code stringlengths 281 23.7M |
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class ListOrValue(BaseType):
_show_valtype = True
def __init__(self, valtype: BaseType, *, none_ok: bool=False, completions: _Completions=None, **kwargs: Any) -> None:
super().__init__(none_ok=none_ok, completions=completions)
assert (not isinstance(valtype, (List, ListOrValue))), valtype
... |
class RequestParserSchemaTest(object):
def test_empty_parser(self):
parser = RequestParser()
assert (parser.__schema__ == [])
def test_primitive_types(self):
parser = RequestParser()
parser.add_argument('int', type=int, help='Some integer')
parser.add_argument('str', type... |
def nppro_solve_qp(P: np.ndarray, q: np.ndarray, G: Optional[np.ndarray]=None, h: Optional[np.ndarray]=None, A: Optional[np.ndarray]=None, b: Optional[np.ndarray]=None, lb: Optional[np.ndarray]=None, ub: Optional[np.ndarray]=None, initvals: Optional[np.ndarray]=None, **kwargs) -> Optional[np.ndarray]:
problem = Pro... |
def bench_pathlib(loops, tmp_path):
base_path = pathlib.Path(tmp_path)
path_objects = list(base_path.iterdir())
for p in path_objects:
p.stat()
assert (len(path_objects) == NUM_FILES), len(path_objects)
range_it = range(loops)
t0 = pyperf.perf_counter()
for _ in range_it:
for... |
def attrs(maybe_cls=None, these=None, repr_ns=None, repr=None, cmp=None, hash=None, init=None, slots=False, frozen=False, weakref_slot=True, str=False, auto_attribs=False, kw_only=False, cache_hash=False, auto_exc=False, eq=None, order=None, auto_detect=False, collect_by_mro=False, getstate_setstate=None, on_setattr=No... |
class VNetConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, layers=2):
super(VNetConvBlock, self).__init__()
self.layers = layers
self.afs = torch.nn.ModuleList()
self.convs = torch.nn.ModuleList()
self.bns = torch.nn.ModuleList()
self.convs.append(n... |
class AttrVI_ATTR_USB_RECV_INTR_SIZE(RangeAttribute):
resources = [constants.EventType.usb_interrupt]
py_name = 'size'
visa_name = 'VI_ATTR_USB_RECV_INTR_SIZE'
visa_type = 'ViUInt16'
default = NotAvailable
(read, write, local) = (True, False, True)
(min_value, max_value, values) = (0, 65535,... |
class ValueConflictValidator():
requires_context = True
def __call__(self, data, serializer):
if serializer.instance:
updated = serializer.context['view'].request.data.get('updated')
if (updated is not None):
delta = abs((parse_datetime(updated) - serializer.insta... |
_loss('swav_loss')
class SwAVLoss(ClassyLoss):
def __init__(self, loss_config: AttrDict):
super().__init__()
self.loss_config = loss_config
self.queue_start_iter = self.loss_config.queue.start_iter
self.was_using_queue = False
self.swav_criterion = SwAVCriterion(self.loss_con... |
class Test2_Forever(unittest.TestCase):
def setUp(self):
self.s = serial.serial_for_url(PORT, timeout=None)
def tearDown(self):
self.s.close()
def test1_inWaitingEmpty(self):
self.assertEqual(self.s.in_waiting, 0, 'expected empty buffer')
def test2_Loopback(self):
for blo... |
_ordering
class ID3TimeStamp(object):
import re
def __init__(self, text):
if isinstance(text, ID3TimeStamp):
text = text.text
elif (not isinstance(text, str)):
raise TypeError('not a str')
self.text = text
__formats = (['%04d'] + (['%02d'] * 5))
__seps = [... |
def mv_images_to_folder(data_root='data/ref-davis', output_root='data/ref-davis'):
train_img_path = os.path.join(output_root, 'train/JPEGImages')
train_anno_path = os.path.join(output_root, 'train/Annotations')
val_img_path = os.path.join(output_root, 'valid/JPEGImages')
val_anno_path = os.path.join(out... |
class NormalQueue1EntryRTL(Component):
def construct(s, EntryType):
s.enq = EnqIfcRTL(EntryType)
s.deq = DeqIfcRTL(EntryType)
s.count = OutPort(Bits1)
s.entry = Wire(EntryType)
s.full = Wire(Bits1)
s.count //= s.full
s.deq.ret //= s.entry
s.enq.rdy //=... |
class Box(RegisterOp):
error_kind = ERR_NEVER
def __init__(self, src: Value, line: int=(- 1)) -> None:
super().__init__(line)
self.src = src
self.type = object_rprimitive
if (is_none_rprimitive(self.src.type) or is_bool_rprimitive(self.src.type) or is_bit_rprimitive(self.src.type... |
def check_struct_group(crystal, group, dim=3, tol=0.01):
import warnings
with warnings.catch_warnings():
warnings.simplefilter('ignore')
if (type(crystal) == random_crystal):
lattice = struct.lattice.matrix
if (dim != 0):
old_coords = deepcopy(crystal.stru... |
def get_selfie_and_smiles_info(smiles_list, filename):
(largest_smiles_len, largest_selfies_len) = get_largest_string_len(smiles_list, filename)
(smiles_alphabet, selfies_alphabet) = get_string_alphabet(smiles_list, filename)
return (selfies_alphabet, largest_selfies_len, smiles_alphabet, largest_smiles_len... |
def _launch_qt_console(connection_file):
from subprocess import Popen
exe = None
if (sys.executable and (os.path.basename(sys.executable) in ('python.exe', 'pythonw.exe'))):
path = os.path.join(os.path.dirname(sys.executable), 'Scripts')
exe = os.path.join(path, 'jupyter-qtconsole.exe')
... |
class BasicSingleContextAndQuestionIndependentModel(MultipleContextModel):
def __init__(self, encoder: QuestionsAndParagraphsEncoder, word_embed: Optional[WordEmbedder], char_embed: Optional[CharWordEmbedder], embed_mapper: Optional[Union[(SequenceMapper, ElmoWrapper)]], sequence_encoder: SequenceEncoder, merger: M... |
def test_junction_group():
jg = pyodrx.JunctionGroup('my roundabout', 0)
jg.add_junction(1)
jg.add_junction(2)
jg.add_junction(3)
prettyprint(jg.get_element())
jg2 = pyodrx.JunctionGroup('my roundabout', 0)
jg2.add_junction(1)
jg2.add_junction(2)
jg2.add_junction(3)
jg3 = pyodrx.... |
class SimpleTokenizer(object):
def __init__(self, bpe_path: str=default_bpe(), special_tokens=None):
self.byte_encoder = bytes_to_unicode()
self.byte_decoder = {v: k for (k, v) in self.byte_encoder.items()}
merges = gzip.open(bpe_path).read().decode('utf-8').split('\n')
merges = merg... |
class Conv_BN_LeakyReLU(nn.Module):
def __init__(self, in_channels, out_channels, ksize, padding=0, stride=1, dilation=1):
super(Conv_BN_LeakyReLU, self).__init__()
self.convs = nn.Sequential(nn.Conv2d(in_channels, out_channels, ksize, padding=padding, stride=stride, dilation=dilation), nn.BatchNorm... |
def extract_summary_without_rerank(article, true_labels, opts):
pred_summary = []
backup = []
for (sent_id, lbl) in enumerate(true_labels):
if (lbl == 'T'):
pred_summary.append(article[sent_id])
if (len(pred_summary) >= opts['topk']):
break
elif (lbl =... |
def qube_general():
with open('QUBE_general_pi.xml', 'w+') as qube:
qube.write('<ForceField>\n <Info>\n <DateGenerated>2019-02-14--correctedHIS,THR,LYS,ASP issues, PRO-amino are still opls </DateGenerated>\n <Reference>modified using amber forcefield template +amber charges + opls atomtype+modified s... |
class KS_With_Include_TestCase(TestCase):
def setUp(self):
super(KS_With_Include_TestCase, self).setUp()
self._include_path = mktempfile('unknown_command --foo=bar', prefix='ks-include')
ks_content = ('autopart --type=lvm\n%%include %s' % self._include_path)
self._ks_path = mktempfil... |
class SyncApis(Generic[ClientT]):
def __init__(self, host: str=None, **kwargs: Any):
self.client = ApiClient(host, **kwargs)
self.cluster_api = SyncClusterApi(self.client)
self.collections_api = SyncCollectionsApi(self.client)
self.points_api = SyncPointsApi(self.client)
self... |
class Shader():
VERSION = '1.10'
def __init__(self, vertex, frag, name):
self.vertex = vertex
self.frag = frag
self.compiled = False
self.name = name
self.uniforms = {}
shaders[name] = self
def __deepcopy__(self, memo=None):
memo[id(self)] = self
... |
def build_type_map(mapper: Mapper, modules: list[MypyFile], graph: Graph, types: dict[(Expression, Type)], options: CompilerOptions, errors: Errors) -> None:
classes = []
for module in modules:
module_classes = [node for node in module.defs if isinstance(node, ClassDef)]
classes.extend([(module,... |
class Wavelet_LSTM(nn.Module):
def __init__(self, seq_len, hidden_size, output_size):
super(Wavelet_LSTM, self).__init__()
self.seq_len = seq_len
self.hidden_size = hidden_size
self.output_size = output_size
self.mWDN1_H = nn.Linear(seq_len, seq_len)
self.mWDN1_L = nn... |
class Director5x5(nn.Module):
def __init__(self, channel, groups, outChannels=None):
super().__init__()
if (outChannels is None):
outChannels = channel
self._net = nn.Sequential(conv5x5(channel, channel, 1, groups=groups))
def forward(self, x: torch.Tensor):
return se... |
class GetChatJoinRequests():
async def get_chat_join_requests(self: 'pyrogram.Client', chat_id: Union[(int, str)], limit: int=0, query: str='') -> Optional[AsyncGenerator[('types.ChatJoiner', None)]]:
current = 0
total = (abs(limit) or ((1 << 31) - 1))
limit = min(100, total)
offset_... |
_fixtures(DependencyScenarios)
def test_dependency_types_detected(dependency_scenarios):
main_egg = ReahlEggStub('main_egg', {'1.0': []})
dependency_egg = ReahlEggStub('dependency_egg', {'5.0': []})
[mv1] = main_egg.get_versions()
[dv1] = dependency_egg.get_versions()
main_egg.dependencies = {str(mv... |
def test_render_very_verbose_better_error_message() -> None:
io = BufferedIO()
io.set_verbosity(Verbosity.VERY_VERBOSE)
try:
simple.simple_exception()
except Exception as e:
trace = ExceptionTrace(e)
trace.render(io)
expected = f'''
Stack trace:
1 {trace._get_relative_file_p... |
def load_config(filename):
cp = ConfigParser()
cp.add_section('irc')
cp.set('irc', 'port', '6667')
cp.set('irc', 'nick', 'twitterbot')
cp.set('irc', 'prefixes', 'cats')
cp.add_section('twitter')
cp.set('twitter', 'oauth_token_file', OAUTH_FILE)
cp.read((filename,))
(cp.get('twitter',... |
def iterate_testfiles(skip_encrypted=True):
encrypted = (TestFiles.encrypted,)
for attr_name in dir(TestFiles):
if attr_name.startswith('_'):
continue
member = getattr(TestFiles, attr_name)
if (skip_encrypted and (member in encrypted)):
continue
(yield mem... |
class DimmerLightOnCommand(Command):
light: Light
prevLevel: int = 0
def __init__(self, light: Light):
self.light = light
def execute(self) -> None:
self.prevLevel = self.light.getLevel()
self.light.dim(75)
def undo(self) -> None:
self.light.dim(self.prevLevel) |
class SqueezeExciteCl(nn.Module):
def __init__(self, channels, rd_ratio=(1.0 / 16), rd_channels=None, rd_divisor=8, bias=True, act_layer=nn.ReLU, gate_layer='sigmoid'):
super().__init__()
if (not rd_channels):
rd_channels = make_divisible((channels * rd_ratio), rd_divisor, round_limit=0.... |
class Runtime(threading.Thread):
SHUTDOWN_TRIGGER = 'RUNTIME SHUTDOWN TRIGGERED'
def __init__(self, expert_backends: Dict[(str, ExpertBackend)], prefetch_batches=64, sender_threads: int=1, device: torch.device=None, stats_report_interval: Optional[int]=None):
super().__init__()
self.expert_backe... |
class ProgressBar(object):
def __init__(self, widgets=['progress'], maxval=1, *args, **kwargs):
self._widgets = widgets
self._maxval = maxval
self._val = 0
self._time = time.time()
def label(self):
for widget in self._widgets:
if isinstance(widget, str):
... |
class Effect11696(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Capital Hybrid Turret')), 'trackingSpeed', src.getModifiedItemAttr('shipBonusDreadnoughtC1'), skill='Caldari Dreadnought', **kwarg... |
class Variable(QuadraticProgramElement):
Type = VarType
def __init__(self, quadratic_program: Any, name: str, lowerbound: Union[(float, int)]=0, upperbound: Union[(float, int)]=INFINITY, vartype: VarType=VarType.CONTINUOUS) -> None:
if (lowerbound > upperbound):
raise QiskitOptimizationError... |
class CallExpr(Expression):
__slots__ = ('callee', 'args', 'arg_kinds', 'arg_names', 'analyzed')
__match_args__ = ('callee', 'args', 'arg_kinds', 'arg_names')
def __init__(self, callee: Expression, args: list[Expression], arg_kinds: list[ArgKind], arg_names: list[(str | None)], analyzed: (Expression | None)... |
def load_json_logs(json_logs):
log_dicts = [{} for _ in json_logs]
for (json_log, log_dict) in zip(json_logs, log_dicts):
with open(json_log, 'r') as log_file:
for line in log_file:
log = json.loads(line.strip())
if ('epoch' not in log):
co... |
class LogItemBundle(Event):
def from_dict(self):
super().from_dict()
self.character = objects.Character(self._data.get('character', {}))
self.parent_item = objects.Item(self._data.get('parentItem', {}))
self.child_item = objects.Item(self._data.get('childItem', {})) |
class Visualization():
def __init__(self, eigenstates):
pass
def plot_eigenstate(self):
pass
def slider_plot(self):
pass
def animate_eigenstates(self):
pass
def superpositions(self, states: Union[(int, List[int], Dict[(int, complex)])], **kw):
pass |
def is_an_upcast(type1, type2):
category = {'bool': (0, 0), 'uint8': (1, 1), 'uint16': (1, 2), 'uint32': (1, 3), 'uint64': (1, 4), 'int8': (2, 1), 'int16': (2, 2), 'int32': (2, 3), 'int64': (2, 4), 'float16': (3, 1.5), 'float32': (3, 2.5), 'float64': (3, 3.5), 'complex64': (4, 3), 'complex128': (4, 4)}
cat1 = c... |
class MarkConfig():
def __init__(self, keyword, run_by_default, addoption=True, option=None, help=None, condition_for_skip=None, reason=None):
self.addoption = addoption
if (option is None):
option = f"--{('skip' if run_by_default else 'run')}-{keyword.replace('_', '-')}"
self.op... |
def check_cert(host, cert):
try:
b = pem.dePem(cert, 'CERTIFICATE')
x = x509.X509(b)
except:
traceback.print_exc(file=sys.stdout)
return
try:
x.check_date()
expired = False
except:
expired = True
m = ('host: %s\n' % host)
m += ('has_expired... |
def test_animal_zebra_dataset():
dataset = 'AnimalZebraDataset'
dataset_class = DATASETS.get(dataset)
dataset_info = Config.fromfile('configs/_base_/datasets/zebra.py').dataset_info
channel_cfg = dict(num_output_channels=9, dataset_joints=9, dataset_channel=[[0, 1, 2, 3, 4, 5, 6, 7, 8]], inference_chann... |
class OpInstanceConfigGenerator():
def __init__(self, op_type_supported_kernels: dict, op_type_pcq: dict):
self.op_type_supported_kernels = op_type_supported_kernels
self.op_type_pcq = op_type_pcq
assert (ConfigDictKeys.DEFAULTS in self.op_type_supported_kernels)
assert (ConfigDictKe... |
def block_layer(inputs, filters, bottleneck, block_fn, blocks, strides, training, name, data_format):
filters_out = ((filters * 4) if bottleneck else filters)
def projection_shortcut(inputs):
return conv2d_fixed_padding(inputs=inputs, filters=filters_out, kernel_size=1, strides=strides, data_format=data... |
def _normalize_msid(msid, normalization, n, k, ts):
normed_msid = msid.copy()
if (normalization == 'empty'):
normed_msid /= n
elif (normalization == 'complete'):
normed_msid /= (1 + ((n - 1) * np.exp(((- (1 + (1 / (n - 1)))) * ts))))
elif (normalization == 'er'):
xs = np.linspace... |
def deprocess_fit(coef, intercept, pre_pro_out, fit_intercept):
coef = np.array(coef)
is_mr = is_multi_response(coef)
if (not is_mr):
coef = coef.ravel()
if ((pre_pro_out is not None) and ('X_scale' in pre_pro_out)):
coef = (diags((1 / pre_pro_out['X_scale'])) coef)
if fit_intercept... |
def test_disabled_command_not_in_history(disable_commands_app):
message_to_print = 'These commands are currently disabled'
disable_commands_app.disable_command('has_helper_funcs', message_to_print)
saved_len = len(disable_commands_app.history)
run_cmd(disable_commands_app, 'has_helper_funcs')
assert... |
.functions
(df=categoricaldf_strategy())
(deadline=None)
def test_all_cat_not_None(df):
result = df.encode_categorical(numbers=np.array([3, 1, 2]))
categories = pd.CategoricalDtype(categories=[3, 1, 2], ordered=True)
expected = df.astype({'numbers': categories})
assert expected['numbers'].equals(result[... |
def test_unpacking_starred_and_dicts_in_assignment() -> None:
node = extract_node('\n a, *b = {1:2, 2:3, 3:4}\n b\n ')
inferred = next(node.infer())
assert isinstance(inferred, nodes.List)
assert (inferred.as_string() == '[2, 3]')
node = extract_node('\n a, *b = {1:2}\n b\n ')
... |
('pymodbus.transport.transport_serial.serial.serial_for_url', mock.MagicMock())
class TestBasicSerial():
(name='use_port')
def get_port_in_class(base_ports):
base_ports[__class__.__name__] += 1
return base_ports[__class__.__name__]
async def test_init(self):
SerialTransport(asyncio.g... |
def notification(subject, body, urgency=None, timeout=None):
cmds = []
urgs = {0: 'low', 1: 'normal', 2: 'critical'}
urg_level = urgs.get(urgency, 'normal')
if (urg_level != 'normal'):
cmds += ['-u', urg_level]
if timeout:
cmds += ['-t', '{}'.format(timeout)]
cmds += [subject, bo... |
class PrioritizedReplayBuffer(ReplayBuffer):
def __init__(self, size, alpha):
super(PrioritizedReplayBuffer, self).__init__(size)
assert (alpha > 0)
self._alpha = alpha
it_capacity = 1
while (it_capacity < size):
it_capacity *= 2
self._it_sum = SumSegmentT... |
def read_smiles(file_path):
if any([('gz' in ext) for ext in os.path.basename(file_path).split('.')[1:]]):
logger.debug("'gz' found in file path: using gzip")
with gzip.open(file_path) as f:
smiles = f.read().splitlines()
smiles = [smi.decode('utf-8') for smi in smiles]
e... |
def upgrade(op, tables, tester):
op.create_table('tagtorepositorytag', sa.Column('id', sa.Integer(), nullable=False), sa.Column('repository_id', sa.Integer(), nullable=False), sa.Column('tag_id', sa.Integer(), nullable=False), sa.Column('repository_tag_id', sa.Integer(), nullable=False), sa.ForeignKeyConstraint(['r... |
def test_AddValueToZero_simple_matrix():
dm = skcriteria.mkdm(matrix=[[1, 0, 3], [0, 5, 6]], objectives=[min, max, min], weights=[1, 2, 0])
expected = skcriteria.mkdm(matrix=[[1.5, 0.5, 3], [0.5, 5.5, 6]], objectives=[min, max, min], weights=[1, 2, 0])
scaler = AddValueToZero(value=0.5, target='matrix')
... |
def _legacy_decay_learning_rate(network: Model, initial_learning_rate: float, epochs: int) -> None:
current_learning_rate = K.get_value(network.optimizer.lr)
new_learning_rate = (current_learning_rate - ((initial_learning_rate - LEGACY_FINAL_LEARNING_RATE) / epochs))
K.set_value(network.optimizer.lr, new_le... |
def get_seq_bkg(seq, kid, start=0):
frames = sorted(os.listdir(seq))
depths = []
for frame in frames[start:]:
depth_file = join(seq, frame, f'k{kid}.depth.png')
depth = cv2.imread(depth_file, cv2.IMREAD_ANYDEPTH)
if (depth is not None):
depths.append(depth)
avg = np.s... |
class TestKaldiIO(unittest.TestCase):
def testClassifyRxfilename(self):
self.assertEqual(InputType.STANDARD_INPUT, classify_rxfilename(''))
self.assertEqual(InputType.NO_INPUT, classify_rxfilename(' '))
self.assertEqual(InputType.NO_INPUT, classify_rxfilename(' a '))
self.assertEqual... |
class Loss(torch.nn.Module):
def __init__(self, batch_size, args):
super().__init__()
self.rot_loss = torch.nn.CrossEntropyLoss().cuda()
self.recon_loss = torch.nn.L1Loss().cuda()
self.contrast_loss = Contrast(args, batch_size).cuda()
self.alpha1 = 1.0
self.alpha2 = 1... |
def _generate_markdown(cwl_spec: str, conformance: str, failed_tests: list[str]) -> str:
time = datetime.now().strftime('%Y-%m-%d')
(passed, failed, unsupported) = conformance.split(',')
tests_list = ''.join([f''' - {test}
''' for test in failed_tests])
return f'''
# CWL {cwl_spec} specification conform... |
class LruWrappedModel(objectmodel.FunctionModel):
def attr___wrapped__(self):
return self._instance
def attr_cache_info(self):
cache_info = extract_node('\n from functools import _CacheInfo\n _CacheInfo(0, 0, 0, 0)\n ')
class CacheInfoBoundMethod(BoundMethod):
... |
class BasicBlock(nn.Module):
def __init__(self, inplanes, expansion=1, growthRate=12, dropRate=0):
super(BasicBlock, self).__init__()
planes = (expansion * growthRate)
self.bn1 = nn.BatchNorm2d(inplanes)
self.conv1 = nn.Conv2d(inplanes, growthRate, kernel_size=3, padding=1, bias=Fals... |
def forward_for_loss(model, loader, loss):
model.eval()
model.zero_grad()
loss_total = 0
for (batch_idx, (x, y)) in enumerate(loader):
(x, y) = (x.cuda(), y.cuda())
(loss_batch, pred_y) = loss(x, y, model)
loss_total += loss_batch
loss_total /= len(loader)
return loss_tot... |
def test_expert_mapping_3(device=rank):
if (dist.get_world_size() != 4):
return
dgrid = DistributionGrid(expert_parallel_group_size=2, expert_parallel_replica_group_size=2)
((nrank_0, nid_0), (nrank_1, nid_1)) = dgrid.map_expert_id_global_to_local(64, 42)
assert ((nrank_0 == 1) and (nid_0 == 10)... |
(epilog=fragdb_constants_epilog, name='fragdb_constants')
('--min-count', type=nonnegative_int())
('--max-count', type=nonnegative_int())
('--min-frequency', '--min-freq', type=frequency_type())
('--max-frequency', '--max-freq', type=frequency_type())
('--min-heavies-per-const-frag', type=nonnegative_int(), help='Lower... |
def test_no_ipywidget_repr(monkeypatch, capsys):
pytest.importorskip('ipywidgets')
import ipywidgets
source = Stream()
source._ipython_display_()
assert ('Output()' in capsys.readouterr().out)
def get(*_, **__):
raise ImportError
monkeypatch.setattr(ipywidgets.Output, '__init__', get... |
def make_res_layer(block, inplanes, planes, blocks, stride=1, dilation=1, groups=1, base_width=4, style='pytorch', with_cp=False, conv_cfg=None, norm_cfg=dict(type='BN'), dcn=None, gcb=None):
downsample = None
if ((stride != 1) or (inplanes != (planes * block.expansion))):
downsample = nn.Sequential(bui... |
class LGLBlock(nn.Module):
def __init__(self, dim, num_heads, mlp_ratio=4.0, qkv_bias=False, qk_scale=None, drop=0.0, attn_drop=0.0, drop_path=0.0, act_layer=nn.GELU, norm_layer=nn.LayerNorm, sr_ratio=1.0):
super().__init__()
if (sr_ratio > 1):
self.LocalAgg = LocalAgg(dim, num_heads, ml... |
def generate(cfg):
set_seed(cfg.seed)
if cfg.input.endswith('.bvh'):
base_dir = osp.join(cfg.output_dir, cfg.input.split('/')[(- 1)].split('.')[0])
motion_data = [BVHMotion(cfg.input, skeleton_name=cfg.skeleton_name, repr=cfg.repr, use_velo=cfg.use_velo, keep_up_pos=cfg.keep_up_pos, up_axis=cfg.... |
.usefixtures('log_extension_output')
def test_command_set_invalid_command(caplog, fake_qtile):
extension = CommandSet(pre_commands=['run pre-command'], commands={'missing': 'run testcommand'})
extension._configure(fake_qtile)
extension.run()
assert (caplog.record_tuples == [('libqtile', logging.WARNING,... |
class MeasurementGoodput(Measurement):
FILESIZE = (10 * MB)
_result = 0.0
def name():
return 'goodput'
def unit() -> str:
return 'kbps'
def testname(p: Perspective):
return 'transfer'
def abbreviation():
return 'G'
def desc():
return 'Measures connecti... |
class Migration(migrations.Migration):
dependencies = [('questions', '0054_meta'), migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('projects', '0046_project_mptt')]
operations = [migrations.CreateModel(name='Continuation', fields=[('id', models.AutoField(auto_created=True, primary_key=True, serializ... |
class NestedTensor(object):
def __init__(self, tensors, mask: Optional[Tensor]):
self.tensors = tensors
self.mask = mask
def to(self, device):
cast_tensor = self.tensors.to(device)
mask = self.mask
if (mask is not None):
assert (mask is not None)
c... |
def build_backbone(args):
position_embedding = build_position_encoding(args)
backbone = Backbone(backbone_name=args.backbone, num_feature_levels=args.num_feature_levels, pretrained=args.pretrained, use_checkpoint=args.use_checkpoint, dilation=args.dilation)
model = Joiner(backbone, position_embedding)
r... |
def test_from_recap_union():
converter = ProtobufConverter()
recap_type = UnionType(types=[IntType(signed=True, bits=32, name='some_int'), StringType(bytes_=100, name='some_string')], name='some_union')
struct_type = StructType(fields=[recap_type], alias='build.recap.MyStruct')
result = converter.from_r... |
def uninstall_nvpmodel(args):
if os.path.isfile('/usr/bin/nvpmodel'):
print('Removing nvpmodel')
os.remove('/usr/bin/nvpmodel')
if os.path.isfile('/etc/nvpmodel.conf'):
print('Removing /etc/nvpmodel.conf')
os.remove('/etc/nvpmodel.conf')
if os.path.isfile('/tmp/nvp_model_test... |
.parametrize('linker', [VMLinker(allow_partial_eval=True, use_cloop=False), 'cvm'])
def test_partial_function_with_output_keys(linker):
x = scalar('input')
y = (3 * x)
f = function([x], {'a': (y * 5), 'b': (y - 7)}, mode=Mode(optimizer=None, linker=linker))
assert (f(5, output_subset=['a'])['a'] == f(5)... |
class TestOrbitsGappyOrbitLatData(TestOrbitsGappyData):
def setup_method(self):
self.testInst = pysat.Instrument('pysat', 'testing', clean_level='clean', orbit_info={'index': 'latitude', 'kind': 'polar'}, use_header=True)
self.stime = pysat.instruments.pysat_testing._test_dates['']['']
self.... |
class RedisSearcher(BaseSearcher):
search_params = {}
client = None
parser = RedisConditionParser()
def init_client(cls, host, distance, connection_params: dict, search_params: dict):
cls.client = redis.Redis(host=host, port=REDIS_PORT, db=0)
cls.search_params = search_params
def sea... |
def watch_zookeeper_nodes(zookeeper: KazooClient, nodes: Any) -> NoReturn:
for node in nodes:
watcher = NodeWatcher(node.dest, node.owner, node.group, node.mode)
zookeeper.DataWatch(node.source, watcher.on_change)
while True:
time.sleep(HEARTBEAT_INTERVAL)
if zookeeper.connected:... |
def validate_rest(text):
settings = docutils.frontend.get_default_settings(rst.Parser)
document = docutils.utils.new_document('', settings)
rst.Parser().parse(text, document)
try:
document.walk(ReSTValidatorVisitor(document))
return (False, None)
except InvalidReSTError as e:
... |
def list_file_names(image_dir=None, file_ext=None):
if (file_ext is None):
file_ext = get_image_extension()
if (image_dir is None):
image_dir = get_local_data_folder()
if (not image_dir.endswith('/')):
image_dir += '/'
file_names = glob.glob(((image_dir + '*') + file_ext))
fi... |
class TestCaseBlackhole(TestCase):
def name():
return 'blackhole'
def testname(p: Perspective):
return 'transfer'
def abbreviation():
return 'B'
def desc():
return 'Transfer succeeds despite underlying network blacking out for a few seconds.'
def scenario() -> str:
... |
def crawl_board_list(top_n: Optional[int]=None) -> Iterator[DcardBoard]:
url = f'{DCARD_BASE_URL}/forums'
resp = requests.get(url, headers=headers)
logger.info('Crawl dcard board list')
for (i, board) in enumerate(resp.json()):
created_at = datetime.strptime(board['createdAt'], ISO_FORMAT)
... |
(frozen=True, slots=True)
class Region():
name: str
areas: list[Area]
extra: dict[(str, typing.Any)]
def __repr__(self) -> str:
return f'World[{self.name}]'
def dark_name(self) -> (str | None):
return self.extra.get('dark_name')
def all_nodes(self) -> Iterator[Node]:
for ... |
def main_run(arglist, security_override=False):
discovered_actions = actions_mgr.get_actions_dict()
parsed_args = arguments.parse(arglist, 'rdiff-backup {ver}'.format(ver=Globals.version), actions_mgr.get_generic_parsers(), discovered_actions)
if (parsed_args.terminal_verbosity is not None):
log.Log... |
def get_water(water=None):
tip3p = '<ForceField>\n <AtomTypes>\n <Type name="tip3p-O" class="OW" element="O" mass="15.99943"/>\n <Type name="tip3p-H" class="HW" element="H" mass="1.007947"/>\n </AtomTypes>\n <Residues>\n <Residue name="HOH">\n <Atom name="O" type="tip3p-O"/>\n <Atom name="H1" type="tip3p-H"/... |
class QtHandler(QtHandlerBase):
pin_signal = pyqtSignal(object, object)
matrix_signal = pyqtSignal(object)
close_matrix_dialog_signal = pyqtSignal()
def __init__(self, win, pin_matrix_widget_class, device):
super(QtHandler, self).__init__(win, device)
self.pin_signal.connect(self.pin_dia... |
class IGANet(nn.Module):
def __init__(self, depth, embed_dim, adj, drop_rate=0.1, length=27):
super().__init__()
drop_path_rate = 0.2
norm_layer = partial(nn.LayerNorm, eps=1e-06)
dpr = [x.item() for x in torch.linspace(0, drop_path_rate, depth)]
self.blocks = nn.ModuleList([... |
class VideoLoader(object):
def __init__(self, image_name_formatter, image_loader=None):
self.image_name_formatter = image_name_formatter
if (image_loader is None):
self.image_loader = ImageLoaderPIL()
else:
self.image_loader = image_loader
def __call__(self, video... |
def _test_TestModuleNonBlockingIfc(cls):
A = cls()
A.elaborate()
A.apply(GenDAGPass())
A.apply(OpenLoopCLPass())
A.sim_reset()
rdy = A.push.rdy()
print('- push_rdy?', rdy)
assert (not rdy)
rdy = A.push.rdy()
print('- push_rdy?', rdy)
assert (not rdy)
rdy = A.push.rdy()
... |
def test_branch_name_with_period(project):
branch_name = 'my.branch.name'
branch = project.branches.create({'branch': branch_name, 'ref': 'main'})
assert (branch.name == branch_name)
fetched_branch = project.branches.get(branch_name)
assert (branch.name == fetched_branch.name)
branch.delete() |
def test_pytest_fixture_setup_and_post_finalizer_hook(pytester: Pytester) -> None:
pytester.makeconftest("\n def pytest_fixture_setup(fixturedef, request):\n print('ROOT setup hook called for {0} from {1}'.format(fixturedef.argname, request.node.name))\n def pytest_fixture_post_finalizer(fi... |
class QFlaskApplication(Singleton):
version = '0.1'
def init_app(self):
self.flask_app = None
self.init_flask_app()
def _set_base_url(self, base_url):
base_url = base_url.strip()
if (not base_url.startswith('/')):
base_url = ('/' + base_url)
self.base_url ... |
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