code stringlengths 281 23.7M |
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class Account(rlp.Serializable, AccountAPI):
fields = [('nonce', big_endian_int), ('balance', big_endian_int), ('storage_root', trie_root), ('code_hash', hash32)]
def __init__(self, nonce: int=0, balance: int=0, storage_root: bytes=BLANK_ROOT_HASH, code_hash: bytes=EMPTY_SHA3, **kwargs: Any) -> None:
su... |
class Player(GstPlay.Play):
__gtype_name__ = 'SoundPlayer'
def __init__(self, sound):
super().__init__()
self.sound = sound
self.saved_volume = 0.0
self.set_volume(0)
self.set_uri(self.sound.uri)
self.name = self.sound.name
self.prerolled = False
s... |
def find_test_files2(dir0, suffix0, dir1, suffix1):
D = collections.defaultdict(list)
for (root, dirnames, filenames) in os.walk(dir0):
for filename in filenames:
if ('.' in filename):
(basename, suffix) = filename.rsplit('.', 1)
if (suffix == suffix0):
... |
class TextImageDataset(torch.utils.data.Dataset):
def __init__(self, dir_path, prompt_filepath, transform=None):
self.dir_path = dir_path
path = pathlib.Path(dir_path)
self.files = sorted([file for ext in IMAGE_EXTENSIONS for file in path.glob('*.{}'.format(ext))], key=(lambda x: int(os.path... |
class EffiInitBlock(nn.Module):
def __init__(self, in_channels, out_channels, bn_eps, activation, tf_mode):
super(EffiInitBlock, self).__init__()
self.tf_mode = tf_mode
self.conv = conv3x3_block(in_channels=in_channels, out_channels=out_channels, stride=2, padding=(0 if tf_mode else 1), bn_e... |
def test_use_scm_version_callable(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv('SETUPTOOLS_SCM_DEBUG')
p = ((tmp_path / 'sub') / 'package')
p.mkdir(parents=True)
p.joinpath('setup.py').write_text('from setuptools import setup\ndef vcfg():\n from setuptools_scm.version ... |
def assert_plugin_installation(subprocess_run, dependencies: list[str], *, verbosity=0):
command = [sys.executable, '-u', '-m', 'pip', 'install', '--disable-pip-version-check', '--no-python-version-warning']
add_verbosity_flag(command, verbosity, adjustment=(- 1))
command.extend(dependencies)
subprocess... |
class _AbstractSignalBlocker():
def __init__(self, timeout=5000, raising=True):
self._loop = qt_api.QtCore.QEventLoop()
self.timeout = timeout
self.signal_triggered = False
self.raising = raising
self._signals = None
self._timeout_message = ''
if ((timeout is ... |
class BoxList(list):
def __init__(self, iterable=None, box_class=Box, **box_options):
self.box_class = box_class
self.box_options = box_options
self.box_org_ref = self.box_org_ref = (id(iterable) if iterable else 0)
if iterable:
for x in iterable:
self.app... |
def train(args):
hvd.init()
if args.cuda:
torch.cuda.set_device(hvd.local_rank())
kwargs = ({'num_workers': args.num_workers, 'pin_memory': True} if args.cuda else {})
train_dataset = VCDBPairDataset(annotation_path=args.annotation_path, feature_path=args.feature_path, padding_size=args.padding_... |
def evaluate(args, accelerator, dataloader, eval_set, model, checkpoint, has_labels=True, write_to_file=True):
num_examples = args.num_examples[eval_set]
eval_metric = None
completed_steps = 0
eval_loss = 0.0
all_predictions = None
all_references = None
all_probabilities = None
if has_la... |
def main(args):
cfg = setup_cfg(args)
if (cfg.SEED >= 0):
print('Setting fixed seed: {}'.format(cfg.SEED))
set_random_seed(cfg.SEED)
setup_logger(cfg.OUTPUT_DIR)
if (torch.cuda.is_available() and cfg.USE_CUDA):
torch.backends.cudnn.benchmark = True
print_args(args, cfg)
p... |
class LAVertex():
def __init__(self, point, edge_left, edge_right, direction_vectors=None):
self.point = point
self.edge_left = edge_left
self.edge_right = edge_right
self.prev = None
self.next = None
self.lav = None
self._valid = True
creator_vectors ... |
()
('--full-report/--short-report', default=False, cls=MutuallyExclusiveOption, mutually_exclusive=['output'], with_values={'output': ['json', 'bare']}, help='Full reports include a security advisory (if available). Default: --short-report')
('--output', '-o', type=click.Choice(['screen', 'text', 'json', 'bare'], case_... |
class SEConvOp(BaseOp):
def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, dilation=1, transposed=False, dropout_rate=0, ops_order='weight_norm'):
super().__init__(in_channels, out_channels, dropout_rate, ops_order=(ops_order if (stride > 1) else 'weight'))
self.stride = stride
... |
class ThemedWidget():
size: int
theme: str
primary_color: str
secondary_color: str
def __init__(self, theme: str, color_palette: Tuple[(str, str)], options: Dict=None) -> None:
if options:
self.setup_options(options)
else:
self.size = 5
self.apply_them... |
def np_calculate_dist(anchor, positive):
d1 = np.sum((anchor * anchor), axis=1).reshape(1, 1)
d2 = np.sum((positive * positive), axis=1).reshape((- 1), 1)
eps = 1e-12
a = d1.repeat(int(positive.shape[0])).reshape(1, (- 1))
b = d2.T
c = (2.0 * np.dot(anchor, positive.T))
return np.sqrt((np.ab... |
class CombinedController(DictController):
def _initialize_action_space(self):
super()._initialize_action_space()
(self.action_space, self.action_mapping) = flatten_action_spaces(self.action_space.spaces)
def set_action(self, action: np.ndarray):
action_dim = self.action_space.shape[0]
... |
class ExceptionSaver():
def __enter__(self):
return self
def __exit__(self, type, exc, tb):
if (not exc):
return
self._saved = UnpickleableException.dump(type, exc)
self._tb = tb
return True
def resume(self):
if ('_saved' not in vars(self)):
... |
class TransformFactory(object):
current_transforms = {'default': Transform, 'simple_qa': QATransform, 'multi_choice_qa': MultiChoiceQATransform, 'db': DBTransform, 'table': TableTransform}
def get_transform(transform: str) -> Type[Transform]:
if (transform in TransformFactory.current_transforms):
... |
class ScrimsSlotmSelector(discord.ui.Select):
def __init__(self, records: List[ScrimsSlotManager]):
_o = []
for record in records:
_o.append(discord.SelectOption(label=getattr(record.main_channel, 'name', 'channel-not-found'), value=record.id, description=truncate_string(f"Scrims: {', '.... |
def _scan_qrcode_using_zbar(*, parent: Optional[QWidget], config: 'SimpleConfig', callback: Callable[([bool, str, Optional[str]], None)]) -> None:
from electrum import qrscanner
data = None
try:
data = qrscanner.scan_barcode(config.get_video_device())
except UserFacingException as e:
suc... |
class OperatingModes():
def __init__(self, default_mode):
self.default_mode = default_mode
self.named_modes = ['current', 'voltage', 'power', 'differential power', 'explicit power', 'resistance', 'differential resistance', 'explicit resistance', 'CCCV']
def __contains__(self, value):
nam... |
class GroupDeployTokenManager(RetrieveMixin, CreateMixin, DeleteMixin, RESTManager):
_path = '/groups/{group_id}/deploy_tokens'
_from_parent_attrs = {'group_id': 'id'}
_obj_cls = GroupDeployToken
_create_attrs = RequiredOptional(required=('name', 'scopes'), optional=('expires_at', 'username'))
_list... |
def generate_guarded(mod: str, target: str, ignore_errors: bool=True, verbose: bool=False) -> Iterator[None]:
if verbose:
print(f'Processing {mod}')
try:
(yield)
except Exception as e:
if (not ignore_errors):
raise e
else:
print('Stub generation failed... |
.with_default_category('Fruits')
class CommandSetA(cmd2.CommandSet):
def do_apple(self, statement: cmd2.Statement):
self._cmd.poutput('Apple!')
def do_banana(self, statement: cmd2.Statement):
self._cmd.poutput('Banana!!')
cranberry_parser = cmd2.Cmd2ArgumentParser()
cranberry_parser.add_... |
class WebhookPathFinder(BasePathFinder):
def _get_paths_iter(self, name: str) -> Iterator[Path]:
webhooks = (self.spec / 'webhooks')
if (not webhooks.exists()):
raise PathsNotFound(webhooks.as_uri())
for (webhook_name, path) in list(webhooks.items()):
if (name == webh... |
.parametrize('mean, sigma, size', [(np.array(100, dtype=config.floatX), np.array(0.01, dtype=config.floatX), None), (np.array(100, dtype=config.floatX), np.array(0.01, dtype=config.floatX), []), (np.full((1, 2), 100, dtype=config.floatX), np.array(0.01, dtype=config.floatX), None)])
def test_normal_samples(mean, sigma,... |
(SponsorEmailNotificationTemplate)
class SponsorEmailNotificationTemplateAdmin(BaseEmailTemplateAdmin):
def get_form(self, request, obj=None, **kwargs):
help_texts = {'content': SPONSOR_TEMPLATE_HELP_TEXT}
kwargs.update({'help_texts': help_texts})
return super().get_form(request, obj, **kwar... |
def test_win_defaults(windows, no_xdg_envs):
pp = platform.get_platform_paths('pypyr', 'config.yaml')
assert (pp == platform.PlatformPaths(config_user=Path(HOME, '.config/pypyr/config.yaml'), config_common=[Path('C:/ProgramData1/pypyr/config.yaml')], data_dir_user=Path(HOME, '.local/share/pypyr'), data_dir_comm... |
_grad()
def validate_mrc(model, val_loader):
LOGGER.info('start running MRC validation...')
val_loss = 0
n_feat = 0
st = time.time()
tot_score = 0
for (i, batch) in enumerate(val_loader):
(view_logits, view_targets, _, _) = model(batch, task='mrc', compute_loss=False)
view_logpro... |
def retrieve_nfrms_from_gulp(gulp_dir):
id2nfrms = dict()
gulp = GulpDirectory(gulp_dir)
pbar = pb.ProgressBar(widgets=[pb.Percentage(), pb.Bar()], maxval=gulp.num_chunks).start()
i = 0
for chunk in gulp:
for (frames, meta) in chunk:
id2nfrms[meta['id']] = len(frames)
pba... |
.parametrize('version, expected', [('1.2a1', '1.2a2'), ('2!1.2a1', '2!1.2a2'), ('1.2dev0', '1.2a0'), ('1.2a1.dev0', '1.2a1'), ('1.2a1.post1.dev0', '1.2a2')])
def test_next_prerelease(version: str, expected: str) -> None:
v = PEP440Version.parse(version)
assert (v.next_prerelease().text == expected) |
def test_abi_vision_decoder():
model = ABIVisionDecoder(in_channels=128, num_channels=16, max_seq_len=10, use_result=None)
x = torch.randn(2, 128, 8, 32)
result = model(x, None)
assert (result['feature'].shape == torch.Size([2, 10, 128]))
assert (result['logits'].shape == torch.Size([2, 10, 90]))
... |
def main():
import argparse
parser = argparse.ArgumentParser(description='Serial port enumeration')
parser.add_argument('regexp', nargs='?', help='only show ports that match this regex')
parser.add_argument('-v', '--verbose', action='store_true', help='show more messages')
parser.add_argument('-q', ... |
_existing_mirrors
('util.repomirror.skopeomirror.SkopeoMirror.run_skopeo')
def test_successful_mirror_verbose_logs(run_skopeo_mock, initialized_db, app, monkeypatch):
(mirror, repo) = create_mirror_repo_robot(['latest', '7.1'])
skopeo_calls = [{'args': ['/usr/bin/skopeo', '--debug', 'list-tags', '--tls-verify=T... |
def get_file_paths():
test_files = []
for (_, _, files) in os.walk(_EXAMPLES_PATH, topdown=True):
for filename in files:
if ((filename not in IGNORED_TESTS) and filename.endswith('.py')):
test_files.append((_EXAMPLES_PATH + filename))
return test_files |
def main():
(path, output) = getParams()
mrc_header = io_file.read_mrc_header(path)
voxel_spacing_in_nm = ((mrc_header['MRC']['xlen'] / mrc_header['MRC']['nx']) / 10)
print(('voxel_spacing_in_nm: %s' % voxel_spacing_in_nm))
sigma1 = 2
try:
sigma1 = max(int((7 / voxel_spacing_in_nm)), sig... |
class ConnectionManager(object):
def __init__(self, sock):
config = H2Configuration(client_side=False)
self.sock = sock
self.conn = H2Connection(config=config)
def run_forever(self):
self.conn.initiate_connection()
self.sock.sendall(self.conn.data_to_send())
while... |
def make_sockaddr_in6():
class in6_addr(ctypes.BigEndianStructure):
_fields_ = (('Byte', (ctypes.c_uint8 * 16)),)
class sockaddr_in6(ctypes.BigEndianStructure):
_fields_ = (('sin6_family', ctypes.c_int16), ('sin6_port', ctypes.c_uint16), ('sin6_flowinfo', ctypes.c_uint32), ('sin6_addr', in6_addr... |
class PythonEnvironment(BaseEnvironment):
def __init__(self, num_agents=2, max_episode_length=200, env_task_set=None, observation_types=None, agent_goals=None, output_folder=None, seed=123):
self.seed = seed
random.seed(seed)
np.random.seed(seed)
self.steps = 0
self.env_id = ... |
def test_nested_while_with_break() -> None:
src = '\n while n > 10:\n while n > 20:\n break\n print(n - 1)\n break\n print(n)\n '
cfg = build_cfg(src)
expected_blocks = [['n > 10'], ['n > 20'], ['break'], ['print(n - 1)', 'break'], ['print(n)'], []]
assert (expec... |
class EventLoop(asyncio.SelectorEventLoop):
def __init__(self):
self._greenlet = None
selector = _Selector(self)
super(EventLoop, self).__init__(selector=selector)
if _GEVENT10:
def time(self):
return gevent.core.time()
def call_soon(self, callback, *args, context... |
def _make_handshake_rejection(status_code: int, body: Optional[bytes]=None) -> List[h11.Event]:
client = h11.Connection(h11.CLIENT)
server = WSConnection(SERVER)
nonce = generate_nonce()
server.receive_data(client.send(h11.Request(method='GET', target='/', headers=[(b'Host', b'localhost'), (b'Connection... |
()
('--prompt', '-p', 'prompt', type=str, required=True, help='Input prompt.')
('--backend', '-b', 'backends', type=str, multiple=True, default=['openai|text-davinci-003'], help='LLM APIs to use as backends. Use "backend|model_name" notation. For example: "openai|text-davinci-003".')
('--max-length', '-l', 'max_lengths... |
def test_select_device():
assert (_select_device('cpu') == torch.device('cpu'))
assert (_select_device('gpu') == torch.device('cuda'))
assert (_select_device('cuda:0') == torch.device('cuda', index=0))
if torch.cuda.is_available():
assert (_select_device('auto') == torch.device('cuda'))
else... |
def build_optim_other(args, model, checkpoint):
if (checkpoint is not None):
optim = checkpoint['optims'][1]
saved_optimizer_state_dict = optim.optimizer.state_dict()
optim.optimizer.load_state_dict(saved_optimizer_state_dict)
if (args.visible_gpus != '-1'):
for state in ... |
()
('-e', '--extension', multiple=True, help='File or module path to a zipline extension to load.')
('--strict-extensions/--non-strict-extensions', is_flag=True, help='If --strict-extensions is passed then zipline will not run if it cannot load all of the specified extensions. If this is not passed or --non-strict-exte... |
class Chat():
def __init__(self, msg: object) -> None:
if isinstance(msg, str):
self.msg = {'text': msg}
else:
self.msg = msg
def from_string(cls, text: str) -> Chat:
return cls({'text': text})
def to_string(self, mode: str) -> str:
def parse(msg):
... |
class TestHooks():
(autouse=True)
def create_test_file(self, pytester: pytest.Pytester) -> None:
pytester.makepyfile('\n import os\n def test_a(): pass\n def test_b(): pass\n def test_c(): pass\n ')
def test_runtest_logreport(self, pytester: pytest.... |
class Service(BaseImageObject):
mode = 'service'
def __init__(self, docker_client):
super().__init__(docker_client)
self.monitored = self.monitor_filter()
def monitor_filter(self):
services = self.client.services.list(filters={'label': 'com.ouroboros.enable'})
monitored_servi... |
class NInfinity(object):
def __lt__(self, other):
if isinstance(other, NInfinity):
return False
return True
def __gt__(self, other):
return False
def __eq__(self, other):
return isinstance(other, NInfinity)
def __neg__(self):
return infinity
def __... |
def attach_player_object_to_vehicle(player_id: int, object_id: int, vehicle_id: int, offset_x: float, offset_y: float, offset_z: float, rotation_x: float, rotation_y: float, rotation_z: float) -> bool:
return AttachPlayerObjectToVehicle(player_id, object_id, vehicle_id, offset_x, offset_y, offset_z, rotation_x, rot... |
def get_filtered_command_list(cpaddrs=[], isrunning=None, goodwords=[], badwords=[]):
base = 'commandmetadata'
i = 0
retval = list()
while True:
i += 1
good = True
try:
dsz.cmd.data.Get('commandmetadata::id', dsz.TYPE_INT, i)[0]
except:
break
... |
class BoundSymbol(object):
def __init__(self, symbol, database):
if (symbol.type == 'proc'):
proc = database.proc(symbol)
self.method = proc.__call__
self.object = proc
else:
ps = database.prepare(symbol)
m = symbol.method
if (m... |
def check_tasks_unique(tasks, env_names):
env_to_rand_vecs = {}
for env_name in env_names:
env_to_rand_vecs[env_name] = np.array([pickle.loads(task.data)['rand_vec'] for task in tasks if (task.env_name == env_name)])
unique_task_rand_vecs = np.unique(np.array(env_to_rand_vecs[env_name]), axis=0)... |
class _ModelZooUrls(object):
S3_PREFIX = '
CONFIG_PATH_TO_URL_SUFFIX = {'COCO-Detection/faster_rcnn_R_50_C4_1x': '/model_final_721ade.pkl', 'COCO-Detection/faster_rcnn_R_50_DC5_1x': '/model_final_51d356.pkl', 'COCO-Detection/faster_rcnn_R_50_FPN_1x': '/model_final_b275ba.pkl', 'COCO-Detection/faster_rcnn_R_50_C... |
def _check_if_params_are_ray_dmatrix(X, sample_weight, base_margin, eval_set, sample_weight_eval_set, base_margin_eval_set, eval_qid=None):
train_dmatrix = None
evals = ()
eval_set = (eval_set or ())
if isinstance(X, RayDMatrix):
params_to_warn_about = ['y']
if (sample_weight is not None... |
class IntermediateLayerGetter(nn.ModuleDict):
_version = 2
__annotations__ = {'return_layers': Dict[(str, str)]}
def __init__(self, model, return_layers):
if (not set(return_layers).issubset([name for (name, _) in model.named_children()])):
raise ValueError('return_layers are not present... |
class MobileNetV2(nn.Module):
cfg = [(1, 16, 1, 1), (6, 24, 2, 1), (6, 32, 3, 2), (6, 64, 4, 2), (6, 96, 3, 1), (6, 160, 3, 2), (6, 320, 1, 1)]
def __init__(self, num_classes=10):
super(MobileNetV2, self).__init__()
self.conv1 = nn.Conv2d(3, 32, kernel_size=3, stride=1, padding=1, bias=False)
... |
def geth_generate_poa_genesis(genesis_path: str, genesis_description: GenesisDescription, seal_account: Address) -> None:
alloc = {to_normalized_address(account.address): {'balance': str(account.balance)} for account in genesis_description.prefunded_accounts}
seal_address_normalized = remove_0x_prefix(encode_he... |
class StyleEdit(QtWidgets.QWidget):
styleChanged = QtCore.Signal(str, str)
def __init__(self, defaultStyle, *args, **kwargs):
super().__init__(*args, **kwargs)
self.styleKey = defaultStyle.key
self.layout = layout = QtWidgets.QHBoxLayout()
self.setters = {}
fmtParts = def... |
def load_pretrian_model(model, model_path):
checkpoint = torch.load(model_path, map_location=(lambda storage, loc: storage))
state_dict_ = checkpoint
state_dict = {}
for k in state_dict_:
if (k.startswith('module') and (not k.startswith('module_list'))):
state_dict[k[7:]] = state_dic... |
_fixtures(FieldFixture)
def test_date_validation(fixture):
field = DateField()
obj = fixture.model_object
field.bind('date_value', obj)
with expected(DateConstraint):
field.set_user_input('sdfdf')
with expected(NoException):
field.set_user_input('13 Dec')
limit_date = datetime.da... |
class MixChannelParent(CommonBaseTesting):
channels = CommonBase.MultiChannelCreator(GenericBase, ('A', 'B', 'C'))
ch_D = CommonBase.ChannelCreator(GenericBase, 'D')
output_Z = CommonBase.ChannelCreator(GenericBase, 'Z')
analog = CommonBase.MultiChannelCreator(GenericBase, list(range(0, 10)), prefix='an... |
.parametrize('executor_config,expected_quay_builder_unit_contents', [({'CONTAINER_RUNTIME': 'docker'}, '[Unit]\nWants=docker.service network-online.target\nAfter=docker.service network-online.target\nRequires=docker.service\n\n[Service]\nType=oneshot\nTimeoutStartSec=10800\nTimeoutStopSec=2000\n\nExecStartPre=/usr/bin/... |
class BloomTokenizerFast(PreTrainedTokenizerFast):
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
model_input_names = ['input_ids', 'attention_mask']
slow_tokenizer_class = None
def __init__(self, vocab_file=None, merges_file=None, tokenizer_file=None, ... |
def _sampled_video_weight_inputs(non_zeros, radius: float, shape):
(num_frames, num_classes) = shape
weights = np.zeros((num_frames, num_classes))
(frame_indexes, class_indexes) = non_zeros
for (frame_index, class_index) in zip(frame_indexes, class_indexes):
weight_range = create_frame_range(fra... |
class SparseIndexParams(BaseModel, extra='forbid'):
full_scan_threshold: Optional[int] = Field(default=None, description='We prefer a full scan search upto (excluding) this number of vectors. Note: this is number of vectors, not KiloBytes.')
on_disk: Optional[bool] = Field(default=None, description='Store inde... |
def ratio_threshold(depth1, depth2, threshold):
assert (threshold > 0.0)
assert np.all((((np.isfinite(depth1) & np.isfinite(depth2)) & (depth1 >= 0)) & (depth2 >= 0)))
log_diff = (np.log(depth1) - np.log(depth2))
num_pixels = float(log_diff.size)
if (num_pixels == 0):
return np.nan
else:... |
def _moverc(src, dst, overwrite):
exists = os.path.exists
move = shutil.move
removedirs = os.removedirs
for (src_dir, dirnames, filenames) in os.walk(src):
dst_dir = src_dir.replace(src, dst, 1)
if exists(dst_dir):
_shdorc(move, filenames, src_dir, dst_dir, overwrite)
... |
def prepare_lima_data_and_index(r_tokenizer, r_model):
lima_dataset = load_dataset('GAIR/lima')
idx2alignment_data = dict()
alignment_prompt_list = [e['conversations'][0] for e in lima_dataset['train']]
alignment_data_prompt_embeddings = compute_embeddings(r_tokenizer, r_model, alignment_prompt_list)
... |
class CmdWield(Command):
key = 'wield'
help_category = 'combat'
def func(self):
if is_in_combat(self.caller):
if (not is_turn(self.caller)):
self.caller.msg('You can only do that on your turn.')
return
if (not self.args):
self.caller.ms... |
class RequiredImgAssetConfigurationTests(TestCase):
def setUp(self):
self.sponsor_benefit = baker.make(SponsorBenefit, sponsorship__sponsor__name='Foo')
self.config = baker.make(RequiredImgAssetConfiguration, related_to=AssetsRelatedTo.SPONSOR.value, internal_name='config_name')
def test_get_ben... |
.parametrize('version, index', [('1.2.3', (- 1)), ('1.2.3', (- 2)), ('1.2.3', slice((- 2), 2)), ('1.2.3', slice(2, (- 2))), ('1.2.3', slice((- 2), (- 2)))])
def test_version_info_should_throw_index_error_when_negative_index(version, index):
version_info = Version.parse(version)
with pytest.raises(IndexError, ma... |
class Closer(object):
def __init__(self, atexit_register=True):
self.lock = threading.Lock()
self.next_id = (- 1)
self.closeables = weakref.WeakValueDictionary()
if atexit_register:
atexit.register(self.close)
def generate_next_id(self):
with self.lock:
... |
class AverageMeter(object):
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.average = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += (val * n)
self.count += n
self.average = (sel... |
def create_bar_from_face(bm, face, trans, trans_space, depth, vertical=False):
dup = duplicate_face_translate_scale(bm, face, trans, trans_space).get('geom')
edges = [filter_horizontal_edges, filter_vertical_edges][vertical](filter_geom(dup, BMEdge))
extrude_edges_to_depth(bm, edges, depth) |
def word2vec(post, word_id_map, W):
word_embedding = []
mask = []
for sentence in post:
sen_embedding = []
seq_len = (len(sentence) - 1)
mask_seq = np.zeros(args.sequence_len, dtype=np.float32)
mask_seq[:len(sentence)] = 1.0
for (i, word) in enumerate(sentence):
... |
class Signature(object):
def from_der(der):
d = get_bytes(der)
if (len(d) < 8):
raise ValueError('DER signature string is too short.')
if (len(d) > 72):
raise ValueError('DER signature string is too long.')
if (d[0] != 48):
raise ValueError('DER si... |
class Dictionary(PymiereBaseObject):
def __init__(self, pymiere_id=None):
super(Dictionary, self).__init__(pymiere_id)
def getGroups(self):
return Array(**self._eval_on_this_object('getGroups()'))
def getClasses(self):
return Array(**self._eval_on_this_object('getClasses()'))
def... |
class QnliProcessor(DataProcessor):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
warnings.warn(DEPRECATION_WARNING.format('processor'), FutureWarning)
def get_example_from_tensor_dict(self, tensor_dict):
return InputExample(tensor_dict['idx'].numpy(), tensor_dic... |
class ExtraKeyTLV(TLV):
typ = 8
__slots__ = ['appid', 'appdata']
def __init__(self, appid, appdata):
super(ExtraKeyTLV, self).__init__()
self.appid = appid
self.appdata = appdata
if (appdata is None):
self.appdata = b''
def getPayload(self):
return (se... |
def parse_rst(text: str) -> docutils.nodes.document:
import docutils.nodes
import docutils.parsers.rst
import docutils.utils
parser = docutils.parsers.rst.Parser()
components = (docutils.parsers.rst.Parser,)
settings = docutils.frontend.OptionParser(components=components).get_default_values()
... |
def split_images_by_identify(src_dir, dst_dir):
plant_identifier = plantid.PlantIdentifier()
filenames = glob.glob(os.path.join(src_dir, '*'))
start_time = time.time()
for (k, filename) in enumerate(filenames):
image = khandy.imread_cv(filename)
outputs = plant_identifier.identify(image,... |
class QMysqlServer():
def __init__(self, **kwargs):
self.auto_disabled = None
self.process = None
self.uuid = (((('honeypotslogger' + '_') + __class__.__name__) + '_') + str(uuid4())[:8])
self.config = kwargs.get('config', '')
if self.config:
self.logs = setup_log... |
def test_transform_direction__string(scalar_and_array):
forward_transformer = Transformer.from_crs(4326, 3857)
inverse_transformer = Transformer.from_crs(3857, 4326)
assert_array_equal(inverse_transformer.transform(scalar_and_array((- 33)), scalar_and_array(24), direction='INVERSE'), forward_transformer.tra... |
class TestDriverPsi4(QiskitNatureTestCase, TestDriver):
((not _optionals.HAS_PSI4), 'psi4 not available.')
def setUp(self):
super().setUp()
driver = Psi4Driver(['molecule h2 {', ' 0 1', ' H 0.0 0.0 0.0', ' H 0.0 0.0 0.735', ' no_com', ' no_reorient', '}', '', 'set {', ' basis sto-3g', ' ... |
def test_explicit_timer_with_initial_text_true(capsys: pytest.CaptureFixture[str]) -> None:
t = Timer(text=TIME_MESSAGE, initial_text=True)
t.start()
waste_time()
t.stop()
(stdout, stderr) = capsys.readouterr()
assert RE_TIME_MESSAGE_INITIAL_TEXT_TRUE.match(stdout)
assert (stdout.count('\n')... |
class ReadFileRecordResponse(ModbusResponse):
function_code = 20
_rtu_byte_count_pos = 2
def __init__(self, records=None, **kwargs):
ModbusResponse.__init__(self, **kwargs)
self.records = (records or [])
def encode(self):
total = sum(((record.response_length + 1) for record in se... |
def cardiac_data():
data = {}
for i in range(5):
case_id = str((i + 1)).zfill(3)
ct_arr = (np.ones((60, 128, 128)) * (- 1000))
mask_arr = np.zeros((60, 128, 128))
submask_arr = np.zeros((60, 128, 128))
ct_arr = insert_sphere(ct_arr, sp_radius=25, sp_centre=((30 + i), (64 ... |
def maybe_resume_checkpoint(args, model, optimizer, scheduler, reporter, train_dl):
if ((args.resume is not None) and Path(args.resume).is_file()):
checkpoint = args.resume
logging.info(f'Resume from the provided checkpoitn {args.resume}')
else:
ckpts = list(Path(args.exp_dir).glob('ep*.... |
class TestFDDBBCD(TestFDDB):
def eval(self):
bcd = build_whole_network.DetectionNetworkBCD(cfgs=self.cfgs, is_training=False)
all_boxes_r = self.eval_with_plac(img_dir=self.args.img_dir, det_net=bcd, image_ext=self.args.image_ext)
imgs = os.listdir(self.args.img_dir)
real_test_imgnam... |
class SecondPipeline(FeatureSetPipeline):
def __init__(self):
super(SecondPipeline, self).__init__(source=Source(readers=[TableReader(id='t', database='db', table='table')], query=f'select * from t'), feature_set=FeatureSet(name='second', entity='entity', description='description', features=[Feature(name='f... |
class LogicExpressionASTVisitor(ast.NodeVisitor):
def __init__(self, globals=dict()):
self.arg_pos = {}
self.iddefs = {}
self.globals = globals
super(ast.NodeVisitor).__init__()
def generic_visit(self, node):
print(ast.dump(node))
raise NotImplementedError
def... |
class TestBindCollector(CollectorTestCase):
def setUp(self):
config = get_collector_config('BindCollector', {'interval': 10})
self.collector = BindCollector(config, None)
def test_import(self):
self.assertTrue(BindCollector)
(Collector, 'publish')
def test_should_work_with_real_d... |
_fixtures(WebFixture)
def test_bookmarks(web_fixture):
fixture = web_fixture
user_interface = UserInterface(None, '/a_ui', {}, False, 'test_ui')
view = UrlBoundView(user_interface, '/aview', 'A View title')
bookmark = view.as_bookmark()
assert (bookmark.href.path == '/a_ui/aview')
assert (bookma... |
class PackagesSectionCamelCase_TestCase(TestCase):
def setUp(self):
super(PackagesSectionCamelCase_TestCase, self).setUp()
ks_content = '%packages --instLangs=en\n%end\n'
self._ks_path = mktempfile(ks_content)
def runTest(self):
(retval, _out) = ksvalidator.main([self._ks_path, '... |
_grad()
def main():
args = parse_args()
accelerator = Accelerator(mixed_precision=args.mixed_precision)
if accelerator.is_main_process:
if (args.output_dir is not None):
os.makedirs(args.output_dir, exist_ok=True)
accelerator.wait_for_everyone()
if (args.seed is not None):
... |
def meteor_chained_flow_module(xyz, xyz_flowed, time, points, npoint, radius, nsample, mlp, mlp2, group_all, is_training, bn_decay, scope, module_type='ind', fps=True, bn=True, pooling='max', knn=False, use_xyz=True, use_nchw=False):
data_format = ('NCHW' if use_nchw else 'NHWC')
sample_idx = None
batch_siz... |
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