code stringlengths 281 23.7M |
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def add_parser():
parser = argparse.ArgumentParser()
parser.add_argument('--logdir', required=True)
parser.add_argument('--config', required=True)
parser.add_argument('--config-args')
parser.add_argument('--step', type=int)
parser.add_argument('--section', required=True)
parser.add_argument(... |
def _get_notebook_kwargs(initial_path=None, notebook_path=None, subcommand=None):
if ((initial_path is not None) and (notebook_path is not None)):
raise RuntimeError("'initial_path' and 'notebook_path' cannot both be set.")
if (notebook_path is not None):
if (not os.path.exists(notebook_path)):
... |
class ViTFeatureExtractor(FeatureExtractionMixin, ImageFeatureExtractionMixin):
model_input_names = ['pixel_values']
def __init__(self, do_resize=True, size=224, resample=Image.BILINEAR, do_normalize=True, image_mean=None, image_std=None, **kwargs):
super().__init__(**kwargs)
self.do_resize = do... |
class DataCollatorForEnDe(DataCollatorForSeq2Seq):
tokenizer: PreTrainedTokenizerBase
text_tokenizer: Optional[Any] = None
train_image_tokenizer: Optional[Any] = None
eval_image_tokenizer: Optional[Any] = None
model: Optional[Any] = None
padding: Union[(bool, str, PaddingStrategy)] = True
ma... |
class Solution():
def isLongPressedName(self, name: str, typed: str) -> bool:
stack1 = []
stack2 = []
for i in name:
stack1.append(i)
for j in typed:
stack2.append(j)
if (len(stack1) > len(stack2)):
return False
while (stack1 and st... |
class AnalogClock(QWidget):
hourHand = QPolygon([QPoint(7, 8), QPoint((- 7), 8), QPoint(0, (- 40))])
minuteHand = QPolygon([QPoint(7, 8), QPoint((- 7), 8), QPoint(0, (- 70))])
hourColor = QColor(127, 0, 127)
minuteColor = QColor(0, 127, 127, 191)
def __init__(self, parent=None):
super(Analog... |
def aggregate_costs(n, flatten=False, opts=None, existing_only=False):
components = dict(Link=('p_nom', 'p0'), Generator=('p_nom', 'p'), StorageUnit=('p_nom', 'p'), Store=('e_nom', 'p'), Line=('s_nom', None), Transformer=('s_nom', None))
costs = {}
for (c, (p_nom, p_attr)) in zip(n.iterate_components(compon... |
class SmoothMSE(nn.Module):
def __init__(self, opt=None, threshold=0.001):
super().__init__()
self.opt = opt
self.threshold = threshold
def forward(self, x1, x2):
(_, c, h, w) = x1.shape
mse = ((x1 - x2) ** 2).clamp(min=self.threshold)
return mse.mean() |
def symbolic_trace(td_module: TensorDictModule) -> TDGraphModule:
if isinstance(td_module, TensorDictSequential):
return _trace_tensordictsequential(td_module)
elif isinstance(td_module, TensorDictModule):
return _trace_tensordictmodule(td_module)
raise TypeError(f'Unsupported type {type(td_... |
def main():
parser = HfArgumentParser((ModelArguments, DataTrainingArguments, Seq2SeqTrainingArguments))
if ((len(sys.argv) == 2) and sys.argv[1].endswith('.json')):
(model_args, data_args, training_args) = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))
else:
(model_args, dat... |
class CustomNamespace(argparse.Namespace):
from_: 'FromArg'
order: 'OrderArg'
format_: 'FormatArg'
summary: bool
output_file: str
ignore_packages: List[str]
packages: List[str]
with_system: bool
with_authors: bool
with_urls: bool
with_description: bool
with_license_file: ... |
('pypyr.steps.filewritejson.Path')
def test_filewritejson_pass_with_payload_substitutions_encoding(mock_path):
context = Context({'k1': 'v1', 'intkey': 3, 'pathkey': '/arb/path', 'enc': 'utf-32', 'parent': [0, 1, {'child': ['{k1}', '{intkey}', ['a', 'b', 'c']]}], 'nested': '{parent[2][child]}', 'fileWriteJson': {'p... |
def build_progress_bar(args, iterator, epoch=None, prefix=None, default='tqdm', no_progress_bar='none'):
if (args.log_format is None):
args.log_format = (no_progress_bar if args.no_progress_bar else default)
if ((args.log_format == 'tqdm') and (not sys.stderr.isatty())):
args.log_format = 'simpl... |
def _write_to_tfrecord(filenames, labels, tfrecord_writer):
num_images = len(filenames)
with tf.Graph().as_default():
image_placeholder = tf.placeholder(dtype=tf.uint8)
encoded_image = tf.image.encode_png(image_placeholder)
with tf.Session('') as sess:
for i in range(num_imag... |
class PuzzleSystemCmdSet(CmdSet):
def at_cmdset_creation(self):
super(PuzzleSystemCmdSet, self).at_cmdset_creation()
self.add(CmdCreatePuzzleRecipe())
self.add(CmdEditPuzzle())
self.add(CmdArmPuzzle())
self.add(CmdListPuzzleRecipes())
self.add(CmdListArmedPuzzles())
... |
class MenuButtonWebApp(MenuButton):
__slots__ = ('text', 'web_app')
def __init__(self, text: str, web_app: WebAppInfo, *, api_kwargs: Optional[JSONDict]=None):
super().__init__(type=constants.MenuButtonType.WEB_APP, api_kwargs=api_kwargs)
with self._unfrozen():
self.text: str = text
... |
class Ui_Form(object):
def setupUi(self, Form):
if (not Form.objectName()):
Form.setObjectName(u'Form')
Form.resize(410, 401)
self.directory = QLineEdit(Form)
self.directory.setObjectName(u'directory')
self.directory.setGeometry(QRect(140, 39, 251, 21))
se... |
class MineIDOAuth2Test(OAuth2Test):
backend_path = 'social_core.backends.mineid.MineIDOAuth2'
user_data_url = '
expected_username = ''
access_token_body = json.dumps({'access_token': 'foobar', 'token_type': 'bearer'})
user_data_body = json.dumps({'email': '', 'primary_profile': None})
def test_l... |
class _BaseTestDB(object):
def setup(self):
if self.should_skip():
pytest.skip(('%r unsupported on this system' % self.class_to_test))
(fd, fname) = tempfile.mkstemp(prefix='taskw-testsrc')
dname = tempfile.mkdtemp(prefix='taskw-tests-data')
with open(fname, 'w') as f:
... |
def test_fail_on_errors(error_pytester: Pytester) -> None:
result = error_pytester.runpytest('-v', '--strict-markers', '--stepwise')
assert (_strip_resource_warnings(result.stderr.lines) == [])
stdout = result.stdout.str()
assert ('test_error ERROR' in stdout)
assert ('test_success_after_fail' not i... |
class TestUtils(unittest.TestCase):
def test_load(self):
problem = Problem(P=np.eye(3), q=np.zeros(3), G=None, h=None, A=None, b=None, lb=None, ub=None, name='TEST')
fpath = os.path.join(tempfile.gettempdir(), 'FOOBAR.npz')
problem.save(fpath)
loaded = Problem.load(fpath)
sel... |
class Extract():
def __init__(self, arguments):
logger.debug('Initializing %s: (args: %s', self.__class__.__name__, arguments)
self.args = arguments
Utils.set_verbosity(self.args.loglevel)
self.output_dir = get_folder(self.args.output_dir)
logger.info('Output Directory: %s', ... |
def gen_src1_dep_nottaken_test():
return [gen_br2_src1_dep_test(5, 'bne', 1, 1, False), gen_br2_src1_dep_test(4, 'bne', 2, 2, False), gen_br2_src1_dep_test(3, 'bne', 3, 3, False), gen_br2_src1_dep_test(2, 'bne', 4, 4, False), gen_br2_src1_dep_test(1, 'bne', 5, 5, False), gen_br2_src1_dep_test(0, 'bne', 6, 6, False)... |
def create_example(path, pkg_root):
pyproject = (path / 'pyproject.toml')
files = [f'{pkg_root}/pkg/__init__.py', '_files/file.txt']
if (pkg_root != '.'):
files.append(f'{pkg_root}/other/nested/__init__.py')
for file in files:
(path / file).parent.mkdir(exist_ok=True, parents=True)
... |
class TestAsync(PyScriptTest):
coroutine_script = '\n <script type="py">\n import js\n import asyncio\n js.console.log("first")\n async def main():\n await asyncio.sleep(1)\n js.console.log("third")\n asyncio.{func}(main())\n js.console.log("sec... |
class State(pc.State):
ticker: str = 'Stock Symbol'
ticker2: str = ''
username: str = 'Jay'
logged_in: bool = True
loading: bool = False
def ticker_update2(self):
self.loading = True
self.ticker2 = self.ticker
self.loading = False
def df1(self) -> pd.DataFrame:
... |
def test_parent(pytester):
pytester.makefile('.feature', parent=textwrap.dedent(' Feature: Parent\n Scenario: Parenting is easy\n Given I have a parent fixture\n And I have an overridable fixture\n '))
pytester.makeconftest(textwrap.dede... |
def getBombMult(mod, src, tgt, distance, tgtSigRadius):
modRange = mod.maxRange
if (modRange is None):
return 0
blastRadius = mod.getModifiedChargeAttr('explosionRange')
atkRadius = src.getRadius()
tgtRadius = tgt.getRadius()
if ((distance is not None) and (distance < max(0, (((modRange ... |
def sum_of_ratio_of_minima_among_subsets(num_denom_pairs):
(numerators, denominators) = zip(*num_denom_pairs)
sorted_num_idx = np.argsort(numerators)
sorted_denom_idx = np.argsort(denominators)
sum_ratio = 0
for (i, j) in product(range(len(num_denom_pairs)), range(len(num_denom_pairs))):
can... |
def load_checkpoint(experiment_directory, checkpoint):
checkpoint_path = os.path.join(experiment_directory, Checkpoint.CHECKPOINT_DIR_NAME, checkpoint)
logging.info('Loading checkpoint from {}'.format(checkpoint_path))
checkpoint = Checkpoint.load(checkpoint_path)
seq2seq = checkpoint.model
input_vo... |
class ReplacementField():
arg_name: Union[(None, int, str)]
index_attribute: Sequence[Tuple[(IndexOrAttribute, str)]] = ()
conversion: Optional[str] = None
format_spec: Optional[FormatString] = None
def iter_replacement_fields(self) -> Iterable['ReplacementField']:
(yield self)
if se... |
class TDF(nn.Module):
def __init__(self, channels, f, bn_factor=16, bias=False, min_bn_units=16, activation=nn.ReLU):
super(TDF, self).__init__()
if (bn_factor is None):
self.tdf = nn.Sequential(nn.Linear(f, f, bias), nn.BatchNorm2d(channels), activation())
else:
bn_u... |
class Ed448PrivateKey(metaclass=abc.ABCMeta):
def generate(cls) -> Ed448PrivateKey:
from cryptography.hazmat.backends.openssl.backend import backend
if (not backend.ed448_supported()):
raise UnsupportedAlgorithm('ed448 is not supported by this version of OpenSSL.', _Reasons.UNSUPPORTED_P... |
def get_val_dataloader(data_pth, vocab, max_seq_length, val_batch_size, mode='eval', beam_size=0):
data = get_data(data_pth)
(features, vocab) = convert_example_to_feature(data, max_seq_length, vocab, sum_mode=args.sum_mode, context_mode=args.context_mode, get_vocab=False)
if (mode == 'eval'):
val_d... |
def run_eval(args):
print(hparams_debug_string())
synth = Synthesizer()
synth.load(args.checkpoint)
base_path = get_output_base_path(args.checkpoint)
wav = load_wav(args.reference_audio)
mel = melspectrogram(wav).transpose()
for (i, text) in enumerate(tests):
path = ('%s-%d.wav' % (b... |
class GridProportion(Enum):
One = 'one'
Two = 'two'
Three = 'three'
Four = 'four'
Five = 'five'
Six = 'six'
Seven = 'seven'
Eight = 'eight'
Nine = 'nine'
Ten = 'ten'
Eleven = 'eleven'
Twelve = 'twelve'
Thirteen = 'thirteen'
Fourteen = 'fourteen'
Fifteen = 'fif... |
_config
def test_floats_kept_above(xmanager):
conn = xcbq.Connection(xmanager.display)
def _wnd(name):
return xmanager.c.window[{w['name']: w['id'] for w in xmanager.c.windows()}[name]]
def _clients():
root = conn.default_screen.root.wid
q = conn.conn.core.QueryTree(root).reply()
... |
_pypy
def test_instance_method_by_subclass_spy(mocker: MockerFixture) -> None:
class Base():
def bar(self, arg):
return (arg * 2)
class Foo(Base):
pass
spy = mocker.spy(Foo, 'bar')
foo = Foo()
other = Foo()
assert (foo.bar(arg=10) == 20)
assert (other.bar(arg=10) ... |
def test_struct_prop_arity():
m = run_mod('\n #lang pycket\n (require racket/private/kw)\n\n (struct evens (proc)\n #:property prop:procedure (struct-field-index proc)\n #:property prop:arity-string\n (lambda (p)\n "an even number of arguments"))\n (define pairs\n (evens\n (... |
def test_events_for_expired_pairs():
setup = factories.make_transfers_pair(2)
pair = setup.transfers_pair[0]
first_unsafe_block = BlockNumber((pair.payer_transfer.lock.expiration - UNIT_REVEAL_TIMEOUT))
mediator.events_for_expired_pairs(setup.channel_map, setup.transfers_pair, None, first_unsafe_block)
... |
.parametrize('algorithm', [pytest.param('RS256'), pytest.param('RS384')])
def test_decode_jwt_invalid_algorithm(private_key_pem, public_key, algorithm):
token = jwt.encode(_token_data('aud', 'subject', 'someissuer'), private_key_pem, algorithm)
with pytest.raises(InvalidAlgorithmError) as ite:
max_exp =... |
class TemplatePlugin(object):
name = 'template'
api = 2
def apply(self, callback, route):
conf = route.config.get('template')
if (isinstance(conf, (tuple, list)) and (len(conf) == 2)):
return view(conf[0], **conf[1])(callback)
elif isinstance(conf, str):
retur... |
.parametrize('username,password', users)
def test_delete(db, client, username, password):
client.login(username=username, password=password)
instances = QuestionSet.objects.all()
for instance in instances:
url = reverse(urlnames['detail'], args=[instance.pk])
response = client.delete(url)
... |
def identifiers_info(code):
try:
tree = ast.parse(code)
except Exception:
return {}
if (not isinstance(tree, ast.Module)):
return {}
identifier2doc = {}
for node in tree.body:
if isinstance(node, ast.Assign):
for name in node.targets:
if ha... |
def _build_context(img: str, workspace: str) -> IO[bytes]:
f = tempfile.NamedTemporaryFile(prefix='torchx-context', suffix='.tar')
with tarfile.open(fileobj=f, mode='w') as tf:
_copy_to_tarfile(workspace, tf)
if (TORCHX_DOCKERFILE not in tf.getnames()):
info = tarfile.TarInfo(TORCHX_... |
class TestColor():
def test_color_jitter():
imgs = list(np.random.randint(0, 255, size=(3, 112, 112, 3), dtype=np.uint8))
results = dict(imgs=imgs)
eig_val = np.array([55.46, 4.794, 1.148], dtype=np.float32)
eig_vec = np.array([[(- 0.5675), 0.7192, 0.4009], [(- 0.5808), (- 0.0045), (... |
class TestBasicFeatures(TempDirectoryTestCase, OverridePreferencesTestCase):
override_preferences = {'project_manager.sublime-settings': {}}
project_name = None
def setUpClass(cls):
(yield from super().setUpClass())
cls.project_name = os.path.basename(cls._temp_dir)
cls.manager = Man... |
class SawyerDrawerOpenEnv(SawyerXYZEnv):
def __init__(self):
hand_low = ((- 0.5), 0.4, 0.05)
hand_high = (0.5, 1, 0.5)
obj_low = ((- 0.1), 0.9, 0.04)
obj_high = (0.1, 0.9, 0.04)
goal_low = ((- 0.1), 0.5499, 0.04)
goal_high = (0.1, 0.5501, 0.04)
super().__init_... |
def test_parse_args_unset(capsys):
with pytest.raises(SystemExit) as e:
args = client_parameters.parse_args(('unset',))
assert (e.type == SystemExit)
assert (e.value.code == 2)
captured = capsys.readouterr()
assert ('arguments are required: --hostname, --parameter' in captured.err)
with ... |
def get_volatility(qf_series: QFSeries, frequency: Frequency=None, annualise: bool=True) -> float:
returns_tms = qf_series.to_log_returns()
assert (len(returns_tms) >= 2), 'minimal num_of_rows to receive a real result is 2'
assert ((not annualise) or (frequency is not None))
volatility = returns_tms.std... |
class DarcsCommands():
def __init__(self, root):
self.root = root
self.normal_actions = FileSystemCommands()
def create_file(self, path):
self.normal_actions.create_file(path)
self._do(['add', path])
def create_folder(self, path):
self.normal_actions.create_folder(pat... |
('pypyr.steps.filewritejson.Path')
def test_filewritejson_pass_no_payload(mock_path):
context = Context({'k1': 'v1', 'fileWriteJson': {'path': '/arb/blah'}})
with io.StringIO() as out_text:
with patch('pypyr.steps.filewritejson.open', mock_open()) as mock_output:
mock_output.return_value.wri... |
class ElasticConfigurator(BaseConfigurator):
DISTANCE_MAPPING = {Distance.L2: 'l2_norm', Distance.COSINE: 'cosine', Distance.DOT: 'dot_product'}
INDEX_TYPE_MAPPING = {'int': 'long', 'geo': 'geo_point'}
def __init__(self, host, collection_params: dict, connection_params: dict):
super().__init__(host,... |
class TestCopyPlane(EndianTest):
def setUp(self):
self.req_args_0 = {'bit_plane': , 'dst_drawable': , 'dst_x': (- 25480), 'dst_y': (- 26229), 'gc': , 'height': 60447, 'src_drawable': , 'src_x': (- 4634), 'src_y': (- 17345), 'width': 53771}
self.req_bin_0 = b'?\x00\x00\x080\xf8 \x8do\xa4)H\x04\xf5\xe... |
class DataTrainingArguments():
dataset_name: Optional[str] = field(default='segments/sidewalk-semantic', metadata={'help': 'Name of a dataset from the hub (could be your own, possibly private dataset hosted on the hub).'})
dataset_config_name: Optional[str] = field(default=None, metadata={'help': 'The configura... |
def get_all_var_mappings(a):
if (is_ast(a) and (not is_literal(a))):
if (type(a) == name_e):
return {a.id: None}
if is_comprehension(a):
vs = get_all_var_mappings(a.expr)
for g in a.generators:
gvs = vs.update(get_all_var_mappings(g))
... |
def _add_se(cv_results, copy=False):
n_folds = None
if copy:
cv_results = deepcopy(cv_results)
scores_with_std = [k for k in cv_results.keys() if (k[0:4] == 'std_')]
for k in scores_with_std:
s = k.split('_')
s[0] = 'se'
se_name = '_'.join(s)
if (se_name not in cv... |
def test_includes() -> None:
poetry = Factory().create_poetry(project('with-include'))
builder = SdistBuilder(poetry)
builder.build()
sdist = (((fixtures_dir / 'with-include') / 'dist') / 'with_include-1.2.3.tar.gz')
assert sdist.exists()
with tarfile.open(str(sdist), 'r') as tar:
assert... |
def video_loader(video_dir_path, frame_indices, image_loader):
video = []
for i in frame_indices:
image_path = os.path.join(video_dir_path, 'image-{:04d}.png'.format(i))
if os.path.exists(image_path):
video.append(image_loader(image_path))
else:
print(image_path)
... |
def test_setup_proxies_all_addresses_are_given():
chain_id = ChainID(5)
config = RaidenConfig(chain_id=chain_id, environment_type=Environment.DEVELOPMENT)
contracts = load_deployed_contracts_data(config, chain_id)
proxy_manager = MockProxyManager(node_address=make_address())
deployed_addresses = loa... |
def main():
cache = get_cache()
failed_uris = get_failed()
parse_failed_uris = get_parse_failed()
uris = cache.keys()
peak_missing = [uri for uri in uris if (LISTENERPEAK not in cache[uri])]
peak_missing = (set(peak_missing) - failed_uris)
peak_missing = {get_root(uri) for uri in peak_missin... |
def format_type_distinctly(*types: Type, options: Options, bare: bool=False) -> tuple[(str, ...)]:
overlapping = find_type_overlaps(*types)
for verbosity in range(2):
strs = [format_type_inner(type, verbosity=verbosity, options=options, fullnames=overlapping) for type in types]
if (len(set(strs)... |
class TestAllocNamedColor(EndianTest):
def setUp(self):
self.req_args_0 = {'cmap': , 'name': 'octarin'}
self.req_bin_0 = b'U\x00\x05\x00\x19\x00X\x1f\x07\x00\x00\x00octarin\x00'
self.reply_args_0 = {'exact_blue': 50619, 'exact_green': 55944, 'exact_red': 40316, 'pixel': , 'screen_blue': 2741... |
class TFCI(BinaryCodec):
fmt = '.tfci'
_models = ['bmshj2018-factorized-mse', 'bmshj2018-hyperprior-mse', 'mbt2018-mean-mse']
def description(self):
return 'TFCI'
def name(self):
return f'{self.model}'
def setup_args(cls, parser):
super().setup_args(parser)
parser.add... |
class Snowflake(IDConverter):
async def convert(self, ctx: Context, arg: str) -> int:
error = f'Invalid snowflake {arg!r}'
if (not self._get_id_match(arg)):
raise BadArgument(error)
snowflake = int(arg)
try:
time = snowflake_time(snowflake)
except (Ove... |
def process_scale(args):
sampler = BoundarySampler()
reader = FrameDataReader(args.seq_folder, check_image=True)
batch_end = reader.cvt_end(args.end)
outdir = paths['PROCESSED_PATH']
smpl_name = args.smpl_name
obj_name = args.obj_name
landmark = BodyLandmarks(assets_root=paths['SMPL_ASSETS_R... |
def create_dataset(h5_path='test.h5'):
X = np.random.randn(200, 10).astype('float32')
y = np.random.randint(0, 2, size=(200, 1))
f = h5py.File(h5_path, 'w')
X_dset = f.create_dataset('my_data', (200, 10), dtype='f')
X_dset[:] = X
y_dset = f.create_dataset('my_labels', (200, 1), dtype='i')
y_... |
def train_config(parser):
base_dir = os.getenv('PT_OUTPUT_DIR', '../model_data/san/')
parser.add_argument('--cuda', type=bool, default=torch.cuda.is_available(), help='Use GPU acceleration.')
parser.add_argument('--multi_gpu', action='store_true', help='multi gpu training.')
parser.add_argument('--log_p... |
_required
def org_create(request):
if (settings.RESTRICT_ORG_CREATION and (not request.user.is_superuser)):
messages.error(request, _('Only super users can create an organization.'))
return redirect('user_dashboard')
user = get_session_user(request)
ctx = {'user': user}
if (request.metho... |
class PropertyGroup(bpy.types.PropertyGroup):
start_frame: bpy.props.IntProperty(name='Start Frame', description='Start Frame of the Exemplar Moition.', default=1)
end_frame: bpy.props.IntProperty(name='End Frame', description='End Frame of the Exemplar Moition.', default=(- 1))
up_axis: bpy.props.EnumPrope... |
class OneAndOnlyOne(_BaseChildElement):
def __init__(self, nsptagname: str):
super(OneAndOnlyOne, self).__init__(nsptagname, ())
def populate_class_members(self, element_cls: MetaOxmlElement, prop_name: str) -> None:
super(OneAndOnlyOne, self).populate_class_members(element_cls, prop_name)
... |
def _sync_tensor_states(metric_name: str, state_name: str, my_state_data: torch.Tensor, gathered_states: List[Dict[(str, Dict[(str, Any)])]], process_group: Optional[dist.ProcessGroup], rank: Optional[int]) -> None:
gathered_state_data = send_tensors(my_state_data, group=process_group, rank=rank)
if (gathered_s... |
def display_comparison(Dict, col=5):
row = 0
end = False
while (not end):
for (key, value_list) in Dict.items():
print(('%10s:' % key), end='')
for i in range(col):
idx = ((row * col) + i)
if isinstance(value_list[idx], float):
... |
class AdditionsPane(TogglePanel):
def __init__(self, parent, mainFrame):
TogglePanel.__init__(self, parent, force_layout=1)
self.mainFrame = mainFrame
self.SetLabel(_t('Additions'))
pane = self.GetContentPanel()
baseSizer = wx.BoxSizer(wx.HORIZONTAL)
pane.SetSizer(bas... |
class PageIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
title = indexes.CharField(model_attr='title')
description = indexes.CharField(model_attr='description')
path = indexes.CharField(model_attr='path')
include_template = indexes.CharField... |
class Callback():
def __init__(self):
pass
def set_params(self, params):
self.params = params
def set_trainer(self, model):
self.trainer = model
def on_epoch_begin(self, epoch, logs=None):
pass
def on_epoch_end(self, epoch, logs=None):
pass
def on_batch_be... |
class HspecLexer(HaskellLexer):
name = 'Hspec'
aliases = ['hspec']
filenames = ['*Spec.hs']
mimetypes = []
version_added = '2.4'
tokens = {'root': [('(it)(\\s*)("[^"]*")', bygroups(Text, Whitespace, String.Doc)), ('(describe)(\\s*)("[^"]*")', bygroups(Text, Whitespace, String.Doc)), ('(context)(... |
def cached_path(url_or_filename, cache_dir=None, force_download=False, proxies=None, resume_download=False, user_agent=None, extract_compressed_file=False, force_extract=False, local_files_only=False) -> Optional[str]:
if (cache_dir is None):
cache_dir = TRANSFORMERS_CACHE
if isinstance(url_or_filename,... |
def save_dataset(path, data, format, dicts, src_type):
if (format in ['raw', 'bin']):
print((('Saving data to ' + os.path.join(path, 'data.pt')) + '...'))
save_data = {'type': opt.src_type, 'data': data}
torch.save(save_data, os.path.join(path, 'data.pt'))
print('Done')
elif (for... |
def retry_with_exponential_backoff(func, initial_delay: float=1, exponential_base: float=2, jitter: bool=True, max_retries: int=10, errors: tuple=(TimeoutError, nemollm.exceptions.ApiException)):
def wrapper(*args, **kwargs):
num_retries = 0
delay = initial_delay
while True:
try:... |
def test_kuccsd_supercell_vs_kpts_high_cost():
cell = gto.M(unit='B', a=[[0.0, 3., 3.], [3., 0.0, 3.], [3., 3., 0.0]], mesh=([13] * 3), atom='He 0 0 0\n He 1. 1. 1.', basis=[[0, (1.0, 1.0)], [0, (0.5, 1.0)]], verbose=0)
nmp = [3, 3, 1]
supcell = super_cell(cell, nmp)
gmf = scf.UHF(supce... |
def concat_files(split, src, tgt, extracted_folders, split_urls, path_patterns, to_folder, debug=False):
for lang in [src, tgt]:
to_file = f'{to_folder}/{split}.{src}-{tgt}.{lang}'
(s_src, s_tgt, s_lang) = (src.split('_')[0], tgt.split('_')[0], lang.split('_')[0])
files = []
for url ... |
def test_strict_mode_cmdline(testdir):
testdir.makepyfile(dedent(" import asyncio\n import pytest\n\n pytest_plugins = 'pytest_asyncio'\n\n .asyncio\n async def test_a():\n await asyncio.sleep(0)\n "))
result = testdir.runpytest('--asyncio-mode=strict')
r... |
class Model(nn.Module):
def __init__(self, args):
super(Model, self).__init__()
self.args = args
self.num_classes = args.num_classes
self.conv1_1 = nn.Conv2d(3, 64, kernel_size=3, padding=1)
self.relu1_1 = nn.ReLU(inplace=True)
self.conv1_2 = nn.Conv2d(64, 64, kernel_... |
class RHEL7_TestCase(F18_TestCase):
def runTest(self):
self.assert_parse('timezone --utc')
self.assert_parse('timezone Europe/Sofia')
self.assert_parse('timezone --isUtc')
self.assert_parse('timezone --ntpservers=ntp.cesnet.cz')
self.assert_parse('timezone --ntpservers=ntp.ce... |
def calculate_sentence_transformer_embedding(examples, embedding_model, mean_normal=False):
text_to_encode = [e['history'] for e in examples]
num = len(text_to_encode)
emb_model = INSTRUCTOR(embedding_model)
embeddings = []
bar = tqdm(range(0, num, 20), desc='calculate embeddings')
for i in rang... |
_config
def test_keypress(manager):
manager.test_window('one')
manager.test_window('two')
with pytest.raises(CommandError):
manager.c.simulate_keypress(['unknown'], 'j')
assert (manager.c.get_groups()['a']['focus'] == 'two')
manager.c.simulate_keypress(['control'], 'j')
assert (manager.c... |
def purge_processor(caller):
try:
del caller.ndb.batch_stack
del caller.ndb.batch_stackptr
del caller.ndb.batch_pythonpath
del caller.ndb.batch_batchmode
except Exception:
pass
if caller.ndb.batch_cmdset_backup:
caller.cmdset.cmdset_stack = caller.ndb.batch_cm... |
class _HashableValue(TypedValue):
def can_assign(self, other: Value, ctx: CanAssignContext) -> CanAssign:
if isinstance(other, SubclassValue):
return {}
elif (isinstance(other, TypedValue) and (other.typ is type)):
return {}
elif isinstance(other, KnownValue):
... |
class Effect6705(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
lvl = src.level
fit.modules.filteredItemBoost((lambda mod: (mod.item.group.name == 'Rig Shield')), 'drawback', (src.getModifiedItemAttr('rigDrawbackBonus') * lvl), **kwargs) |
class Priors(BaseModel):
Proper_k: float = Field(6.0, description='The initial prior for the proper torsion k values.')
def format_priors(self) -> Dict[(str, Any)]:
data = {}
for (prior, value) in self.__dict__.items():
prior = prior.split('_')
prior = '/'.join(prior)
... |
class CLIPVisionConfig(PretrainedConfig):
model_type = 'clip_vision_model'
def __init__(self, hidden_size=768, intermediate_size=3072, num_hidden_layers=12, num_attention_heads=12, num_channels=3, image_size=224, patch_size=32, hidden_act='quick_gelu', layer_norm_eps=1e-05, dropout=0.0, attention_dropout=0.0, i... |
def generate_random_paths(sample_len: int, sample_size: int, mean: float, std: float, leverage: float=1.0):
mean = (mean * leverage)
std = (std * leverage)
time = np.arange(1, (1 + sample_len))
returns_vector = np.random.normal(loc=mean, scale=std, size=((sample_len * sample_size), 1))
returns = np.... |
def test_child_scope():
TestKey = NewType('TestKey', str)
TestKey2 = NewType('TestKey2', str)
def parent_module(binder):
binder.bind(TestKey, to='in parent', scope=singleton)
def first_child_module(binder):
binder.bind(TestKey2, to='in first child', scope=singleton)
def second_child_... |
class TestGeostationaryTools():
def test_get_full_geostationary_bbox(self, truncated_geos_area):
nb_points = 20
(x, y) = get_full_geostationary_bounding_box_in_proj_coords(truncated_geos_area, nb_points)
assert (len(x) == nb_points)
assert (len(y) == nb_points)
assert (x[0] !... |
def assert_ne(expected, actual, message=None, tolerance=None, extra=None):
if (tolerance is None):
assert (expected != actual), _assert_fail_message(message, expected, actual, '==', extra)
else:
assert isinstance(tolerance, _number_types), ('tolerance parameter to assert_eq must be a number: %a'... |
def _create_dataloaders(config, dataset_class, tf1, tf2, partitions, target_transform=None, shuffle=False):
train_imgs_list = []
for train_partition in partitions:
if ('STL10' == config.dataset):
train_imgs_curr = dataset_class(root=config.dataset_root, transform=tf1, split=train_partition, ... |
def make_lazy_wikioscar_dataset(tokenizer, probs: Sequence[float]=(0.23, 0.77), shuffle_buffer_size: int=(10 ** 4), shuffle_seed: Optional[int]=None, preprocessing_batch_size: int=256):
wiki = load_dataset('lhoestq/wikipedia_bn', split='train')
oscar = load_dataset('oscar', 'unshuffled_deduplicated_bn', split='... |
class Effect6982(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
fit.modules.filteredChargeBoost((lambda mod: mod.item.requiresSkill('Torpedoes')), 'explosiveDamage', src.getModifiedItemAttr('shipBonusTitanG2'), skill='Gallente Titan', **kwargs)
fit.modul... |
def is_neg(var):
var_node = var.owner
if (not var_node):
return None
if (var_node.op == neg):
return var_node.inputs[0]
if ((var_node.op == mul) and (len(var_node.inputs) >= 2)):
for (idx, mul_input) in enumerate(var_node.inputs):
try:
constant = get_u... |
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