code stringlengths 281 23.7M |
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def setup_model_and_optimizer(model_provider_func):
args = get_args()
model = get_model(model_provider_func)
optimizer = get_optimizer(model)
lr_scheduler = get_learning_rate_scheduler(optimizer)
if (args.load is not None):
args.iteration = load_checkpoint(model, optimizer, lr_scheduler)
... |
('view')
def view() -> None:
try:
container_list = get_list_environments()
if (not container_list):
print(':computer: No freshenv environments found.')
for container in container_list:
if ('Exited' in container.get('Status')):
img = ':arrow_down: '
... |
_small_list(immutable=True, unbox_num=True)
class W_ImpVectorStar(W_InterposeVector):
import_from_mixin(ImpersonatorMixin)
errorname = 'impersonate-vector'
def self_arg(self):
return True
def post_set_cont(self, new, i, env, cont, app=None):
return imp_vec_set_cont(self.inner, i, app, en... |
class ConstantType(click.ParamType):
name = 'SMILES'
def convert(self, value, param, ctx):
if (not isinstance(value, str)):
return value
try:
(mol, frags) = parse_smiles_then_fragment(value)
if (not (1 <= len(frags) <= 3)):
raise MolProcessingE... |
(frozen=True)
class FakeCommand():
name: str = ''
desc: str = ''
hide: bool = False
debug: bool = False
deprecated: bool = False
completion: Any = None
maxsplit: int = None
takes_count: Callable[([], bool)] = (lambda : False)
modes: Tuple[usertypes.KeyMode] = (usertypes.KeyMode.norma... |
.parametrize('username,password', users)
.parametrize('issue_id', issues)
def test_update(db, client, username, password, issue_id):
client.login(username=username, password=password)
url = reverse(urlnames['detail'], args=[issue_id])
data = {}
response = client.put(url, data, content_type='application/... |
def my_syscall_write(ql: Qiling, fd: int, buf: int, count: int):
try:
data = ql.mem.read(buf, count)
fobj = ql.os.fd[fd]
if hasattr(fobj, 'write'):
fobj.write(data)
except:
ret = (- 1)
else:
ret = count
ql.log.info(f'my_syscall_write({fd}, {buf:#x}, {c... |
class SeqEntityScore(object):
def __init__(self, id2label, markup='bio'):
self.id2label = id2label
self.markup = markup
self.reset()
def reset(self):
self.origins = []
self.founds = []
self.rights = []
def compute(self, origin, found, right):
recall = ... |
_REGISTRY.register()
class bjzBlack(bjzStation, ImageDataset):
dataset_name = 'bjzblack'
def __init__(self, root='datasets'):
self.root = root
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.query_dir = osp.join(self.dataset_dir, 'benchmark/black_general_reid/query')
... |
class ArchX86(Arch):
def __init__(self):
super().__init__()
def arch_insn_size(self):
return 15
def regs(self):
return ('eax', 'ebx', 'ecx', 'edx', 'esp', 'ebp', 'esi', 'edi', 'eip', 'ss', 'cs', 'ds', 'es', 'fs', 'gs', 'eflags')
def read_insn(self, address: int) -> bytes:
... |
class FakeNetCDF4FileHandlerMimicLow(FakeNetCDF4FileHandler):
def get_test_content(self, filename, filename_info, filetype_info):
dt_s = filename_info.get('start_time', DEFAULT_DATE)
dt_e = filename_info.get('end_time', DEFAULT_DATE)
if (filetype_info['file_type'] == 'mimicTPW2_comp'):
... |
def bit_mask_of_modes_acted_on_by_fermionic_terms(fermion_term_list, n_qubits=None):
if (n_qubits is None):
n_qubits = 0
for term in fermion_term_list:
n_qubits = max(n_qubits, count_qubits(term))
mask = numpy.zeros((n_qubits, len(fermion_term_list)), dtype=bool)
for (term_number... |
class TestFactoryMethods():
def test_empty(self, shape, density):
nnz = (int(((shape[0] * shape[1]) * density)) or 1)
base = csr.empty(shape[0], shape[1], nnz)
sci = base.as_scipy(full=True)
assert isinstance(base, data.CSR)
assert isinstance(sci, scipy.sparse.csr_matrix)
... |
def join_user_profile(user_profile_file, behavior_file, joined_file):
user_profile_dict = {}
with open(user_profile_file, 'r') as f:
for line in f:
(uid, aid, gid) = line[:(- 1)].split(',')
user_profile_dict[uid] = ','.join([aid, gid])
newlines = []
with open(behavior_fil... |
_module()
class MobileNetV2(nn.Module):
arch_settings = [[1, 16, 1], [6, 24, 2], [6, 32, 3], [6, 64, 4], [6, 96, 3], [6, 160, 3], [6, 320, 1]]
def __init__(self, widen_factor=1.0, strides=(1, 2, 2, 2, 1, 2, 1), dilations=(1, 1, 1, 1, 1, 1, 1), out_indices=(1, 2, 4, 6), frozen_stages=(- 1), conv_cfg=None, norm_c... |
class C(nn.Module):
def __init__(self, nIn, nOut, kSize, stride=1):
super().__init__()
padding = int(((kSize - 1) / 2))
self.conv = nn.Conv2d(nIn, nOut, (kSize, kSize), stride=stride, padding=(padding, padding), bias=False)
def forward(self, input):
output = self.conv(input)
... |
def attack_one_batch(sess, ops, attacked_data):
is_training = False
attacked_label = (np.ones(shape=len(attacked_data), dtype=int) * TARGET)
attacked_label = np.squeeze(attacked_label)
lower_bound = np.zeros(BATCH_SIZE)
WEIGHT = (np.ones(BATCH_SIZE) * INITIAL_WEIGHT)
upper_bound = (np.ones(BATCH... |
def mpl_time_axis(axes, approx_ticks=5.0):
from matplotlib.ticker import Locator, Formatter
class labeled_float(float):
pass
class TimeLocator(Locator):
def __init__(self, approx_ticks=5.0):
self._approx_ticks = approx_ticks
Locator.__init__(self)
def __call__... |
def eval_adv_test_blackbox(model_target, model_source, device, test_loader):
model_target.eval()
model_source.eval()
robust_err_total = 0
natural_err_total = 0
for (data, target) in test_loader:
(data, target) = (data.to(device), target.to(device))
(X, y) = (Variable(data, requires_g... |
def test_abi_label_convertor():
tmp_dir = tempfile.TemporaryDirectory()
dict_file = osp.join(tmp_dir.name, 'fake_dict.txt')
_create_dummy_dict_file(dict_file)
label_convertor = ABIConvertor(dict_file=dict_file, max_seq_len=10)
label_convertor.end_idx
strings = ['hell']
targets_dict = label_c... |
def test_calculate_ssim():
with pytest.raises(AssertionError):
calculate_ssim(np.ones((16, 16)), np.ones((10, 10)), crop_border=0)
with pytest.raises(ValueError):
calculate_ssim(np.ones((16, 16)), np.ones((16, 16)), crop_border=1, input_order='WRONG')
out = calculate_ssim(np.ones((10, 10, 3)... |
def test_trustme_cli_expires_on(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.chdir(tmp_path)
main(argv=['--expires-on', '2035-03-01'])
assert tmp_path.joinpath('server.key').exists()
assert tmp_path.joinpath('server.pem').exists()
assert tmp_path.joinpath('client.pem').exist... |
.skipif((not modeltest.HAS_QT_TESTER), reason='No Qt modeltester available')
def test_qt_tester_invalid(testdir):
testdir.makeini('\n [pytest]\n qt_log_level_fail = NO\n ')
testdir.makepyfile('\n from pytestqt.qt_compat import qt_api\n from pytestqt import modeltest\n\n ass... |
def read_validation_evaluation_run(save_dir: str) -> Optional[EvaluationRun]:
save_path = os.path.join(save_dir, VALIDATION_EVALUATION_DIR, EVALUATION_RUN_PICKLE_FILE_NAME)
if (not os.path.exists(save_path)):
return None
with open(save_path, 'rb') as pkl_file:
return pickle.load(pkl_file) |
def _normalize(x, params, forward=True):
assert ('scale' in params)
if isinstance(x, np.ndarray):
x = torch.from_numpy(x)
scale = params['scale']
offset = params['offset']
x = x.to(device=scale.device, dtype=scale.dtype)
src_shape = x.shape
x = x.reshape((- 1), scale.shape[0])
if... |
.supported(only_if=(lambda backend: backend.ed25519_supported()), skip_message='Requires OpenSSL with Ed25519 support')
_tests('eddsa_test.json')
def test_ed25519_signature(backend, wycheproof):
assert (wycheproof.testgroup['key']['curve'] == 'edwards25519')
key = Ed25519PublicKey.from_public_bytes(binascii.unh... |
class TestConvModuleMeta():
def test_main(self):
conv_module_meta = {'kernel_size': (2,), 'stride': (3,), 'padding': (4,), 'dilation': (5,)}
x = make_conv_module(nn.Conv1d, **conv_module_meta)
actual = meta.conv_module_meta(x)
desired = conv_module_meta
assert (actual == desi... |
class DynamicImportPatchTest(TestPyfakefsUnittestBase):
def __init__(self, methodName='runTest'):
super(DynamicImportPatchTest, self).__init__(methodName)
def test_os_patch(self):
import os
os.mkdir('test')
self.assertTrue(self.fs.exists('test'))
self.assertTrue(os.path.e... |
def transcribe(audio, speech2text=None, config=None):
if (config is None):
config = TranscribeConfig()
if (speech2text is None):
speech2text = load_default_model()
if isinstance(audio, str):
audio = librosa.load(audio, sr=config.samplerate)[0]
nsamples = len(audio)
pos = 0
... |
class FSDPStrategy(Strategy):
process_group: Optional[ProcessGroup] = None
sharding_strategy: Optional[ShardingStrategy] = None
cpu_offload: Optional[CPUOffload] = None
auto_wrap_policy: Optional[Callable[([torch.nn.Module, bool, int], bool)]] = None
backward_prefetch: Optional[BackwardPrefetch] = B... |
class ReconnectLDAPObject(SimpleLDAPObject):
__transient_attrs__ = {'_l', '_ldap_object_lock', '_trace_file', '_reconnect_lock', '_last_bind'}
def __init__(self, uri, trace_level=0, trace_file=None, trace_stack_limit=5, bytes_mode=None, bytes_strictness=None, retry_max=1, retry_delay=60.0, fileno=None):
... |
class ResUnit(nn.Module):
def __init__(self, in_channels, out_channels, stride, padding=1, dilation=1, bottleneck=True, conv1_stride=False):
super(ResUnit, self).__init__()
self.resize_identity = ((in_channels != out_channels) or (stride != 1))
if bottleneck:
self.body = ResBottl... |
def main():
args = parse_args()
root_path = args.root_path
split_info = mmcv.load(osp.join(root_path, 'annotations', 'train_valid_test_split.json'))
split_info['training'] = split_info.pop('train')
split_info['val'] = split_info.pop('valid')
for split in ['training', 'val', 'test']:
prin... |
def _read_spotting_detections_and_labels(args: Dict, num_classes: int) -> Tuple[(List[np.ndarray], List[np.ndarray])]:
splits_dir = Path(args[ARGS_SPLITS_DIR])
results_dir = Path(args[ARGS_RESULTS_DIR])
labels_dir = Path(args[ARGS_LABELS_DIR])
features_dir = Path(args[ARGS_FEATURES_DIR])
game_one_ho... |
def _list_paths_with_resource(game, print_only_area: bool, resource: ResourceInfo, needed_quantity: (int | None)):
from randovania.game_description.game_description import GameDescription
count = 0
game = typing.cast(GameDescription, game)
for area in game.region_list.all_areas:
area_had_resourc... |
class Selector(Layer):
def __init__(self, select, **kwargs):
super(Selector, self).__init__(**kwargs)
self.select = select
self.select_neuron = K.constant(value=self.select)
def build(self, input_shape):
super(Selector, self).build(input_shape)
def call(self, x):
retu... |
(nodes.TypeAlias)
def verify_typealias(stub: nodes.TypeAlias, runtime: MaybeMissing[Any], object_path: list[str]) -> Iterator[Error]:
stub_target = mypy.types.get_proper_type(stub.target)
stub_desc = f'Type alias for {stub_target}'
if isinstance(runtime, Missing):
(yield Error(object_path, 'is not p... |
class PFContextMenuPref(PreferenceView):
def populatePanel(self, panel):
self.title = _t('Context Menus')
self.settings = ContextMenuSettings.getInstance()
self.mainFrame = gui.mainFrame.MainFrame.getInstance()
self.dirtySettings = False
mainSizer = wx.BoxSizer(wx.VERTICAL)
... |
def test_lowest_common_ancestor(graph_nodes, test_instance, root=None):
leaves = imagenet_spec.get_leaves(graph_nodes)
for _ in range(10000):
first_ind = np.random.randint(len(leaves))
second_ind = np.random.randint(len(leaves))
while (first_ind == second_ind):
second_ind = n... |
class inconv(nn.Module):
def __init__(self, in_ch, out_ch, kernel_size=[3, 3, 3], block=BasicBlock, norm=nn.BatchNorm3d):
super().__init__()
if isinstance(kernel_size, int):
kernel_size = ([kernel_size] * 3)
pad_size = [(i // 2) for i in kernel_size]
self.conv1 = nn.Conv3... |
def search(word, exact=True, return_words=True, cache=True):
response_text = request_search(word, cache=cache)
soup = bs4.BeautifulSoup(response_text, 'html.parser')
definitions = soup.find_all('h2', class_='vignette__title')
if (definitions is None):
return []
urlnames = []
for definiti... |
def test_parameterized_types(hive_client):
hms = HMS(hive_client)
client = HiveMetastoreClient(hms)
table = client.schema('test_db', 'test_table3')
fields = table.fields
assert (len(fields) == 7)
assert (fields[0].extra_attrs['name'] == 'col16')
assert isinstance(fields[0], UnionType)
as... |
def update_last_accessed(token_or_user):
if (not config.app_config.get('FEATURE_USER_LAST_ACCESSED')):
return
threshold = timedelta(seconds=config.app_config.get('LAST_ACCESSED_UPDATE_THRESHOLD_S', 120))
if ((token_or_user.last_accessed is not None) and ((datetime.utcnow() - token_or_user.last_acces... |
def _create_walkable_graph(state: EnvironmentState):
doors = state.get_nodes_by_attr('class_name', 'door')
doorjambs = state.get_nodes_by_attr('class_name', 'doorjamb')
adj_lists = {}
for door_node in doors:
door_rooms = state.get_nodes_from(door_node, Relation.BETWEEN)
if (len(door_room... |
()
def eggs_clean(context):
with context.cd(TASK_ROOT_STR):
dirs = set()
dirs.add('.eggs')
for name in os.listdir(os.curdir):
if name.endswith('.egg-info'):
dirs.add(name)
if name.endswith('.egg'):
dirs.add(name)
rmrf(dirs) |
def get_nuScenes_label_name(label_mapping):
with open(label_mapping, 'r') as stream:
nuScenesyaml = yaml.safe_load(stream)
nuScenes_label_name = dict()
for i in sorted(list(nuScenesyaml['learning_map'].keys()))[::(- 1)]:
val_ = nuScenesyaml['learning_map'][i]
nuScenes_label_name[val_... |
_wraps(_stdlib_socket.socketpair, assigned=(), updated=())
def socketpair(family: FamilyT=FamilyDefault, type: TypeT=SocketKind.SOCK_STREAM, proto: int=0) -> tuple[(SocketType, SocketType)]:
(left, right) = _stdlib_socket.socketpair(family, type, proto)
return (from_stdlib_socket(left), from_stdlib_socket(right... |
class ConfigOptionsHandler(ConfigHandler['Distribution']):
section_prefix = 'options'
def __init__(self, target_obj: 'Distribution', options: AllCommandOptions, ignore_option_errors: bool, ensure_discovered: expand.EnsurePackagesDiscovered):
super().__init__(target_obj, options, ignore_option_errors, en... |
class RegexTest(object):
.parametrize('value', ['123', '', '00000'])
def test_valid_input(self, value):
num_only = inputs.regex('^[0-9]+$')
assert (num_only(value) == value)
.parametrize('value', ['abc', '123abc', 'abc123', ''])
def test_bad_input(self, value):
num_only = inputs.... |
def main():
config = read_config(sys.argv[1])
if ('logging' in config):
logging.config.dictConfig(config['logging'])
else:
logging.basicConfig(level=logging.INFO)
downloader = Downloader(config)
db = SQLiteTLE(config['database']['path'], config['platforms'], config['text_writer'])
... |
def rouge(hypotheses, references):
hyps_and_refs = zip(hypotheses, references)
hyps_and_refs = [_ for _ in hyps_and_refs if (len(_[0]) > 0)]
(hypotheses, references) = zip(*hyps_and_refs)
rouge_1 = [rouge_n([hyp], [ref], 1) for (hyp, ref) in zip(hypotheses, references)]
rouge_2 = [rouge_n([hyp], [re... |
class SvgDraggablePoint(gui.SvgRectangle, DraggableItem):
def __init__(self, app_instance, name_coord_x, name_coord_y, compatibility_iterable, **kwargs):
self.w = 15
self.h = 15
super(SvgDraggablePoint, self).__init__(0, 0, self.w, self.h, **kwargs)
DraggableItem.__init__(self, app_i... |
.parametrize('username,password', users)
.parametrize('project_id', projects)
def test_list(db, client, username, password, project_id):
client.login(username=username, password=password)
url = reverse(urlnames['list'], args=[project_id])
response = client.get(url)
if (project_id in view_integration_per... |
class SYSTEM_PROCESS_INFORMATION(Structure):
_fields_ = [('NextEntryOffset', ULONG), ('NumberOfThreads', ULONG), ('WorkingSetPrivate', LARGE_INTEGER), ('HardFaultCount', ULONG), ('NumberOfThreadsHighWatermark', ULONG), ('CycleTime', c_ulonglong), ('CreateTime', LARGE_INTEGER), ('UserTime', LARGE_INTEGER), ('KernelT... |
class Describe_NumberingDefinitions():
def it_knows_how_many_numbering_definitions_it_contains(self, len_fixture):
(numbering_definitions, numbering_definition_count) = len_fixture
assert (len(numbering_definitions) == numbering_definition_count)
(params=[0, 1, 2, 3])
def len_fixture(self, r... |
def test_exit(manager_nospawn, minimal_conf_noscreen):
qewidget = widget.QuickExit(timer_interval=0.001, countdown_start=1)
config = minimal_conf_noscreen
config.screens = [libqtile.config.Screen(top=libqtile.bar.Bar([qewidget], 10))]
manager_nospawn.start(config)
topbar = manager_nospawn.c.bar['top... |
def make_loop_careduce(loop_orders, dtypes, loop_tasks, sub):
def loop_over(preloop, code, indices, i):
iterv = f'ITER_{int(i)}'
update = ''
suitable_n = '1'
for (j, index) in enumerate(indices):
var = sub[f'lv{int(j)}']
update += f'''{var}_iter += {var}_jump{... |
class Venue(Object):
def __init__(self, *, client: 'pyrogram.Client'=None, location: 'types.Location', title: str, address: str, foursquare_id: str=None, foursquare_type: str=None):
super().__init__(client)
self.location = location
self.title = title
self.address = address
se... |
class VariationalEncoderDecoderGen(keras.utils.Sequence):
def __init__(self, feature_root, modalities, split_root, phase, batch_size, shuffle=True):
assert (phase in ['train', 'val', 'test']), 'phase must be one of train, val, test!'
index_path = os.path.join(split_root, '{}.txt'.format(phase))
... |
def test_unicode_issue368(pytester: Pytester) -> None:
path = pytester.path.joinpath('test.xml')
log = LogXML(str(path), None)
ustr = '!'
class Report(BaseReport):
longrepr = ustr
sections: List[Tuple[(str, str)]] = []
nodeid = 'something'
location = ('tests/filename.py',... |
def test_load_adaptor_twice():
old_sys_path = sys.path
path = os.path.split(os.path.abspath(__file__))[0]
sys.path.append(path)
Engine()._load_adaptors(['mockadaptor_enabled', 'mockadaptor_enabled'])
cpis = Engine().loaded_adaptors()
mocks = cpis['radical.saga.job.Job']['mock']
assert (len(m... |
def add_verbosity_args(parser, train=False):
verbosity_group = parser.add_argument_group('Verbosity')
verbosity_group.add_argument('--log-verbose', action='store_true', help='Whether to output more verbose logs for debugging/profiling.')
verbosity_group.add_argument('--args-verbosity', default=1, type=int, ... |
def negative_sampling(pos_samples, num_entity, negative_rate):
size_of_batch = len(pos_samples)
num_to_generate = (size_of_batch * negative_rate)
neg_samples = np.tile(pos_samples, (negative_rate, 1))
labels = np.zeros((size_of_batch * (negative_rate + 1)), dtype=np.float32)
labels[:size_of_batch] =... |
def main():
multiprocessing.freeze_support()
import randovania
randovania.setup_logging('INFO', None, quiet=True)
logging.debug('Starting Randovania...')
dotnet_path = randovania.get_data_path().joinpath('dotnet_runtime')
if (randovania.is_frozen() and dotnet_path.exists()):
os.environ['... |
class PreActivationBottleneck(nn.Module):
expansion = 4
def __init__(self, inplanes, planes, stride=1, downsample=None):
super(PreActivationBottleneck, self).__init__()
self.bn1 = nn.BatchNorm3d(inplanes)
self.conv1 = nn.Conv3d(inplanes, planes, kernel_size=1, bias=False)
self.bn... |
def make_layers(cfg, batch_norm=False, deconv=None):
layers = []
in_channels = 3
if (not deconv):
for v in cfg:
if (v == 'M'):
layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
else:
conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1)
... |
def _get_ticklabels(band_type, kHz, separator):
if (separator is None):
import locale
separator = locale.localeconv()['decimal_point']
if (band_type == 'octave'):
if (kHz is True):
ticklabels = TICKS_OCTAVE_KHZ
else:
ticklabels = TICKS_OCTAVE
elif (kHz... |
class PassportElementErrorSelfie(PassportElementError):
__slots__ = ('file_hash',)
def __init__(self, type: str, file_hash: str, message: str, *, api_kwargs: Optional[JSONDict]=None):
super().__init__('selfie', type, message, api_kwargs=api_kwargs)
with self._unfrozen():
self.file_ha... |
def get_service_ips_and_ports(component_name):
try:
get_service_cmd = ['kubectl', 'get', 'service', component_name, '-o', 'json']
service_spec = subprocess.check_output(get_service_cmd).strip().decode('UTF-8')
spec = json.loads(service_spec)
external_ips = spec['spec'].get('externalI... |
class Conv2d_Atari(nn.Module):
def __init__(self, in_channels=4, feature_dim=512):
super().__init__()
self.conv1 = layer_init(nn.Conv2d(in_channels, 32, kernel_size=8, stride=4))
self.conv2 = layer_init(nn.Conv2d(32, 64, kernel_size=4, stride=2))
self.conv3 = layer_init(nn.Conv2d(64,... |
class Win32Raw(Escpos):
def is_usable() -> bool:
return is_usable()
_win32print
def __init__(self, printer_name: str='', *args, **kwargs) -> None:
Escpos.__init__(self, *args, **kwargs)
self.printer_name = printer_name
self.job_name = ''
self._device: Union[(Literal[F... |
('PyQt6.QtWidgets.QGraphicsPixmapItem.keyPressEvent')
def test_key_press_event_other(key_mock, qapp, item):
item.exit_crop_mode = MagicMock()
event = MagicMock()
event.key.return_value = Qt.Key.Key_Space
item.keyPressEvent(event)
item.exit_crop_mode.assert_not_called()
key_mock.assert_called_onc... |
class BacktestPositionFactory():
def create_position(ticker: Ticker) -> BacktestPosition:
sec_type = ticker.security_type
if (sec_type == SecurityType.STOCK):
return BacktestEquityPosition(ticker)
elif (sec_type == SecurityType.FUTURE):
return BacktestFuturePosition(t... |
def run_gat_target(args, device, data):
(train_g, val_g, test_g, in_feats, labels, n_classes, g, num_heads) = data
train_nid = train_g.nodes()
val_nid = val_g.nodes()
test_nid = test_g.nodes()
sampler = dgl.dataloading.MultiLayerNeighborSampler([int(fanout) for fanout in args.fan_out.split(',')])
... |
def get_files(**kwargs):
relative_root = kwargs.get('relative_root', '')
files = [File(Path(relative_root, f.path), f.contents) for f in get_template_files(**kwargs)]
files.extend((File(Path(relative_root, kwargs['package_name'], 'lib.so'), ''), File(Path(relative_root, '.hgignore'), 'syntax: glob\n*.pyc\n\... |
.end_to_end()
.skipif((not _TEST_SHOULD_RUN), reason='pygraphviz is required')
.parametrize('layout', _GRAPH_LAYOUTS)
.parametrize('format_', _TEST_FORMATS)
.parametrize('rankdir', ['LR'])
def test_create_graph_via_cli(tmp_path, runner, format_, layout, rankdir):
if ((sys.platform == 'win32') and (format_ == 'pdf')... |
class SmtLib20Parser(SmtLibParser):
def __init__(self, environment=None, interactive=False):
SmtLibParser.__init__(self, environment, interactive)
del self.commands['check-sat-assuming']
del self.commands['declare-const']
del self.commands['define-fun-rec']
del self.commands[... |
def SelectPeakIndex(FFT_Data, endpoint=True):
D1 = (FFT_Data[1:(- 1)] - FFT_Data[0:(- 2)])
D2 = (FFT_Data[1:(- 1)] - FFT_Data[2:])
D3 = np.logical_and((D1 > 0), (D2 > 0))
tmp = np.where((D3 == True))
sel_ind = (tmp[0] + 1)
if endpoint:
if ((FFT_Data[0] - FFT_Data[1]) > 0):
se... |
class ConcatInternalConnectivity(InternalConnectivity):
def __init__(self, input_mask_and_length_tuple: List[Tuple[(List, int)]], output_mask_and_length_tuple: List[Tuple[(List, int)]]):
assert (len(input_mask_and_length_tuple) > 1)
assert (len(output_mask_and_length_tuple) == 1)
super().__i... |
class VanillaOption(Instrument):
def __init__(self, option_type, expiry_type, strike, expiry_date, derivative_type):
self.option_type = (option_type or VanillaOptionType.CALL.value)
self.expiry_type = (expiry_type or ExpiryType.EUROPEAN.value)
self.strike = strike
self.expiry_date = ... |
def listen_cli(args):
dicom_listener = DicomListener(host=args.host, port=args.port, ae_title=args.aetitle, storage_directory=args.storage_directory)
logging.info('Starting DICOM listener')
logging.info('IP: %s', args.host)
logging.info('Port: %s', args.port)
logging.info('AE Title: %s', args.aetitl... |
class TestInterpreterVersion():
def test_warn(self, monkeypatch):
class MockConfigVar():
def __init__(self, return_):
self.warn = None
self._return = return_
def __call__(self, name, warn):
self.warn = warn
return self._... |
class CIFARPyramidNet(nn.Module):
def __init__(self, channels, init_block_channels, bottleneck, in_channels=3, in_size=(32, 32), num_classes=10):
super(CIFARPyramidNet, self).__init__()
self.in_size = in_size
self.num_classes = num_classes
self.features = nn.Sequential()
self... |
def parse_args():
parser = argparse.ArgumentParser(description='Collect data to be submitted to the server')
group = parser.add_mutually_exclusive_group()
group.add_argument('--plugins', action='store_true', help='Only run plugins (no commands)')
group.add_argument('--commands', action='store_true', hel... |
_fixtures(WebFixture)
def test_activating_javascript(web_fixture):
(Widget)
class WidgetWithJavaScript(Widget):
def __init__(self, view, fake_js):
super().__init__(view)
self.fake_js = fake_js
def get_js(self, context=None):
return [self.fake_js]
class MyP... |
class MultiWozV22(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version('2.2.0')
def _info(self):
features = datasets.Features({'dialogue_id': datasets.Value('string'), 'db_root_path': datasets.Value('string'), 'services': datasets.Sequence(datasets.Value('string')), 'db_paths': datasets.Sequence(... |
class HeisenbergModel(LatticeModel):
def __init__(self, lattice: Lattice, coupling_constants: tuple=(1.0, 1.0, 1.0), ext_magnetic_field: tuple=(0.0, 0.0, 0.0)) -> None:
super().__init__(lattice)
self.coupling_constants = coupling_constants
self.ext_magnetic_field = ext_magnetic_field
def... |
def any_causes_overload_ambiguity(items: list[CallableType], return_types: list[Type], arg_types: list[Type], arg_kinds: list[ArgKind], arg_names: (Sequence[(str | None)] | None)) -> bool:
if all_same_types(return_types):
return False
actual_to_formal = [map_formals_to_actuals(arg_kinds, arg_names, item... |
class Cache():
def __init__(self, cache_file_location: str='.pyspark_ai.json', file_format: str='json'):
self._staging_updates: Dict[(str, str)] = {}
if (file_format == 'json'):
self._file_cache: FileCache = JsonCache(cache_file_location)
else:
self._file_cache = SQLi... |
class TestExpandXarrayDims(object):
def setup_method(self):
self.test_inst = pysat.Instrument(inst_module=pysat.instruments.pysat_ndtesting, use_header=True)
self.start_time = pysat.instruments.pysat_ndtesting._test_dates['']['']
self.data_list = []
self.out = None
self.meta ... |
def evaluate(instruction, input=None, temperature=0.1, top_p=0.75, top_k=40, num_beams=4, max_new_tokens=256, **kwargs):
prompt = generate_prompt(instruction, input)
inputs = tokenizer(prompt, return_tensors='pt')
input_ids = inputs['input_ids'].to(device)
generation_config = GenerationConfig(temperatur... |
.parametrize(('t', 't2', 'result'), ((TClass[(int, int)], str, TClass(TClass(1, 2), 'a')), (List[TClass[(int, int)]], str, TClass([TClass(1, 2)], 'a'))))
def test_structure_nested_generics(converter: BaseConverter, t, t2, result):
res = converter.structure(asdict(result), TClass[(t, t2)])
assert (res == result) |
class FCNHead(nn.Sequential):
def __init__(self, in_channels, channels):
inter_channels = (in_channels // 4)
layers = [nn.Conv2d(in_channels, inter_channels, 3, padding=1, bias=False), nn.BatchNorm2d(inter_channels), nn.ReLU(), nn.Dropout(0.1), nn.Conv2d(inter_channels, channels, 1)]
super(F... |
class CallError(Error):
def __str__(self) -> str:
if (len(self.args) == 1):
return self.args[0]
(instance, method, args, kwargs, original_error, stack) = self.args
cls = (instance.__class__.__name__ if (instance is not None) else '')
full_method = '.'.join((cls, method.__... |
class GitVisionConfig(PretrainedConfig):
model_type = 'git_vision_model'
def __init__(self, hidden_size=768, intermediate_size=3072, num_hidden_layers=12, num_attention_heads=12, num_channels=3, image_size=224, patch_size=16, hidden_act='quick_gelu', layer_norm_eps=1e-05, attention_dropout=0.0, initializer_rang... |
def test_one(args, wav_root, store_root, rescale, soundstream):
(wav, sr) = librosa.load(wav_root, sr=args.sr)
wav = torch.tensor(wav).unsqueeze(0)
wav = wav.unsqueeze(1).cuda()
compressed = soundstream.encode(wav, target_bw=args.target_bw)
print('finish compressing')
out = soundstream.decode(co... |
_module()
class BCELossWithLogits(BaseWeightedLoss):
def __init__(self, loss_weight=1.0, class_weight=None):
super().__init__(loss_weight=loss_weight)
self.class_weight = None
if (class_weight is not None):
self.class_weight = torch.Tensor(class_weight)
def _forward(self, cls... |
class TResNet(nn.Module):
def __init__(self, layers, in_chans=3, num_classes=1000, width_factor=1.0, v2=False, global_pool='fast', drop_rate=0.0):
self.num_classes = num_classes
self.drop_rate = drop_rate
super(TResNet, self).__init__()
aa_layer = BlurPool2d
self.inplanes = i... |
class ScheduleInvitation():
id: strawberry.ID
option: ScheduleInvitationOption
notes: str
title: str
submission: Submission
dates: List[ScheduleInvitationDate]
def from_django_model(cls, instance):
return cls(id=instance.submission.hashid, title=instance.title, option=ScheduleInvitat... |
class CMDefaults():
user = User(1, 'First name', False)
custom_title: str = 'PTB'
is_anonymous: bool = True
until_date: datetime.datetime = to_timestamp(datetime.datetime.utcnow())
can_be_edited: bool = False
can_change_info: bool = True
can_post_messages: bool = True
can_edit_messages: ... |
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