_length
self.act_dim = act_dim
sel... |
def get_zip_manifest(zip_root, zip_filename):
zip_path = op.join(zip_root, zip_filename)
with zipfile.ZipFile(zip_path, mode='r') as f:
info = f.infolist()
manifest = {}
for i in tqdm(info):
utt_id = op.splitext(i.filename)[0]
(offset, file_size) = (((i.header_offset + 30) + len(... |
def test(args, device_id, pt, step):
device = ('cpu' if (args.visible_gpus == '-1') else 'cuda')
if (pt != ''):
test_from = pt
else:
test_from = args.test_from
logger.info(('Loading checkpoint from %s' % test_from))
checkpoint = torch.load(test_from, map_location=(lambda storage, loc... |
def test_get_pipeline_path_absolute_path_ignore_parent():
abs_path = Path('tests/testpipelinewd.yaml').resolve()
str_abs_sans_yaml = str(abs_path.with_suffix(''))
path_found = fileloader.get_pipeline_path(str_abs_sans_yaml, 'parent')
expected_path = cwd_tests.joinpath('testpipelinewd.yaml')
assert (... |
def parse_search_arg(search):
groups = search.split()
entries = dict((g.split('=') for g in groups))
entry_names = list(entries.keys())
sets = [[f'--{k} {v}' for v in vs.split(':')] for (k, vs) in entries.items()]
matrix = [list(x) for x in itertools.product(*sets)]
return (matrix, entry_names) |
def test_change_mychar(skip_qtbot: pytestqt.qtbot.QtBot) -> None:
cosmetic_patches = CSCosmeticPatches()
dialog = CSCosmeticPatchesDialog(None, cosmetic_patches)
skip_qtbot.addWidget(dialog)
skip_qtbot.mouseClick(dialog.mychar_left_button, QtCore.Qt.MouseButton.LeftButton)
assert (dialog.cosmetic_pa... |
def _partial_compare_list(val1, val2, *, indent):
if (len(val1) < len(val2)):
outcome = PartialCompareOutcome('Second list is longer than first list')
print_i(outcome.error, indent, error=True)
return outcome
for (item1, item2) in zip(val1, val2):
outcome = partial_compare(item1,... |
class GreedyPerfPartitioner(Partitioner):
def __init__(self, sort_by: SortBy=SortBy.STORAGE, balance_modules: bool=False) -> None:
self._sort_by = sort_by
self._balance_modules = balance_modules
def partition(self, proposal: List[ShardingOption], storage_constraint: Topology) -> List[ShardingOpt... |
def test_single_output(mode):
n_steps = int64('n_steps')
x0 = float64('x0')
const = float64('const')
x = (x0 + const)
op = ScalarLoop(init=[x0], constant=[const], update=[x])
x = op(n_steps, x0, const)
fn = function([n_steps, x0, const], x, mode=mode)
np.testing.assert_allclose(fn(5, 0, ... |
def test_mice_ordering():
phi1 = mice()
phi2 = mice(phi=(1.0 + (EPSILON * 2)), partition=())
assert (phi1 < phi2)
assert (phi2 > phi1)
assert (phi1 <= phi2)
assert (phi2 >= phi1)
different_direction = mice(direction='different')
assert (phi2 > different_direction)
assert (different_d... |
def closeness_centrality(graph, name='closeness', weight='mm_len', radius=None, distance=None, verbose=True, **kwargs):
netx = graph.copy()
if radius:
lengraph = len(netx)
for n in tqdm(netx, total=len(netx), disable=(not verbose)):
sub = nx.ego_graph(netx, n, radius=radius, distance... |
class FCTDecoderLayer(nn.Module):
def __init__(self, h, d_model, p, d_ff, attn_p=0.1):
super(FCTDecoderLayer, self).__init__()
self.preprocess_attn = PrePostProcessing(d_model, p, sequence='n')
self.postprocess_attn = PrePostProcessing(d_model, p, sequence='da', static=True)
self.pre... |
class PageSerializer(ThroughModelSerializerMixin, TranslationSerializerMixin, ElementModelSerializerMixin, ElementWarningSerializerMixin, ReadOnlyObjectPermissionSerializerMixin, serializers.ModelSerializer):
model = serializers.SerializerMethodField()
uri_path = serializers.CharField(required=True)
section... |
class TestKernprof(unittest.TestCase):
def test_enable_disable(self):
profile = ContextualProfile()
self.assertEqual(profile.enable_count, 0)
profile.enable_by_count()
self.assertEqual(profile.enable_count, 1)
profile.enable_by_count()
self.assertEqual(profile.enable_... |
def write_tokenizer(tokenizer_path, input_tokenizer_path):
print(f'Fetching the tokenizer from {input_tokenizer_path}.')
os.makedirs(tokenizer_path, exist_ok=True)
write_json({}, os.path.join(tokenizer_path, 'special_tokens_map.json'))
write_json({'bos_token': '', 'eos_token': '', 'model_max_length': in... |
def test_logxml_changingdir(pytester: Pytester) -> None:
pytester.makepyfile('\n def test_func():\n import os\n os.chdir("a")\n ')
pytester.mkdir('a')
result = pytester.runpytest('--junitxml=a/x.xml')
assert (result.ret == 0)
assert pytester.path.joinpath('a/x.xml').e... |
def resp_create_group_access_token():
content = {'user_id': 141, 'scopes': ['api'], 'name': 'token', 'expires_at': '2021-01-31', 'id': 42, 'active': True, 'created_at': '2021-01-20T22:11:48.151Z', 'revoked': False}
with responses.RequestsMock(assert_all_requests_are_fired=False) as rsps:
rsps.add(method... |
def print_scatter(model, p=0.0, interface=None):
if (interface is not None):
discontinuities = [model.discontinuity(interface)]
else:
discontinuities = model.discontinuities()
for discontinuity in discontinuities:
print(('%s (%g km)' % (discontinuity, (discontinuity.z / cake.km))))
... |
class NotRequiredTests(BaseTestCase):
def test_basics(self):
if (not TYPING_3_11_0):
with self.assertRaises(TypeError):
NotRequired[1]
with self.assertRaises(TypeError):
NotRequired[(int, str)]
with self.assertRaises(TypeError):
NotRequired... |
class ConfigDict(Dict):
def __missing__(self, name):
raise KeyError(name)
def __getattr__(self, name):
try:
value = super(ConfigDict, self).__getattr__(name)
except KeyError:
ex = AttributeError("'{}' object has no attribute '{}'".format(self.__class__.__name__, n... |
def test_any_value() -> None:
any = AnyValue(AnySource.unannotated)
assert (not any.is_type(int))
assert_can_assign(any, KnownValue(1))
assert_can_assign(any, TypedValue(int))
assert_can_assign(any, MultiValuedValue([KnownValue(1), TypedValue(int)]))
assert (str(any) == 'Any[unannotated]')
a... |
def prune_model(args):
device = torch.device(('cuda:{}'.format(args.gpu) if ((args.gpu >= 0) and torch.cuda.is_available()) else 'cpu'))
if ((args.gpu >= 0) and torch.cuda.is_available()):
cudnn.benchmark = True
if (args.type == 'float64'):
dtype = torch.float64
elif (args.type == 'float... |
class BaseObject(nn.Module):
def __init__(self, name=None):
super().__init__()
self._name = name
def __name__(self):
if (self._name is None):
name = self.__class__.__name__
s1 = re.sub('(.)([A-Z][a-z]+)', '\\1_\\2', name)
return re.sub('([a-z0-9])([A-Z... |
_module
class WIDERFaceDataset(XMLDataset):
CLASSES = ('face',)
def __init__(self, **kwargs):
super(WIDERFaceDataset, self).__init__(**kwargs)
def load_annotations(self, ann_file):
img_infos = []
img_ids = mmcv.list_from_file(ann_file)
for img_id in img_ids:
filen... |
def createRelationalTables():
query = QSqlQuery()
query.exec_('create table employee(id int, name varchar(20), city int, country int)')
query.exec_("insert into employee values(1, 'Espen', 5000, 47)")
query.exec_("insert into employee values(2, 'Harald', 80000, 49)")
query.exec_("insert into employe... |
def create_inline(project, resource, offset):
pyname = _get_pyname(project, resource, offset)
message = 'Inline refactoring should be performed on a method, local variable or parameter.'
if (pyname is None):
raise exceptions.RefactoringError(message)
if isinstance(pyname, pynames.ImportedName):
... |
class PrettifyBaseEntryTestCase(unittest.TestCase):
def setUp(self):
self.element = dict(name='soccer shoes', value=(- 123.45), date='04-01', category='sport equipment')
def test_prettify(self):
self.assertEqual(prettify_entry(self.element, default_category=CategoryEntry.DEFAULT_NAME), 'Name ... |
def bench_pickle_list(loops, pickle, options):
range_it = range(loops)
dumps = pickle.dumps
obj = LIST
protocol = options.protocol
t0 = pyperf.perf_counter()
for _ in range_it:
dumps(obj, protocol)
dumps(obj, protocol)
dumps(obj, protocol)
dumps(obj, protocol)
... |
def sample_initial_conditions(model, points_to_sample, traj_length=1000, pts_per_period=30):
initial_sol = model.make_trajectory(traj_length, resample=True, pts_per_period=pts_per_period, postprocess=False)
sample_inds = np.random.choice(np.arange(initial_sol.shape[0]), points_to_sample, replace=False)
samp... |
def pairwise(accuracy_balanced, method_names, out_results_dir, num_repetitions):
bal_acc_transposed = accuracy_balanced.T
num_datasets = len(method_names)
median_bal_acc = np.nanmedian(accuracy_balanced, axis=0)
ranks = np.rank(median_bal_acc)
critical_dist = compute_critical_dist(ranks)
signif_... |
def test_translate():
mt = dlt.TranslationModel()
msg_en = 'Hello everyone, how are you?'
assert (mt.translate(msg_en, source='English', target='Spanish') == 'Hola a todos, como estas?')
fr_1 = mt.translate(msg_en, source='English', target='French')
ch = mt.translate(msg_en, source='English', target... |
class DialogueManager():
def __init__(self, rec, agent, user, bftracker):
self.tracker_idx_list = [0, 1, 2, 3, 4]
self.facet_action_dict = {'categories': 0, 'state': 1, 'city': 2, 'price': 3, 'stars': 4, 'recommend': 5}
self.rec = rec
self.agent = agent
self.user = user
... |
.parametrize('molecule, atom_index, expected', [pytest.param('water', 0, 'O', id='O'), pytest.param('water', 1, 'X', id='Polar H'), pytest.param('acetone', 4, 'H', id='Normal H')])
def test_get_param_code(molecule, atom_index, expected, request):
molecule = request.getfixturevalue(molecule)
rfree_code = _get_pa... |
class Effect5793(BaseEffect):
type = 'passive'
def handler(fit, container, context, projectionRange, **kwargs):
level = (container.level if ('skill' in context) else 1)
for attr in ('maxRangeBonus', 'falloffBonus'):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('W... |
class RandomValuePicker():
def __init__(self, pools):
self._pools = []
for pool in pools:
self._pools.append(pool)
def _cell_size(self):
return self._pools[0]['cell_size']
def _get_static_size(self, th):
return ((th * 8000) * self._cell_size())
def _get_size(s... |
def apply_along_last_axis(func, *args, **kwargs):
first_arg_name = getfullargspec(func)[0][0]
has_positional_arg = (len(args) > 0)
input_arg = (args[0] if has_positional_arg else kwargs[first_arg_name])
if (input_arg.ndim == 1):
ret = func(*args, **kwargs)
else:
if (len(args) == 0):
... |
def test_region_locked_error():
with pytest.raises(exceptions.VideoUnavailable):
raise exceptions.VideoRegionBlocked('hZpzr8TbF08')
try:
raise exceptions.VideoRegionBlocked('hZpzr8TbF08')
except exceptions.VideoRegionBlocked as e:
assert (e.video_id == 'hZpzr8TbF08')
assert (... |
def dropout(x, drop_prob, shared_axes=[], training=False):
if ((drop_prob == 0) or (drop_prob == None) or (not training)):
return x
sz = list(x.size())
for i in shared_axes:
sz[i] = 1
mask = x.new(*sz).bernoulli_((1.0 - drop_prob)).div_((1.0 - drop_prob))
mask = mask.expand_as(x)
... |
def _identify_slide(group):
def _possible_offset(all_args):
for arg1 in all_args[1]:
for (i, arg0) in enumerate(all_args[0]):
if (arg0 == arg1):
return i
return None
if (isinstance(group.abstraction, dict) and (len([v for v in group.abstraction.val... |
class RepoMirrorAPI(object):
def __init__(self, config, server_hostname=None, skip_validation=False, instance_keys=None):
feature_enabled = config.get('FEATURE_REPO_MIRROR', False)
has_valid_config = skip_validation
if ((not skip_validation) and feature_enabled):
config_validator... |
def test_error_stream(testcase: DataDrivenTestCase) -> None:
options = Options()
options.show_traceback = True
options.hide_error_codes = True
logged_messages: list[str] = []
def flush_errors(filename: (str | None), msgs: list[str], serious: bool) -> None:
if msgs:
logged_message... |
class SeedScheduler():
def has_seed_remaining(self) -> bool:
raise NotImplementedError()
def add(self, seed: Seed) -> None:
raise NotImplementedError()
def update_worklist(self, coverage: GlobalCoverage) -> None:
raise NotImplementedError()
def can_solve_models(self) -> bool:
... |
def main(gpu, ngpus_per_node, cfg, args):
args.local_rank = gpu
if (args.local_rank <= 0):
os.makedirs(args.save_path, exist_ok=True)
logger = init_log_save(args.save_path, 'global', logging.INFO)
logger.propagate = 0
if (args.local_rank <= 0):
tb_dir = args.save_path
tb = Su... |
def set_partitions(in_dict):
rules = _get_partition_rules()
replace = _replacement_rules(rules)
initd = {k: _unmatched for k in flatten_dict(in_dict)}
result = {k: replace(k, v) for (k, v) in initd.items()}
assert (_unmatched not in result.values()), 'Incomplete partition spec.'
return freeze(un... |
def generate_pairs_reverse(numCat, numRep, pre_graph):
result = []
for i in range(numCat):
cat_result = []
for j in range(len(pre_graph)):
if (i in pre_graph[j]):
cat_result.append(j)
for _ in range(numRep):
result.append(torch.tensor(cat_result))
... |
class MemoryFileObject():
def __init__(self, file):
self.file = file
if ((not getattr(self.file, 'seek', None)) or (not getattr(self.file, 'tell', None))):
raise Exception('File object does not support seeking.')
self.file.seek(0, 2)
self.file_size = self.file.tell()
... |
class LowLevelIRBuilder():
def __init__(self, current_module: str, errors: Errors, mapper: Mapper, options: CompilerOptions) -> None:
self.current_module = current_module
self.errors = errors
self.mapper = mapper
self.options = options
self.args: list[Register] = []
s... |
def calculate_SNR(pxx_pred, f_pred, currHR, signal):
currHR = (currHR / 60)
f = f_pred
pxx = pxx_pred
gtmask1 = ((f >= (currHR - 0.1)) & (f <= (currHR + 0.1)))
gtmask2 = ((f >= ((currHR * 2) - 0.1)) & (f <= ((currHR * 2) + 0.1)))
sPower = np.sum(np.take(pxx, np.where((gtmask1 | gtmask2))))
i... |
class HFProxy(Proxy):
def __init__(self, node: Node, tracer: Optional[Tracer]=None):
super().__init__(node, tracer=tracer)
if (hasattr(self, 'tracer') and (self.tracer is not None)):
self.device = self.tracer.root.device
self.dtype = next(self.tracer.root.parameters()).dtype
... |
class AbbeMaterial(Material):
def __init__(self, n=1.0, v=np.inf, lambda_ref=lambda_d, lambda_long=lambda_C, lambda_short=lambda_F, **kwargs):
super().__init__(**kwargs)
self.n = n
self.v = v
self.lambda_ref = lambda_ref
self.lambda_short = lambda_short
self.lambda_lo... |
class AverageLearner(BaseLearner):
def __init__(self, function: Callable[([int], Real)], atol: (float | None)=None, rtol: (float | None)=None, min_npoints: int=2) -> None:
if ((atol is None) and (rtol is None)):
raise Exception('At least one of `atol` and `rtol` should be set.')
if (atol... |
def test_driven_control_default_values():
_rabi_rates = np.array([np.pi, np.pi, 0])
_azimuthal_angles = np.array([(np.pi / 2), 0, (- np.pi)])
_detunings = np.array([0, 0, 0])
_durations = np.array([1, 2, 3])
_name = 'driven_control'
driven_control = DrivenControl(rabi_rates=None, azimuthal_angle... |
class Module():
def __init__(self, name, title=None, *, automodule_options=None, append=None):
self.append = append
self.name = name
self.title = (title or ' '.join(map(str.title, self.name.split('.')[1:])))
self.automodule_options = (automodule_options or list())
def __repr__(se... |
def random_date(begin: datetime.datetime, end: datetime.datetime):
epoch = datetime.datetime(1970, 1, 1)
begin_seconds = int((begin - epoch).total_seconds())
end_seconds = int((end - epoch).total_seconds())
dt_seconds = random.randint(begin_seconds, end_seconds)
return datetime.datetime.fromtimestam... |
def test_aws_session_class_endpoint():
pytest.importorskip('boto3')
sesh = AWSSession(endpoint_url='example.com')
assert (sesh.get_credential_options()['AWS_S3_ENDPOINT'] == 'example.com')
sesh = AWSSession(endpoint_url='example.com', aws_unsigned=True)
assert (sesh.get_credential_options()['AWS_S3_... |
def _multiprocessing_managers_transform():
return parse("\n import array\n import threading\n import multiprocessing.pool as pool\n import queue\n\n class Namespace(object):\n pass\n\n class Value(object):\n def __init__(self, typecode, value, lock=True):\n self._typecode ... |
class _StreamCloser(_Closer):
def __init__(self, write, close_on_exit):
self.write = write
self.close_on_exit = close_on_exit
def close(self, parent_close):
super().close(parent_close)
if self.close_on_exit:
closer = getattr(self.write, 'close', None)
if c... |
def test_multi_addr():
r2p = r2pipe.open('-', flags=['-2'])
r2p.cmd('wa mov [rax], rbx')
esilsolver = ESILSolver(r2p, debug=True, trace=False)
state = esilsolver.init_state()
state.set_symbolic_register('rax')
rax = state.registers['rax']
state.solver.add((rax > 7))
state.solver.add((rax... |
class TestPolyFillArc(EndianTest):
def setUp(self):
self.req_args_0 = {'arcs': [{'x': (- 3276), 'y': (- 22928), 'width': 33490, 'height': 20525, 'angle1': (- 10916), 'angle2': (- 19386)}], 'drawable': , 'gc': }
self.req_bin_0 = b'G\x00\x06\x00\x82\\\xc1)\x1b\xdb\x8234\xf3p\xa6\xd2\x82-P\\\xd5F\xb4'
... |
class BaseLastTransitionLog(BaseTransitionLog):
class Meta():
verbose_name = _('XWorkflow last transition log')
verbose_name_plural = _('XWorkflow last transition logs')
abstract = True
def _update_or_create(cls, unique_fields, **kwargs):
(last_transition, created) = cls.objects.... |
def get_hiformer_b_configs():
cfg = ml_collections.ConfigDict()
cfg.swin_pyramid_fm = [96, 192, 384]
cfg.image_size = 224
cfg.patch_size = 4
cfg.num_classes = 9
if (not os.path.isfile('./weights/swin_tiny_patch4_window7_224.pth')):
print('Downloading Swin-transformer model ...')
... |
class RandomMaskingGenerator():
def __init__(self, input_size, mask_ratio):
self.num_patches = int(input_size)
self.num_mask = int((mask_ratio * self.num_patches))
def __repr__(self):
repr_str = 'Maks: total patches {}, mask patches {}'.format(self.num_patches, self.num_mask)
ret... |
def seek_backward(_request: WSGIRequest) -> None:
player.seek_backward(SEEK_DISTANCE)
try:
current_song = models.CurrentSong.objects.get()
now = timezone.now()
current_song.created += datetime.timedelta(seconds=SEEK_DISTANCE)
current_song.created = min(current_song.created, now)
... |
def create_data_files(input_path: str, output_path: str, download: bool):
input_path = os.path.expanduser(input_path)
output_path = os.path.expanduser(output_path)
if download:
os.makedirs(input_path, exist_ok=True)
output_train_folder = os.path.join(output_path, 'train')
train_set = PatchCa... |
def main(args):
assert (args.dataset in ['mnist', 'cifar', 'svhn']), "Dataset parameter must be either 'mnist', 'cifar' or 'svhn'"
assert (args.attack in ['fgsm', 'bim-a', 'bim-b', 'jsma', 'cw-l2', 'all']), "Attack parameter must be either 'fgsm', 'bim-a', 'bim-b', 'jsma' or 'cw-l2'"
assert (args.characteri... |
class RandomUsernameTest(BaseActionTest):
user_data_body = json.dumps({'id': 1, 'avatar_url': ' 'gravatar_id': 'somehexcode', 'url': ' 'name': 'monalisa foobar', 'company': 'GitHub', 'blog': ' 'location': 'San Francisco', 'email': '', 'hireable': False, 'bio': 'There once was...', 'public_repos': 2, 'public_gists':... |
class RayExecutor():
def set_env_var(self, key: str, value: str):
if (value is not None):
value = str(value)
os.environ[key] = value
def set_env_vars(self, keys: List[str], values: List[str]):
assert (len(keys) == len(values))
for (key, value) in zip(keys, values)... |
class PushTImageEnv(PushTEnv):
metadata = {'render.modes': ['rgb_array'], 'video.frames_per_second': 10}
def __init__(self, legacy=False, block_cog=None, damping=None, render_size=96):
super().__init__(legacy=legacy, block_cog=block_cog, damping=damping, render_size=render_size, render_action=False)
... |
def update_maxmind_dbs(outdir):
print('Updating the GeoIP databases from MaxMind...')
if (not MAXMIND_LICENSE_KEY):
raise RuntimeError('No envvar MAXMIND_LICENSE_KEY. Cannot download the databases without this. Create a MaxMind account.')
for url in (MAXMIND_COUNTRY_DATABASE, MAXMIND_CITY_DATABASE):... |
class DirectSDBWriter():
def __init__(self, sdb_filename, buffering=BUFFER_SIZE, audio_type=AUDIO_TYPE_OPUS, bitrate=None, id_prefix=None, labeled=True):
self.sdb_filename = sdb_filename
self.id_prefix = (sdb_filename if (id_prefix is None) else id_prefix)
self.labeled = labeled
if (... |
class LineSegmentROI(ROI):
def __init__(self, positions=(None, None), pos=None, handles=(None, None), **args):
if (pos is None):
pos = [0, 0]
ROI.__init__(self, pos, [1, 1], **args)
if (len(positions) > 2):
raise Exception('LineSegmentROI must be defined by exactly 2 ... |
(params=[{}, {'teleporters': TeleporterShuffleMode.ONE_WAY_ANYTHING, 'translator_configuration': True}])
def layout_config(request, default_echoes_configuration):
if ('translator_configuration' in request.param):
translator_requirement = copy.copy(default_echoes_configuration.translator_configuration.transl... |
.end_to_end()
def test_parametrization_in_for_loop_with_ids(tmp_path, runner):
source = '\n import pytask\n\n for i in range(2):\n\n .task(\n "deco_task", id=str(i), kwargs={"i": i, "produces": f"out_{i}.txt"}\n )\n def example(produces, i):\n produces.write_text(str... |
def test_order_with_dependency(item_names_for):
tests_content = '\n import pytest\n\n .dependency(depends=["test_b"])\n .order("second")\n def test_a():\n pass\n\n .dependency()\n def test_b():\n pass\n '
assert (item_names_for(tests_content... |
.utils
.parametrize('arguments, func_args, expected', [(['a'], [0, 0], 0), (['b'], [1, 1], 2), (['a', 'b'], [0, 1], 1), (['b', 'a'], [0, 1], 1)])
def test_without_error(arguments, func_args, expected):
_kwargs(*arguments)
def simple_sum(alpha, beta, a=0, b=0):
return (alpha + beta)
assert (simple_su... |
def main(mode='folder'):
opt = {}
opt['dist'] = False
opt['phase'] = 'train'
opt['name'] = 'DIV2K'
opt['type'] = 'PairedImageDataset'
if (mode == 'folder'):
opt['dataroot_gt'] = 'datasets/DIV2K/DIV2K_train_HR_sub'
opt['dataroot_lq'] = 'datasets/DIV2K/DIV2K_train_LR_bicubic/X4_sub... |
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None, style='pytorch', with_cp=False, conv_cfg=None, norm_cfg=dict(type='BN'), dcn=None, gcb=None, gen_attention=None):
super(BasicBlock, self).__init__()
assert (dcn is None), 'Not i... |
()
def _django_db_helper(request: pytest.FixtureRequest, django_db_setup: None, django_db_blocker: DjangoDbBlocker) -> Generator[(None, None, None)]:
from django import VERSION
if is_django_unittest(request):
(yield)
return
marker = request.node.get_closest_marker('django_db')
if marker:... |
def modality_fcn(net_spec, data, modality):
n = net_spec
(n[('conv1_1' + modality)], n[('relu1_1' + modality)]) = conv_relu(n[data], 64, pad=100)
(n[('conv1_2' + modality)], n[('relu1_2' + modality)]) = conv_relu(n[('relu1_1' + modality)], 64)
n[('pool1' + modality)] = max_pool(n[('relu1_2' + modality)]... |
class ObjectEditForm(ObjectCreateForm):
class Meta(object):
fields = '__all__'
db_lock_storage = forms.CharField(label='Locks', required=False, widget=forms.Textarea(attrs={'cols': '100', 'rows': '2'}), help_text='In-game lock definition string. If not given, defaults will be used. This string should be... |
def test_equation_of_time():
times = pd.date_range(start='1/1/2015 0:00', end='12/31/2015 23:00', freq='H')
output = solarposition.spa_python(times, 37.8, (- 122.25), 100)
eot = output['equation_of_time']
eot_rng = (eot.max() - eot.min())
eot_1 = solarposition.equation_of_time_spencer71(times.dayofy... |
_time('14-06-15 15:44:25')
class TestListAPIView(CassandraTestCase):
def test_get(self):
thing = create_thing()
response = self.client.get(reverse('thing_listview_api'))
self.assertEqual(response.status_code, client.OK)
expected_response = [{'created_on': '2015-06-14T15:44:25Z', 'dat... |
class SlugModelTest(TestCase):
def setUp(self):
User = get_user_model()
u = User.objects.create_user('julia', password='julia')
def test_autocreateSlug(self):
pu = PytitionUser.objects.get(user__username='julia')
self.assertEqual(SlugModel.objects.count(), 0)
p = Petition... |
def test_parameterset_for_fail_at_collect(pytester: Pytester) -> None:
pytester.makeini('\n [pytest]\n {}=fail_at_collect\n '.format(EMPTY_PARAMETERSET_OPTION))
config = pytester.parseconfig()
from _pytest.mark import pytest_configure, get_empty_parameterset_mark
pytest_configure(config)
wi... |
class EnclaveCreationBreakpoint():
def __init__(self, target):
breakpoint = target.BreakpointCreateByName('oe_debug_enclave_created_hook')
breakpoint.SetScriptCallbackFunction('lldb_sgx_plugin.EnclaveCreationBreakpoint.onHit')
def onHit(frame, bp_loc, dict):
enclave_addr = frame.FindValu... |
class ANETclassification(object):
GROUND_TRUTH_FIELDS = ['database', 'taxonomy', 'version']
PREDICTION_FIELDS = ['results', 'version', 'external_data']
def __init__(self, ground_truth_filename=None, prediction_filename=None, ground_truth_fields=GROUND_TRUTH_FIELDS, prediction_fields=PREDICTION_FIELDS, subse... |
class QuantizableInception(Inception):
def __init__(self, *args, **kwargs):
super(QuantizableInception, self).__init__(*args, conv_block=QuantizableBasicConv2d, **kwargs)
self.cat = nn.quantized.FloatFunctional()
def forward(self, x):
outputs = self._forward(x)
return self.cat.ca... |
class Migration(migrations.Migration):
dependencies = [('devices', '0001_initial')]
operations = [migrations.AlterField(model_name='device', name='verification_code_expires_at', field=models.DateTimeField(default=junction.devices.models.expiry_time, verbose_name='Verification Code Expires At'), preserve_default... |
def append_call_sample_docstring(model_class, tokenizer_class, checkpoint, output_type, config_class, mask=None):
model_class.__call__ = copy_func(model_class.__call__)
model_class.__call__ = add_code_sample_docstrings(processor_class=tokenizer_class, checkpoint=checkpoint, output_type=output_type, config_class... |
def nca(similarities, targets, class_weights=None, focal_gamma=None, scale=1.0, margin=0.6, exclude_pos_denominator=True, hinge_proxynca=False, memory_flags=None):
margins = torch.zeros_like(similarities)
margins[(torch.arange(margins.shape[0]), targets)] = margin
similarities = (scale * (similarities - mar... |
class P3S_TD3(MARLAlgorithm, Serializable):
def __init__(self, base_kwargs, env, arr_actor, best_actor, dict_ph, arr_initial_exploration_policy, with_best=False, initial_beta_t=1, plotter=None, specific_type=0, target_noise_scale=0.2, target_noise_clip=0.5, target_ratio=2, target_range=0.04, lr=0.003, discount=0.99... |
class UniformPolicy(Policy, Serializable):
def __init__(self, env_spec):
Serializable.quick_init(self, locals())
self._Da = env_spec.action_space.flat_dim
super(UniformPolicy, self).__init__(env_spec)
def get_action(self, observation):
return (np.random.uniform((- 1.0), 1.0, self... |
class Git():
def __init__(self, directory):
self.directory = directory
def last_commit_time(self):
with TemporaryFile(mode='w+') as out:
with open(os.devnull, 'w') as DEVNULL:
Executable('git').check_call('log -r -1 --pretty="%ci"'.split(), cwd=self.directory, stdout=... |
def command_server(conn):
while True:
(cmd, cwd, verbose) = conn.recv()
res: subprocess.CompletedProcess = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, cwd=cwd)
if verbose:
print((f'{cwd}$ ' + ' '.join(res.args)))
print(res.stdout.decode(), en... |
def parse_replay(replay_player_path, sampled_action_path, reward):
if os.path.isfile(os.path.join(FLAGS.parsed_replay_path, 'GlobalFeatures', replay_player_path)):
return
with open(os.path.join(FLAGS.parsed_replay_path, 'GlobalInfos', replay_player_path)) as f:
global_info = json.load(f)
uni... |
_LAYERS.register_module('DCNv2')
class ModulatedDeformConv2dPack(ModulatedDeformConv2d):
_version = 2
def __init__(self, *args, **kwargs):
super(ModulatedDeformConv2dPack, self).__init__(*args, **kwargs)
self.conv_offset = nn.Conv2d(self.in_channels, (((self.deform_groups * 3) * self.kernel_size... |
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