code stringlengths 281 23.7M |
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def resize_pos_embed(state_dict, model, interpolation: str='bicubic', antialias: bool=True):
old_pos_embed = state_dict.get('visual.positional_embedding', None)
if ((old_pos_embed is None) or (not hasattr(model.visual, 'grid_size'))):
return
grid_size = to_2tuple(model.visual.grid_size)
extra_to... |
def test_unlocks_dependencies_if_necessary_to_ensure_that_a_new_dependency_is_satisfied(root: ProjectPackage, repo: Repository, pool: RepositoryPool) -> None:
root.add_dependency(Factory.create_dependency('foo', '*'))
root.add_dependency(Factory.create_dependency('newdep', '2.0.0'))
add_to_repo(repo, 'foo',... |
class CenteredLayout(Layout):
def customise_widget(self):
self.container = self.widget.add_child(Div(self.view))
self.container.use_layout(Container(fluid=False))
self.centre = self.container.add_child(Div(self.view))
column_layout = ColumnLayout(ColumnOptions('left', ResponsiveSize(... |
_bpe('byte_bpe', dataclass=ByteBpeConfig)
class ByteBPE(object):
def __init__(self, cfg):
vocab = file_utils.cached_path(cfg.sentencepiece_model_path)
try:
import sentencepiece as spm
self.sp = spm.SentencePieceProcessor()
self.sp.Load(vocab)
except Import... |
def main():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-g', '--gpu', type=int, required=True, help='gpu id')
parser.add_argument('--resume', help='checkpoint path')
parser.add_argument('--max-iteration', type=int, default=100000, help='m... |
class aux_classifier(nn.Module):
def __init__(self, block, inplanes, planes, groups, base_width, num_classes):
super(aux_classifier, self).__init__()
downsample3 = nn.Sequential(conv1x1(inplanes, (planes * block.expansion), stride=2), nn.BatchNorm2d((planes * block.expansion)))
self.module3 ... |
def get_parameter_values():
return {'chemistry': 'lithium_ion', 'Ratio of lithium moles to SEI moles': 2.0, 'Inner SEI reaction proportion': 0.5, 'Inner SEI partial molar volume [m3.mol-1]': 9.585e-05, 'Outer SEI partial molar volume [m3.mol-1]': 9.585e-05, 'SEI reaction exchange current density [A.m-2]': 1.5e-07, ... |
_uncanonicalize
_rewriter([Reshape])
def local_reshape_dimshuffle(fgraph, node):
if isinstance(node.op, Reshape):
input_ = node.inputs[0]
if (input_.owner and isinstance(input_.owner.op, DimShuffle)):
new_order = input_.owner.op.new_order
offset = 0
for dim in new... |
_module()
class RandomSampleFrames():
def __call__(self, results):
assert (results['total_frames'] > 0)
results['frame_inds'] = np.array([0, (results['total_frames'] - 1)])
if (results['total_frames'] > 2):
results['frame_inds'] = np.concatenate([results['frame_inds'], np.random.... |
def test_project_issue_milestone_events(project, resp_project_issue_milestone_events):
issue = project.issues.list()[0]
milestone_events = issue.resourcemilestoneevents.list()
assert isinstance(milestone_events, list)
milestone_event = milestone_events[0]
assert isinstance(milestone_event, ProjectIs... |
def test_perform_sequence():
def code_under_test():
r = (yield Effect(MyIntent('a')))
r2 = (yield Effect(OtherIntent('b')))
return (r, r2)
seq = [(MyIntent('a'), (lambda i: 'result1')), (OtherIntent('b'), (lambda i: 'result2'))]
eff = code_under_test()
assert (perform_sequence(se... |
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--dataset-folder', dest='cityscapesPath', help="path to the Cityscapes dataset 'gtFine' folder", default=None, type=str)
parser.add_argument('--output-folder', dest='outputFolder', help='path to the output folder.', default=None, type=str)
... |
def get_locale() -> Optional[Locale]:
ctx = _get_current_context()
if (ctx is None):
return None
locale = getattr(ctx, 'babel_locale', None)
if (locale is None):
babel = get_babel()
if (babel.locale_selector is None):
locale = babel.instance.default_locale
els... |
def test_interconnect_exceptions():
P = ct.tf(1, [1, 0], input='u', output='y')
C = ct.tf(10, [1, 1], input='e', output='u')
sumblk = ct.summing_junction(inputs=['r', '-y'], output='e')
T = ct.interconnect((P, C, sumblk), input='r', output='y')
assert ((T.ninputs, T.noutputs, T.nstates) == (1, 1, 2)... |
.parametrize('changelog_template', (CHANGELOG_TEMPLATE,))
.parametrize('repo, commit_parser, expected_changelog', [(lazy_fixture('repo_with_single_branch_and_prereleases_angular_commits'), lazy_fixture('default_angular_parser'), EXPECTED_CHANGELOG_CONTENT_ANGULAR), (lazy_fixture('repo_with_single_branch_and_prereleases... |
def install_urllib2_ca_file():
try:
import ssl
except ImportError:
return
base = request_module.HTTPSHandler
class MyHandler(base):
def __init__(self, debuglevel=0, context=None):
ca_file = get_ca_file()
if ((context is None) and (ca_file is not None)):
... |
_start_docstrings('The bare EfficientNet model outputting raw features without any specific head on top.', EFFICIENTNET_START_DOCSTRING)
class EfficientNetModel(EfficientNetPreTrainedModel):
def __init__(self, config: EfficientNetConfig):
super().__init__(config)
self.config = config
self.em... |
def get_cached_bind_group_layout(device, *args):
key = ('bind_group_layout', hash_from_value(args))
result = LAYOUT_CACHE.get(key)
if (result is None):
(entries,) = args
result = device.create_bind_group_layout(entries=entries)
LAYOUT_CACHE.set(key, result)
return result |
class TiddlyWiki5Lexer(RegexLexer):
name = 'tiddler'
url = '
aliases = ['tid']
filenames = ['*.tid']
mimetypes = ['text/vnd.tiddlywiki']
version_added = '2.7'
flags = re.MULTILINE
def _handle_codeblock(self, match):
from pygments.lexers import get_lexer_by_name
(yield (ma... |
def test_dumping_subclass(retort, debug_trail):
class Parent():
foo: int
class Child(Parent):
bar: int
dumper_ = Retort(debug_trail=debug_trail).get_dumper(Union[(Parent, str)])
assert (dumper_(Parent(foo=1)) == {'foo': 1})
assert (dumper_(Child(foo=1, bar=2)) == {'foo': 1})
asse... |
def strip_input_shape_fields(shape: InputShape, skipped_fields: Collection[str]) -> InputShape:
skipped_required_fields = [field.id for field in shape.fields if (field.is_required and (field.id in skipped_fields))]
if skipped_required_fields:
raise ValueError(f'Required fields {skipped_required_fields} ... |
class NullXcelRTL(Component):
def construct(s, nbits=32):
dtype = mk_bits(32)
(xreq_class, xresp_class) = mk_xcel_msg(5, nbits)
s.xcel = XcelMinionIfcRTL(xreq_class, xresp_class)
s.xcelreq_q = NormalQueueRTL(xreq_class, 2)
s.xcelreq_q.enq //= s.xcel.req
s.xr0 = RegEn(... |
class PywrSchematic():
def __init__(self, model, width=500, height=400, labels=False, attributes=False, css=None):
if isinstance(model, Model):
self.graph = pywr_model_to_d3_json(model, attributes)
self.json = None
else:
self.graph = pywr_json_to_d3_json(model, at... |
(connect={'type': 'list', 'limits': ['all', 'pairs', 'finite', 'array']})
def update(antialias=pg.getConfigOption('antialias'), connect='all', skipFiniteCheck=False):
global ptr
if (next(iterations_counter) > args.iterations):
timer.stop()
app.quit()
return None
if (connect == 'array... |
def test_reconfigure_logging_on_change(capsys):
log = logging.getLogger('pyphi.config')
with config.override(LOG_STDOUT_LEVEL='WARNING'):
log.warning('Just a warning, folks.')
(out, err) = capsys.readouterr()
assert ('Just a warning, folks.' in err)
with config.override(LOG_STDOUT_LEVEL='ERR... |
('/sign-up', methods=['GET', 'POST'])
def sign_up():
form = SignUpForm()
user = User()
if form.validate_on_submit():
user_name = request.form.get('user_name')
user_email = request.form.get('user_email')
password = request.form.get('password')
password = generate_password_hash... |
('PyQt6.QtWidgets.QGraphicsView.mousePressEvent')
def test_mouse_press_unhandled(mouse_event_mock, view):
event = MagicMock()
event.button.return_value = Qt.MouseButton.LeftButton
event.modifiers.return_value = None
view.mousePressEvent(event)
assert (view.pan_active is False)
assert (view.zoom_... |
.parametrize('config', [btrack.datasets.cell_config(), btrack.datasets.particle_config()])
def test_config_to_widgets_round_trip(track_widget, config):
expected_config = btrack.config.load_config(config).json()
unscaled_config = btrack.napari.config.UnscaledTrackerConfig(config)
btrack.napari.sync.update_wi... |
def sit_heuristic(agent_id, char_index, unsatisfied, env_graph, simulator, object_target):
observations = simulator.get_observations(env_graph, char_index=char_index)
target_id = int(object_target.split('_')[(- 1)])
observed_ids = [node['id'] for node in observations['nodes']]
agent_close = [edge for ed... |
class Script_Object_TestCase(ParserTest):
def runTest(self):
self.get_parser()
body = 'import sys\nsys.exit(1)\n'
obj = Script(body, type=KS_SCRIPT_PRE, interp='/usr/bin/python', logfile='/tmp/log', errorOnFail=True)
self.assertEqual(obj.type, KS_SCRIPT_PRE)
self.assertEqual(... |
def kvector(a: float, t: float=0, p: float=np.pi, fraction: float=0.2, points: int=50, vin: np.ndarray=None) -> np.ndarray:
s3 = np.sqrt(3)
Xkmax = ((2 * np.pi) / a)
Lkmax = ((s3 * np.pi) / a)
X = np.array([[1, 0, 0], [(- 1), 0, 0], [0, 1, 0], [0, (- 1), 0], [0, 0, 1], [0, 0, (- 1)]])
L = ((1 / s3) ... |
_grad()
def accuracy(output, target, topk=(1,)):
maxk = max(topk)
num_items = output.size(0)
(_, pred) = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target)
res = []
for k in topk:
correct_k = correct[:k].view((- 1)).float().sum(0)
res.append(correct_k.... |
def output_db(prefix, db):
res = ''
for (comp, group) in db.items():
if (len(group) > 2):
res = (res + ('%s%s: %s\n' % (prefix, comp, output_escape(group[2]))))
res = (res + output_db(((prefix + comp) + '.'), group[0]))
res = (res + output_db(((prefix + comp) + '*'), group[1]... |
def main():
from optparse import OptionParser
parser = OptionParser(usage='\n %prog [binfile|-]\n %prog -r hexfile\n %prog --test [logfile]', version=__version__)
parser.add_option('-r', '--restore', action='store_true', help='restore binary from hex dump')
parser.add_option('--test', action='store_t... |
def test_print_available_captions(capsys):
caption1 = Caption({'url': 'url1', 'name': {'simpleText': 'name1'}, 'languageCode': 'en', 'vssId': '.en'})
caption2 = Caption({'url': 'url2', 'name': {'simpleText': 'name2'}, 'languageCode': 'fr', 'vssId': '.fr'})
query = CaptionQuery([caption1, caption2])
cli.... |
_arg_scope
def pool(inputs, kernel_size, pooling_type, padding='VALID', data_format=None, dilation_rate=1, stride=1, outputs_collections=None, scope=None):
with ops.name_scope(scope, ('%s_pool' % pooling_type.lower()), [inputs]) as sc:
inputs = ops.convert_to_tensor(inputs)
input_rank = inputs.get_s... |
class AutoapiSummary(Autosummary):
def get_items(self, names):
items = []
env = self.state.document.settings.env
all_objects = env.autoapi_all_objects
max_item_chars = 60
for name in names:
obj = all_objects[name]
if isinstance(obj, PythonFunction):
... |
def main(data_dir, client, bc, config):
benchmark(read_tables, data_dir, bc, dask_profile=config['dask_profile'])
query = f'''
SELECT DISTINCT wcs_user_sk
FROM
(
SELECT DISTINCT
wcs_user_sk,
wcs_click_date_sk
FROM web_clickstreams, ... |
class InceptionB(nn.Module):
def __init__(self, in_channels, kernel_size=3, stride=2, padding=0):
self.stride = stride
super(InceptionB, self).__init__()
self.branch3x3 = BasicConv2d(in_channels, 384, kernel_size=kernel_size, stride=stride)
self.branch3x3dbl_1 = BasicConv2d(in_channe... |
def check_dev_info_removed(prog_file=None, map_file=None):
bpftool_prog_list(expected=0)
(ret, err) = bpftool(('prog show pin %s' % prog_file), fail=False)
fail((ret == 0), 'Showing prog with removed device did not fail')
fail((err['error'].find('No such device') == (- 1)), ('Showing prog with removed d... |
def test_recursion_error_inferring_slice() -> None:
node = extract_node('\n class MyClass:\n def __init__(self):\n self._slice = slice(0, 10)\n\n def incr(self):\n self._slice = slice(0, self._slice.stop + 1)\n\n def test(self):\n self._slice #\n ')
in... |
class BertSoftmaxForSequenceLabeling(BertPreTrainedModel):
def __init__(self, config):
super(BertSoftmaxForSequenceLabeling, self).__init__(config)
self.num_labels = config.num_labels
self.bert = BertModel(config)
if self.config.use_freezing:
self.bert = freezer.freeze_lm... |
def _process_dt_keyword(keywords, defaults={}, static=False):
if (static and ('dt' not in keywords) and ('dt' not in defaults)):
dt = None
elif ('dt' in keywords):
dt = keywords.pop('dt')
elif ('dt' in defaults):
dt = defaults.pop('dt')
else:
dt = config.defaults['control... |
class LinuxSocketSS(Socket):
def _iter_sockets(self, listening):
cmd = '%s --numeric'
if listening:
cmd += ' --listening'
else:
cmd += ' --all'
if (self.protocol == 'tcp'):
cmd += ' --tcp'
elif (self.protocol == 'udp'):
cmd += '... |
class ELMoTuner(Tuner):
def __init__(self, train_corpus_fname, test_corpus_fname, vocab_fname, options_fname, pretrain_model_fname, model_save_path, max_characters_per_token=30, batch_size=32, num_labels=2):
super().__init__(train_corpus_fname=train_corpus_fname, tokenized_train_corpus_fname=(train_corpus_f... |
def test_retry_init_defaults_max():
rd = RetryDecorator({'max': 3})
assert (rd.backoff is None)
assert (rd.backoff_args is None)
assert (rd.jrc == 0)
assert (rd.max == 3)
assert (rd.sleep_max is None)
assert (rd.sleep == 0)
assert (rd.stop_on is None)
assert (rd.retry_on is None)
... |
class Win32CanvasConfigARB(CanvasConfig):
attribute_ids = {'double_buffer': wglext_arb.WGL_DOUBLE_BUFFER_ARB, 'stereo': wglext_arb.WGL_STEREO_ARB, 'buffer_size': wglext_arb.WGL_COLOR_BITS_ARB, 'aux_buffers': wglext_arb.WGL_AUX_BUFFERS_ARB, 'sample_buffers': wglext_arb.WGL_SAMPLE_BUFFERS_ARB, 'samples': wglext_arb.W... |
_fixtures(ReahlSystemFixture, WebFixture, RemoteMethodFixture, RegenerateMethodResultScenarios)
def test_regenerating_method_results(reahl_system_fixture, web_fixture, remote_method_fixture, regenerate_method_result_scenarios):
wsgi_app = remote_method_fixture.new_wsgi_app(remote_method=regenerate_method_result_sce... |
class TestNetscalerSNMPCollector(CollectorTestCase):
def setUp(self, allowed_names=None):
if (not allowed_names):
allowed_names = []
config = get_collector_config('NetscalerSNMPCollector', {'allowed_names': allowed_names, 'interval': 1})
self.collector = NetscalerSNMPCollector(co... |
def list_short(venv_dirs: Collection[Path]) -> VenvProblems:
all_venv_problems = VenvProblems()
for venv_dir in venv_dirs:
(venv_metadata, venv_problems, warning_str) = get_venv_metadata_summary(venv_dir)
if venv_problems.any_():
logger.warning(warning_str)
else:
... |
def resnext101_32x8d(num_classes, loss='softmax', pretrained=True, **kwargs):
model = ResNet(num_classes=num_classes, loss=loss, block=Bottleneck, layers=[3, 4, 23, 3], last_stride=2, fc_dims=None, dropout_p=None, groups=32, width_per_group=8, **kwargs)
if pretrained:
init_pretrained_weights(model, mode... |
class R2():
def __init__(self, ql: 'Qiling', baseaddr=((1 << 64) - 1), loadaddr=0):
super().__init__()
self.ql = ql
self.baseaddr = baseaddr
self.loadaddr = loadaddr
self.analyzed = False
self._r2c = libr.r_core.r_core_new()
if ql.code:
self._setup... |
class TestCGA2D(_TestBase):
(layout, blades, stuff) = clifford.conformalize(clifford.Cl(2)[0])
e1 = blades['e1']
e2 = blades['e2']
(params=[layout.scalar, e1, (e1 ^ e2)])
def direction(self, request):
return request.param
(params=[(layout.scalar * 0), (3 * e1)])
def location(self, re... |
class BackwardsCompatibilityTests(DeprecationTestCase):
def test_server_connection_class(self):
with self.assertDeprecationWarning('ServerConnection was renamed to ServerProtocol'):
from websockets.server import ServerConnection
server = ServerConnection()
self.assertIsInstan... |
def windows_setup():
keymaps = ['Apple keyboard standard', 'Windows keyboard standard', 'Chromebook', 'IBM - No Super/Win', 'Uninstall']
for (index, item) in enumerate(keymaps):
print((' %i. %s' % ((index + 1), item)))
default = 0
while (not (int(default) in range(1, (len(keymaps) + 1)))):
... |
(kw_only=True)
class DataCatalog():
default_node: type[PNode] = PickleNode
entries: dict[(str, PNode)] = field(factory=dict)
name: str = 'default'
path: (Path | None) = None
_session_config: dict[(str, Any)] = field(factory=(lambda *x: {'check_casing_of_paths': True}))
_instance_path: Path = fie... |
def quant_analyzer_example():
model = models.resnet18(pretrained=True).cuda().eval()
input_shape = (1, 3, 224, 224)
dummy_input = torch.randn(*input_shape).cuda()
prepared_model = prepare_model(model)
forward_pass_callback_fn = CallbackFunc(forward_pass_callback, func_callback_args=None)
eval_ca... |
class GeneralError(Exception):
MAJOR_MESSAGE = 'General error'
FMT_STR = '{maj}: {min}.'
def __init__(self, minor_message: str, **kwargs: str) -> None:
maj_str = self.MAJOR_MESSAGE.format(**kwargs)
err_str = self.FMT_STR.format(maj=maj_str, min=minor_message)
super(GeneralError, self... |
def test_inject_decorated_singleton_class():
class A():
def __init__(self, b: SingletonB):
self.b = b
def configure(binder):
binder.bind(A)
binder.bind(SingletonB)
injector1 = Injector(configure)
a1 = injector1.get(A)
a2 = injector1.get(A)
assert (a1.b is a2.b... |
def _test_app():
test_folder = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), 'apps/MouseTester')
if (sys.platform == 'win32'):
return os.path.join(test_folder, 'mousebuttons.exe')
else:
return os.path.join(test_folder, 'mousebuttons') |
def convert_db_to_csv(filename: str, targetcsv: str) -> int:
with open(filename, 'r') as db:
json_loaded = json.load(db)['data']
csv_file = open(targetcsv, 'a')
csv_writer = csv.writer(csv_file)
try:
header = json_loaded[0].keys()
except IndexError:
pr... |
class TieredImageNet(Dataset):
def __init__(self, args, partition='train', pretrain=True, transform=None):
super(Dataset, self).__init__()
self.data_root = args.data_root
self.partition = partition
self.data_aug = args.data_aug
self.mean = [(120. / 255.0), (115. / 255.0), (10... |
class MSMR(DFN):
def __init__(self, options=None, name='MSMR', build=True):
options = (options or {})
if ('number of MSMR reactions' not in options):
raise pybamm.OptionError('number of MSMR reactions must be specified for MSMR')
if (('open-circuit potential' in options) and (opt... |
def tokenizer_class_from_name(class_name: str):
if (class_name == 'PreTrainedTokenizerFast'):
return PreTrainedTokenizerFast
for (module_name, tokenizers) in TOKENIZER_MAPPING_NAMES.items():
if (class_name in tokenizers):
module_name = model_type_to_module_name(module_name)
... |
def get_externsheet_local_range_b57(bk, raw_extshtx, ref_first_sheetx, ref_last_sheetx, blah=0):
if (raw_extshtx > 0):
if blah:
print(('/// get_externsheet_local_range_b57(raw_extshtx=%d) -> external' % raw_extshtx), file=bk.logfile)
return ((- 4), (- 4))
if ((ref_first_sheetx == (- ... |
class ELF64_Rel(ELF_Rel):
Rel_SIZE = (8 * 2)
def __init__(self, buf, endian=0, ptr=None):
if (len(buf) != self.Rel_SIZE):
raise
self.ptr = ptr
self.fmt = ('<QQ' if (endian == 0) else '>QQ')
(r_offset, r_info) = struct.unpack(self.fmt, buf)
super(ELF64_Rel, sel... |
class Migration(migrations.Migration):
dependencies = [('questions', '0014_meta')]
operations = [migrations.AddField(model_name='question', name='unit', field=models.CharField(blank=True, help_text='Unit for this question.', max_length=64, verbose_name='Unit', default=''), preserve_default=False), migrations.Ad... |
.parametrize('ignore_unknown_mediatypes', [True, False])
def test_validate_manifest_invalid_config_type(ignore_unknown_mediatypes):
manifest_bytes = '{\n "schemaVersion": 2,\n "config": {\n "mediaType": "application/some.other.thing",\n "digest": "sha256:6bd578ec7d1e7381f63184dfe5fbe7f2f1580... |
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--data_dir', default=None, type=str, required=True, help='The input data dir. Should contain the .tsv files (or other data files) for the task.')
parser.add_argument('--model_type', default=None, type=str, required=True, help=('Model type s... |
def _segmentation_trainer_head(args: SharedArgs, head_name: str, training_set: Dataset, class_weights: np.ndarray) -> SegmentationTrainerHead:
if args.segmentation_weight_temperature:
weight_creator = SegmentationWeightCreator(training_set, args.segmentation_weight_temperature, class_weights)
else:
... |
def _glibc_version_string_ctypes() -> Optional[str]:
try:
import ctypes
except ImportError:
return None
try:
process_namespace = ctypes.CDLL(None)
except OSError:
return None
try:
gnu_get_libc_version = process_namespace.gnu_get_libc_version
except Attribu... |
class Video():
fourcc = VideoWriter_fourcc(*'mp4v')
fps = config['fps']
width = config['width']
height = config['height']
output_dir = os.sep.join(['.', 'output'])
def __init__(self, *args, **kwargs):
return super().__init__(*args, **kwargs)
def create_video(radio: Radio):
if... |
class CopyrightChecker():
_UTF_STRING = '# -*- coding: utf-8 -*-'
_COPYRIGHT_STRING = '# (C) Copyright IBM '
def __init__(self, root_dir: str, check: bool) -> None:
self._root_dir = root_dir
self._check = check
self._current_year = datetime.datetime.now().year
self._changed_f... |
class PyOggFLACSource(PyOggSource):
def _load_source(self):
if self.file:
self._stream = MemoryFLACFileStream(self.filename, self.file)
else:
self._stream = UnclosedFLACFileStream(self.filename)
self.sample_size = self._stream.bits_per_sample
self._duration = ... |
def get_serializer(serializer):
if (serializer == 'json'):
return JSONSerializer
if (serializer == 'pickle'):
return PickleSerializer
if ((serializer == 'yaml') and (yaml is not None)):
return YAMLSerializer
if ((serializer == 'yaml') and (yaml is None)):
logger.warning('... |
def get_reward_mask_and_value(shape: Tuple[(int, int)], token_offset_mapping: List[List[Tuple[(int, int)]]], reward_offset_mapping: List[Mapping[(Tuple[(int, int)], Union[(float, None)])]]) -> Tuple[(np.ndarray, np.ndarray)]:
has_reward_mask = np.zeros(shape, dtype=np.bool_)
reward_val = np.zeros(shape, dtype=n... |
def _get_earth_fixed_coords(point, unit_vector_x, unit_vector_y, unit_vector_z):
(ux, uy, uz) = (unit_vector_x, unit_vector_y, unit_vector_z)
return Vector3D(x=(((ux.x * point.x) + (uy.x * point.y)) + (uz.x * point.z)), y=(((ux.y * point.x) + (uy.y * point.y)) + (uz.y * point.z)), z=(((ux.z * point.x) + (uy.z *... |
def test_skip_test_with_unicode(pytester: Pytester) -> None:
pytester.makepyfile(" import unittest\n class TestClass():\n def test_io(self):\n raise unittest.SkipTest('')\n ")
result = pytester.runpytest()
result.stdout.fnmatch_lines(['* 1 skipped *']) |
def create_datetime_index(year=None, month=None, day=None, uts=None):
if (not hasattr(year, '__iter__')):
raise ValueError('Must provide an iterable for all inputs.')
if (len(year) == 0):
raise ValueError('Length of array must be larger than 0.')
if (month is None):
month = np.ones(s... |
class CmdLineApp(cmd2.Cmd):
def __init__(self):
super().__init__(include_ipy=True)
self._set_prompt()
self.intro = 'Happy Day. Note the full Unicode support: '
def _set_prompt(self):
self.cwd = os.getcwd()
self.prompt = ansi.style(f'{self.cwd} $ ', fg='cyan')
def ... |
class GrammarSymbol(object):
def __init__(self, lbp=0, value=None, payload=None):
self.lbp = lbp
self.value = value
self.payload = payload
def nud(self, parser):
raise PysmtSyntaxError(("Syntax error at token '%s'." % parser.token))
def led(self, parser, left):
raise ... |
def multistart_hyperparameter_optimization(log_likelihood_optimizer, num_multistarts, randomness=None, max_num_threads=DEFAULT_MAX_NUM_THREADS, status=None):
if (randomness is None):
randomness = C_GP.RandomnessSourceContainer(max_num_threads)
randomness.SetRandomizedUniformGeneratorSeed(0)
... |
def _evaluate_goal_directed_benchmarks(goal_directed_molecule_generator: GoalDirectedGenerator, benchmarks: List[GoalDirectedBenchmark]) -> List[GoalDirectedBenchmarkResult]:
logger.info(f'Number of benchmarks: {len(benchmarks)}')
results = []
for (i, benchmark) in enumerate(benchmarks, 1):
logger.i... |
class Chat(Object):
def __init__(self, *, client: 'pyrogram.Client'=None, id: int, type: 'enums.ChatType', is_verified: bool=None, is_restricted: bool=None, is_creator: bool=None, is_scam: bool=None, is_fake: bool=None, is_support: bool=None, title: str=None, username: str=None, first_name: str=None, last_name: str... |
_module()
class TransformerEncoder(BaseModule):
def __init__(self, n_layers=2, n_head=8, d_model=512, d_inner=2048, dropout=0.1, max_len=(8 * 32), init_cfg=None):
super().__init__(init_cfg=init_cfg)
assert ((d_model % n_head) == 0), 'd_model must be divisible by n_head'
self.pos_encoder = Po... |
class SendSubmissionInput(BaseSubmissionInput):
conference: ID
title: MultiLingualInput
abstract: MultiLingualInput
languages: list[ID]
type: ID
duration: ID
elevator_pitch: MultiLingualInput
notes: str
audience_level: ID
short_social_summary: str
speaker_bio: str
speaker... |
class LogoutWorker(QThread):
succeeded = pyqtSignal()
msg = pyqtSignal(str, int)
def __init__(self, parent=None):
super(LogoutWorker, self).__init__(parent)
self._disk = None
self.update_ui = True
self._mutex = QMutex()
self._is_work = False
def set_disk(self, dis... |
class SophiaLexer(RegexLexer):
name = 'Sophia'
aliases = ['sophia']
filenames = ['*.aes']
mimetypes = []
url = '
version_added = '2.11'
keywords = ('contract', 'include', 'let', 'switch', 'type', 'record', 'datatype', 'if', 'elif', 'else', 'function', 'stateful', 'payable', 'public', 'entryp... |
_config
def test_togroup_toggle(manager):
manager.test_window('one')
assert (manager.c.group.info()['name'] == 'a')
assert (manager.c.get_groups()['a']['focus'] == 'one')
assert (manager.c.get_groups()['b']['focus'] is None)
manager.c.window.togroup('b', switch_group=True)
assert (manager.c.grou... |
class CO2Corrector(ModifierBase):
def __call__(self, projectables, optional_datasets=None, **info):
(ir_039, ir_108, ir_134) = projectables
logger.info('Applying CO2 correction')
dt_co2 = ((ir_108 - ir_134) / 4.0)
rcorr = ((ir_108 ** 4) - ((ir_108 - dt_co2) ** 4))
t4_co2corr ... |
class F17_Iscsi(RHEL6_Iscsi):
def _getParser(self):
op = super(F17_Iscsi, self)._getParser()
for action in op._actions:
if ('--iface' in action.option_strings):
action.help = action.help.replace(versionToLongString(RHEL6), versionToLongString(F17))
return op |
def process_prediction(action, objects, pad, vocab_action, clean_special_tokens, predict_object=True):
if (pad in action):
pad_start_idx = action.index(pad)
action = action[:pad_start_idx]
objects = objects[:pad_start_idx]
if clean_special_tokens:
stop_token = vocab_action.word2i... |
def test_successful_handshake() -> None:
client = H11Handshake(CLIENT)
server = H11Handshake(SERVER)
server.receive_data(client.send(Request(host='localhost', target='/')))
assert isinstance(next(server.events()), Request)
client.receive_data(server.send(AcceptConnection()))
assert isinstance(ne... |
class OpenDataStartTab(QtWidgets.QWidget):
def __init__(self, *args, m=None, **kwargs):
super().__init__(*args, **kwargs)
self.m = m
icon = (iconpath / 'open.png')
self.b_str = f"<img src={icon} height=20 style='display: inline; vertical-align:bottom;'></img>"
self.t1 = QtWid... |
.skipif(PYPY, reason='garbage-collection differences make this flaky')
.filterwarnings('default::pytest.PytestUnraisableExceptionWarning')
def test_unraisable_in_teardown(pytester: Pytester) -> None:
pytester.makepyfile(test_it='\n import pytest\n\n class BrokenDel:\n def __del__(self):\n ... |
def table_row_wise(host_index: int) -> ParameterShardingGenerator:
def _parameter_sharding_generator(param: nn.Parameter, local_size: int, world_size: int, device_type: str, sharder: ModuleSharder[nn.Module]) -> ParameterSharding:
size_and_offsets = _get_parameter_size_offsets(param, ShardingType.TABLE_ROW_... |
class SemiSupervisedTinyImagenet(SemiSupervisedDataset):
def load_base_dataset(self, train=False, **kwargs):
assert (self.base_dataset == 'tiny-imagenet'), 'Only semi-supervised tiny-imagenet is supported. Please use correct dataset!'
if train:
self.dataset = TinyImagenet(split='train', ... |
def list_paths_with_dangerous_command(sub_parsers):
parser: ArgumentParser = sub_parsers.add_parser('list-dangerous-usage', help='List all connections that needs a resource to be missing.', formatter_class=argparse.MetavarTypeHelpFormatter)
parser.add_argument('--print-only-area', help='Only print the area name... |
class ParetoRV(ScipyRandomVariable):
name = 'pareto'
ndim_supp = 0
ndims_params = [0, 0]
dtype = 'floatX'
_print_name = ('Pareto', '\\operatorname{Pareto}')
def __call__(self, b, scale=1.0, size=None, **kwargs):
return super().__call__(b, scale, size=size, **kwargs)
def rng_fn_scipy(... |
class CamRender(Render):
def __init__(self, width=1600, height=1200, name='Cam Renderer', program_files=['simple.fs', 'simple.vs'], color_size=1):
Render.__init__(self, width, height, name, program_files, color_size)
self.camera = None
glutDisplayFunc(self.display)
glutKeyboardFunc(s... |
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