code stringlengths 281 23.7M |
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def write_audacity_labels(dst_path, labels):
with open(dst_path, 'w') as of:
for (s, e, l) in labels:
(s, e) = ((s * 1e-07), (e * 1e-07))
if (('-' in l) and ('+' in l)):
ph = l.split('-')[1].split('+')[0]
else:
ph = l
of.write('... |
def patch_game_name_and_id(game_files_path: Path, new_name: str, publisher_id: str):
b = new_name.encode('ASCII')
if (len(b) > 40):
raise ValueError(f"Name '{new_name}' is bigger than 40 bytes")
b = (b + (b'\x00' * (40 - len(b))))
pid = publisher_id.encode('ASCII')
if (len(pid) != 2):
... |
def readable(tag, plural=False):
try:
if (tag[0] == '~'):
if (tag[1] == '#'):
tag = tag[2:]
else:
tag = tag[1:]
except IndexError:
return ngettext('Invalid tag', 'Invalid tags', 1)
def desc(tag):
if plural:
plural_de... |
class TestDataID(unittest.TestCase):
def test_basic_init(self):
from satpy.dataset.dataid import DataID
from satpy.dataset.dataid import default_id_keys_config as dikc
from satpy.dataset.dataid import minimal_default_keys_config as mdkc
did = DataID(dikc, name='a')
assert (di... |
_menu('Selection to IPython', menu='IPython')
def set_selection_in_ipython(*args):
try:
if ((not getattr(sys, '_ipython_app', None)) or (not sys._ipython_kernel_running)):
raise Exception('IPython kernel not running')
xl = xl_app(com_package='win32com')
selection = xl.Selection
... |
class ProxyPLoss(nn.Module):
def __init__(self, num_classes, scale):
super(ProxyPLoss, self).__init__()
self.soft_plus = nn.Softplus()
self.label = torch.LongTensor([i for i in range(num_classes)])
self.scale = scale
def forward(self, feature, target, proxy):
feature = F.... |
class TestEvaluate(BaseTestCase):
async def test_evaluate(self):
result = (await self.page.evaluate('() => 7 * 3'))
self.assertEqual(result, 21)
async def test_await_promise(self):
result = (await self.page.evaluate('() => Promise.resolve(8 * 7)'))
self.assertEqual(result, 56)
... |
class CapacitorViewFull(StatsView):
name = 'capacitorViewFull'
def __init__(self, parent):
StatsView.__init__(self)
self.parent = parent
def getHeaderText(self, fit):
return _t('Capacitor')
def getTextExtentW(self, text):
(width, height) = self.parent.GetTextExtent(text)
... |
def get_comp_grnd_probs(model, pointer_logprobs, step_history, grounding):
assert (len(model.ids_to_grounding_choices) == len(pointer_logprobs))
keep_pointer_logprobs = []
refs = [idx for (rule, idx) in step_history if (rule == 'ref')]
assert (len(refs) == 2), refs
is_filter = (refs[0] == refs[1])
... |
def test_parse_tree():
problem = '(q-transform/hint (quote (lambda (cdr (cdr (var ()))))) (quote ((() y . 1) (#f y () . #t) (#f b () b . y) (x #f (#f . #f) . #t) (a #f y x s . a))))'
step = 0
print('Starting problem:', problem)
with Interaction(lisp.parse(problem)) as env:
signal = None
... |
def tensor2imgs(tensor, mean=(0, 0, 0), std=(1, 1, 1), to_rgb=True):
num_imgs = tensor.size(0)
mean = np.array(mean, dtype=np.float32)
std = np.array(std, dtype=np.float32)
imgs = []
for img_id in range(num_imgs):
img = tensor[(img_id, ...)].cpu().numpy().transpose(1, 2, 0)
img = mmc... |
((enum is None), 'enum is not available')
class TestNestedStateEnums(TestEnumsAsStates):
def setUp(self):
super(TestNestedStateEnums, self).setUp()
self.machine_cls = HierarchicalMachine
def test_root_enums(self):
states = [self.States.RED, self.States.YELLOW, {'name': self.States.GREEN,... |
class BridgeTowerVisionConfig(PretrainedConfig):
model_type = 'bridgetower_vision_model'
def __init__(self, hidden_size=768, num_hidden_layers=12, num_channels=3, patch_size=16, image_size=288, initializer_factor=1, layer_norm_eps=1e-05, stop_gradient=False, share_layernorm=True, remove_last_layer=False, **kwar... |
class CalculatorForm(Form):
def __init__(self, view):
super().__init__(view, 'dynamic_content_error_form')
self.use_layout(FormLayout())
self.calculator = Calculator.for_current_session()
try:
self.enable_refresh(on_refresh=self.calculator.events.inputs_changed)
e... |
def put_html(html: Any, sanitize: bool=False, scope: str=None, position: int=OutputPosition.BOTTOM) -> Output:
if hasattr(html, '__html__'):
html = html.__html__()
elif hasattr(html, '_repr_html_'):
html = html._repr_html_()
spec = _get_output_spec('html', content=html, sanitize=sanitize, sc... |
def _inner_fmt(k: str, v: Any, table: TableFmt) -> Iterator[str]:
quote_function = table.get('quote', (lambda a: a))
if isinstance(v, list):
for inner_v in v:
qv = quote_function(inner_v)
(yield table['item'].format(k=k, v=qv))
else:
qv = quote_function(v)
(yi... |
class ClientGenerator(BaseGenerator):
def __init__(self, keep_sync: Optional[List[str]]=None, class_replace_map: Optional[Dict[(str, str)]]=None, import_replace_map: Optional[Dict[(str, str)]]=None, exclude_methods: Optional[List[str]]=None):
super().__init__()
self._async_methods: Optional[List[str... |
class TestUTCDateTimeAttribute():
def setup_method(self):
self.attr = UTCDateTimeAttribute()
self.dt = datetime(2047, 1, 6, 8, 21, 30, 2000, tzinfo=timezone.utc)
def test_utc_datetime_attribute(self):
attr = UTCDateTimeAttribute(default=self.dt)
assert (attr.attr_type == STRING)
... |
('beeref.selection.SelectableMixin.mousePressEvent')
def test_mouse_press_event_when_leftclick(mouse_mock):
item = MultiSelectItem()
item.fit_selection_area(QtCore.QRectF(0, 0, 100, 80))
event = MagicMock(button=MagicMock(return_value=Qt.MouseButton.LeftButton))
item.mousePressEvent(event)
event.ign... |
class TestMWSResponseObject():
def test_mwsresponse_repr(self, simple_mwsresponse):
assert (repr(simple_mwsresponse) == '<MWSResponse [200]>')
def test_mwsresponse_base_attrs(self, simple_mwsresponse):
mws_response = simple_mwsresponse
assert isinstance(mws_response.original, Response)
... |
def main():
utils.change_cwd()
out_filename = 'misc/file_version_info.txt'
filevers = (qutebrowser.__version_info__ + (0,))
prodvers = (qutebrowser.__version_info__ + (0,))
str_filevers = qutebrowser.__version__
str_prodvers = qutebrowser.__version__
comment_text = qutebrowser.__doc__
co... |
('--update', is_flag=True, help='Update shared modules everywhere?', default=False)
('--status', is_flag=True, help='Show status of shared modules everywhere.', default=False)
('--delete', is_flag=True, help='Delete shared modules everywhere?', default=False)
_commands.command(name='git-submodule')
def git_submodule(up... |
class MixedNonTagRefTest(models.Model):
name = models.CharField(max_length=10)
singletag = tagulous.models.SingleTagField(MixedNonTagModel, blank=True, related_name='singletags')
tags = tagulous.models.TagField(MixedNonTagModel, blank=True, related_name='tags')
fk = models.ForeignKey(MixedNonTagModel, b... |
def test_reduce_concatenations() -> None:
assert (str(parse('aa').reduce()) == 'a{2}')
assert (str(parse('bb').reduce()) == 'b{2}')
assert (str(parse('b*b').reduce()) == 'b+')
assert (str(parse('aa{2,}').reduce()) == 'a{3,}')
assert (str(parse('a*a{2}').reduce()) == 'a{2,}')
assert (str(parse('a... |
def test_to_recap_decimal():
converter = AvroConverter()
avro_schema = {'type': 'record', 'name': 'test_decimal', 'fields': [{'name': 'decimal', 'type': {'type': 'bytes', 'logicalType': 'decimal', 'precision': 5, 'scale': 2}}]}
schema = converter.to_recap(json.dumps(avro_schema))
field = schema.fields[0... |
def uccsd_generator(single_amplitudes, double_amplitudes, anti_hermitian=True):
generator = FermionOperator()
if (isinstance(single_amplitudes, numpy.ndarray) or isinstance(double_amplitudes, numpy.ndarray)):
(single_amplitudes, double_amplitudes) = uccsd_convert_amplitude_format(single_amplitudes, doub... |
def is_duplicate_mapping(mapping: list[int], actual_types: list[Type], actual_kinds: list[ArgKind]) -> bool:
return ((len(mapping) > 1) and (not ((len(mapping) == 2) and (actual_kinds[mapping[0]] == nodes.ARG_STAR) and (actual_kinds[mapping[1]] == nodes.ARG_STAR2))) and (not all((((actual_kinds[m] == nodes.ARG_STAR... |
class RustLexer(RegexLexer):
name = 'Rust'
url = '
filenames = ['*.rs', '*.rs.in']
aliases = ['rust', 'rs']
mimetypes = ['text/rust', 'text/x-rust']
version_added = '1.6'
keyword_types = (words(('u8', 'u16', 'u32', 'u64', 'u128', 'i8', 'i16', 'i32', 'i64', 'i128', 'usize', 'isize', 'f32', 'f... |
def plot_rat_stats(rat_sim, save_root, fmt):
for rating in range(1, 6):
exp_sim = (rat_sim == rating).astype(np.int32)
name = 'rat_stats_{}.{}'.format(rating, fmt)
title = 'Item Rating {} Distribution'.format(rating)
plot_exp_stats(exp_sim, save_root, fmt, name, title) |
class MenuButton(TelegramObject):
__slots__ = ('type',)
def __init__(self, type: str, *, api_kwargs: Optional[JSONDict]=None):
super().__init__(api_kwargs=api_kwargs)
self.type: str = type
self._id_attrs = (self.type,)
self._freeze()
def de_json(cls, data: Optional[JSONDict],... |
def RunGUI(sdkpath, args):
root = tk.Tk()
style = ttk.Style(root)
style.theme_use('default')
ttk.Style().configure('TButton', padding=6, relief='groove', border=2, foreground=GetButtonTextColour(), background=GetButtonBackground())
ttk.Style().configure('TLabel', foreground=GetTextColour(), backgrou... |
class CallBackVerification(object):
def __init__(self, val_targets, rec_prefix, summary_writer=None, image_size=(112, 112)):
self.rank: int = distributed.get_rank()
self.highest_acc: float = 0.0
self.highest_acc_list: List[float] = ([0.0] * len(val_targets))
self.ver_list: List[objec... |
def attr_parse(stream, length, attr_type_cls):
values = collections.OrderedDict()
while (length > 0):
(attr_type, value) = struct.unpack('>HH', stream.read(4))
length -= 4
if (attr_type & 32768):
attr_type &= 32767
else:
length -= value
value =... |
class ValidationCallback(Callback):
def __init__(self, manager: Manager, summary_writer: SummaryWriter, args, training_state: 'TrainingState', last_model_path, validation_frequency):
super().__init__()
self._args = args
self._validation_frequency = validation_frequency
self._training... |
def test_geodesic_inv__string_init(scalar_and_array):
geod = Geod('+ellps=clrk66')
(az12, az21, dist) = geod.inv(scalar_and_array(_BOSTON_LON), scalar_and_array(_BOSTON_LAT), scalar_and_array(_PORTLAND_LON), scalar_and_array(_PORTLAND_LAT))
assert_almost_equal((az12, az21, dist), (scalar_and_array((- 66.531... |
def _expand_shape_to_4d(weight_tensor: libpymo.TensorParams):
dims = len(weight_tensor.shape)
if (dims > 5):
raise RuntimeError
if (dims == 4):
(yield weight_tensor)
else:
orig_shape = weight_tensor.shape
if (dims < 4):
_4d_shape = np.append(orig_shape, [1 for... |
def get_version_and_doc(filename):
NS = dict(__version__='', __doc__='')
docStatus = 0
with open(filename, 'rb') as fd:
data = fd.read()
for line in data.decode().splitlines():
if line.startswith('__version__'):
exec(line.strip(), NS, NS)
elif line.startswith('"""'):
... |
def recover_coef1(seed):
input_list = ['m', 'k', 'A0', 'c']
output_coef = 'm_coef'
D_in = np.mat('1, 0, 0; 1, 0, -2; 0, 1, 0; 1, 0, -1').T
D_out = np.mat('0;, 0; 1')
dimension_info = [D_in, D_out]
basis1_in = np.array([1, 1, 0, (- 2)]).reshape((- 1), 1)
basis2_in = np.array([1, 0, 0, (- 1)])... |
class Effect6600(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.ship.boostItemAttr('shieldThermalDamageResonance', src.getModifiedItemAttr('shipBonusCarrierC1'), skill='Caldari Carrier', **kwargs)
fit.ship.boostItemAttr('shieldEmDamageResonance', src... |
class TestReadmeSample(QiskitMLTestCase):
def test_readme_sample(self):
def print(*args):
if args:
self.log.debug(args[0], *args[1:])
from qiskit import BasicAer
from qiskit.aqua import QuantumInstance, aqua_globals
from qiskit.aqua.algorithms import VQC
... |
_config
def test_maximize_with_move_to_screen(manager):
manager.test_window('one')
manager.c.window.toggle_maximize()
assert (manager.c.window.info()['width'] == 464)
assert (manager.c.window.info()['height'] == 316)
assert (manager.c.window.info()['x'] == 16)
assert (manager.c.window.info()['y'... |
def get_matching_convtransp(conv_op: Type[_ConvNd]=None, dimension: int=None) -> Type[_ConvTransposeNd]:
assert (not ((conv_op is not None) and (dimension is not None))), 'You MUST set EITHER conv_op OR dimension. Do not set both!'
if (conv_op is not None):
dimension = convert_conv_op_to_dim(conv_op)
... |
def train(epoch, criterion_list, optimizer):
train_loss = AverageMeter('train_loss', ':.4e')
train_loss_cls = AverageMeter('train_loss_cls', ':.4e')
train_loss_div = AverageMeter('train_loss_div', ':.4e')
top1_num = 0
top5_num = 0
total = 0
if (epoch >= args.warmup_epoch):
lr = adjus... |
def _create_method_tolerance_ap_values(tolerance_ap_data_frame, method, ordered_class_names: List[str]):
method_tolerance_ap_data_frame = tolerance_ap_data_frame[(tolerance_ap_data_frame[METHOD] == method)]
return [method_tolerance_ap_data_frame[(method_tolerance_ap_data_frame[SpottingEvaluation.CLASS_NAME] == ... |
class HSTPIPIER(IntEnum):
RXINES = (1 << 0)
TXOUTES = (1 << 1)
TXSTPES = (1 << 2)
UNDERFIES = (1 << 2)
PERRES = (1 << 3)
NAKEDES = (1 << 4)
OVERFIES = (1 << 5)
RXSTALLDES = (1 << 6)
CRCERRES = (1 << 6)
SHORTPACKETIES = (1 << 7)
NBUSYBKES = (1 << 12)
PDISHDMAS = (1 << 16)
... |
def init_network_weights(model, init_type='normal', gain=0.02):
def _init_func(m):
classname = m.__class__.__name__
if (hasattr(m, 'weight') and ((classname.find('Conv') != (- 1)) or (classname.find('Linear') != (- 1)))):
if (init_type == 'normal'):
nn.init.normal_(m.weig... |
def create_access_token(repo, role, kind=None, friendly_name=None):
role = Role.get((Role.name == role))
kind_ref = None
if (kind is not None):
kind_ref = AccessTokenKind.get((AccessTokenKind.name == kind))
new_token = AccessToken.create(repository=repo, temporary=True, role=role, kind=kind_ref,... |
def _dump_test(unit, test_type, test_files, timeout, test_dir, custom_deps, test_data, python_paths, split_factor, fork_mode, test_size, tags, requirements, binary_path='', old_pytest=False, test_cwd=None):
if (test_type == 'PY_TEST'):
script_rel_path = 'py.test'
elif (test_type == 'FLEUR'):
scr... |
class _DebuggingTips(SetuptoolsWarning):
_SUMMARY = 'Problem in editable installation.'
_DETAILS = '\n An error happened while installing `{project}` in editable mode.\n\n The following steps are recommended to help debug this problem:\n\n - Try to install the project normally, without using the editab... |
_funcify.register(ptr.RandomVariable)
def jax_funcify_RandomVariable(op, node, **kwargs):
rv = node.outputs[1]
out_dtype = rv.type.dtype
out_size = rv.type.shape
if (op.ndim_supp > 0):
out_size = node.outputs[1].type.shape[:(- op.ndim_supp)]
if (None in out_size):
assert_size_argumen... |
def test_direct_junction_offsets_suc_suc_2_left(direct_junction_left_lane_fixture):
(main_road, small_road, junction_creator) = direct_junction_left_lane_fixture
main_road.add_successor(xodr.ElementType.junction, junction_creator.id)
small_road.add_successor(xodr.ElementType.junction, junction_creator.id)
... |
class MPRIS(EventPlugin):
PLUGIN_ID = 'mpris'
PLUGIN_NAME = _('MPRIS D-Bus Support')
PLUGIN_DESC_MARKUP = _('Allows control of Quod Libet using the <a href=" 2</a> D-Bus Interface Specification. This allows various Linux desktop integrations (e.g. multimedia keys).')
PLUGIN_ICON = Icons.NETWORK_WORKGROU... |
class KnownValues(unittest.TestCase):
def test_ea_adc2_k(self):
(e, v, p, x) = kadc.kernel(nroots=3, kptlist=[0])
self.assertAlmostEqual(e[0][0], 0., 4)
self.assertAlmostEqual(e[0][1], 1., 4)
self.assertAlmostEqual(e[0][2], 1., 4)
self.assertAlmostEqual(p[0][0], 1., 4)
... |
def _sanitize_args_with_chunks(*args):
new_args = []
for arg in args:
if (_is_chunk_tuple(arg) and _chunks_are_irregular(arg)):
new_chunks = _regular_chunks_from_irregular_chunks(arg)
new_args.append(new_chunks)
else:
new_args.append(arg)
return new_args |
def test_invalid_coverage_source(testdir):
script = testdir.makepyfile(SCRIPT)
testdir.makeini('\n [pytest]\n console_output_style=classic\n ')
result = testdir.runpytest('-v', '--cov=non_existent_module', '--cov-report=term-missing', script)
result.stdout.fnmatch_lines(['*10 passed*'])... |
def test_pytest() -> None:
ast_node = builder.extract_node('\n import pytest\n pytest #\n ')
module = next(ast_node.infer())
attrs = ['deprecated_call', 'warns', 'exit', 'fail', 'skip', 'importorskip', 'xfail', 'mark', 'raises', 'freeze_includes', 'set_trace', 'fixture', 'yield_fixture']
for at... |
class TFBaseModelOutputWithPastAndCrossAttentions(ModelOutput):
last_hidden_state: tf.Tensor = None
past_key_values: Optional[List[tf.Tensor]] = None
hidden_states: Optional[Tuple[tf.Tensor]] = None
attentions: Optional[Tuple[tf.Tensor]] = None
cross_attentions: Optional[Tuple[tf.Tensor]] = None |
def generate_model_output_with_no_positive_examples() -> Dict[(str, torch._tensor.Tensor)]:
return {'predictions': torch.tensor([[1.0, 0.0, 0.51, 0.8, 1.0, 0.0, 0.51, 0.8, 1.0, 0.0, 0.51, 0.8]]), 'session': torch.tensor([[1, 1, 1, 1, 1, 1, 1, (- 1), (- 1), (- 1), (- 1), (- 1)]]), 'labels': torch.tensor([([0.0] * 12... |
def select_best2(acc_dict, sess):
sess_all_acc = acc_dict[str(sess)]
f = 0
best_e = (len(sess_all_acc) - 1)
for (e, pr) in enumerate(sess_all_acc):
if ((pr[0] < pr[1]) and (f == 0)):
best_base = pr[0]
best_novel = pr[1]
best_e = e
f = 1
if ... |
class TimeGraph():
def setup(self):
test_file_path = mm.datasets.get_path('bubenec')
self.df_streets = gpd.read_file(test_file_path, layer='streets')
self.network = mm.gdf_to_nx(self.df_streets)
self.network = mm.node_degree(self.network)
self.dual = mm.gdf_to_nx(self.df_stre... |
def parse_data(in_file='../../data/GYAFC/em/trn.tsv'):
with open(in_file, 'r') as f:
data = f.read().split('\n')
data.remove('')
contexted = []
for (i, line) in enumerate(data):
source_txt = line.split('\t')[0]
target_txt = line.split('\t')[1]
row = (i, source_txt, ta... |
class Effect5125(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Remote Armor Repair Systems')), 'armorDamageAmount', src.getModifiedItemAttr('shipBonusGC2'), skill='Gallente Cruiser', **kwargs) |
def get_ibnbresnet(blocks, model_name=None, pretrained=False, root=os.path.join('~', '.torch', 'models'), **kwargs):
if (blocks == 50):
layers = [3, 4, 6, 3]
elif (blocks == 101):
layers = [3, 4, 23, 3]
elif (blocks == 152):
layers = [3, 8, 36, 3]
else:
raise ValueError('... |
def pdf_a(x, p, m):
scalar = False
if (not hasattr(x, '__len__')):
scalar = True
x = np.asarray([x])
pr = np.array([((pdf_a_single_angle(xi, p, m, alpha) + pdf_a_single_angle(xi, p, m, beta)) if (xi not in [0, 1]) else pdf_a_single_angle(xi, p, m, alpha)) for xi in x]).flatten()
return (... |
class RedHatUserApi(object):
def __init__(self, app_config):
self.cert = (MARKETPLACE_FILE, MARKETPLACE_SECRET)
self.user_endpoint = app_config.get('ENTITLEMENT_RECONCILIATION_USER_ENDPOINT')
def get_account_number(self, user):
email = user.email
account_number = entitlements.get... |
class Jfif(Jpeg):
def from_stream(cls, stream):
markers = _JfifMarkers.from_stream(stream)
px_width = markers.sof.px_width
px_height = markers.sof.px_height
horz_dpi = markers.app0.horz_dpi
vert_dpi = markers.app0.vert_dpi
return cls(px_width, px_height, horz_dpi, ver... |
def test_skipif_has_precendence_over_ancestor_failed(runner, tmp_path):
source = '\n from pathlib import Path\n import pytask\n\n def task_example(produces=Path("file.txt")):\n raise Exception\n\n .skipif(True, reason="God knows.")\n def task_example_2(path=Path("file.txt")): ...\n '
tm... |
class Gen_Data_loader():
def __init__(self, batch_size):
self.batch_size = batch_size
self.token_stream = []
def create_batches(self, data_file):
self.token_stream = []
with open(data_file, 'r') as f:
for line in f:
line = line.strip().split()
... |
class uvm_nonblocking_peek_port(uvm_port_base):
def try_peek(self):
try:
(success, data) = self.export.try_peek()
except AttributeError:
raise UVMTLMConnectionError(f'Missing or wrong export in {self.get_full_name()}. Did you connect it?')
return (success, data)
d... |
class TestMulticomp(TestCase):
def test_fdr(self):
(reject, pval_corr) = fdr(pvals)
assert_array_equal(reject, [False, False, True, False, False])
assert_array_almost_equal(pval_corr, [0.52, 0.175, 0.0005, 0.075, 0.175])
(_, pval_corr) = fdr(pvals2_NA)
assert_array_almost_equ... |
def _print_preview(tab: apitypes.Tab) -> None:
def print_callback(ok: bool) -> None:
if (not ok):
message.error('Printing failed!')
tab.printing.check_preview_support()
diag = QPrintPreviewDialog(tab)
diag.setAttribute(Qt.WidgetAttribute.WA_DeleteOnClose)
diag.setWindowFlags(((di... |
class Info(OracleDatabase):
def __init__(self, args):
logging.debug('Info object created')
OracleDatabase.__init__(self, args)
self.version = ''
self.os = ''
def isVersion(self, version=None):
if (version in self.version):
return True
else:
... |
def process_camera_connector_chart():
connector_chart_dict = load_connector_chart()
res = subprocess.run(['v4l2-ctl', '--list-devices'], stdout=subprocess.PIPE)
output_string = res.stdout
providers = []
topic_names = []
for (topic_name, usb_id) in connector_chart_dict.items():
dev_number... |
def test_solver_returns_extras_if_requested_in_dependencies_and_not_in_root_package(solver: Solver, repo: Repository, package: ProjectPackage) -> None:
package.add_dependency(Factory.create_dependency('A', '*'))
package.add_dependency(Factory.create_dependency('B', '*'))
package.add_dependency(Factory.creat... |
def main():
default_cass = import_module('settings.default_cassandra')
default_only_cass = import_module('settings.default_only_cassandra')
secondary_cassandra = import_module('settings.secondary_cassandra')
multi_cassandra = import_module('settings.multi_cassandra')
metadata_disabled = import_modul... |
class WhisperTokenizer(PreTrainedTokenizer):
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
max_model_input_sizes = MAX_MODEL_INPUT_SIZES
model_input_names = ['input_ids', 'attention_mask']
def __init__(self, vocab_file, merges_file, normalizer_file=Non... |
def monitor_kevent(ident: int, filter: int) -> ContextManager[_core.UnboundedQueue[select.kevent]]:
locals()[LOCALS_KEY_KI_PROTECTION_ENABLED] = True
try:
return GLOBAL_RUN_CONTEXT.runner.io_manager.monitor_kevent(ident, filter)
except AttributeError:
raise RuntimeError('must be called from ... |
def eval_train(model, device, train_loader):
model.eval()
train_loss = 0
correct = 0
with torch.no_grad():
for (data, target) in train_loader:
(data, target) = (data.to(device), target.to(device))
output = model(data)
train_loss += F.cross_entropy(output, targ... |
_mode()
def binary_recall_at_fixed_precision(input: torch.Tensor, target: torch.Tensor, *, min_precision: float) -> Tuple[(torch.Tensor, torch.Tensor)]:
_binary_recall_at_fixed_precision_update_input_check(input, target, min_precision)
return _binary_recall_at_fixed_precision_compute(input, target, min_precisio... |
class IdleTask(Task):
def __init__(self, i, p, w, s, r):
Task.__init__(self, i, 0, None, s, r)
def fn(self, pkt, r):
i = r
assert isinstance(i, IdleTaskRec)
i.count -= 1
if (i.count == 0):
return self.hold()
elif ((i.control & 1) == 0):
i.c... |
def expectation_counts(counts: Dict[(str, int)]) -> Dict[(str, int)]:
shots = np.sum(list(counts.values()))
numq = len(list(counts.keys())[0])
subsets = []
for r in range(numq):
subsets += list(combinations(range(numq), (r + 1)))
exp_data = {'00': shots}
for subset in subsets:
ex... |
def test_connection_request_key_header() -> None:
with pytest.raises(RemoteProtocolError) as excinfo:
_make_connection_request([(b'Host', b'localhost'), (b'Connection', b'Keep-Alive, Upgrade'), (b'Upgrade', b'websocket'), (b'Sec-WebSocket-Version', b'13')])
assert (str(excinfo.value) == "Missing header,... |
def create_container(services=None, factory=Container):
container = (factory(services) if services else factory())
if (not ('fs' in container)):
import bonobo
container.setdefault('fs', bonobo.open_fs())
if (not (' in container)):
import requests
container.setdefault(' reques... |
.parametrize('linesep', ['\n', '\r\n'])
def test_init_existing_pyproject_consistent_linesep(tester: CommandTester, source_dir: Path, init_basic_inputs: str, init_basic_toml: str, linesep: str) -> None:
pyproject_file = (source_dir / 'pyproject.toml')
existing_section = '\n[tool.black]\nline-length = 88\n'.repla... |
('mmcv.__path__', [osp.join(osp.dirname(__file__), 'data/')])
def test_default_mmcv_home():
os.environ.pop(ENV_MMCV_HOME, None)
os.environ.pop(ENV_XDG_CACHE_HOME, None)
assert (_get_mmcv_home() == os.path.expanduser(os.path.join(DEFAULT_CACHE_DIR, 'mmcv')))
model_urls = get_external_models()
assert ... |
class TransformerLayer(nn.Module):
def __init__(self, dim, num_heads, mlp_ratio=4.0, qkv_bias=False, drop=0.0, attn_drop=0.0, drop_path=0.0, act_layer=nn.GELU, norm_layer=nn.LayerNorm):
super().__init__()
self.norm1 = norm_layer(dim)
self.attn = Attention(dim, num_heads=num_heads, qkv_bias=q... |
class TMVARegressor(TMVABase, Regressor):
def __init__(self, method='kBDT', features=None, factory_options='', **method_parameters):
TMVABase.__init__(self, factory_options=factory_options, method=method, **method_parameters)
Regressor.__init__(self, features=features)
def set_params(self, **par... |
class PyrockoSourceDialog(SourceEditDialog):
def __init__(self, delegate, ui_file, *args, **kwargs):
SourceEditDialog.__init__(self, delegate, ui_file, *args, **kwargs)
self.completer = QtWidgets.QCompleter()
self.completer_model = QtGui.QFileSystemModel(self.completer)
self.complete... |
def extrinsic_events(network, previous_state, current_state, next_state, indices=None, major_complex=None):
if major_complex:
mc_nodes = major_complex.subsystem.node_indices
elif indices:
mc_nodes = indices
else:
major_complex = compute.network.major_complex(network, current_state)
... |
def test_ddpg():
env = CartpoleEnv()
policy = DeterministicMLPPolicy(env.spec)
qf = ContinuousMLPQFunction(env.spec)
es = OUStrategy(env.spec)
algo = DDPG(env=env, policy=policy, qf=qf, es=es, n_epochs=1, epoch_length=100, batch_size=32, min_pool_size=50, replay_pool_size=1000, eval_samples=100)
... |
class Marcus(BaseKinetics):
def __init__(self, param, domain, reaction, options, phase='primary'):
super().__init__(param, domain, reaction, options, phase)
pybamm.citations.register('Sripad2020')
def _get_kinetics(self, j0, ne, eta_r, T, u):
RT = (self.param.R * T)
Feta_RT = ((s... |
.parametrize('fill_color', [(255, 255, 255, 255), (60, 70, 80, 100), (255, 255, 255, 255), (0, 255, 255, 255), (255, 0, 255, 255), (255, 255, 0, 255)])
def test_render_page_fill_color(fill_color, sample_page):
kwargs = dict(fill_color=fill_color, scale=0.5)
image = sample_page.render(**kwargs).to_pil()
imag... |
class LxDeviceFindByClassName(gdb.Function):
def __init__(self):
super(LxDeviceFindByClassName, self).__init__('lx_device_find_by_class_name')
def invoke(self, cls, name):
name = name.string()
cls = get_class_by_name(cls.string())
for dev in class_for_each_device(cls):
... |
class OPICHaircut(Haircut):
def __init__(self, source, min_weight: float=0.001, tendency: float=0.7):
super().__init__(source, min_weight)
self.tendency = tendency
def push(self, node, edges: list, **kwargs):
(in_sum, out_sum) = (0, 0)
(in_edges, out_edges) = (list(), list())
... |
class HTMLReporter(PythonTaReporter):
name = 'HTMLReporter'
_COLOURING = {'black': '<span class="black">', 'black-line': '<span class="black line-num">', 'bold': '<span>', 'code-heading': '<span>', 'style-heading': '<span>', 'code-name': '<span>', 'style-name': '<span>', 'highlight': '<span class="highlight-pyt... |
class CmdPose(RPCommand):
key = 'pose'
def parse(self):
args = self.args.strip()
default = args.startswith('default')
reset = args.startswith('reset')
if default:
args = re.sub('^default', '', args)
if reset:
args = re.sub('^reset', '', args)
... |
def test_vertical_crs__from_methods():
assert_maker_inheritance_valid(VerticalCRS.from_epsg(5703), VerticalCRS)
assert_maker_inheritance_valid(VerticalCRS.from_string('EPSG:5703'), VerticalCRS)
with pytest.raises(CRSError, match='Invalid type'):
VerticalCRS.from_proj4('+proj=latlon')
assert_make... |
def read_required(validator: Validator, required: List[str], instance: Any, schema: Mapping[(Hashable, Any)]) -> Iterator[ValidationError]:
if (not validator.is_type(instance, 'object')):
return
for property in required:
if (property not in instance):
prop_schema = schema.get('proper... |
class TypeHintingFactory(interfaces.ITypeHintingFactory):
def make_param_provider(self):
providers = [docstrings.ParamProvider(docstrings.DocstringParamParser(), self.make_resolver()), docstrings.ParamProvider(numpydocstrings.NumPyDocstringParamParser(), self.make_resolver())]
return inheritance.Par... |
class Solution():
def checkRecord(self, s: str) -> bool:
A = 0
L = (- 1)
if (s == ''):
return True
try:
A = s.count('A')
except:
pass
if (A > 1):
return False
try:
L = s.find('LLL')
except:
... |
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