code
stringlengths
281
23.7M
_WRAPPERS.register_module('mmseg.DDPWrapper') class DistributedDataParallelWrapper(nn.Module): def __init__(self, module, device_ids, dim=0, broadcast_buffers=False, find_unused_parameters=False, **kwargs): super().__init__() assert (len(device_ids) == 1), f'Currently, DistributedDataParallelWrapper...
def setup_environ_items(environ, headers): for (key, value) in environ.items(): if isinstance(value, string_types): environ[key] = wsgi_encoding_dance(value) for (key, value) in headers.items(): key = ('HTTP_' + key.upper().replace('-', '_')) if (key not in ('HTTP_CONTENT_TYP...
class TAPETextValue(TestCase): from mutagen.apev2 import APETextValue as TV TV = TV def setUp(self): self.sample = ['foo', 'bar', 'baz'] self.value = mutagen.apev2.APEValue('\x00'.join(self.sample), mutagen.apev2.TEXT) def test_parse(self): self.assertRaises(APEBadItemError, self...
class BNBlurBlock(nn.Module): def __init__(self, in_filters, sfilter=(1, 1), pad_mode='constant', **kwargs): super(PreactBlurBlock, self).__init__() self.bn = layers.bn(in_filters) self.relu = layers.relu() self.blur = layers.blur(in_filters, sfilter=sfilter, pad_mode=pad_mode) d...
class __diag__(__config_flags): _type_desc = 'diagnostic' warn_multiple_tokens_in_named_alternation = False warn_ungrouped_named_tokens_in_collection = False warn_name_set_on_empty_Forward = False warn_on_multiple_string_args_to_oneof = False enable_debug_on_named_expressions = False _all_na...
class TrialShortNamer(): PREFIX = 'hp' DEFAULTS = {} NAMING_INFO = None def set_defaults(cls, prefix, defaults): cls.PREFIX = prefix cls.DEFAULTS = defaults cls.build_naming_info() def shortname_for_word(info, word): if (len(word) == 0): return '' ...
class Grey(DefaultTheme): DEFAULTS = dict(legendgroup_postfix=' (greyed)', direction=dict(cause_color='black', effect_color='black'), purviews=dict(marker=dict(opacity=0.75, colorscale='greys')), cause_effect_links=dict(opacity=0.2, line=dict(color='grey')), mechanism_purview_links=dict(opacity=0.2, line=dict(color...
class PluginRenameTestCase(TestCase): fixtures = ['fixtures/styles.json', 'fixtures/auth.json', 'fixtures/simplemenu.json'] _settings(MEDIA_ROOT='api/tests') def setUp(self): self.client = Client() self.url_upload = reverse('plugin_upload') self.user = User.objects.create_user(userna...
class TRandomAlbum(PluginTestCase): WEIGHTS = {'rating': 0, 'added': 0, 'laststarted': 0, 'lastplayed': 0, 'length': 0, 'skipcount': 0, 'playcount': 0} def setUp(self): config.init() init_fake_app() app.player.paused = False app.library.clear() app.window.browser = AlbumL...
class UnsupportedPasswordHashVersion(InvalidPassword, WalletFileException): def __init__(self, version): self.version = version def __str__(self): return '{unsupported}: {version}\n{instruction}'.format(unsupported=_('Unsupported password hash version'), version=self.version, instruction=f'''To ...
def save_progress(object_to_save, placeholder_token, output_dir, name='learned_embeds.bin', method='inversion'): logger.info('Saving embeddings') base_path = os.path.join(output_dir, 'embeds') os.makedirs(base_path, exist_ok=True) save_path = os.path.join(base_path, name) if (method == 'inversion'):...
_tests('aes_gcm_test.json') def test_aes_gcm(backend, wycheproof): key = binascii.unhexlify(wycheproof.testcase['key']) iv = binascii.unhexlify(wycheproof.testcase['iv']) aad = binascii.unhexlify(wycheproof.testcase['aad']) msg = binascii.unhexlify(wycheproof.testcase['msg']) ct = binascii.unhexlify...
class NonLinearElementMultiply(nn.Module): def __init__(self, image_feat_dim, ques_emb_dim, **kwargs): super(NonLinearElementMultiply, self).__init__() self.fa_image = ReLUWithWeightNormFC(image_feat_dim, kwargs['hidden_dim']) self.fa_txt = ReLUWithWeightNormFC(ques_emb_dim, kwargs['hidden_d...
class GraphPartition(GraphOptimizationApplication): def to_quadratic_program(self) -> QuadraticProgram: mdl = Model(name='Graph partition') n = self._graph.number_of_nodes() x = {i: mdl.binary_var(name=f'x_{i}') for i in range(n)} for (w, v) in self._graph.edges: self._gr...
class RepositoryLocalState(): def __init__(self, repository): self.repository = repository self.uploaded_project_ids = set() def is_uploaded(self, package): return (package.unique_id in self.uploaded_project_ids) def set_uploaded(self, package): self.uploaded_project_ids.add(...
def test_lid_unit_params(): with Simulation(MODEL_LIDS_PATH) as sim: sub_2_lid_units = LidGroups(sim)['2'] first_unit = sub_2_lid_units[0] assert (first_unit.unit_area == approx(10000, rel=UT_PRECISION)) assert (first_unit.full_width == approx(20, rel=UT_PRECISION)) assert (f...
def get_raw(path, fin, fout, cat='other', new=True, is_dev=True, form='conll', is_space=False): fout = codecs.open(((path + '/') + fout), 'w', encoding='utf-8') fout_dev = None if (not is_dev): fout_dev = codecs.open((path + '/raw_dev.txt'), 'w', encoding='utf-8') cter = 0 if (form == 'conll...
class TrainUnit(AppStateMixin, _OnExceptionMixin, Generic[TTrainData], ABC): def __init__(self) -> None: super().__init__() self.train_progress = Progress() def on_train_start(self, state: State) -> None: pass def on_train_epoch_start(self, state: State) -> None: pass def...
class _SerializedRelationship(): def __init__(self, baseURI, rel_elm): super(_SerializedRelationship, self).__init__() self._baseURI = baseURI self._rId = rel_elm.rId self._reltype = rel_elm.reltype self._target_mode = rel_elm.target_mode self._target_ref = rel_elm.ta...
def associated_cell_is_useful(a_i, a_j, type_c, pos_i, pos_j, cell_id, useful_cell_positions, useful_cell_ids, betas): if ((a_i, a_j) in useful_cell_positions): _c_id = useful_cell_ids[useful_cell_positions.index((a_i, a_j))] else: return False associated_beta = betas[_c_id][type_c] if (...
def compare_two(P: Sequence[cirq.Qid], Q: Sequence[cirq.Qid], equal, less_than, greater_than) -> cirq.OP_TREE: P = P[::(- 1)] Q = Q[::(- 1)] xor = cirq.NamedQubit('xor') (yield cirq.CNOT(P[1], xor)) (yield cirq.CNOT(Q[1], xor)) (yield cirq.CSWAP(xor, *P)) (yield cirq.CSWAP(xor, *Q)) anc ...
(os.environ.get('CIRCLECI'), 'Caffe2 tests crash on CircleCI.') class TestCaffe2Export(unittest.TestCase): def setUp(self): setup_logger() def _test_model(self, config_path, device='cpu'): cfg = model_zoo.get_config(config_path) cfg.MODEL.DEVICE = device model = model_zoo.get(con...
class TestUmap(unittest.TestCase): def setUp(self): (X, y) = fetch_openml('mnist_784', version=1, return_X_y=True) X = normalize(X) self.X = X self.y = y def tearDown(self): pass def test_numberDataPoints(self): reducer = humap.UMAP(n_neighbors=15) emb...
(bdd.parsers.re('the (?P<what>primary selection|clipboard) should contain "(?P<content>.*)"')) def clipboard_contains(quteproc, server, what, content): expected = content.replace('(port)', str(server.port)) expected = expected.replace('\\n', '\n') expected = expected.replace('(linesep)', os.linesep) qut...
class GPT4AllHandler(LLMHandler): def __init__(self, settings, modelspath, llm): self.key = 'local' self.settings = settings self.modelspath = modelspath self.model = None self.llm = llm self.history = {} self.prompts = [] if (not os.path.isdir(self.mo...
def get_indexed_dataset_to_local(path): local_index_path = PathManager.get_local_path(index_file_path(path)) local_data_path = PathManager.get_local_path(data_file_path(path)) assert (local_index_path.endswith('.idx') and local_data_path.endswith('.bin')), f'PathManager.get_local_path does not return files ...
class Signal(_SignalObjectBase): def __init__(self, s, t, country, Type, subtype='-1', countryRevision=None, id=None, name=None, dynamic=Dynamic.no, value=None, unit=None, zOffset=1.5, orientation=Orientation.positive, hOffset=0, pitch=0, roll=0, height=None, width=None): super().__init__(s, t, id, Type, su...
class OneAlbum(qltk.Notebook): def __init__(self, songs): super().__init__() swin = SW() swin.title = _('Information') vbox = Gtk.VBox(spacing=12) vbox.set_border_width(12) swin.add_with_viewport(vbox) songs = sorted(songs) self._title(songs, vbox) ...
def test_custom_theme_options_become_text(): my_theme = CustomTheme(bg='yellow', fg='blue', text_size=12, text_font='arial', text_align='left', outline='yes', line_wrap=0.5) options_dict = my_theme assert (options_dict.get('bg') == 'yellow') assert (options_dict.get('fg') == 'blue') assert (options_...
def print_progress(iteration, total, prefix='', suffix='', decimals=1, bar_length=100): str_format = (('{0:.' + str(decimals)) + 'f}') percents = str_format.format((100 * (iteration / float(total)))) filled_length = int(round(((bar_length * iteration) / float(total)))) bar = (('' * filled_length) + ('-'...
.parametrize('has_custom_path', [False, True]) def test_on_custom_path_button_exists(skip_qtbot, tmp_path, mocker, has_custom_path): mock_prompt = mocker.patch('randovania.gui.lib.common_qt_lib.prompt_user_for_output_file', autospec=True) if has_custom_path: output_directory = tmp_path.joinpath('output_...
def generate_format_ops(specifiers: list[ConversionSpecifier]) -> (list[FormatOp] | None): format_ops = [] for spec in specifiers: if ((spec.whole_seq == '%s') or (spec.whole_seq == '{:{}}')): format_op = FormatOp.STR elif (spec.whole_seq == '%d'): format_op = FormatOp.IN...
class PointCompoundSourceDelegate(SourceDelegate): __represents__ = 'PointCompoundSource' display_backend = 'Compound Model' display_name = 'PointCompoundSource' parameters = ['easting', 'northing', 'depth', 'dVx', 'dVy', 'dVz', 'rotation_x', 'rotation_y', 'rotation_z', 'nu'] ro_parameters = ['volum...
def parse_arch(arch_str): if isinstance(arch_str, str): match = re.match('^(\\d+)bit$', arch_str) if match: return int(next(iter(match.groups()))) error = f'invalid format {arch_str}' else: error = f'arch is not string: {arch_str!r}' raise ValueError(error)
class TDSF(TestCase): silence_1 = os.path.join(DATA_DIR, '2822400-1ch-0s-silence.dsf') silence_2 = os.path.join(DATA_DIR, '5644800-2ch-s01-silence.dsf') has_tags = os.path.join(DATA_DIR, 'with-id3.dsf') no_tags = os.path.join(DATA_DIR, 'without-id3.dsf') def setUp(self): self.filename_1 = ge...
def _preset_with_locked_pb(preset: Preset, locked: bool): pickup_database = default_database.pickup_database_for_game(RandovaniaGame.METROID_DREAD) preset = dataclasses.replace(preset, configuration=dataclasses.replace(preset.configuration, ammo_configuration=preset.configuration.ammo_pickup_configuration.repla...
def main(): args = parse_args() send_example_telemetry('run_image_classification_no_trainer', args) accelerator_log_kwargs = {} if args.with_tracking: accelerator_log_kwargs['log_with'] = args.report_to accelerator_log_kwargs['logging_dir'] = args.output_dir accelerator = Accelerator...
class TestLanguageModel(unittest.TestCase): def testLanguageModelTest(self): (vocab_size, data) = getTestingData() opts = LanguageModelOptions() opts.no_prune_ngram_order = kaldi_math.rand_int(1, 3) opts.ngram_order = (opts.no_prune_ngram_order + kaldi_math.rand_int(0, 3)) op...
class InceptionTest(tf.test.TestCase): def testBuildLogits(self): batch_size = 5 (height, width) = (299, 299) num_classes = 1000 inputs = tf.random_uniform((batch_size, height, width, 3)) (logits, end_points) = inception.inception_v4(inputs, num_classes) auxlogits = e...
class DescribeZipPkgWriter(): def it_is_used_by_PhysPkgWriter_unconditionally(self, tmp_docx_path): phys_writer = PhysPkgWriter(tmp_docx_path) assert isinstance(phys_writer, _ZipPkgWriter) def it_opens_pkg_file_zip_on_construction(self, ZipFile_): pkg_file = Mock(name='pkg_file') ...
def _option(info, title, predicate): model = completionmodel.CompletionModel(column_widths=(20, 70, 10)) options = ((opt.name, opt.description, info.config.get_str(opt.name)) for opt in configdata.DATA.values() if predicate(opt)) model.add_category(listcategory.ListCategory(title, options)) return model
.parametrize('metric', ['euclidean', 'minkowski', 'cityblock', 'chebyshev', 'haversine']) def test_metric_k(metric): data = (grocs.to_crs(4326) if (metric == 'haversine') else grocs) if ((not HAS_SKLEARN) and (metric in ['chebyshev', 'haversine'])): pytest.skip('metric not supported by scipy') (head...
def current_migration(): if (os.getenv('ENSURE_NO_MIGRATION', '').lower() == 'true'): raise Exception('Cannot call migration when ENSURE_NO_MIGRATION is true') if (not app.config.get('SETUP_COMPLETE', False)): return 'head' elif (ActiveDataMigration is not None): return ActiveDataMig...
def try_parse(code, args, args_ctypes, compile_opt): if (not compile_opt['try_parse']): variables = [(('self.' + name), name, 'object') for name in args if (name in code)] (code, variables) = use_hinted_type(variables, code, args_ctypes) return (code, variables, [], True) (ncode, variabl...
class DropboxOAuth2V2(BaseOAuth2): name = 'dropbox-oauth2' ID_KEY = 'uid' AUTHORIZATION_URL = ' ACCESS_TOKEN_URL = ' ACCESS_TOKEN_METHOD = 'POST' REDIRECT_STATE = False def get_user_details(self, response): name = response.get('name') return {'username': str(response.get('acc...
def test_combine_molecules_offxml_plugin_deepdiff(tmpdir, coumarin, rfree_data): coumarin_copy = coumarin.copy(deep=True) MBISCharges.apply_symmetrisation(coumarin_copy) with tmpdir.as_cwd(): _combine_molecules_offxml(molecules=[coumarin_copy], parameters=elements, rfree_data=rfree_data, filename='o...
class GANLoss(nn.Module): def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0, tensor=torch.FloatTensor, opt=None): super(GANLoss, self).__init__() self.real_label = target_real_label self.fake_label = target_fake_label self.real_label_tensor = None self...
class BoosterSideEffects(ContextMenuSingle): def __init__(self): self.mainFrame = gui.mainFrame.MainFrame.getInstance() def display(self, callingWindow, srcContext, mainItem): if ((self.mainFrame.getActiveFit() is None) or (srcContext not in 'boosterItem')): return False if (...
def make_stage(block_class, num_blocks, first_stride, *, in_channels, out_channels, **kwargs): assert ('stride' not in kwargs), 'Stride of blocks in make_stage cannot be changed.' blocks = [] for i in range(num_blocks): blocks.append(block_class(in_channels=in_channels, out_channels=out_channels, st...
def weird_physchem() -> GoalDirectedBenchmark: min_bertz = RdkitScoringFunction(descriptor=bertz, score_modifier=MaxGaussianModifier(mu=1500, sigma=200)) mol_under_400 = RdkitScoringFunction(descriptor=mol_weight, score_modifier=MinGaussianModifier(mu=400, sigma=40)) aroma = RdkitScoringFunction(descriptor=...
def get_D(xp: list[int], Ann): S = sum(xp) if (S == 0): return 0 n_coins = len(xp) d_prev = 0.0 d = float(S) for i in range(255): d_p = d for x in xp: d_p = ((d_p * d) / (x * n_coins)) d_prev = d d = ((((Ann * S) + (d_p * n_coins)) * d) / (((An...
class H2StreamStateMachine(): def __init__(self, stream_id): self.state = StreamState.IDLE self.stream_id = stream_id self.client = None self.headers_sent = None self.trailers_sent = None self.headers_received = None self.trailers_received = None self....
class HSTPIPIMR(IntEnum): RXINE = (1 << 0) TXOUTE = (1 << 1) TXSTPE = (1 << 2) UNDERFIE = (1 << 2) PERRE = (1 << 3) NAKEDE = (1 << 4) OVERFIE = (1 << 5) RXSTALLDE = (1 << 6) CRCERRE = (1 << 6) SHORTPACKETIE = (1 << 7) NBUSYBKE = (1 << 12) FIFOCON = (1 << 14) PDISHDMA ...
def unravel(list_): result = [list_] for (i, x) in enumerate(list_): if (len(list(x[1])) > 1): members = list(x[1]) temp = copy.deepcopy(result) for each_list in result: each_list[i][1] = members[0] for n in range(1, len(members)): ...
def filter_acceptable_routes(route_states: List[RouteState], blacklisted_channel_ids: List[ChannelID], addresses_to_channel: Dict[(Tuple[(TokenNetworkAddress, Address)], NettingChannelState)], token_network_address: TokenNetworkAddress, our_address: Address) -> List[RouteState]: acceptable_routes = [] for route...
class CompositeEncoder(FairseqEncoder): def __init__(self, encoders): super().__init__(next(iter(encoders.values())).dictionary) self.encoders = encoders for key in self.encoders: self.add_module(key, self.encoders[key]) def forward(self, src_tokens, src_lengths): enc...
def main(): if (len(sys.argv) < 3): sys.exit('Needs args: hook_name, control_dir') hook_name = sys.argv[1] control_dir = sys.argv[2] if (hook_name not in HOOK_NAMES): sys.exit(('Unknown hook: %s' % hook_name)) hook = globals()[hook_name] hook_input = read_json(pjoin(control_dir, ...
def test_class_weights_rescale_C(): from sklearn.svm import LinearSVC (X, Y) = make_blobs(n_samples=210, centers=3, random_state=1, cluster_std=3, shuffle=False) X = np.hstack([X, np.ones((X.shape[0], 1))]) weights = (1.0 / np.bincount(Y)) weights *= (len(weights) / np.sum(weights)) pbl_class_we...
class SendEmail(object): local_dir = path.dirname(__file__) with open(os.path.join(local_dir, 'mailbox.txt'), 'r') as f: mail_setting = f.readlines() from_addr = mail_setting[0].strip() password = mail_setting[1].strip() smtp_server = mail_setting[2].strip() def __init__(self, text, send...
def read_pep621_metadata(proj, path) -> LoadedConfig: lc = LoadedConfig() md_dict = lc.metadata if ('name' not in proj): raise ConfigError('name must be specified in [project] table') _check_type(proj, 'name', str) md_dict['name'] = proj['name'] lc.module = md_dict['name'].replace('-', '...
def build_filter_repr_dict(filter_list: FilterList, list_type: ListType, filter_type: type[Filter], settings_overrides: dict, extra_fields_overrides: dict) -> dict: default_setting_values = {} for settings_group in filter_list[list_type].defaults: for (_, setting) in settings_group.items(): ...
.parametrize('screenshot_manager', [{}, {'icon_size': 30}], indirect=True) .usefixtures('dbus') def ss_statusnotifier(screenshot_manager): win = screenshot_manager.test_window('TestSNI', export_sni=True) wait_for_icon(screenshot_manager.c.widget['statusnotifier'], hidden=False) screenshot_manager.take_scree...
.skipif((not HAVE_DEPS_FOR_RESOURCE_ESTIMATES), reason='pyscf and/or jax not installed.') def test_costing_helper(): nRe = 108 lamRe = 294.8 dE = 0.001 LRe = 360 LxiRe = 13031 chi = 10 betaRe = 16 nLi = 152 lamLi = 1171.2 LLi = 394 LxiLi = 20115 betaLi = 20 res = comp...
def obtain_discrm_data(disc_enc_type, molecules_reference, smiles_mutated, selfies_mutated, max_molecules_len, num_processors, generation_index): if (disc_enc_type == 'smiles'): random_dataset_selection = np.random.choice(list(molecules_reference.keys()), size=len(smiles_mutated)).tolist() dataset_s...
class GaussianPolicy(NNPolicy, Serializable): def __init__(self, env_spec, hidden_layer_sizes=(100, 100), reg=0.001, squash=True, reparameterize=True, todropoutpi=False, dropoutpi=1.0, batchnormpi=False, name='gaussian_policy'): Serializable.quick_init(self, locals()) self._hidden_layers = hidden_la...
def makeUpdateMatrixTensoredSv(updateMatrix, qnnArch, l, m): numInputQubits = qnnArch[(l - 1)] numOutputQubits = qnnArch[l] if ((numOutputQubits - 1) != 0): updateMatrix = qt.tensor(updateMatrix, tensoredId((numOutputQubits - 1))) return swappedOp(updateMatrix, numInputQubits, (numInputQubits + ...
class File(object): def __init__(self, f, type_label='TEST', version='0000', record_formats={}): assert (len(type_label) == 4) assert (len(version) == 4) self._file_type_label = type_label self._file_version = version self._record_formats = record_formats self._curren...
class F39_NetworkData(F27_NetworkData): removedKeywords = F27_NetworkData.removedKeywords removedAttrs = F27_NetworkData.removedAttrs def __init__(self, *args, **kwargs): F27_NetworkData.__init__(self, *args, **kwargs) self.ipv4_dns_search = kwargs.get('ipv4_dns_search', None) self.i...
.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION) class Glue(datasets.Metric): def _info(self): if (self.config_name not in ['sst2', 'mnli', 'mnli_mismatched', 'mnli_matched', 'cola', 'stsb', 'mrpc', 'qqp', 'qnli', 'rte', 'wnli', 'hans', 'ag', 'amazon', 'chemprot', 'citation_intent', 'hype...
class TestSetAttr(): def test_change(self): def hook(*a, **kw): return 'hooked!' class Hooked(): x = attr.ib(on_setattr=hook) y = attr.ib() h = Hooked('x', 'y') assert ('x' == h.x) assert ('y' == h.y) h.x = 'xxx' h.y = 'yyy'...
class RequestPresetsView(discord.ui.View): def __init__(self): super().__init__(timeout=None) .button(label='Attach presets', style=discord.ButtonStyle.secondary, custom_id='attach_presets_of_permalink') async def button_callback(self, button: Button, interaction: discord.Interaction): try: ...
def ExtendRule(Valid, Curr, order, MaxOrder, Trajectory, MinSupport): if (order >= MaxOrder): AddToRules(Valid) else: Distr = Distribution[Valid] if (KLD(MaxDivergence(Distribution[Curr]), Distr) < KLDThreshold((order + 1), Curr)): AddToRules(Valid) else: ...
class Migration(migrations.Migration): dependencies = [('sponsors', '0076_auto__1550')] operations = [migrations.CreateModel(name='SponsorshipCurrentYear', fields=[('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('year', models.PositiveIntegerField(validators=[...
class TestUUIDField(TestCase): def setUp(self): self.field = fields.UUIDField() def test_serialize(self): arbitrary_uuid = uuid.uuid4() actual_result = self.field.serialize(arbitrary_uuid) expected_result = str(arbitrary_uuid) self.assertEqual(actual_result, expected_resu...
class AvgMeterHolder(): def __init__(self): self.time_to_get_batch = AverageMeter() self.time_to_forward = AverageMeter() self.time_to_step = AverageMeter() def reset(self): for elem in self.__dict__.values(): if isinstance(elem, AverageMeter): elem.re...
def test_aggregated_storage_scenarios(three_storage_model): from pywr.core import Scenario from pywr.parameters import ConstantScenarioParameter m = three_storage_model sc = Scenario(m, 'A', size=5) agg_stg = m.nodes['Total Storage'] stgs = [m.nodes['Storage {}'.format(num)] for num in range(3)]...
def get_linear_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, last_epoch=(- 1)): def lr_lambda(current_step: int): if (current_step < num_warmup_steps): return (float(current_step) / float(max(1, num_warmup_steps))) return max(0.0, (float((num_training_steps - curr...
def format_time(time): if (time < 0): time = abs(time) prefix = '-' else: prefix = '' if (time >= 3600): return ('%s%d:%02d:%02d' % (prefix, (time // 3600), ((time % 3600) // 60), (time % 60))) else: return ('%s%d:%02d' % (prefix, (time // 60), (time % 60)))
def do_train(cfg, model, train_loader, val_loader, optimizer, scheduler, loss_fn, num_query): log_period = cfg.SOLVER.LOG_PERIOD checkpoint_period = cfg.SOLVER.CHECKPOINT_PERIOD eval_period = cfg.SOLVER.EVAL_PERIOD output_dir = cfg.OUTPUT_DIR device = cfg.MODEL.DEVICE epochs = cfg.SOLVER.MAX_EPO...
def test_cached_inputoutput(): (Z, nblock, itype) = slicot_example() m = len(nblock) mr = np.count_nonzero((1 == itype)) (mu0, d0, g0, x0) = ab13md(Z, nblock, itype) assert (((m + mr) - 1) == len(x0)) (mu1, d1, g1, x1) = ab13md(Z, nblock, itype, x0) assert_allclose(mu1, mu0) with pytest....
def test_asyncio_mark_on_sync_function_emits_warning(pytester: Pytester): pytester.makepyfile(dedent(' import pytest\n\n .asyncio\n def test_a():\n pass\n ')) result = pytester.runpytest('--asyncio-mode=strict', '-W default') result.assert_outcomes(...
class PikeLexer(CppLexer): name = 'Pike' aliases = ['pike'] filenames = ['*.pike', '*.pmod'] mimetypes = ['text/x-pike'] version_added = '2.0' tokens = {'statements': [(words(('catch', 'new', 'private', 'protected', 'public', 'gauge', 'throw', 'throws', 'class', 'interface', 'implement', 'abstra...
class NativeScalerWithGradNormCount(): state_dict_key = 'amp_scaler' def __init__(self): self._scaler = torch.cuda.amp.GradScaler() def __call__(self, loss, optimizer, clip_grad=None, parameters=None, create_graph=False, update_grad=True): self._scaler.scale(loss).backward(create_graph=creat...
class ApplicationSettingsManager(GetWithoutIdMixin, UpdateMixin, RESTManager): _path = '/application/settings' _obj_cls = ApplicationSettings _update_attrs = RequiredOptional(optional=('id', 'default_projects_limit', 'signup_enabled', 'password_authentication_enabled_for_web', 'gravatar_enabled', 'sign_in_t...
def render(raw, stream=None): if (stream is None): stream = io.StringIO() settings = SETTINGS.copy() settings['warning_stream'] = stream writer = Writer() writer.translator_class = ReadMeHTMLTranslator try: parts = publish_parts(raw, writer=writer, settings_overrides=settings) ...
def get_trainer(cfg: DictConfig) -> Trainer: logger = get_logger(cfg) checkpoint_callback = get_saver(cfg) args = dict(cfg[__key__]) args = {str(k).lower(): v for (k, v) in args.items()} args['logger'] = logger args['callbacks'] = [checkpoint_callback] return Trainer(**args)
def compute_mAP(index, good_index, junk_index): ap = 0 cmc = torch.IntTensor(len(index)).zero_() if (good_index.size == 0): cmc[0] = (- 1) return (ap, cmc) mask = np.in1d(index, junk_index, invert=True) index = index[mask] ngood = len(good_index) mask = np.in1d(index, good_in...
class KITTIDepthDataset(KITTIDataset): def __init__(self, *args, **kwargs): super(KITTIDepthDataset, self).__init__(*args, **kwargs) def get_image_path(self, folder, frame_index, side): f_str = '{:010d}{}'.format(frame_index, self.img_ext) image_path = os.path.join(self.data_path, folder...
class TestExecution(): pytestmark = skiponwin32 def test_sysfind_no_permisson_ignored(self, monkeypatch, tmpdir): noperm = tmpdir.ensure('noperm', dir=True) monkeypatch.setenv('PATH', str(noperm), prepend=':') noperm.chmod(0) try: assert (local.sysfind('jaksdkasldqwe'...
class QcQuantizeOp(): def __init__(self, quant_info: libquant_info.QcQuantizeInfo, quant_scheme: QuantScheme=QuantScheme.post_training_tf_enhanced, rounding_mode: str='nearest', encodings: Union[(libpymo.TfEncoding, None)]=None, op_mode: Union[(OpMode, None)]=None, bitwidth: int=8, use_symmetric_encodings: bool=Fal...
def differentiable_graph2smiles_v0(origin_smiles, differentiable_graph, leaf_extend_idx_pair, leaf_nonleaf_lst, max_num_offspring=100, topk=3): new_smiles_set = set() origin_mol = Chem.rdchem.RWMol(Chem.MolFromSmiles(origin_smiles)) (origin_idx_lst, origin_node_mat, origin_substructure_lst, origin_atomidx_2...
class ProxiesOnHost(Proxies): def mem_usage_add(self, proxy: ProxyObject) -> None: self._mem_usage += sizeof(proxy) def mem_usage_remove(self, proxy: ProxyObject) -> None: self._mem_usage -= sizeof(proxy) def buffer_info(self) -> List[Tuple[(float, int, List[ProxyObject])]]: ret = []...
class Mesh(object): def __init__(self, vertices, faces, textures=None, texture_size=4): self.vertices = vertices self.faces = faces self.num_vertices = self.vertices.shape[0] self.num_faces = self.faces.shape[0] if (textures is None): shape = (self.num_faces, text...
class ItemStats(ContextMenuSingle): def __init__(self): self.mainFrame = gui.mainFrame.MainFrame.getInstance() def display(self, callingWindow, srcContext, mainItem): if (srcContext not in ('marketItemGroup', 'marketItemMisc', 'fittingModule', 'fittingCharge', 'fittingShip', 'baseShip', 'cargoIt...
class HalloweenFacts(commands.Cog): def random_fact(self) -> tuple[(int, str)]: return random.choice(FACTS) (name='spookyfact', aliases=('halloweenfact',), brief='Get the most recent Halloween fact') async def get_random_fact(self, ctx: commands.Context) -> None: (index, fact) = self.random_...
def parameters(): params = TrackerParams() params.debug = 0 params.visualization = False params.use_gpu = True deep_params = TrackerParams() params.max_image_sample_size = ((18 * 16) ** 2) params.min_image_sample_size = ((18 * 16) ** 2) params.search_area_scale = 5 params.feature_siz...
class Res15DataProcessor(DataProcessor): def __init__(self, tokenizer, max_length): self.tokenizer = tokenizer self.max_length = max_length def get_train_examples(self, data_dir): return self._create_examples(self._read_txt(os.path.join(data_dir, 'train_triplets.txt')), 'train') def ...
class J0(UnaryScalarOp): nfunc_spec = ('scipy.special.j0', 1, 1) def st_impl(x): return scipy.special.j0(x) def impl(self, x): return self.st_impl(x) def grad(self, inp, grads): (x,) = inp (gz,) = grads return [((gz * (- 1)) * j1(x))] def c_code(self, node, na...
class File(PymiereBaseObject): def __init__(self, pymiere_id=None): super(File, self).__init__(pymiere_id) ' If true, the object refers to a file system alias or shortcut. ' def alias(self): return self._eval_on_this_object('alias') def alias(self, alias): raise AttributeError("A...
class IntegersRV(RandomVariable): name = 'integers' ndim_supp = 0 ndims_params = [0, 0] dtype = 'int64' _print_name = ('integers', '\\operatorname{integers}') def __call__(self, low, high=None, size=None, **kwargs): if (high is None): (low, high) = (0, low) return sup...