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class StatusBar(Gtk.HBox):
def __init__(self, task_controller):
super().__init__()
self.__dirty = False
self.set_spacing(12)
self.task_controller = task_controller
self.task_controller.parent = self
self.default_label = Gtk.Label(selectable=True)
self.default_... |
def does_conv_have_relu_activation(input_op: Op) -> bool:
if (input_op.type not in ['Conv2D', 'DepthwiseConv2dNative']):
raise ValueError((('Op type: ' + input_op.type) + ' is not CONV2D!'))
if ((len(input_op.output.consumers) == 1) and ((input_op.output.consumers[0].type == 'Relu') or (input_op.output.... |
def setUpModule():
global mol, mf
mol = gto.Mole()
mol.verbose = 7
mol.output = '/dev/null'
mol.atom = [[8, (0.0, 0.0, 0.0)], [1, (0.0, (- 0.757), 0.587)], [1, (0.0, 0.757, 0.587)]]
mol.spin = 2
mol.basis = '631g'
mol.build()
mf = scf.UHF(mol)
mf.conv_tol_grad = 1e-08
mf.kern... |
class TorsionProfileSmirnoff(TargetBase):
target_name: Literal['TorsionProfile_SMIRNOFF'] = 'TorsionProfile_SMIRNOFF'
description = 'Relaxed energy and RMSD fitting for torsion drives only.'
energy_denom: PositiveFloat = Field(1.0, description='The energy denominator used by forcebalance to weight the energ... |
def test_pattern_no_version_group(temp_dir):
source = RegexSource(str(temp_dir), {'path': 'a/b', 'pattern': '.+'})
file_path = ((temp_dir / 'a') / 'b')
file_path.ensure_parent_dir_exists()
file_path.write_text('foo')
with temp_dir.as_cwd(), pytest.raises(ValueError, match='no group named `version` w... |
class TabBarStyle(QProxyStyle):
ICON_PADDING = 4
def __init__(self, style=None):
super().__init__(style)
def _base_style(self) -> QStyle:
style = self.baseStyle()
assert (style is not None)
return style
def _draw_indicator(self, layouts, opt, p):
color = opt.palet... |
class BilinearUpsampling(Layer):
def __init__(self, upsampling=(2, 2), output_size=None, data_format=None, **kwargs):
super(BilinearUpsampling, self).__init__(**kwargs)
self.data_format = K.normalize_data_format(data_format)
self.input_spec = InputSpec(ndim=4)
if output_size:
... |
def test_pool_timeout_with_long_deadline_budget():
baseplate = _create_baseplate_object('5 milliseconds')
baseplate.add_to_context('deadline_budget', 1000)
context = baseplate.make_context_object()
with baseplate.make_server_span(context, 'test'):
with pytest.raises(ServerTimeout):
g... |
class BTOOLS_OT_add_fill(bpy.types.Operator):
bl_idname = 'btools.add_fill'
bl_label = 'Add Fill'
bl_options = {'REGISTER', 'UNDO', 'PRESET'}
props: bpy.props.PointerProperty(type=FillProperty)
def poll(cls, context):
return ((context.object is not None) and (context.mode == 'EDIT_MESH'))
... |
def test_video_keywords(cipher_signature):
expected = ['Rewind', 'Rewind 2019', 'youtube rewind 2019', '#YouTubeRewind', 'MrBeast', 'PewDiePie', 'James Charles', 'Shane Dawson', 'CaseyNeistat', 'RiceGum', 'Simone Giertz', 'JennaMarbles', 'Lilly Singh', 'emma chamberlain', 'The Try Guys', 'Fortnite', 'Minecraft', 'R... |
def compute_parameters(node: FunctionNode, enclosing_class: Optional[TypedValue], ctx: Context, *, is_nested_in_class: bool=False, is_staticmethod: bool=False, is_classmethod: bool=False) -> Sequence[ParamInfo]:
defaults = [_visit_default(node, ctx) for node in node.args.defaults]
kw_defaults = [(None if (kw_de... |
def convert_conv(vars, source_name, target_name, bias=True, start=0):
weight = vars[(source_name + '/weight')].value().eval()
dic = {'weight': weight.transpose((3, 2, 0, 1))}
if bias:
dic['bias'] = vars[(source_name + '/bias')].value().eval()
dic_torch = {}
dic_torch[(target_name + '.{}.weig... |
class BasicConvolutionStack(ConvolutionStackInterface):
def __init__(self, convolution_block: ConvolutionBlockInterface, layer_num_blocks: List[int]) -> None:
self._convolution_block = convolution_block
self._layer_num_blocks = layer_num_blocks
def convolve(self, tensor: Tensor, num_filters: int... |
class Mixable(EvscaperoomObject):
mixer_flag = 'mixer'
ingredient_recipe = ['ingredient1', 'ingredient2', 'ingredient3']
def at_object_creation(self):
super().at_object_creation()
self.set_flag(self.mixer_flag)
self.db.ingredients = []
def check_mixture(self):
ingredients... |
class InceptionD(nn.Module):
def __init__(self, in_channels, conv_block=None):
super(InceptionD, self).__init__()
if (conv_block is None):
conv_block = BasicConv2d
self.branch3x3_1 = conv_block(in_channels, 192, kernel_size=1)
self.branch3x3_2 = conv_block(192, 320, kerne... |
class GeneratorLatentFromNoise():
def __init__(self, name, fc_sizes=[128], latent_dim=128, activation_fn=tf.nn.relu, bn=True):
self.name = name
self.fc_sizes = fc_sizes.copy()
self.latent_dim = latent_dim
self.activation_fn = activation_fn
self.bn = bn
self.reuse = Fa... |
class XLONExchangeCalendar(TradingCalendar):
regular_early_close = time(12, 30)
name = 'XLON'
tz = timezone('Europe/London')
open_times = ((None, time(8, 1)),)
close_times = ((None, time(16, 30)),)
def regular_holidays(self):
return HolidayCalendar([LSENewYearsDay, GoodFriday, EasterMond... |
def sq_relative(depth_pred, depth_gt):
assert np.all((((np.isfinite(depth_pred) & np.isfinite(depth_gt)) & (depth_pred > 0)) & (depth_gt > 0)))
diff = (depth_pred - depth_gt)
num_pixels = float(diff.size)
if (num_pixels == 0):
return np.nan
else:
return (np.sum((np.square(diff) / dep... |
def read_binary_image(file_path):
img = cv2.imread(file_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = (255 - gray)
(ret, binary) = cv2.threshold(gray, 50, 255, cv2.THRESH_BINARY)
(contours, hierarchy) = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
print(f'contour ... |
class EscposIO():
def __init__(self, printer: Escpos, autocut: bool=True, autoclose: bool=True, **kwargs) -> None:
self.printer = printer
self.params = kwargs
self.autocut = autocut
self.autoclose = autoclose
def set(self, **kwargs) -> None:
self.params.update(kwargs)
... |
class JobPreview(LoginRequiredMixin, JobDetail, UpdateView):
template_name = 'jobs/job_detail.html'
form_class = JobForm
def get_success_url(self):
return reverse('jobs:job_thanks')
def post(self, request, *args, **kwargs):
self.object = self.get_object()
if (self.request.POST.ge... |
def compute_align_loss(model, desc_enc, example):
root_node = example.tree
rel_cols = list(reversed([val for val in model.ast_wrapper.find_all_descendants_of_type(root_node, 'column')]))
rel_tabs = list(reversed([val for val in model.ast_wrapper.find_all_descendants_of_type(root_node, 'table')]))
rel_co... |
def get_queries_from_smiles_and_query(smiles, query_smiles, fragment_filter, reporter):
reporter.explain(f'Fragmenting {smiles} to find the query {query_smiles}')
for frag_term in get_queries_from_smiles(smiles, fragment_filter, reporter):
(frag_constant, frag_variables) = frag_term
if (frag_var... |
def test_newer_pairwise_group(groups_target):
older = newer_pairwise_group([groups_target.older], [groups_target.target])
newer = newer_pairwise_group([groups_target.newer], [groups_target.target])
assert (older == ([], []))
assert (newer == ([groups_target.newer], [groups_target.target])) |
def get_name_params_div(named_parameters1, named_parameters2=None, scalar=1.0):
if (named_parameters2 is not None):
common_names = list(set(named_parameters1.keys()).intersection(set(named_parameters2.keys())))
named_diff_parameters = {}
for key in common_names:
named_diff_parame... |
def add_residual(x, brange, residual, residual_scale_factor, scaling_vector=None):
if (scaling_vector is None):
x_flat = x.flatten(1)
residual = residual.flatten(1)
x_plus_residual = torch.index_add(x_flat, 0, brange, residual.to(dtype=x.dtype), alpha=residual_scale_factor)
else:
... |
class _Selector(selectors._BaseSelectorImpl):
def __init__(self, loop: SelectorEventLoop) -> None:
super(_Selector, self).__init__()
self._notified: Dict[(Any, Any)] = {}
self._loop = loop
self._event = None
self._gevent_events: Dict[(Any, Any)] = {}
if _GEVENT10:
... |
class WindowCount(base._TextBox):
defaults: list[tuple[(str, Any, str)]] = [('font', 'sans', 'Text font'), ('fontsize', None, 'Font pixel size. Calculated if None.'), ('fontshadow', None, 'font shadow color, default is None(no shadow)'), ('padding', None, 'Padding left and right. Calculated if None.'), ('foreground... |
def test_run_with_optional_and_platform_restricted_dependencies(installer: Installer, locker: Locker, repo: Repository, package: ProjectPackage, mocker: MockerFixture) -> None:
mocker.patch('sys.platform', 'darwin')
package_a = get_package('A', '1.0')
package_b = get_package('B', '1.1')
package_c12 = ge... |
class _ASPP(nn.Module):
def __init__(self, in_channels=2048, out_channels=256):
super().__init__()
output_stride = cfg.MODEL.OUTPUT_STRIDE
if (output_stride == 16):
dilations = [6, 12, 18]
elif (output_stride == 8):
dilations = [12, 24, 36]
elif (outpu... |
class StateVariableType(GeneratedsSuper):
__hash__ = GeneratedsSuper.__hash__
subclass = None
superclass = None
def __init__(self, sendEvents='yes', name=None, dataType=None, defaultValue=None, allowedValueList=None, allowedValueRange=None, gds_collector_=None, **kwargs_):
self.gds_collector_ = ... |
def process_batch_new(input_filename_list, input_label_list, dim_input, batch_sample_num, reshape_with_one=True):
new_path_list = []
new_label_list = []
for k in range(batch_sample_num):
class_idxs = range(0, FLAGS.way_num)
random.shuffle(class_idxs)
for class_idx in class_idxs:
... |
def test_handle_inittarget_bad_expiration():
block_number = 1
pseudo_random_generator = random.Random()
channels = make_channel_set([channel_properties])
expiration = ((channels[0].reveal_timeout + block_number) + 1)
from_transfer = make_target_transfer(channels[0], expiration=expiration)
channe... |
def test_project_create_post_forbidden(db, client, settings):
settings.PROJECT_CREATE_RESTRICTED = True
client.login(username='user', password='user')
url = reverse('project_create')
data = {'title': 'A new project', 'description': 'Some description', 'catalog': catalog_id}
response = client.post(ur... |
class TwitterJSONIter(object):
def __init__(self, handle, uri, arg_data, block, timeout, heartbeat_timeout):
self.handle = handle
self.uri = uri
self.arg_data = arg_data
self.timeout_token = Timeout
self.timeout = None
self.heartbeat_timeout = HEARTBEAT_TIMEOUT
... |
class FastAttentionviaLowRankDecomposition(FastAttention):
def __init__(self, matrix_creator, kernel_feature_creator, renormalize_attention, numerical_stabilizer, redraw_features, unidirectional, lax_scan_unroll=1):
rng = random.PRNGKey(0)
self.matrix_creator = matrix_creator
self.projection... |
def wrap_flask_restful_resource(fun: Callable, flask_restful_api: FlaskRestfulApi, injector: Injector) -> Callable:
(fun)
def wrapper(*args: Any, **kwargs: Any) -> Any:
resp = fun(*args, **kwargs)
if isinstance(resp, Response):
return resp
(data, code, headers) = flask_respon... |
def is_natural_seq(evaluator, ab, cand_cdrs):
with torch.no_grad():
batch = []
for cdr in cand_cdrs:
ab = deepcopy(ab)
ab['seq'] = ab['VH'].replace(ab['hcdr3'], cdr)
batch.append(ab)
(hX, hS, hL, hmask) = completize(batch)
cand_ppl1 = evaluator[0].... |
def test_pycode_replace_objects():
pycode = "context['alist'] = [0, 1, 2]\ncontext['adict'] = {'a': 'b', 'c': 'd'}\ncontext['anint'] = 456\ncontext['mutate_me'].append(12)\ncontext['astring'] = 'updated'\n"
context = Context({'alist': [0, 1], 'adict': {'a': 'b'}, 'anint': 123, 'mutate_me': [10, 11], 'astring': ... |
def update_output_for_test(type_checker: TypeChecker, results_dir: Path, test_case: Path, output: str):
test_name = test_case.stem
output = f'''
{output}'''
results_file = (results_dir / f'{test_name}.toml')
results_file.parent.mkdir(parents=True, exist_ok=True)
try:
with open(results_file, ... |
def test_PVSystem_pvwatts_dc_kwargs(pvwatts_system_kwargs, mocker):
mocker.spy(pvsystem, 'pvwatts_dc')
irrad = 900
temp_cell = 30
expected = 90
out = pvwatts_system_kwargs.pvwatts_dc(irrad, temp_cell)
pvsystem.pvwatts_dc.assert_called_once_with(irrad, temp_cell, **pvwatts_system_kwargs.arrays[0]... |
('/v1/organization/<orgname>/collaborators')
_param('orgname', 'The name of the organization')
class OrganizationCollaboratorList(ApiResource):
_scope(scopes.ORG_ADMIN)
('getOrganizationCollaborators')
def get(self, orgname):
permission = AdministerOrganizationPermission(orgname)
if (not per... |
def find_executable(executable, path=None):
(_, ext) = os.path.splitext(executable)
if ((sys.platform == 'win32') and (ext != '.exe')):
executable = (executable + '.exe')
if os.path.isfile(executable):
return executable
if (path is None):
path = os.environ.get('PATH', None)
... |
(eq=False, hash=False, slots=True)
class Runner():
clock: Clock = attr.ib()
instruments: Instruments = attr.ib()
io_manager: TheIOManager = attr.ib()
ki_manager: KIManager = attr.ib()
strict_exception_groups: bool = attr.ib()
_locals: dict[(_core.RunVar[Any], Any)] = attr.ib(factory=dict)
ru... |
class AmplitudeEstimationResult(AmplitudeEstimationAlgorithmResult):
def ml_value(self) -> float:
return self.get('ml_value')
_value.setter
def ml_value(self, value: float) -> None:
self.data['ml_value'] = value
def mapped_a_samples(self) -> List[float]:
return self.get('mapped_a... |
class Scoreboard(uvm_component):
def build_phase(self):
self.cmd_fifo = uvm_tlm_analysis_fifo('cmd_fifo', self)
self.result_fifo = uvm_tlm_analysis_fifo('result_fifo', self)
self.cmd_get_port = uvm_get_port('cmd_get_port', self)
self.result_get_port = uvm_get_port('result_get_port', ... |
class TesttestLine():
def test___init__1(self):
for (m, b) in [(4, 0.0), ((- 140), 5), (0, 0)]:
_ = Line(m, b)
def test_y1(self):
l_ = Line(0, 0)
assert (l_.y(0) == 0)
assert (l_.y((- 1e309)) == 0)
assert (l_.y(1e309) == 0)
l_ = Line(1, 1)
asse... |
.skipif('sys.platform == "win32"', reason="SIGTERM isn't really supported on Windows")
.xfail('sys.platform == "darwin"', reason='Something weird going on Macs...')
.xfail('platform.python_implementation() == "PyPy"', reason='Interpreter seems buggy')
.parametrize('setup', [('signal.signal(signal.SIGTERM, signal.SIG_DF... |
.parametrize('bad_level', [None, (- 2), 3])
def test_set_propagate_cast_with_bad_level(bad_level):
(D_in, H, D_out) = (784, 500, 10)
model = NeuralNetSinglePositionalArgument(D_in, H, D_out)
model = ORTModule(model)
strategy = PropagateCastOpsStrategy.INSERT_AND_REDUCE
with pytest.raises(TypeError) ... |
def name_replacer(match: re.Match[str]):
(prefix, resource) = match.group('prefix', 'resource')
override_prefix = prefix.replace('file_filter', 'trans.zh_CN')
pattern = resource.replace('trans/<lang>/', '').replace('glossary_', 'glossary').replace('--', '/').replace('_', '?')
matches = list(glob.glob(pa... |
.unit()
.skipif((sys.platform != 'win32'), reason='Only works on Windows.')
.parametrize(('path', 'existing_paths', 'expected'), [pytest.param('text.txt', [], 'text.txt', id='non-existing path stays the same'), pytest.param('text.txt', ['text.txt'], 'text.txt', id='existing path is same'), pytest.param('Text.txt', ['te... |
class FeedForwardModule(nn.Module):
def __init__(self, dim, hidden_dim_multiplier, dropout, input_dim_multiplier=1, **kwargs):
super().__init__()
input_dim = int((dim * input_dim_multiplier))
hidden_dim = int((dim * hidden_dim_multiplier))
self.linear_1 = nn.Linear(in_features=input_... |
class GLGradientLegendItem(GLGraphicsItem):
def __init__(self, parentItem=None, **kwds):
super().__init__(parentItem=parentItem)
glopts = kwds.pop('glOptions', 'additive')
self.setGLOptions(glopts)
self.pos = (10, 10)
self.size = (10, 100)
self.fontColor = QtGui.QColo... |
class OpenQASampler(Sampler):
def __init__(self, data_source, batch_size):
self.batch_size = batch_size
sample_indice = []
for qa_idx in range(len(data_source.qids)):
batch_data = []
batch_data.append(random.choice(data_source.grouped_idx_has_answer[qa_idx]))
... |
def identity_with_metadata_simple(use):
ints = use.init_artifact('ints', ints1_factory)
md = use.init_metadata('md', md1_factory)
use.action(use.UsageAction(plugin_id='dummy_plugin', action_id='identity_with_metadata'), use.UsageInputs(ints=ints, metadata=md), use.UsageOutputNames(out='out')) |
def test_get_identifications_by_id(requests_mock):
mock_response = load_sample_data('get_identifications.json')
mock_response['results'] = [mock_response['results'][0]]
requests_mock.get(f'{API_V1}/identifications/', json=mock_response, status_code=200)
response = get_identifications_by_id()
assert ... |
def test_postgenerationmethodcall_getfixturevalue(request, factoryboy_request):
secret = request.getfixturevalue('foo__secret')
number = request.getfixturevalue('foo__number')
assert (not factoryboy_request.deferred)
assert (secret == 'super secret')
assert (number is NotProvided) |
class Encoder(nn.Module):
def __init__(self, hidden_channels, sample_size, sample_duration):
super(Encoder, self).__init__()
self.convlstm = ConvLSTM(input_channels=3, hidden_channels=hidden_channels, kernel_size=3, step=sample_duration, effective_step=[(sample_duration - 1)])
self.conv2 = n... |
def test_solver_can_resolve_directory_dependencies_with_extras(solver: Solver, repo: Repository, package: ProjectPackage, fixture_dir: FixtureDirGetter) -> None:
pendulum = get_package('pendulum', '2.0.3')
cleo = get_package('cleo', '1.0.0')
repo.add_package(pendulum)
repo.add_package(cleo)
path = (... |
def get_missing(po_dir: Path) -> Iterable[str]:
src_root = _src_root(po_dir)
potfiles_path = (po_dir / 'POTFILES.in')
skip_path = (po_dir / 'POTFILES.skip')
pot_files = {p.relative_to(src_root) for p in _read_potfiles(src_root, potfiles_path)}
skip_files = {p.relative_to(src_root) for p in _read_pot... |
class QuestionAdminForm(ElementAdminForm):
widget_type = forms.ChoiceField(choices=get_widget_type_choices())
class Meta():
model = Question
fields = '__all__'
def clean(self):
QuestionUniqueURIValidator(self.instance)(self.cleaned_data)
QuestionLockedValidator(self.instance)... |
class ExtractFactory(object):
current_extracts = {'default': Extract, 'regex': RegExtract, 'cot-commonsense_qa': CoTCommonsenseQAExtract}
def get_extract(extract: str) -> Type[Extract]:
if (extract in ExtractFactory.current_extracts):
return ExtractFactory.current_extracts[extract]
e... |
def bench_dumping(lazy_compilation: bool):
if lazy_compilation:
data = create_response(GetRepoIssuesResponseLC, IssueLC, ReactionsLC, PullRequestLC, LabelLC, SimpleUserLC)
data.to_dict()
else:
data = create_response(GetRepoIssuesResponse, Issue, Reactions, PullRequest, Label, SimpleUser)... |
class TimerWidget(Image):
icon = 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACkAAAAvCAYAAAB+OePrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAABswAAAbMBHmbrhwAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAAkTSURBVFiFvZltcFTlFcd/594lb0JChCoUqsEiSLGWQkbbsdo4yMQZsluazlptB0sh3KShjtLOVOuo3daO1nbUDwqTuxuZiKPVItbsJsE3OvGtdipY... |
class GetScreenInfo(rq.ReplyRequest):
_request = rq.Struct(rq.Card8('opcode'), rq.Opcode(5), rq.RequestLength(), rq.Window('window'))
_reply = rq.Struct(rq.ReplyCode(), rq.Card8('set_of_rotations'), rq.Card16('sequence_number'), rq.ReplyLength(), rq.Window('root'), rq.Card32('timestamp'), rq.Card32('config_time... |
class ShelfBinPacker(object):
def __init__(self, dims: mn.Range2D):
self.dims = dims
self.shelves: List[Shelf] = []
self.matches: Dict[(int, Match)] = {}
def assert_consistency(self):
for (prev, next) in zip(self.shelves[:(- 1)], self.shelves[1:]):
if ((prev.dims.top ... |
class PlayControls(Gtk.VBox):
def __init__(self, player, library):
super().__init__(spacing=3)
upper = Gtk.Table(n_rows=1, n_columns=3, homogeneous=True)
upper.set_row_spacings(3)
upper.set_col_spacings(3)
prev = Gtk.Button(relief=Gtk.ReliefStyle.NONE)
prev.add(Symbol... |
def SaveScene(scene, project, path):
location = (project.path / path)
data = [ObjectInfo('Scene', project.GetUuid(scene), {'name': scene.name, 'mainCamera': ObjectInfo.SkipConv(project.GetUuid(scene.mainCamera))})]
SaveGameObjects(scene.gameObjects, data, project)
location.parent.mkdir(parents=True, exi... |
class GlobalScope(Scope):
def __init__(self, pycore, module):
super().__init__(pycore, module, None)
self.names = module._get_concluded_data()
def get_start(self):
return 1
def get_kind(self):
return 'Module'
def get_name(self, name):
try:
return self.... |
def main():
parser = argparse.ArgumentParser(description='Train a model on the Hotpot pairwise relevance dataset')
parser.add_argument('name', help='Where to store the model')
parser.add_argument('-c', '--continue_model', action='store_true', help='Whether to start a new run or continue an existing one')
... |
class GenericLastTransitionLogTestCase(test.TestCase):
def setUp(self):
self.obj = models.GenericWorkflowEnabled.objects.create()
def test_transitions(self):
self.assertEqual(0, models.GenericWorkflowLastTransitionLog.objects.count())
self.obj.ab()
self.assertEqual(1, models.Gene... |
class InfluxClient(object):
def __init__(self, data_manger, config):
self.data_manager = data_manger
self.config = config
self.logger = getLogger()
self.influx = InfluxDBClient(host=self.config.influx_url, port=self.config.influx_port, username=self.config.influx_username, password=s... |
class WebhookRequestBodyValidator(BaseWebhookRequestValidator):
def iter_errors(self, request: WebhookRequest) -> Iterator[Exception]:
try:
(_, operation, _, _, _) = self._find_path(request)
except PathError as exc:
(yield exc)
return
(yield from self._ite... |
class AnnotatedObjectsCoco(AnnotatedObjectsDataset):
def __init__(self, use_things: bool=True, use_stuff: bool=True, **kwargs):
super().__init__(**kwargs)
self.use_things = use_things
self.use_stuff = use_stuff
with open(self.paths['instances_annotations']) as f:
inst_dat... |
class FlyController(Controller):
_default_controls = {'mouse1': ('rotate', 'drag', (0.005, 0.005)), 'q': ('roll', 'repeat', (- 2)), 'e': ('roll', 'repeat', (+ 2)), 'w': ('move', 'repeat', (0, 0, (- 1))), 's': ('move', 'repeat', (0, 0, (+ 1))), 'a': ('move', 'repeat', ((- 1), 0, 0)), 'd': ('move', 'repeat', ((+ 1), ... |
class Transformer2DModel(ModelMixin, ConfigMixin):
_to_config
def __init__(self, num_attention_heads: int=16, attention_head_dim: int=88, in_channels: Optional[int]=None, num_layers: int=1, dropout: float=0.0, norm_num_groups: int=32, cross_attention_dim: Optional[int]=None, attention_bias: bool=False, sample_s... |
_on_failure
.parametrize('number_of_nodes', [1])
.parametrize('channels_per_node', [0])
.parametrize('number_of_tokens', [0])
.parametrize('environment_type', [Environment.DEVELOPMENT])
def test_deposit_amount_must_be_smaller_than_the_token_network_limit(raiden_network: List[RaidenService], contract_manager: ContractMa... |
class SkipDownBlock2D(nn.Module):
def __init__(self, in_channels: int, out_channels: int, temb_channels: int, dropout: float=0.0, num_layers: int=1, resnet_eps: float=1e-06, resnet_time_scale_shift: str='default', resnet_act_fn: str='swish', resnet_pre_norm: bool=True, output_scale_factor=np.sqrt(2.0), add_downsamp... |
def convert_cityscapes_instance_only(data_dir, out_dir):
sets = ['gtFine_val', 'gtFine_train', 'gtFine_test']
ann_dirs = ['gtFine_trainvaltest/gtFine/val', 'gtFine_trainvaltest/gtFine/train', 'gtFine_trainvaltest/gtFine/test']
json_name = 'instancesonly_filtered_%s.json'
ends_in = '%s_polygons.json'
... |
def test(capfd, tmp_path):
project_dir = (tmp_path / 'project')
subdir_package_project.generate(project_dir)
package_dir = Path('src', 'spam')
actual_wheels = utils.cibuildwheel_run(project_dir, package_dir=package_dir, add_env={'CIBW_BEFORE_BUILD': 'python {project}/bin/before_build.py', 'CIBW_TEST_COM... |
class OldUserData(AbstractData):
__slots__ = ['name', 'email', 'role', 'permission', 'template_name']
def __init__(self, name=None, email=None, role=None, permission=None, template_name=None):
self.name = name
self.email = email
self.role = role
self.permission = permission
... |
class SaveMixin(_RestObjectBase):
_id_attr: Optional[str]
_attrs: Dict[(str, Any)]
_module: ModuleType
_parent_attrs: Dict[(str, Any)]
_updated_attrs: Dict[(str, Any)]
manager: base.RESTManager
def _get_updated_data(self) -> Dict[(str, Any)]:
updated_data = {}
for attr in sel... |
def test_import(module, allow_conflict_names, fun, error):
from datar import options
options(allow_conflict_names=allow_conflict_names)
if (not error):
return _import(module, fun)
try:
_import(module, fun)
except Exception as e:
raised = type(e).__name__
assert (raise... |
class LazyCommandInterface(CommandInterface):
def execute(self, call: CommandGraphCall, args: tuple, kwargs: dict) -> LazyCall:
return LazyCall(call, args, kwargs)
def has_command(self, node: CommandGraphNode, command: str) -> bool:
return True
def has_item(self, node: CommandGraphNode, obje... |
class Graphsn_GCN(Module):
def __init__(self, in_features, out_features, bias=True):
super(Graphsn_GCN, self).__init__()
self.in_features = in_features
self.out_features = out_features
self.weight = Parameter(torch.FloatTensor(in_features, out_features))
self.eps = nn.Paramet... |
def main(client, config):
(ws_df, ss_df, date_df, customer_df) = benchmark(read_tables, config=config, compute_result=config['get_read_time'])
filtered_date_df = date_df.query(f'd_year >= {q06_YEAR} and d_year <= {(q06_YEAR + 1)}', meta=date_df._meta).reset_index(drop=True)
web_sales_df = ws_df.merge(filter... |
class NERTrainer():
def __init__(self, config: TrainerConfig, datasets: Tuple[(list, list, list)]):
super(NERTrainer, self).__init__()
writer_folder = os.path.join(config.output_folder, 'summary')
if (not os.path.isdir(writer_folder)):
os.makedirs(writer_folder)
self._con... |
def attention_model(images, texts, model_name, is_training=False, weight_decay=4e-05, scope='attention'):
with tf.variable_scope(scope):
arg_scope = nets_factory.arg_scopes_map[model_name](weight_decay=weight_decay)
with slim.arg_scope(arg_scope):
with slim.arg_scope([slim.batch_norm, sl... |
class IssueResource(models.Model):
issue = models.ForeignKey('Issue', on_delete=models.CASCADE, related_name='resources', verbose_name=_('Issue'), help_text=_('The issue for this issue resource.'))
integration = models.ForeignKey('Integration', on_delete=models.CASCADE, related_name='resources', verbose_name=_(... |
((not has_working_ipv6()), 'Requires IPv6')
(os.environ.get('SKIP_IPV6'), 'IPv6 tests disabled')
def test_filter_address_by_type_from_service_info():
desc = {'path': '/~paulsm/'}
type_ = '_homeassistant._tcp.local.'
name = 'MyTestHome'
registration_name = f'{name}.{type_}'
ipv4 = socket.inet_aton('1... |
def load_centralized_mnist(dataset, data_dir, batch_size, max_train_len=None, max_test_len=None, args=None):
MNIST_MEAN = (0.1307,)
MNIST_STD = (0.3081,)
image_size = 28
train_transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize(mean=MNIST_MEAN, std=MNIST_STD)])
test_transform... |
def process_dis_batch_2_new(input_filename_list, dim_input, num, reshape_with_one=False):
img_list = []
random.seed(6)
random.shuffle(input_filename_list)
for filepath in input_filename_list:
filepath2 = (FLAGS.data_path + filepath)
this_img = scm.imread(filepath2)
this_img = np.... |
def anonymize_relaxed(partition):
if (sum(partition.allow) == 0):
RESULT.append(partition)
return
dim = choose_dimension(partition)
if (dim == (- 1)):
print('Error: dim=-1')
pdb.set_trace()
(split_val, next_val, low, high) = find_median(partition, dim)
if (low is not ... |
class ContextRes():
def __init__(self, gf_dim=64, df_dim=64, gfc_dim=1024, dfc_dim=1024, c_dim=3):
self.gf_dim = gf_dim
self.df_dim = df_dim
self.c_dim = c_dim
self.gfc_dim = gfc_dim
self.dfc_dim = dfc_dim
def build(self, image):
imgshape = image.get_shape().as_li... |
def test_detect_clearsky_time_interval(detect_clearsky_data):
(expected, cs) = detect_clearsky_data
u = np.arange(0, len(cs), 2)
cs2 = cs.iloc[u]
expected2 = expected.iloc[u]
clear_samples = clearsky.detect_clearsky(expected2['GHI'], cs2['ghi'], window_length=6)
assert_series_equal(expected2['Cl... |
def build_base_model(model_opt, fields, gpu, checkpoint=None, gpu_id=None):
try:
model_opt.attention_dropout
except AttributeError:
model_opt.attention_dropout = model_opt.dropout
if ((model_opt.model_type == 'text') or (model_opt.model_type == 'vec')):
src_field = fields['src']
... |
def set_arg(config_dict, params, arg_name, arg_type):
for (_i, _v) in enumerate(params):
if (_v.split('=')[0] == arg_name):
arg_name = _v.split('=')[0].replace('--', '')
arg_value = _v.split('=')[1]
config_dict[arg_name] = arg_type(arg_value)
del params[_i]
... |
def make_unsigned_request(req: 'OnchainInvoice'):
addr = req.get_address()
time = req.time
exp = req.exp
if (time and (type(time) != int)):
time = 0
if (exp and (type(exp) != int)):
exp = 0
amount = req.amount_sat
if (amount is None):
amount = 0
memo = req.message... |
class DescribeTable():
def it_can_add_a_row(self, add_row_fixture):
(table, expected_xml) = add_row_fixture
row = table.add_row()
assert (table._tbl.xml == expected_xml)
assert isinstance(row, _Row)
assert (row._tr is table._tbl.tr_lst[(- 1)])
assert (row._parent is t... |
class TestSecurityOverride():
host_url = '
api_key = '12345'
def api_key_encoded(self):
api_key_bytes = self.api_key.encode('utf8')
api_key_bytes_enc = b64encode(api_key_bytes)
return str(api_key_bytes_enc, 'utf8')
def test_default(self, request_unmarshaller):
args = {'ap... |
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