code stringlengths 281 23.7M |
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def do_setup() -> int:
root = get_root()
try:
cfg = get_config_from_root(root)
except (OSError, configparser.NoSectionError, configparser.NoOptionError) as e:
if isinstance(e, (OSError, configparser.NoSectionError)):
print('Adding sample versioneer config to setup.cfg', file=sys.... |
class KinopoiskObject(object):
id = None
objects = None
_urls = {}
_sources = []
_source_classes = {}
def __init__(self, id=None, **kwargs):
if id:
self.id = id
self.set_defaults()
self.__dict__.update(kwargs)
def set_defaults(self):
pass
def p... |
def ArtistList():
(artist_to_add, set_artist_to_add) = use_state('')
(artists, set_artists) = use_state([])
def handle_change(event):
set_artist_to_add(event['target']['value'])
def handle_click(event):
if (artist_to_add and (artist_to_add not in artists)):
set_artists([*arti... |
def run_and_save(n: int, depth: int, n_data: int, batch_size: int, n_shots: int, save_dir: str, use_engine: bool) -> None:
logging.info('Beginning conventional circuit generation for Weber.')
system_pairs = run_config.qubit_pairs()
system_pairs = system_pairs[:n]
to_run_scramb = [_build_circuit(system_p... |
def make_layers(cfg: List[Union[(str, int)]], batch_norm: bool=False) -> nn.Sequential:
layers = []
in_channels = 3
for v in cfg:
if (v == 'M'):
layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
else:
v = cast(int, v)
conv2d = MetaConv2d(in_channels, v, ke... |
class AdvancedSubtensor1(COp):
__props__ = ()
_f16_ok = True
check_input = False
def __init__(self, sparse_grad=False):
self.sparse_grad = sparse_grad
def make_node(self, x, ilist):
x_ = as_tensor_variable(x)
ilist_ = as_tensor_variable(ilist)
if (ilist_.type.dtype no... |
class ModelArguments():
model_name_or_path: Optional[str] = field(default=None, metadata={'help': "The model checkpoint for weights initialization.Don't set if you want to train a model from scratch."})
model_type: Optional[str] = field(default=None, metadata={'help': ('If training from scratch, pass a model ty... |
.parametrize('orientation', ['vertical', 'horizontal'])
def test_clip_to_plot_data_item(orientation):
init_vals = ((- 1.5), 1.5)
x = np.linspace((- 1), 1, 10)
y = np.linspace(1, 1.2, 10)
p = pg.PlotWidget()
pdi = p.plot(x=x, y=y)
lr = pg.LinearRegionItem(init_vals, clipItem=pdi, orientation=orie... |
def test_call_on_instance_with_inherited_dunder_call_method() -> None:
node = extract_node('\n class Base:\n def __call__(self):\n return self\n\n class Sub(Base):\n pass\n obj = Sub()\n val = obj()\n val #\n ')
assert isinstance(node, nodes.NodeNG)
[val] = node.in... |
class Migration(migrations.Migration):
initial = True
dependencies = [('auth', '0011_update_proxy_permissions')]
operations = [migrations.CreateModel(name='User', fields=[('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_leng... |
class WRNInitBlock(nn.Module):
def __init__(self, in_channels, out_channels):
super(WRNInitBlock, self).__init__()
self.conv = WRNConv(in_channels=in_channels, out_channels=out_channels, kernel_size=7, stride=2, padding=3, activate=True)
self.pool = nn.MaxPool2d(kernel_size=3, stride=2, padd... |
def infer_gsdmm_topics(gsdmm_model, texts):
assert (type(texts) == list)
assert (type(texts[0]) == list)
assert (type(texts[0][0]) == str)
dist_over_topic = [gsdmm_model.score(t) for t in texts]
global_topics = extract_topic_from_gsdmm_prediction(dist_over_topic)
return global_topics |
class TagModelQuerySet(models.query.QuerySet):
def initial(self):
return self.filter(name__in=self.model.tag_options.initial)
def filter_or_initial(self, *args, **kwargs):
return self.filter((models.Q(*args, **kwargs) | models.Q(name__in=self.model.tag_options.initial)))
def weight(self, min... |
def chemcore(mol, spinorb=False):
core = 0
for a in range(mol.natm):
atm_nelec = mol.atom_charge(a)
atm_z = charge(mol.atom_symbol(a))
ne_ecp = (atm_z - atm_nelec)
ncore_ecp = (ne_ecp // 2)
atm_ncore = chemcore_atm[atm_z]
if (ncore_ecp > atm_ncore):
co... |
def assert_plugin_add_result(tester: CommandTester, expected: str, constraint: (str | Mapping[(str, (str | list[str]))])) -> None:
assert (tester.io.fetch_output() == expected)
dependencies: dict[(str, Any)] = get_self_command_dependencies()
assert ('poetry-plugin' in dependencies)
assert (dependencies[... |
class TCN_GCN_unit_5(nn.Module):
def __init__(self, in_channels, out_channels, A, stride=1, residual=True):
super(TCN_GCN_unit_5, self).__init__()
self.gcn1 = unit_gtcn_5(in_channels, out_channels, A)
self.tcn1 = unit_tcn(out_channels, out_channels, stride=stride)
self.relu = nn.ReLU... |
class BaseLM(LM):
def eot_token_id(self):
pass
def max_length(self):
pass
def max_gen_toks(self):
pass
def batch_size(self):
pass
def device(self):
pass
def tok_encode(self, string: str):
pass
def tok_decode(self, tokens: Iterable[int]):
... |
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.conv2_drop = nn.Dropout2d()
self.fc1 = nn.Linear(320, 50)
self.fc2 = nn.Linear(50, 10)
def forward... |
def parse_html_form(attr_filter, html, input_names={}):
attr_str = ('' if callable(attr_filter) else attr_filter)
for form in re.finditer(f'(?P<TAG><form[^>]*{attr_str}.*?>)(?P<CONTENT>.*?)</?(form|body|html).*?>', html, (re.I | re.S)):
if (callable(attr_filter) and (not attr_filter(form.group('TAG'))))... |
class WarmupCosineWithHardRestartsSchedule(WarmupCosineSchedule):
def __init__(self, warmup=0.002, t_total=(- 1), cycles=1.0, **kw):
super(WarmupCosineWithHardRestartsSchedule, self).__init__(warmup=warmup, t_total=t_total, cycles=cycles, **kw)
assert (cycles >= 1.0)
def get_lr_(self, progress):... |
class CoCaLoss(ClipLoss):
def __init__(self, caption_loss_weight, clip_loss_weight, pad_id=0, local_loss=False, gather_with_grad=False, cache_labels=False, rank=0, world_size=1, use_horovod=False):
super().__init__(local_loss=local_loss, gather_with_grad=gather_with_grad, cache_labels=cache_labels, rank=ran... |
_task(name='CosRearrangementTask-v0')
class CosRearrangementTask(NavigationTask):
def __init__(self, **kwargs) -> None:
super().__init__(**kwargs)
self.reset_trackers(False)
self.load_annotations()
self.rec_packers: Dict[(int, ShelfBinPacker)] = {}
def get_translation(self, objec... |
class EvaluateTool(object):
def __init__(self, args):
self.args = args
def evaluate(self, preds, golds, section):
summary = {}
all_match = []
simple_match = []
complex_match = []
small_test_match = []
for (pred, gold_item) in zip(preds, golds):
... |
class CoreNLPTokenizer(Tokenizer):
def __init__(self, **kwargs):
self.classpath = (kwargs.get('classpath') or DEFAULTS['corenlp_classpath'])
self.annotators = copy.deepcopy(kwargs.get('annotators', set()))
self.mem = kwargs.get('mem', '2g')
self._launch()
def _launch(self):
... |
def escape_md_section(text, snob=False):
text = md_backslash_matcher.sub('\\\\\\1', text)
if snob:
text = md_chars_matcher_all.sub('\\\\\\1', text)
text = md_dot_matcher.sub('\\1\\\\\\2', text)
text = md_plus_matcher.sub('\\1\\\\\\2', text)
text = md_dash_matcher.sub('\\1\\\\\\2', text)
... |
def run(args):
locale.setlocale(locale.LC_ALL, '')
QtWidgets.QApplication.setAttribute(QtCore.Qt.ApplicationAttribute.AA_EnableHighDpiScaling, True)
is_preview = args.preview
start_logger(args.local_data, is_preview)
app = QtWidgets.QApplication(sys.argv)
app.applicationStateChanged.connect(_on_... |
class Test_pep440_post(unittest.TestCase, Testing_renderer_case_mixin):
style = 'pep440-post'
expected = {'tagged_0_commits_clean': 'v1.2.3', 'tagged_0_commits_dirty': 'v1.2.3.post0.dev0+g', 'tagged_1_commits_clean': 'v1.2.3.post1+gabc', 'tagged_1_commits_dirty': 'v1.2.3.post1.dev0+gabc', 'untagged_0_commits_cl... |
class ResizeLongest(nn.Module):
def __init__(self, max_size, interpolation=InterpolationMode.BICUBIC, fill=0):
super().__init__()
if (not isinstance(max_size, int)):
raise TypeError(f'Size should be int. Got {type(max_size)}')
self.max_size = max_size
self.interpolation =... |
.parametrize('suffix', ['inline', 'display'])
def test_dark_mode_mathml(webengine_versions, quteproc_new, request, qtbot, suffix):
if (not request.config.webengine):
pytest.skip('Skipped with QtWebKit')
args = (_base_args(request.config) + ['--temp-basedir', '-s', 'colors.webpage.darkmode.enabled', 'tru... |
class TestUserDetails(BaseActionTest):
def test_user_details(self):
self.strategy.set_settings({})
details = {'first_name': 'Test'}
user = User(username='foobar')
backend = None
user_details(self.strategy, details, backend, user)
self.assertEqual(user.first_name, 'Tes... |
class Hg(Vcs):
HEAD = 'tip'
_status_translations = (('AR', 'staged'), ('M', 'changed'), ('!', 'deleted'), ('?', 'untracked'), ('I', 'ignored'))
def _log(self, refspec=None, maxres=None, filelist=None):
args = ['log', '--template', 'json']
if refspec:
args += ['--limit', '1', '--r... |
class UdemyLectureStream(Downloader):
def __init__(self, parent):
self._mediatype = None
self._quality = None
self._resolution = None
self._dimension = None
self._extension = None
self._url = None
self._parent = parent
self._filename = None
sel... |
_module()
class AudioFeatureDataset(BaseDataset):
def __init__(self, ann_file, pipeline, suffix='.npy', **kwargs):
self.suffix = suffix
super().__init__(ann_file, pipeline, modality='Audio', **kwargs)
def load_annotations(self):
if self.ann_file.endswith('.json'):
return self... |
.parametrize('cfg_file', ['configs/ner/bert_softmax/bert_softmax_cluener_18e.py'])
def test_bert_softmax(cfg_file):
texts = ([''] * 47)
img = ([31] * 47)
labels = ([31] * 128)
input_ids = ([0] * 128)
attention_mask = ([0] * 128)
token_type_ids = ([0] * 128)
img_metas = {'texts': texts, 'labe... |
class SharedGDict(GDict):
def __init__(self, gdict=None, shape=None, dtype=None, name=None):
if (gdict is not None):
assert ((shape is None) and (dtype is None) and (name is None))
assert (isinstance(gdict, GDict) and gdict.is_np_all)
shape = gdict.shape.memory
... |
class ResNetBackbone(Backbone):
def __init__(self, backbone):
super(ResNetBackbone, self).__init__(backbone)
self.custom_objects.update(keras_resnet.custom_objects)
def retinanet(self, *args, **kwargs):
return resnet_retinanet(*args, backbone=self.backbone, **kwargs)
def download_ima... |
def test_non_async_context():
()
def async_fn_with_yield(should_yield):
with Ctx():
if should_yield:
ret = (yield ExternalCacheBatchItem(mc._batch, 'get', 'test'))
else:
ret = 0
return ret
()
def batch(should_yield=True):
(r... |
class Networks(nn.Module):
def __init__(self, cfgs, num_classes, samples_per_cls=None):
super(Networks, self).__init__()
self.num_classes = num_classes
self.samples_per_cls = samples_per_cls
self.backbone_with_fc = (cfgs.classifier is None)
self.backbone = self.build_backbone... |
class ResidualBaseDecoder(nn.Module):
def __init__(self, channel, groups):
super().__init__()
self._net = nn.Sequential(ResidualBlock(channel, channel, groups=groups), ResidualBlockShuffle(channel, channel, 2, groups=groups), AttentionBlock(channel, groups=groups), ResidualBlock(channel, channel, gr... |
_config
def test_only_wm_protocols_focus(xmanager, conn):
w = None
def only_wm_protocols_focus():
nonlocal w
w = conn.create_window(5, 5, 10, 10)
w.set_attribute(eventmask=xcffib.xproto.EventMask.FocusChange)
w.set_property('WM_CLASS', 'float', type='STRING', format=8)
hi... |
class Solution(object):
def minIncrementForUnique(self, A):
if ((A is None) or (len(A) == 0)):
return 0
res = 0
num_set = set()
duplicate = []
A.sort()
(left, right) = (A[0], A[(- 1)])
holes = ((right - left) + 1)
for v in A:
if... |
class ExportComplianceException(Exception):
def __init__(self, sso_username, email, quay_username):
self.sso_username = sso_username
self.email = email
self.quay_username = quay_username
def __str__(self):
return f'{self.sso_username}: {self.email} : {self.quay_username}' |
class ImmutableStringStrategy(StringStrategy):
def as_charlist_ascii(self, w_str):
return list(self.as_str_ascii(w_str))
def as_charlist_utf8(self, w_str):
return list(self.as_str_utf8(w_str))
def as_unicharlist(self, w_str):
return list(self.as_unicode(w_str))
def setitem(self, ... |
class ContextMenuUnconditional(ContextMenu, metaclass=ABCMeta):
def display(self, callingWindow, context):
raise NotImplementedError
def getBitmap(self, callingWindow, context):
return
def getText(self, callingWindow, context):
raise NotImplementedError
def getSubMenu(self, calli... |
def test_log_filter():
rules = {'': 'INFO'}
filter_ = LogFilter(rules, default_level='INFO')
assert (filter_.should_log('test', 'DEBUG') is False)
assert (filter_.should_log('test', 'INFO') is True)
assert (filter_.should_log('raiden', 'DEBUG') is False)
assert (filter_.should_log('raiden', 'INF... |
def _apodize(input, ndim, oversamp, width, beta):
output = input
for a in range((- ndim), 0):
i = output.shape[a]
os_i = ceil((oversamp * i))
idx = np.arange(i, dtype=output.dtype)
apod = (((beta ** 2) - ((((np.pi * width) * (idx - (i // 2))) / os_i) ** 2)) ** 0.5)
apod /... |
.parametrize('add_version_condition', [True, False])
def test_delete(add_version_condition: bool) -> None:
item = UserModel('foo', 'bar')
with patch(PATCH_METHOD) as req:
req.return_value = None
item.delete(add_version_condition=add_version_condition)
expected = {'Key': {'user_id': {'S':... |
def Mine_Pattern(FP, ItemS):
global CanNum
ExpSet = []
temp = FP[:]
for pre in temp:
for suf in temp:
pattern = [pre, suf]
CanNum += 1
(count, ItemS[str(pattern)]) = ProMatching(ItemS[str(pre)], suf)
if (count >= int(minsup)):
FP.ap... |
def test_arm():
local = True
funcaddr = 0
varaddr = 1048576
stackaddr = 2097152
if local:
r2p = r2pipe.open('ipa://test/tests/crackme-level0-symbols.ipa', flags=['-2'])
r2p.cmd('s sym._validate; aei; aeim; aer x0 = 0x100000;')
funcaddr = int(r2p.cmd('s'), 16)
else:
... |
.parametrize('report_option', ['term-missing:skip-covered', 'term:skip-covered'])
def test_skip_covered_cli(pytester, testdir, report_option):
testdir.makefile('', coveragerc=SKIP_COVERED_COVERAGERC)
script = testdir.makepyfile(SKIP_COVERED_TEST)
result = testdir.runpytest('-v', f'--cov={script.dirpath()}',... |
def test_life_list__converters():
life_list = LifeList.from_json(j_life_list_1)
assert (life_list.data[0] == life_list[0])
assert (len(life_list) == 10)
assert (life_list.count_without_taxon == 4)
assert (isinstance(life_list.data[0], TaxonCount) and (life_list.data[0].id == 48460))
life_list = ... |
def output_cut(s_partition: List[cirq.Qid]) -> None:
coloring = []
for node in working_graph:
if (node in s_partition):
coloring.append('blue')
else:
coloring.append('red')
edges = working_graph.edges(data=True)
weights = [w['weight'] for (u, v, w) in edges]
n... |
.functions
def test_add_column_iterator_repeat(dataframe):
df = dataframe.add_column('city_pop', range(3), fill_remaining=True)
assert (df.city_pop.iloc[0] == 0)
assert (df.city_pop.iloc[1] == 1)
assert (df.city_pop.iloc[2] == 2)
assert (df.city_pop.iloc[3] == 0)
assert (df.city_pop.iloc[4] == 1... |
class Register():
def __init__(self) -> None:
self._generators = {}
self._on_packet = ({}, {}, {}, {})
self._on_server_start = {}
self._on_server_stop = {}
def add_world_generator(self, name: str):
def deco(cls):
if (not issubclass(cls, AbstractWorldGenerator)... |
def transform_ptt_post_to_spacy(post: ptt.PttPost, nlp: Language, disable: Iterable[str]=['tok2vec']) -> spacy.SpacyPttPost:
title_bytes = nlp(post.title, disable=disable).to_bytes()
content_bytes = nlp(post.content, disable=disable).to_bytes()
comments = []
for comment in post.comments:
comment... |
def test_thread_cache_basics() -> None:
q: Queue[Outcome[object]] = Queue()
def fn() -> NoReturn:
raise RuntimeError('hi')
def deliver(outcome: Outcome[object]) -> None:
q.put(outcome)
start_thread_soon(fn, deliver)
outcome = q.get()
with pytest.raises(RuntimeError, match='hi'):
... |
def test__vf_ground_sky_2d(test_system_fixed_tilt):
(ts, pts, vfs_gnd_sky) = test_system_fixed_tilt
vfs = utils.vf_ground_sky_2d(ts['rotation'], ts['gcr'], pts, ts['pitch'], ts['height'], max_rows=1)
assert np.allclose(vfs, vfs_gnd_sky, rtol=0.1)
vf = utils.vf_ground_sky_2d(ts['rotation'], ts['gcr'], pt... |
class VhdlLexer(RegexLexer):
name = 'vhdl'
aliases = ['vhdl']
filenames = ['*.vhdl', '*.vhd']
mimetypes = ['text/x-vhdl']
url = '
version_added = '1.5'
flags = (re.MULTILINE | re.IGNORECASE)
tokens = {'root': [('\\s+', Whitespace), ('(\\\\)(\\n)', bygroups(String.Escape, Whitespace)), ('... |
def parse_location(file_desc):
file_desc = os.fsencode(file_desc)
file_parts = [x for x in re.split(b'(?<!\\\\)(\\\\{2})*::', file_desc) if (x is not None)]
concat_parts = []
keep = None
for part in reversed(file_parts):
if re.match(b'^(\\\\{2})+$', part):
keep = part
els... |
def test_internal_error_with_maxfail(pytester: pytest.Pytester) -> None:
pytester.makepyfile("\n import pytest\n\n (params=['1', '2'])\n def crasher():\n raise RuntimeError\n\n def test_aaa0(crasher):\n pass\n def test_aaa1(crasher):\n pass\n ")... |
def lr_schedule(lrnrate, epoch, warmupperiod=5, schedule=[100, 150, 200], max_epoch=250):
if (schedule is None):
schedule = [(max_epoch // 2.667), (max_epoch // 1.6), (max_epoch // 1.142)]
warmupfactor = min(1, ((epoch + 1) / (1e-06 + warmupperiod)))
if (epoch < schedule[0]):
return ((1.0 * ... |
def time_serie(ts_code: int, start: str, end: str, strict: bool=False) -> pd.Series:
if strict:
ts_data = api.get_data_with_strict_range(ts_code, start, end)
else:
ts_data = api.get_data(ts_code, start, end)
values = []
index = []
for i in ts_data:
values.append(i['valor'])
... |
class StatsReporter(threading.Thread):
def __init__(self, report_interval: int):
super().__init__()
self.report_interval = report_interval
self.stop = threading.Event()
self.stats_queue = SimpleQueue()
def run(self):
while (not self.stop.wait(self.report_interval)):
... |
class ResizeObservation(gym.ObservationWrapper):
def __init__(self, env, shape):
super().__init__(env)
if isinstance(shape, int):
self.shape = (shape, shape)
else:
self.shape = tuple(shape)
obs_shape = (self.shape + self.observation_space.shape[2:])
se... |
class BaseResourceDetailsPopup(QDialog, Ui_TrickDetailsPopup):
def __init__(self, parent: QWidget, window_manager: WindowManager, game_description: GameDescription, areas_to_show: list[tuple[(Region, Area, list[str])]], trick_levels: (TrickLevelConfiguration | None)=None):
super().__init__(parent)
s... |
def _set_adlr_autoresume(args):
global _GLOBAL_ADLR_AUTORESUME
_ensure_var_is_not_initialized(_GLOBAL_ADLR_AUTORESUME, 'adlr autoresume')
if args.adlr_autoresume:
if (args.rank == 0):
print('enabling autoresume ...', flush=True)
sys.path.append(os.environ.get('SUBMIT_SCRIPTS', '.... |
class TestDataPipeFSSpec(expecttest.TestCase):
def setUp(self):
self.temp_dir = create_temp_dir()
self.temp_files = create_temp_files(self.temp_dir)
self.temp_sub_dir = create_temp_dir(self.temp_dir.name)
self.temp_sub_files = create_temp_files(self.temp_sub_dir, 4, False)
se... |
def bbox2d(bboxA, bboxB):
minx_overlap = max(bboxA[0], bboxB[0])
miny_overlap = max(bboxA[1], bboxB[1])
maxx_overlap = min(bboxA[2], bboxB[2])
maxy_overlap = min(bboxA[3], bboxB[3])
interArea = (max(0, (maxx_overlap - minx_overlap)) * max(0, (maxy_overlap - miny_overlap)))
boxAArea = ((bboxA[2] ... |
class StoryCategory(NameSlugModel):
class Meta():
ordering = ('name',)
verbose_name = 'story category'
verbose_name_plural = 'story categories'
def __str__(self):
return self.name
def get_absolute_url(self):
return reverse('success_story_list_category', kwargs={'slug'... |
class _WrappedModel():
def __init__(self, model, timestep_map, original_num_steps):
self.model = model
self.timestep_map = timestep_map
self.original_num_steps = original_num_steps
def __call__(self, x, ts, **kwargs):
map_tensor = th.tensor(self.timestep_map, device=ts.device, dt... |
def test_multi_mass_spring_damper():
(k0, m0, g, c0) = sm.symbols('k0, m0, g, c0')
(x0, v0, f0) = me.dynamicsymbols('x0, v0, f0')
sys = multi_mass_spring_damper()
assert (sys.constants_symbols == {k0, c0, m0})
assert (sys.specifieds_symbols == set())
assert (sys.coordinates == [x0])
assert (... |
class FileUploader(Container):
_attribute_decorator('WidgetSpecific', 'If True multiple files can be \n selected at the same time', bool, {})
def multiple_selection_allowed(self):
return ('multiple' in self.__dict__.keys())
_selection_allowed.setter
def multiple_selection_allowed(self, va... |
def _construct_prop_item(key: str, value: ast.expr) -> tuple[(str, ast.expr)]:
if ((key == 'style') and isinstance(value, (ast.Dict, ast.Call))):
new_value = copy(value)
if _rewrite_props(new_value, (lambda k, v: ((k, v) if (k == 'style') else _construct_prop_item(k, v)))):
value = new_v... |
def add_attribute_to_class(api: SemanticAnalyzerPluginInterface, cls: ClassDef, name: str, typ: Type, final: bool=False, no_serialize: bool=False, override_allow_incompatible: bool=False, fullname: (str | None)=None, is_classvar: bool=False, overwrite_existing: bool=False) -> Var:
info = cls.info
if ((name in i... |
def create_dataloader(dataset_classname, dataset_config, batch_size=1, collate_fn=None, shuffle=False, num_workers=0, drop_last=False) -> DataLoader:
dataset = dataset_class_dict[dataset_classname](**dataset_config)
dataloader = DataLoader(dataset, batch_size=batch_size, collate_fn=collate_fn, shuffle=shuffle, ... |
def configure_converter(converter: BaseConverter):
converter.register_structure_hook(bytes, (lambda v, _: b85decode(v)))
converter.register_unstructure_hook(bytes, (lambda v: (b85encode(v) if v else b'').decode('utf8')))
def gen_unstructure_mapping(cl: Any, unstructure_to=None):
key_handler = str
... |
def test_slice_penumbra():
profiler = Profile().from_tuples(PROFILER).resample_x(0.1)
(lt_penum, rt_penum) = profiler.slice_penumbra()
assert np.all((lt_penum.x < 0))
assert np.all((rt_penum.x > 0))
assert np.all((lt_penum.y < profiler.get_y(0)))
assert np.all((rt_penum.y < profiler.get_y(0))) |
class XLMTokenizer(PreTrainedTokenizer):
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION
max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
def __init__(self, vocab_file, merges_fi... |
def addScriptCode(hf, testruns):
t0 = (testruns[0].start * 1000)
tMax = (testruns[(- 1)].end * 1000)
detail = '\tvar devtable = [];\n'
for data in testruns:
topo = data.deviceTopology()
detail += ('\tdevtable[%d] = "%s";\n' % (data.testnumber, topo))
detail += ('\tvar bounds = [%f,%f... |
class PrepDetails(MWSDataType):
AMAZON = 'AMAZON'
SELLER = 'SELLER'
def __init__(self, prep_instruction: Union[(PrepInstruction, str)], prep_owner: str=SELLER):
self.prep_instruction = prep_instruction
self.prep_owner = prep_owner
def params_dict(self) -> dict:
return {'PrepInstr... |
class Effect5871(BaseEffect):
type = 'passive'
def handler(fit, ship, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Shield Operation')), 'shieldBonus', ship.getModifiedItemAttr('shipBonusMI2'), skill='Minmatar Hauler', **kwargs) |
class VIIRSSurfaceReflectanceWithVIHandler(VIIRSJRRFileHandler):
def __init__(self, *args, filter_veg: bool=True, **kwargs) -> None:
super().__init__(*args, **kwargs)
self._filter_veg = filter_veg
def _mask_invalid(self, data_arr: xr.DataArray, ds_info: dict) -> xr.DataArray:
new_data_ar... |
class SAFEMSIMDXML(SAFEMSIXMLMetadata):
def calibrate_to_reflectances(self, data, band_name):
quantification = int(self.root.find('.//QUANTIFICATION_VALUE').text)
data = self._sanitize_data(data)
return (((data + self.band_offset(band_name)) / quantification) * 100)
def _sanitize_data(se... |
def _get_expr(s: str) -> Tuple[(str, str)]:
level: int = 0
for (i, c) in enumerate(s):
if (c in ['(', '{']):
level += 1
elif ((level > 0) and (c in [')', '}'])):
level -= 1
elif ((level == 0) and (c in [')', '}', ','])):
break
return (s[0:i], s[i:]... |
_destruct_output_when_exp('content')
def put_scope(name: str, content: Union[(Output, List[Output])]=[], scope: str=None, position: int=OutputPosition.BOTTOM) -> Output:
if (not isinstance(content, list)):
content = [content]
check_dom_name_value(name, 'scope name')
dom_id = scope2dom(name, no_css_s... |
class CostRegNet(nn.Module):
def __init__(self):
super(CostRegNet, self).__init__()
self.conv0 = ConvBnReLU3D(32, 8)
self.conv1 = ConvBnReLU3D(8, 16, stride=2)
self.conv2 = ConvBnReLU3D(16, 16)
self.conv3 = ConvBnReLU3D(16, 32, stride=2)
self.conv4 = ConvBnReLU3D(32, ... |
class Player():
def __init__(self, playerid: int):
self.id: int = playerid
def set_spawn_info(self, team: int, skin: int, x: float, y: float, z: float, rotation: float, weapon1: int, weapon1_ammo: int, weapon2: int, weapon2_ammo: int, weapon3: int, weapon3_ammo: int) -> bool:
return set_spawn_in... |
def muti_loss_fusion_kl(preds, target, dfs, fs, mode='MSE'):
loss0 = 0.0
loss = 0.0
for i in range(0, len(preds)):
if ((preds[i].shape[2] != target.shape[2]) or (preds[i].shape[3] != target.shape[3])):
tmp_target = F.interpolate(target, size=preds[i].size()[2:], mode='bilinear', align_co... |
class Scenario(ScenarioGenerator):
def __init__(self):
super().__init__()
self.open_scenario_version = 2
def scenario(self, **kwargs):
catalog = xosc.Catalog()
catalog.add_catalog('VehicleCatalog', '../xosc/Catalogs/Vehicles')
road = xosc.RoadNetwork(roadfile='../xodr/str... |
class ResourceDatabaseItemModel(ResourceDatabaseGenericModel):
def __init__(self, db: ResourceDatabase):
super().__init__(db, ResourceType.ITEM)
def all_columns(self):
return ITEM_FIELDS
def _create_item(self, short_name) -> ItemResourceInfo:
return ItemResourceInfo(self.db.first_unu... |
def _synchronize_async_fixture(fixturedef: FixtureDef, event_loop_fixture_id: str) -> None:
if inspect.isasyncgenfunction(fixturedef.func):
_wrap_asyncgen_fixture(fixturedef, event_loop_fixture_id)
elif inspect.iscoroutinefunction(fixturedef.func):
_wrap_async_fixture(fixturedef, event_loop_fixt... |
_required
_exempt
_
def unmark_comment_as_spam(request, conference_slug, proposal_slug, proposal_comment_id):
if ((not request.is_ajax()) or (request.user.is_active is False)):
return HttpResponseForbidden()
conference = get_object_or_404(Conference, slug=conference_slug)
proposal = get_object_or_40... |
def test_chunk_boundaries() -> None:
conn = Connection(our_role=SERVER)
request = b'POST / HTTP/1.1\r\nHost: example.com\r\nTransfer-Encoding: chunked\r\n\r\n'
conn.receive_data(request)
assert (conn.next_event() == Request(method='POST', target='/', headers=[('Host', 'example.com'), ('Transfer-Encoding... |
def to_custom_tensor(original: Union[(List, Tuple)], torch_tensors: List[torch.Tensor]) -> List:
outputs = []
for (orig, torch_tensor) in zip(original, torch_tensors):
tensor = torch_tensor
if isinstance(orig, spconv.SparseConvTensor):
tensor = orig.replace_feature(torch_tensor)
... |
def main():
scene = SceneManager.AddScene('Scene')
scene.mainCamera.transform.localPosition = Vector3(0, 0, (- 10))
cube = GameObject('Cube')
texture = Texture2D(resolver.getPath('examples/example8/logo.png'))
renderer = cube.AddComponent(MeshRenderer)
renderer.mesh = Mesh.cube(2)
renderer.m... |
def resume_from_checkpoint(fdir, model, optimizer=None, scheduler=None):
start_epoch = 0
checkpoint_file = osp.join(fdir, 'checkpoint')
if (not osp.exists(checkpoint_file)):
with open(checkpoint_file, 'w') as f:
pass
return start_epoch
with open(checkpoint_file, 'r') as check... |
class RVsAssignmentStepsTester():
def continuous_steps(self, step, step_kwargs):
with pm.Model() as m:
c1 = pm.HalfNormal('c1')
c2 = pm.HalfNormal('c2')
with pytensor.config.change_flags(mode=fast_unstable_sampling_mode):
assert ([m.rvs_to_values[c1]] == s... |
class DictAction(Action):
def _parse_int_float_bool(val):
try:
return int(val)
except ValueError:
pass
try:
return float(val)
except ValueError:
pass
if (val.lower() in ['true', 'false']):
return (True if (val.lower(... |
class SponsorshipBenefitAdminForm(forms.ModelForm):
class Meta():
model = SponsorshipBenefit
widgets = {'year': SPONSORSHIP_YEAR_SELECT}
fields = '__all__'
def clean(self):
cleaned_data = super().clean()
standalone = cleaned_data.get('standalone')
packages = clean... |
class MultiDatasetSampler(Sampler):
def __init__(self, cfg, dataset_dicts, sizes, seed: Optional[int]=None):
self.sizes = sizes
self.sample_epoch_size = cfg.MULTI_DATASET.SAMPLE_EPOCH_SIZE
assert ((self.sample_epoch_size % cfg.SOLVER.IMS_PER_BATCH) == 0)
print('self.epoch_size', self... |
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