code stringlengths 281 23.7M |
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.testinfra_hosts('ansible://debian_bookworm', 'ansible://_bookworm')
def test_ansible_module_become(host):
user_name = host.user().name
assert (host.ansible('shell', 'echo $USER', check=False)['stdout'] == user_name)
assert (host.ansible('shell', 'echo $USER', check=False, become=True)['stdout'] == 'root')
... |
class IgnoreControl(ScalarControl):
def __init__(self, type, name, attrs, index=None):
ScalarControl.__init__(self, type, name, attrs, index)
self._value = None
def is_of_kind(self, kind):
return False
def __setattr__(self, name, value):
if (name == 'value'):
rais... |
class TestSyntheticLocate():
def setup_method(self) -> None:
self.dirpath = os.path.join(os.path.dirname(__file__), './data/')
lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
ntw = spaghetti.Network(in_data=lattice)
gdf = spaghetti.element_as_gdf(ntw, arcs=True)... |
def download_pretrained_models(method, file_ids):
save_path_root = f'./experiments/pretrained_models/{method}'
os.makedirs(save_path_root, exist_ok=True)
for (file_name, file_id) in file_ids.items():
save_path = osp.abspath(osp.join(save_path_root, file_name))
if osp.exists(save_path):
... |
class global_sttr(nn.Module):
def __init__(self, config):
super(global_sttr, self).__init__()
self.embed_channel = config.embed_channel
self.tokenizer = tokenizer(config)
encoder_layer_actor = TransformerEncoderLayer(self.embed_channel, config.Nhead, dropout=config.dropout_porb, norm... |
class CommandDispatcher():
_commands: list[Command] = field(default_factory=list)
_commands_by_trigger: dict[(str, Command)] = field(default_factory=dict)
def _register(self, command: Command) -> None:
self._commands.append(command)
self._commands_by_trigger.update({trigger: command for trig... |
def pack_rows(rows, bitdepth):
assert (bitdepth < 8)
assert ((8 % bitdepth) == 0)
spb = int((8 / bitdepth))
def make_byte(block):
res = 0
for v in block:
res = ((res << bitdepth) + v)
return res
for row in rows:
a = bytearray(row)
n = float(len(a))... |
def build_voc_dirs(outdir):
mkdir = (lambda dir: (os.makedirs(dir) if (not os.path.exists(dir)) else None))
mkdir(outdir)
mkdir(os.path.join(outdir, 'Annotations'))
mkdir(os.path.join(outdir, 'ImageSets'))
mkdir(os.path.join(outdir, 'ImageSets', 'Layout'))
mkdir(os.path.join(outdir, 'ImageSets',... |
def separate_attributes_and_event_handlers(attributes: Mapping[(str, Any)]) -> tuple[(dict[(str, Any)], EventHandlerDict)]:
separated_attributes = {}
separated_event_handlers: dict[(str, EventHandlerType)] = {}
for (k, v) in attributes.items():
handler: EventHandlerType
if callable(v):
... |
def merge_annotations(annotations, comment_annotations):
for (ann, comment_ann) in itertools.zip_longest(annotations, comment_annotations):
if (ann and (not _is_ellipsis(ann))):
(yield ann)
elif (comment_ann and (not _is_ellipsis(comment_ann))):
(yield comment_ann)
el... |
def test_partial():
C = Bobby
with inspect_node(C) as ci:
assert (ci.type == Bobby)
assert (not ci.instance)
assert (len(ci.options) == 4)
assert (len(ci.processors) == 1)
assert (not ci.partial)
f1 = MagicMock()
C = C(f1)
with inspect_node(C) as ci:
a... |
class SemisuperDecayEnv(SemisuperEnv):
DECAY_RATE = 0.999
def __init__(self):
super(SemisuperDecayEnv, self).__init__()
self.prob_get_reward = 1.0
def _distort_reward(self, true_reward):
self.prob_get_reward *= SemisuperDecayEnv.DECAY_RATE
if (self.np_random.uniform() < self.... |
def get_supported_kernel_in_dict_format(act_constraint: Dict, weight_constraint: Dict) -> Dict:
supported_kernel_in_dict_format = {'activation': {'bitwidth': act_constraint['bitwidth'], 'dtype': act_constraint['dtype']}, 'param': {'bitwidth': weight_constraint['bitwidth'], 'dtype': weight_constraint['dtype']}}
... |
class CalendarParameter(Parameter):
itemClass = CalendarParameterItem
def __init__(self, **opts):
opts.setdefault('format', 'TextDate')
super().__init__(**opts)
def _interpretFormat(self, fmt=None):
fmt = (fmt or self.opts.get('format'))
if hasattr(QtCore.Qt.DateFormat, fmt):... |
class deprecated():
def __init__(self, new_name=None, removed_after='next major patch'):
self.new_name = new_name
self.removed_after = removed_after
def __call__(self, func):
def newFunc(*args, **kwargs):
warning = ('%s is deprecated and will be removed in %s. ' % (func.__nam... |
def render_pcl_front_view(vis, cam_params=None, fn=None, img_save_fn=None, pt_size=3):
mesh = o3d.io.read_point_cloud(fn)
vis.add_geometry(mesh)
opt = vis.get_render_option()
opt.point_size = pt_size
ctr = vis.get_view_control()
ctr.convert_from_pinhole_camera_parameters(cam_params)
vis.poll... |
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_channels, channels, stride=1, groups=1, width_per_group=64, sd=0.0, **block_kwargs):
super(BasicBlock, self).__init__()
if ((groups != 1) or (width_per_group != 64)):
raise ValueError('BasicBlock only supports groups=1 ... |
def check_file(filename: str) -> List[LintMessage]:
try:
top_of_file_cat = usort_config.Category('top_of_file')
known = usort_config.known_factory()
known['__strict__'] = top_of_file_cat
known['__static__'] = top_of_file_cat
config = usort_config.Config(categories=(usort_conf... |
def test_logins_fails_with_wrong_password(graphql_client):
user = UserFactory(email='', password='test')
response = graphql_client.query('mutation($input: LoginInput!) {\n login(input: $input) {\n __typename\n }\n }', variables={'input': {'email': user.email, 'passwor... |
def get_icns(svg_path):
ICONS = [(b'is32', 16, 'icon'), (b's8mk', 16, 'mask'), (b'il32', 32, 'icon'), (b'l8mk', 32, 'mask'), (b'ic08', 256, 'png'), (b'ic09', 512, 'png'), (b'icp6', 64, 'png'), (b'ic07', 128, 'png'), (b'ic11', 32, 'png'), (b'ic12', 64, 'png'), (b'ic13', 256, 'png'), (b'ic14', 512, 'png')]
funcs ... |
class TestNcNWCSAFFileKeyPrefix():
def test_get_dataset_uses_file_key_prefix(self, nwcsaf_pps_cmic_filehandler):
dsid_cpp = {'name': 'cpp_cot'}
dsid_cmic = {'name': 'cmic_cot'}
file_key = 'cot'
info_cpp = dict(name='cpp_cot', file_key=file_key, file_type='nc_nwcsaf_cpp')
res_... |
def functionParams(args, vars):
params = {}
index = 1
for var in vars:
value = args.get(var)
if (value is None):
value = args.get(str(index))
if (value is None):
value = ''
else:
index += 1
params[var] = value
re... |
def collapse_lora(model, alpha=1.0):
for (_module, name, _child_module) in _find_modules(model, (UNET_EXTENDED_TARGET_REPLACE | TEXT_ENCODER_EXTENDED_TARGET_REPLACE), search_class=[LoraInjectedLinear, LoraInjectedConv2d]):
if isinstance(_child_module, LoraInjectedLinear):
print('Collapsing Lin L... |
def get_datasets():
configurations_all = {'Task01_BrainTumour': ('3d_fullres', '2d'), 'Task02_Heart': ('3d_fullres', '2d'), 'Task03_Liver': ('3d_cascade_fullres', '3d_fullres', '3d_lowres', '2d'), 'Task04_Hippocampus': ('3d_fullres', '2d'), 'Task05_Prostate': ('3d_fullres', '2d'), 'Task06_Lung': ('3d_cascade_fullre... |
class Cauchy(Continuous):
rv_op = cauchy
def dist(cls, alpha, beta, *args, **kwargs):
alpha = pt.as_tensor_variable(floatX(alpha))
beta = pt.as_tensor_variable(floatX(beta))
return super().dist([alpha, beta], **kwargs)
def moment(rv, size, alpha, beta):
(alpha, _) = pt.broadc... |
.parametrize('function_', ['DCV', 'ACV', 'DCI', 'R2W'])
def test_resolution(resetted_hp34401a, function_):
resetted_hp34401a.function_ = function_
resetted_hp34401a.range_ = 1
resetted_hp34401a.resolution = 0.0001
assert (len(resetted_hp34401a.check_errors()) == 0)
assert (resetted_hp34401a.resoluti... |
class ClientInput():
content: bytes
log_time: str
recv_time: str
elapsed: str
hash: str
path: str
seed_status: SeedType
fuzzer_id: bytes
fuzzer_name: str
broker_status: str
replay_status: str
replay_time: float
new_coverage: list[tuple[(int, int)]] |
def create_unique_list(apps: Apps, _):
filter_list: pydis_site.apps.api.models.FilterList = apps.get_model('api', 'FilterList')
filter_: pydis_site.apps.api.models.Filter = apps.get_model('api', 'Filter')
list_ = filter_list.objects.create(name='unique', list_type=0, guild_pings=[], filter_dm=True, dm_pings... |
def dir(root, type='f', addroot=True):
dirList = []
fileList = []
root = (root + '/')
files = os.listdir(root)
for f in files:
if os.path.isdir((root + f)):
if (addroot == True):
dirList.append((root + f))
else:
dirList.append(f)
... |
def _get_lines_for_constructing_an_object(func: Callable):
(def_line, *pre, ret_line) = inspect.getsource(func).splitlines()
assert def_line.startswith('def '), def_line
trimmed_lines = []
for line in pre:
assert ((line == '') or line.startswith((' ' * 4))), line
trimmed_lines.append(lin... |
.parametrize('helper', model_helpers)
def test_management_navigation(logged_in_admin_user: Page, helper: ModelHelper) -> None:
page = logged_in_admin_user
expect(page.get_by_role('heading', name='Management')).to_be_visible()
name = helper.verbose_name_plural
page.get_by_role('link', name=name, exact=Tr... |
class InstructionMRCForFewCLUEProcessor(CLSProcessor):
def __init__(self, data_args, training_args, model_args, tokenizer=None, post_tokenizer=False, keep_raw_data=True):
super().__init__(data_args, training_args, model_args, tokenizer, post_tokenizer=post_tokenizer, keep_raw_data=keep_raw_data)
par... |
def random_sources_in_disk(size, power, wavelength_mean, bandwidth, r):
source_list = ([None] * size)
(x0, y0) = random_in_unit_disk(size)
(x0, y0) = ((r * x0), (r * y0))
phase = ((np.random.rand(size) * 2) * np.pi)
wavelength = (wavelength_mean + (bandwidth * (np.random.rand(size) - 0.5)))
for ... |
def LoadAbsorption(layer, T, wavelengths, use_Adachi=False):
if use_Adachi:
try:
absorption = adachi_alpha.create_adachi_alpha(InLineComposition(layer), T=T, wl=wavelengths)[3]
except:
print('Warning: Using experimental data to estimate the absorption coefficient of material:... |
def test_set_parent_for_preset(tmp_path):
opt = Options(tmp_path)
u1 = uuid.UUID('b41fde84-1f57-4b79-8cd6-3e5a78077fa6')
u2 = uuid.UUID('b51fdeaa-1fff-4b79-8cd6-3e5a78077fa6')
assert (opt.get_parent_for_preset(u1) is None)
opt.set_parent_for_preset(u1, u2)
assert (opt.get_parent_for_preset(u1) =... |
class ModelUtils():
convert: dict = {'gpt-3.5-turbo': Model.gpt_35_turbo, 'gpt-3.5-turbo-0613': Model.gpt_35_turbo_0613, 'gpt-3.5-turbo-0301': Model.gpt_35_turbo_0301, 'gpt-4': Model.gpt_4, 'gpt-4-0613': Model.gpt_4_0613, 'gpt-4-for-dev': Model.gpt_4_dev, 'gpt-3.5-turbo-16k': Model.gpt_35_turbo_16k, 'gpt-3.5-turbo-... |
class Effect11999(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Small Hybrid Turret')), 'trackingSpeed', src.getModifiedItemAttr('eliteBonusGunship2'), skill='Assault Frigates', **kwargs) |
class BattleCmdSet(default_cmds.CharacterCmdSet):
key = 'DefaultCharacter'
def at_cmdset_creation(self):
self.add(CmdFight())
self.add(CmdAttack())
self.add(CmdRest())
self.add(CmdPass())
self.add(CmdDisengage())
self.add(CmdCombatHelp())
self.add(CmdLearn... |
class TestNoOperation(EndianTest):
def setUp(self):
self.req_args_0 = {}
self.req_bin_0 = b'\x7f\x00\x00\x01'
def testPackRequest0(self):
bin = request.NoOperation._request.to_binary(*(), **self.req_args_0)
self.assertBinaryEqual(bin, self.req_bin_0)
def testUnpackRequest0(se... |
def add_index(shard_dir, index_path):
data_shard_list = []
for shard_address in glob((str(shard_dir) + '/*/')):
data_shard_list.append(load_from_disk(shard_address))
concat = concatenate_datasets(data_shard_list)
faiss.omp_set_num_threads(96)
index = faiss.IndexHNSWFlat(768, 128, faiss.METRI... |
def test_gen_poll_url_xml_has_xmltodict(monkeypatch):
monkeypatch.setitem(sys.modules, 'xmltodict', Mockxml('xmltodict'))
reload(generic_poll_text)
gpurl = generic_poll_text.GenPollUrl(json=False, xml=True, parse=(lambda x: x), url='testing')
monkeypatch.setattr(generic_poll_text, 'Request', MockRequest... |
class _ConfigSettingsTranslator():
def _get_config(self, key: str, config_settings: _ConfigSettings) -> List[str]:
cfg = (config_settings or {})
opts = (cfg.get(key) or [])
return (shlex.split(opts) if isinstance(opts, str) else opts)
def _global_args(self, config_settings: _ConfigSettin... |
def collect_rst_dps(rst_file_location):
rst_dps = set()
with open(rst_file_location) as rst_file:
while ((line := rst_file.readline()) != ''):
if ((line.count('class_template.rst') > 0) or (line.count('function.rst') > 0)):
rst_file.readline()
while (((line :=... |
def slice_aspect_ratio(pixel_dim, axis):
if (pixel_dim.size != 3):
raise ValueError('pixel_dim must be an array of 3 elements for 3D images')
if (axis == 0):
aspect_ratio = (pixel_dim[2] / pixel_dim[1])
elif (axis == 1):
aspect_ratio = (pixel_dim[2] / pixel_dim[0])
elif (axis == ... |
class Container():
def __init__(self, r: Union[(Variable, Type)], storage: list[Any], *, readonly: bool=False, strict: bool=False, allow_downcast: Optional[bool]=None, name: Optional[str]=None) -> None:
if ((not isinstance(storage, list)) or (not (len(storage) >= 1))):
raise TypeError('storage m... |
def CalcuPSNR_int(img1, img2, max_val=255.0):
float_type = 'float64'
img1 = np.round((torch.clamp(img1, 0, 1).detach().cpu().numpy() * 255))
img2 = np.round((torch.clamp(img2, 0, 1).detach().cpu().numpy() * 255))
img1 = img1.astype(float_type)
img2 = img2.astype(float_type)
mse = np.mean(np.squa... |
def max_pool2d(data, l=(2, 2)):
if ((type(data) is tuple) and (len(data) == 3)):
out = (F.max_pool2d(data[0], l), F.max_pool2d(data[1], l), F.max_pool2d(data[2], l))
return out
elif ((type(data) is tuple) and (len(data) == 2)):
if (data[0] is None):
out = (F.max_pool2d(data[1... |
def main() -> None:
version = get_version()
url = f'
with urlopen(url) as response:
if (response.status >= 400):
print(f'Failed to retrieve config.proto: status {response.status}', file=sys.stderr)
sys.exit(1)
with TemporaryDirectory() as dir_name:
file_pa... |
def init_actor(actor, pool, dict_ph, env, num_q, value_fn_params, noise_params):
M1 = value_fn_params['layer_size1']
M2 = value_fn_params['layer_size2']
with tf.variable_scope(actor.name):
policy = DeterministicPolicy(env_spec=env.spec, hidden_layer_sizes=(M1, M2), reg=0.001, observation_ph=dict_ph[... |
def test_safe_getattr() -> None:
helper = ErrorsHelper()
assert (safe_getattr(helper, 'raise_exception', 'default') == 'default')
assert (safe_getattr(helper, 'raise_fail_outcome', 'default') == 'default')
with pytest.raises(BaseException):
assert safe_getattr(helper, 'raise_baseexception', 'def... |
class Test_git_describe(unittest.TestCase, Testing_renderer_case_mixin):
style = 'git-describe'
expected = {'tagged_0_commits_clean': 'v1.2.3', 'tagged_0_commits_dirty': 'v1.2.3-dirty', 'tagged_1_commits_clean': 'v1.2.3-1-gabc', 'tagged_1_commits_dirty': 'v1.2.3-1-gabc-dirty', 'untagged_0_commits_clean': '', 'u... |
def usage(msg=None):
if msg:
print(msg)
print(sys.argv[0], '[-p port] [-l logfile] [-dh] [allowed_client_name ...]]')
print()
print(' -p - Port to bind to')
print(' -l - Path to logfile. If not specified, STDOUT is used')
print(' -d - Run in the background')
p... |
def accumulate_results(game_modifications: dict, items: dict[(str, dict[(str, int)])], locations: dict[(str, dict[(str, int)])], major_progression_items_only: bool):
for (world_name, world_data) in game_modifications['locations'].items():
for (area_name, item_name) in world_data.items():
area_na... |
class CfcCell(tf.keras.layers.Layer):
def __init__(self, units, hparams, **kwargs):
super(CfcCell, self).__init__(**kwargs)
self.units = units
self.state_size = units
self.hparams = hparams
self._no_gate = False
def build(self, input_shape):
if isinstance(input_sh... |
def eval_expression(node: str, rng: np.random.RandomState, scope: dict):
true = True
false = False
def Uniform(low, high):
return rng.uniform(low, high)
def RandomAngleAxis(angle_low, angle_high, axis):
return random_angle_axis(angle_low, angle_high, axis, rng)
if (('$' in node) and ... |
def when(event_type=None, selector=None):
def decorator(func):
if isinstance(selector, str):
elements = document.querySelectorAll(selector)
else:
from pyweb import pydom
if isinstance(selector, pydom.Element):
elements = [selector._js]
... |
class NTU_Fi_ResNet(nn.Module):
def __init__(self, ResBlock, layer_list, num_classes):
super(NTU_Fi_ResNet, self).__init__()
self.reshape = nn.Sequential(nn.Conv2d(3, 3, (15, 23), stride=(3, 9)), nn.ReLU(), nn.Conv2d(3, 3, kernel_size=(3, 23), stride=1), nn.ReLU())
self.in_channels = 64
... |
.parametrize('enabled', [True, False])
def test_trigger_auto_delay_enabled(enabled):
with expected_protocol(HP34401A, [('TRIG:DEL:AUTO?', ('1' if enabled else '0')), (f'TRIG:DEL:AUTO {(1 if enabled else 0)}', None)]) as inst:
assert (enabled == inst.trigger_auto_delay_enabled)
inst.trigger_auto_dela... |
def fix_missing_data(contour_data_list):
contour_data = np.array(contour_data_list)
if (contour_data.any() == ''):
logger.warning(' Missing values detected.')
missing_values = np.where((contour_data == ''))[0]
if (missing_values.shape[0] > 1):
logger.warning(" More than... |
class MSRA10k(BaseImageDataset):
def __init__(self, root=None, image_loader=jpeg4py_loader, data_fraction=None, min_area=None):
root = (env_settings().msra10k_dir if (root is None) else root)
super().__init__('MSRA10k', root, image_loader)
self.image_list = self._load_dataset(min_area=min_ar... |
class CharbonnierLoss(nn.Module):
def __init__(self, loss_weight=1.0, reduction='mean', eps=0.001):
super(CharbonnierLoss, self).__init__()
self.eps = eps
def forward(self, x, y):
diff = (x - y)
loss = torch.mean(torch.sqrt(((diff * diff) + (self.eps * self.eps))))
return... |
class GetTypeHintTests(BaseTestCase):
def setUpClass(cls):
with tempfile.TemporaryDirectory() as tempdir:
sys.path.append(tempdir)
Path(tempdir, 'ann_module.py').write_text(ANN_MODULE_SOURCE)
Path(tempdir, 'ann_module2.py').write_text(ANN_MODULE_2_SOURCE)
Path... |
.parametrize('tensor_shape', [FC_SHAPE, CONV_SHAPE], ids=['FC', 'CONV'])
def test_he_uniform(tensor_shape):
(fan_in, _) = initializers._compute_fans(tensor_shape)
scale = np.sqrt((6.0 / fan_in))
_runner(initializers.he_uniform(), tensor_shape, target_mean=0.0, target_max=scale, target_min=(- scale)) |
def mutable_seq_typed_attrs(draw, defaults=None, allow_mutable_defaults=True, legacy_types_only=False, kw_only=None):
default_val = NOTHING
val_strat = lists(floats(allow_infinity=False, allow_nan=False))
if ((defaults is True) or ((defaults is None) and draw(booleans()))):
default_val = draw(val_st... |
def _parse_specifier(package_spec: str) -> ParsedPackage:
valid_pep508 = None
valid_url = None
valid_local_path = None
try:
package_req = Requirement(package_spec)
except InvalidRequirement:
pass
else:
valid_pep508 = package_req
if (valid_pep508 and package_req.name.e... |
def _create_recorded_proxy_method(proxy: HFProxy, method_name: str, cache_name: str, return_proxy: bool):
original_method = getattr(torch.Tensor, method_name)
(original_method)
def method(*args, **kwargs):
cache = getattr(args[0].tracer.root, cache_name)
res = cache.pop(0)
if return_... |
def parse_by_phrase(path_to_txt_or_xml_file, meter='default_english', minword=5):
txt = read_file(path_to_txt_or_xml_file)
import re
phrases = re.split('[?.,;:\n]', txt)
if minword:
phrases2 = []
phrase = []
for px in phrases:
phrase += px.split()
if (len(... |
def handle_receive_delivered(chain_state: ChainState, state_change: ReceiveDelivered) -> TransitionResult[ChainState]:
queueid = QueueIdentifier(state_change.sender, CANONICAL_IDENTIFIER_UNORDERED_QUEUE)
inplace_delete_message_queue(chain_state, state_change, queueid)
return TransitionResult(chain_state, []... |
class SelfShowCommand(SelfCommand, ShowCommand):
name = 'self show'
options = [option('addons', None, 'List only add-on packages installed.'), *[o for o in ShowCommand.options if (o.name in {'tree', 'latest', 'outdated'})]]
description = "Show packages from Poetry's runtime environment."
help = f'''The ... |
class Job(pydantic.BaseModel):
job_type: JobType
payload: Optional[Dict]
('payload')
def crawler_payload(cls, v, values, **kwargs):
if (not v):
raise Exception('payload is required')
if (values['job_type'] == JobType.CRAWL_PTT_LATEST_POSTS):
for key in ['board']:
... |
class Inception_C(nn.Module):
def __init__(self):
super(Inception_C, self).__init__()
self.branch0 = BasicConv2d(1536, 256, kernel_size=1, stride=1)
self.branch1_0 = BasicConv2d(1536, 384, kernel_size=1, stride=1)
self.branch1_1a = BasicConv2d(384, 256, kernel_size=(1, 3), stride=1, ... |
def relations(distinctions, relation_computation=None, **kwargs):
if (not distinctions.resolved_congruence):
warnings.warn(_CONGRUENCE_WARNING_MSG, PyPhiWarning, stacklevel=2)
return relation_computations[fallback(relation_computation, config.RELATION_COMPUTATION)](distinctions, **kwargs) |
class Thermotron3800(Instrument):
def __init__(self, adapter, name='Thermotron 3800', **kwargs):
super().__init__(adapter, name, includeSCPI=False, **kwargs)
def write(self, command):
super().write(command)
sleep(1)
id = Instrument.measurement('IDEN?', ' Reads the instrument identifi... |
class BackgroundTaskMixin():
progress_update_signal = Signal(str, int)
background_tasks_button_lock_signal = Signal(bool)
abort_background_task_requested: bool = False
_background_thread: (threading.Thread | None) = None
def _start_thread_for(self, target):
randovania.games.prime2.patcher.cs... |
def could_use_op(input):
if ((not enabled) or (not torch.backends.cudnn.enabled)):
return False
if (input.device.type != 'cuda'):
return False
if any((torch.__version__.startswith(x) for x in ['1.7.', '1.8.'])):
return True
warnings.warn(f'conv2d_gradfix not supported on PyTorch ... |
class Textual_Encoder(nn.Module):
def __init__(self, cfg, classnames, clip_model):
super().__init__()
self.cfg = cfg
self.classnames = classnames
self.clip_model = clip_model
self.dtype = clip_model.dtype
def forward(self):
prompts = best_prompt_weight['{}_{}_test... |
class SyncMiddleware(LogMiddleware):
def __init__(self):
self.request_parent = dict()
self.sync_items = dict()
self._lock = asyncio.Lock()
async def process_spider_output(self, response, result, spider):
key = getattr(spider, 'sync_item_key')
if (key is None):
... |
def apply_to_ndarray(f, sample):
if (len(sample) == 0):
return {}
def _apply(x):
if isinstance(x, np.ndarray):
return f(x)
elif isinstance(x, dict):
return {key: _apply(value) for (key, value) in x.items()}
elif isinstance(x, list):
return [_ap... |
class UserDeleteView(DeleteView):
model = User
template_name = 'django_scantron/user_delete.html'
slug_field = 'slug'
slug_url_kwarg = 'slug'
pk_url_kwarg = 'pk'
context_object_name = 'user'
def __init__(self, **kwargs):
return super(UserDeleteView, self).__init__(**kwargs)
def d... |
class GetRootUUIDTests(unittest.TestCase):
def setUpClass(cls):
cls.das = DummyArtifacts()
cls.tempdir = cls.das.tempdir
def tearDownClass(cls):
cls.das.free()
def test_get_root_uuid(self):
exp_root_uuids = {'0': '89af91c0-033d-4e30-8ac4-f29a3b407dc1', '1': '5b929500-e4d6-4d3... |
class Swinv2Config(PretrainedConfig):
model_type = 'swinv2'
attribute_map = {'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}
def __init__(self, image_size=224, patch_size=4, num_channels=3, embed_dim=96, depths=[2, 2, 6, 2], num_heads=[3, 6, 12, 24], window_size=7, mlp_ratio=4.0, qkv_... |
def main(config, args):
if (args.module and (args.module != 'main')):
if (args.module == 'help'):
help()
return
try:
library = importlib.import_module(((__package__ + '.') + args.module))
if args.name:
if (args.name == 'all'):
... |
class FrNet(nn.Module):
def __init__(self, input_nc, output_nc, nf):
super(FrNet, self).__init__()
self.conv1_d_stage1 = nn.Conv2d(input_nc, 8, 3, 1, 1)
self.relu1_d_stage1 = nn.LeakyReLU()
self.conv1_c_stage1 = nn.Conv2d((input_nc * 3), 8, 3, 1, 1)
self.relu1_c_stage1 = nn.L... |
def train(opt):
print('Training Information')
print('start from {}'.format(opt.start_from))
print('box from {}'.format(opt.input_box_dir))
print('attributes from {}'.format(opt.input_att_dir))
print('features from {}'.format(opt.input_fc_dir))
print('batch size ={}'.format(opt.batch_size))
p... |
class BosonicTransformation(Transformation):
def __init__(self, qubit_mapping: BosonicQubitMappingType=BosonicQubitMappingType.DIRECT, transformation_type: BosonicTransformationType=BosonicTransformationType.HARMONIC, basis_size: Union[(int, List[int])]=2, truncation: int=3):
self._qubit_mapping = qubit_map... |
def dicom_input_method(config, key_namespace='', patient_id='', site=None, **_):
monaco_site = site
FILE_UPLOAD = 'File upload'
MONACO_SEARCH = 'Search Monaco file export location'
import_method = st.radio('DICOM import method', [FILE_UPLOAD, MONACO_SEARCH], key=f'{key_namespace}_dicom_file_import_metho... |
class Window(OperatorMixin):
def __init__(self, sdf, n=None, value=None, with_state=False, start=None):
if ((value is None) and isinstance(n, (str, pd.Timedelta))):
value = n
n = None
self.n = n
self.root = sdf
if (isinstance(value, str) and isinstance(self.ro... |
class ModelBuilder():
default_tri_ke = 100.0
default_tri_ka = 100.0
default_tri_kd = 10.0
default_tri_drag = 0.0
default_tri_lift = 0.0
default_edge_ke = 100.0
default_edge_kd = 0.0
def __init__(self):
self.particle_q = []
self.particle_qd = []
self.particle_mass ... |
def verify_online_player(caller, value):
session_list = SESSIONS.get_sessions()
char_list = []
matched_character = None
for session in session_list:
if (not session.logged_in):
continue
char_list.append(session.get_puppet())
for character in char_list:
if (value.l... |
def main():
if (not TOKEN):
print('No token is set, skipping')
return
python = shutil.which('python')
dependency = f'mkdocs-material[imaging] {DEP_REF}{GIT_REF}'
try:
process = subprocess.Popen([python, '-m', 'pip', 'install', '--disable-pip-version-check', dependency], stdout=s... |
def test_from_string__wkt_with_proj():
wkt = 'PROJCS["WGS 84 / Pseudo-Mercator",GEOGCS["WGS 84", DATUM["WGS_1984", SPHEROID["WGS 84",6378137,298., AUTHORITY["EPSG","7030"]], AUTHORITY["EPSG","6326"]], PRIMEM["Greenwich",0, AUTHORITY["EPSG","8901"]], UNIT["degree",0., ... |
class ProviderValidator():
def __call__(self, data):
provider_key = data.get('provider_key')
provider = get_plugin('PROJECT_ISSUE_PROVIDERS', provider_key)
if (provider is None):
raise ValidationError({'provider_key': 'Please provide a valid provider.'})
try:
... |
.parametrize('option_api, backend', [('pyqt5', 'PyQt5'), ('pyqt6', 'PyQt6'), ('pyside2', 'PySide2'), ('pyside6', 'PySide6')])
def test_already_loaded_backend(monkeypatch, option_api, backend):
import builtins
class Mock():
pass
qtcore = Mock()
for method_name in ('qInstallMessageHandler', 'qDebu... |
def parse_davis2017_splits():
with open('data/davis/DAVIS/ImageSets/2017/train.txt') as f:
train_list = [(vid.rstrip(), idx) for (idx, vid) in enumerate(f.readlines())]
with open('data/davis/DAVIS/ImageSets/2017/val.txt') as f:
val_list = [(vid.rstrip(), idx) for (idx, vid) in enumerate(f.readli... |
class MobileViTDeepLabV3(nn.Module):
def __init__(self, config: MobileViTConfig) -> None:
super().__init__()
self.aspp = MobileViTASPP(config)
self.dropout = nn.Dropout2d(config.classifier_dropout_prob)
self.classifier = MobileViTConvLayer(config, in_channels=config.aspp_out_channels... |
class ACLExtractor(meta.FlatExtractor):
def _record_to_object(record):
newline_pos = record.find(b'\n')
first_line = record[:newline_pos]
if (not first_line.startswith(b'# file: ')):
raise meta.ParsingError(('Bad record beginning: %r' % first_line))
filename = first_line[... |
def test_redirect_both(capfd):
msg = 'StdOut'
msg2 = 'StdErr'
stream = StringIO()
stream2 = StringIO()
with redirect_stdout(stream):
with redirect_stderr(stream2):
with m.ostream_redirect():
m.raw_output(msg)
m.raw_err(msg2)
(stdout, stderr) = ... |
class Graph(pg.GraphItem):
def __init__(self):
self.dragPoint = None
self.dragOffset = None
self.textItems = []
pg.GraphItem.__init__(self)
self.scatter.sigClicked.connect(self.clicked)
def setData(self, **kwds):
self.text = kwds.pop('text', [])
self.data ... |
class FusedLeakyReLUFunction(Function):
def forward(ctx, input, bias, negative_slope, scale):
empty = input.new_empty(0)
out = fused_act_ext.fused_bias_act(input, bias, empty, 3, 0, negative_slope, scale)
ctx.save_for_backward(out)
ctx.negative_slope = negative_slope
ctx.scal... |
_arg_scope
def split_separable_conv2d(input_tensor, num_outputs, scope=None, normalizer_fn=None, stride=1, rate=1, endpoints=None, use_explicit_padding=False):
with _v1_compatible_scope_naming(scope) as scope:
dw_scope = (scope + 'depthwise')
endpoints = (endpoints if (endpoints is not None) else {}... |
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