repo_id stringclasses 409
values | prefix large_stringlengths 34 36.3k | target large_stringlengths 1 498 | assertion_type stringclasses 31
values | difficulty stringclasses 8
values | test_file stringlengths 10 121 | test_function stringlengths 1 104 | test_class stringlengths 0 51 | lineno int32 2 11.3k | commit_idx int32 |
|---|---|---|---|---|---|---|---|---|---|
webis-de/small-text | import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal, assert_raises
def assert_array_not_equal(x, y):
assert_raises(AssertionError, assert_array_equal, x, y)
def assert_csr_matrix_equal(x, y, check_shape=True):
if check_shape and x.shape != y.shape:
rai... | other) | assert_* | variable | tests/utils/testing.py | assert_list_of_tensors_not_equal | 41 | null | |
webis-de/small-text | import os
import unittest
import pytest
import small_text
from importlib import reload
from packaging.version import parse, Version
from unittest.mock import patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_QUIET, VERBOSITY_MORE_VERBOSE
... | args.max_length) | self.assertIsNone | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_setfit.py | test_setfit_model_arguments_init_default | TestSetFitModelArguments | 39 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
import numpy as np
from importlib import reload
from unittest.mock import patch
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_MORE_VERBOSE... | classifier.lr) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_classification.py | test_init | TestTransformerBasedClassification | 272 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import call, patch, Mock, ANY
from numpy.testing import assert_array_equal
from scipy import sparse
from scipy.sparse import csr_matrix, vstack
from small_text.active_learner import (
AbstractPoolBasedActiveLearner,
ActiveLearner,
PoolBasedActiveLearne... | clf_mock) | self.assertEqual | variable | tests/unit/small_text/test_active_learner.py | test_update_reuse_model | _PoolBasedActiveLearnerTest | 551 | null |
webis-de/small-text | import unittest
import numpy as np
from scipy.sparse import csr_matrix
from small_text.query_strategies.multi_label import (
CategoryVectorInconsistencyAndRanking,
_label_cardinality_inconsistency,
LabelCardinalityInconsistency,
_uncertainty_weighted_label_cardinality_inconsistency,
AdaptiveActive... | lci.shape) | self.assertEqual | complex_expr | tests/unit/small_text/query_strategies/test_multi_label.py | test_label_cardinality_inconsistency_average_two_labels | LabelCardinalityFunctionTest | 43 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest import mock
from small_text import (
ConfidenceEnhancedLinearSVC,
RandomSampling,
SklearnClassifier,
SklearnDataset
)
from small_text.data.sampling import _get_class_histogram
from small_text.query_strategies.class_balancing import ClassBalancer, _get_r... | n) | assert_* | variable | tests/unit/small_text/query_strategies/test_class_balancing.py | test_subsample_when_not_enough_samples | ClassBalancerSubsamplingTest | 110 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from abc import abstractmethod
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.data.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.excep... | ds_cloned.y) | assert_* | complex_expr | tests/unit/small_text/integrations/pytorch/test_datasets.py | test_clone | _PytorchTextClassificationDatasetTest | 206 | null |
webis-de/small-text | import logging
import unittest
from logging import Logger, INFO, DEBUG
from unittest.mock import patch
from small_text import VerbosityLogger, verbosity_logger, VERBOSITY_QUIET, VERBOSITY_ALL
class VerbosityLoggerTest(unittest.TestCase):
@patch('small_text.utils.logging.Logger.debug')
def test_debug(self, d... | msg) | assert_* | variable | tests/unit/small_text/utils/test_logging.py | test_debug | VerbosityLoggerTest | 19 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import Mock, patch
from numpy.testing import assert_array_equal
from sklearn.preprocessing import normalize
from small_text.classifiers import ConfidenceEnhancedLinearSVC
from small_text.query_strategies import (
LeastConfidence,
AnchorSubs... | str(query_strategy)) | self.assertEqual | func_call | tests/integration/small_text/query_strategies/test_subsampling.py | test_str | AnchorSubsamplingTest | 140 | null |
webis-de/small-text | import os
import numpy as np
def increase_dense_labels_safe(ds):
"""Increase the labels without leaving the range of the target_labels property.
The only purpose of this operation is to alter the labels so we can check for a change later."""
# modulo needs not be used when single index result is 0
if... | seed | assert | variable | tests/utils/misc.py | random_seed | 22 | null | |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_UNLABELED
from small_text.data.datasets import is_multi_label
from small_text.data.datasets import (
SklearnDataset,
DatasetView,
Te... | y_new) | assert_* | variable | tests/unit/small_text/data/test_datasets.py | test_set_labels | _DatasetTest | 159 | null |
webis-de/small-text | import unittest
import numpy as np
from scipy.sparse import csr_matrix
from small_text.base import LABEL_UNLABELED
from small_text.classifiers.classification import ConfidenceEnhancedLinearSVC, SklearnClassifier
from small_text.data.datasets import SklearnDataset
from tests.utils.datasets import random_sklearn_datas... | proba.shape[0]) | self.assertEqual | complex_expr | tests/unit/small_text/classifiers/test_classifiers.py | test_predict_proba_on_empty_data | _ClassifierBaseFunctionalityTest | 55 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.data import balanced_sampling, stratified_sampling
from small_text.data.sampling import _get_class_histogram
from small_text.utils.labels import list_to_csr
class StratifiedSamplingTest... | len(counts)) | self.assertEqual | func_call | tests/unit/small_text/data/test_sampling.py | test_stratified_sampling_with_gaps | StratifiedSamplingTest | 84 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from packaging.version import parse, Version
from unittest.mock import patch
from unittest import mock
from unittest.mock import Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_... | issparse(y_pred)) | self.assertTrue | func_call | tests/integration/small_text/integrations/pytorch/classifiers/test_kimcnn.py | test_fit_and_predict | _KimCNNClassifierTest | 75 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from sklearn.feature_extraction.text import TfidfVectorizer
from unittest.mock import patch
from small_text.data import SklearnDataset, TextDataset
from tests.utils.datasets import random_labeling, random_labels
from tests.utils.testing i... | dataset.y) | assert_* | complex_expr | tests/unit/small_text/data/test_dataset_construction.py | test_from_arrays_with_lists | TextDatasetConstructionSingleLabelTest | 150 | null |
webis-de/small-text | import unittest
import numpy as np
from scipy.sparse import csr_matrix
from small_text.query_strategies.multi_label import (
CategoryVectorInconsistencyAndRanking,
_label_cardinality_inconsistency,
LabelCardinalityInconsistency,
_uncertainty_weighted_label_cardinality_inconsistency,
AdaptiveActive... | uwlci.shape) | self.assertEqual | complex_expr | tests/unit/small_text/query_strategies/test_multi_label.py | test_label_cardinality_inconsistency_average_one_and_a_half_labels | UncertaintyWeightedLabelCardinalityFunctionTest | 142 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import patch
from small_text.utils.clustering import init_kmeans_plusplus_safe
class ClusteringUtilsTest(unittest.TestCase):
@patch('small_text.utils.clustering.warnings.warn')
@patch('small_text.utils.clustering.choice')
@patch('small_... | indices.shape[0]) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_clustering.py | test_init_kmeans_plusplus_safe | ClusteringUtilsTest | 26 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import create_autospec, patch
from scipy.sparse import issparse, csr_matrix
from small_text.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.datasets import t... | y_pred.shape) | self.assertEqual | complex_expr | tests/integration/small_text/integrations/transformers/classifiers/test_setfit.py | test_fit_and_predict | _ClassificationTest | 54 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_almost_equal
from small_text.query_strategies.base import argselect
class ArgselectIntegrationTest(unittest.TestCase):
def test_argselect_maximum(self, n=5):
for _ in range(1000):
arr = np.random.randn(100)
... | np.sort(arr[indices])) | assert_* | func_call | tests/integration/small_text/query_strategies/test_base.py | test_argselect_maximum | ArgselectIntegrationTest | 19 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_IGNORED
from small_text.utils.labels import (
concatenate,
csr_to_list,
get_ignored_labels_mask,
get_num_labels,
list_to_csr,
remove_by_index
)
... | y_new) | assert_* | variable | tests/unit/small_text/utils/test_labels.py | test_remove_by_index_dense | LabelUtilsTest | 85 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNIntegrationTest(unittest.TestCase):
def test_simple_prediction(self):
"""
Simple prediction with default weights (untrained).
"""
n = 10
vocab_size = 11
... | output.size(1)) | self.assertEqual | func_call | tests/integration/small_text/integrations/pytorch/models/test_kimcnn.py | test_simple_prediction | KimCNNIntegrationTest | 33 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from sklearn.feature_extraction.text import TfidfVectorizer
from unittest.mock import patch
from small_text.data import SklearnDataset, TextDataset
from tests.utils.datasets import random_labeling, random_labels
from tests.utils.testing i... | dataset.x) | assert_* | complex_expr | tests/unit/small_text/data/test_dataset_construction.py | test_from_arrays_with_lists | TextDatasetConstructionSingleLabelTest | 149 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import call, patch, Mock, ANY
from numpy.testing import assert_array_equal
from scipy import sparse
from scipy.sparse import csr_matrix, vstack
from small_text.active_learner import (
AbstractPoolBasedActiveLearner,
ActiveLearner,
PoolBasedActiveLearne... | len(dataset) | assert | func_call | tests/unit/small_text/test_active_learner.py | test_query_with_custom_representation_invalid | _PoolBasedActiveLearnerTest | 346 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.misc import increase_dense_labels_safe
from test... | len(result)) | self.assertEqual | func_call | tests/unit/small_text/integrations/transformers/test_datasets.py | test_indexing_single_index | _TransformersDatasetTest | 235 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import patch
from scipy.sparse import csr_matrix
from small_text.data import balanced_sampling, stratified_sampling
from small_text.initialization import random_initialization, \
random_initialization_stratified, random_initialization_balanced
from tests.util... | indices.shape[0]) | self.assertEqual | complex_expr | tests/unit/small_text/initialization/test_strategies.py | test_random_initialization_stratified_multilabel | RandomInitializationStratifiedTest | 63 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import create_autospec, patch
from scipy.sparse import issparse, csr_matrix
from small_text.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.datasets import t... | issparse(y_pred)) | self.assertTrue | func_call | tests/integration/small_text/integrations/transformers/classifiers/test_setfit.py | test_fit_and_predict | _ClassificationTest | 55 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
from importlib import reload
from packaging.version import parse, Version
from unittest.mock import patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_QUIET, VERBOSITY_MORE_VERBOSE
... | args.seed) | self.assertIsNone | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_setfit.py | test_setfit_model_arguments_init_default | TestSetFitModelArguments | 48 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNInitTest(unittest.TestCase):
DEFAULT_KERNEL_HEIGHTS = [3, 4, 5]
def test_init_parameters_default(self):
vocab_size = 1000
max_seq_length = 50
model = KimCNN(vocab_s... | model.device) | self.assertIsNotNone | complex_expr | tests/unit/small_text/integrations/pytorch/models/test_kimcnn.py | test_init_parameters_default | KimCNNInitTest | 34 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import patch
from small_text.utils.clustering import init_kmeans_plusplus_safe
class ClusteringUtilsTest(unittest.TestCase):
@patch('small_text.utils.clustering.warnings.warn')
@patch('small_text.utils.clustering.choice')
@patch('small_... | centers.shape) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_clustering.py | test_init_kmeans_plusplus_safe | ClusteringUtilsTest | 25 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import patch, MagicMock
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class BuildLayerSpecificParamsTest(unittest.TestCase):
def _assert_params(self, params, base_lr, num_different_lrs):
self.assertIsNotNon... | param['lr'] > 0) | self.assertTrue | complex_expr | tests/unit/small_text/integrations/transformers/utils/test_classification.py | _assert_params | BuildLayerSpecificParamsTest | 187 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNInitTest(unittest.TestCase):
DEFAULT_KERNEL_HEIGHTS = [3, 4, 5]
def test_init_parameters_specific(self):
vocab_size = 1000
max_seq_length = 50
num_classes = 3
... | conv.in_channels) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/pytorch/models/test_kimcnn.py | test_init_parameters_specific | KimCNNInitTest | 96 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_IGNORED
from small_text.utils.labels import (
concatenate,
csr_to_list,
get_ignored_labels_mask,
get_num_labels,
list_to_csr,
remove_by_index
)
... | mask) | assert_* | variable | tests/unit/small_text/utils/test_labels.py | test_get_ignored_labels_mask_dense | LabelUtilsTest | 71 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest import mock
from small_text.data.sampling import balanced_sampling, stratified_sampling
from small_text.data.splits import split_data
from tests.utils.datasets import random_sklearn_dataset
class SplitDataTest(unittest.TestCase):
@mock.patch('numpy.random.permut... | len(subset_valid)) | self.assertEqual | func_call | tests/unit/small_text/data/test_splits.py | test_split_data_random | SplitDataTest | 37 | null |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.data.datasets import (
DatasetView,
SklearnDataset,
SklearnDatasetView,
TextDataset,
TextDatasetView
)
from small_text.data.exceptions import U... | ds_cloned.y) | assert_* | complex_expr | tests/unit/small_text/data/test_datatset_views.py | _clone_test | _DatasetViewTest | 168 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from abc import abstractmethod
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.data.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.excep... | len(ds)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/test_datasets.py | test_datasen_len | _PytorchTextClassificationDatasetTest | 299 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import call, patch, Mock, ANY
from numpy.testing import assert_array_equal
from scipy import sparse
from scipy.sparse import csr_matrix, vstack
from small_text.active_learner import (
AbstractPoolBasedActiveLearner,
ActiveLearner,
PoolBasedActiveLearne... | ANY) | assert_* | variable | tests/unit/small_text/test_active_learner.py | test_query | _PoolBasedActiveLearnerTest | 306 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class TransformersDatasetTest(unittest.TestCase):
def test_indexing(self):
data = random_transformer_dataset(10)
dataset = TransformersDataset(data)
subset = data... | len(subset)) | self.assertEqual | func_call | tests/integration/small_text/integrations/transformers/test_datasets.py | test_indexing | TransformersDatasetTest | 29 | null |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.data.datasets import (
DatasetView,
SklearnDataset,
SklearnDatasetView,
TextDataset,
TextDatasetView
)
from small_text.data.exceptions import U... | len(result)) | self.assertEqual | func_call | tests/unit/small_text/data/test_datatset_views.py | test_indexing_single_index | _DatasetViewTest | 202 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from abc import abstractmethod
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.data.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.excep... | ds._data) | self.assertIsNotNone | complex_expr | tests/unit/small_text/integrations/pytorch/test_datasets.py | test_init | _PytorchTextClassificationDatasetTest | 50 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class LossTest(unittest.TestCase):
def test_loss_fct(self):
loss_fct = _LossAdapter2DTo1D(BCEWithLogitsLoss(reduction='none'))
input = torch.randn(5, 3)
target = torch.empty(5, 3).ra... | len(loss.shape)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/utils/test_loss.py | test_loss_fct | LossTest | 26 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNInitTest(unittest.TestCase):
DEFAULT_KERNEL_HEIGHTS = [3, 4, 5]
def test_init_parameters_default(self):
vocab_size = 1000
max_seq_length = 50
model = KimCNN(vocab_s... | len(model.convs)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/models/test_kimcnn.py | test_init_parameters_default | KimCNNInitTest | 48 | null |
webis-de/small-text | import numpy as np
class VectorIndexesTest(object):
def get_vector_index(self):
"""
Defines the vector index to be used for these test cases.
"""
raise NotImplementedError
def _get_random_data(self, n=20, d=4):
return np.random.rand(n, d).astype(np.float32)
def te... | indices.ravel().shape[0]) | self.assertEqual | func_call | tests/integration/small_text/vector_indexes/test_base.py | test_search | VectorIndexesTest | 48 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class _AMPArgumentsTest(object):
def _test_with_no_amp_args_configured(self, clf):
amp_args = clf.amp_args
self.assertIsNotNone( | amp_args) | self.assertIsNotNone | variable | tests/integration/small_text/integrations/pytorch/classifiers/test_base.py | _test_with_no_amp_args_configured | _AMPArgumentsTest | 55 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
import numpy as np
from importlib import reload
from unittest.mock import patch
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_MORE_VERBOSE... | call_args[6]) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_classification.py | test_fit_with_optimizer_and_scheduler | TestTransformerBasedClassification | 470 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from abc import abstractmethod
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.data.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.excep... | ds_new.y) | assert_* | complex_expr | tests/unit/small_text/integrations/pytorch/test_datasets.py | test_set_labels | _PytorchTextClassificationDatasetTest | 144 | null |
webis-de/small-text | import unittest
import numpy as np
from small_text.classifiers import ConfidenceEnhancedLinearSVC
from small_text.data.datasets import SklearnDataset
from small_text.query_strategies import (
EmptyPoolException,
greedy_coreset,
GreedyCoreset,
lightweight_coreset,
LightweightCoreset
)
from tests.un... | (num_samples,)) | self.assertEqual | collection | tests/unit/small_text/query_strategies/test_coresets.py | test_query | _GreedyCoresetFunctionTest | 31 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from packaging.version import parse, Version
from unittest.mock import patch
from unittest import mock
from unittest.mock import Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_... | False) | assert_* | bool_literal | tests/integration/small_text/integrations/pytorch/classifiers/test_kimcnn.py | test_fit_and_predict | _KimCNNClassifierTest | 72 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNInitTest(unittest.TestCase):
DEFAULT_KERNEL_HEIGHTS = [3, 4, 5]
def test_init_parameters_default(self):
vocab_size = 1000
max_seq_length = 50
model = KimCNN(vocab_s... | model.pool_sizes) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/pytorch/models/test_kimcnn.py | test_init_parameters_default | KimCNNInitTest | 31 | null |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_UNLABELED
from small_text.data.datasets import is_multi_label
from small_text.data.datasets import (
SklearnDataset,
DatasetView,
Te... | ds_new.y) | self.assertIsNotNone | complex_expr | tests/unit/small_text/data/test_datasets.py | test_set_features | _DatasetTest | 122 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from packaging.version import parse, Version
from unittest.mock import patch
from unittest import mock
from unittest.mock import Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_... | call_args[5]) | self.assertEqual | complex_expr | tests/integration/small_text/integrations/pytorch/classifiers/test_kimcnn.py | test_fit_with_optimizer_and_scheduler | _KimCNNClassifierTest | 325 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
import numpy as np
from importlib import reload
from unittest.mock import patch
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_MORE_VERBOSE... | model_args.model) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_classification.py | test_transformer_model_arguments_init | TestTransformerModelArguments | 54 | null |
webis-de/small-text | import unittest
import pytest
import warnings
import numpy as np
from packaging.version import parse, Version
from unittest import mock
from unittest.mock import patch, Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.trai... | clf.model) | self.assertIsNotNone | complex_expr | tests/integration/small_text/integrations/transformers/classifiers/test_classification.py | test_fit_with_class_weight | _TransformerBasedClassificationTest | 71 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class PytorchTextClassificationDatasetTest(unittest.TestCase):
def test_dataset_to_copy(self):
ds = random_text_classification_dataset(10)
self.assertTrue(ds.target_label... | hasattr(ds_new, 'TEST')) | self.assertFalse | func_call | tests/integration/small_text/integrations/pytorch/test_datasets.py | test_dataset_to_copy | PytorchTextClassificationDatasetTest | 63 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
from importlib import reload
from packaging.version import parse, Version
from unittest.mock import patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_QUIET, VERBOSITY_MORE_VERBOSE
... | device) | self.assertEqual | variable | tests/unit/small_text/integrations/transformers/classifiers/test_setfit.py | test_init_device | _SetFitClassification | 290 | null |
webis-de/small-text | import unittest
import pytest
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class KimCNNInitTest(unittest.TestCase):
DEFAULT_KERNEL_HEIGHTS = [3, 4, 5]
def test_init_parameters_default(self):
vocab_size = 1000
max_seq_length = 50
model = KimCNN(vocab_s... | len(model.pools)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/models/test_kimcnn.py | test_init_parameters_default | KimCNNInitTest | 44 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.misc import increase_dense_labels_safe
from test... | result.x) | assert_* | complex_expr | tests/unit/small_text/integrations/transformers/test_datasets.py | test_indexing_list_index | _TransformersDatasetTest | 249 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_IGNORED
from small_text.utils.labels import (
concatenate,
csr_to_list,
get_ignored_labels_mask,
get_num_labels,
list_to_csr,
remove_by_index
)
... | result.dtype) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_labels.py | test_list_to_csr | LabelUtilsTest | 132 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.utils.classification import empty_result, prediction_result
from tests.utils.testing import assert_csr_matrix_equal
class ClassificationUtilsTest(unittest.TestCase):
def test_empt... | proba.dtype) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_classification.py | test_empty_result_single_label_proba | ClassificationUtilsTest | 132 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import patch, MagicMock
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class BuildLayerSpecificParamsTest(unittest.TestCase):
def _assert_params(self, params, base_lr, num_different_lrs):
self.assertIsNotNo... | params) | self.assertIsNotNone | variable | tests/unit/small_text/integrations/transformers/utils/test_classification.py | _assert_params | BuildLayerSpecificParamsTest | 183 | null |
webis-de/small-text | import unittest
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
from small_text.classifiers import ConfidenceEnhancedLinearSVC
class ConfidenceEnhancedLinearSVCIntegrationTest(unittest.TestCase):
def _get_20news_vectors(self, categories=None):
... | len(y_pred.shape)) | self.assertEqual | func_call | tests/integration/classifiers/test_svm.py | test_predict_binary | ConfidenceEnhancedLinearSVCIntegrationTest | 27 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.datasets import random_labeling, random_labels, _train_tokenizer
class PytorchTextClassificationDatasetSingleLabelTest(unittest.TestCase):
def test_from_arrays_with_lists... | len(dataset)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/test_dataset_construction.py | test_from_arrays_with_lists | PytorchTextClassificationDatasetSingleLabelTest | 26 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.misc import increase_dense_labels_safe
from test... | ds_new.y) | assert_* | complex_expr | tests/unit/small_text/integrations/transformers/test_datasets.py | test_set_labels | _TransformersDatasetTest | 135 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import patch
from scipy.sparse import csr_matrix
from small_text.data import balanced_sampling, stratified_sampling
from small_text.initialization import random_initialization, \
random_initialization_stratified, random_initialization_balanced
from tests.util... | len(np.unique(indices))) | self.assertEqual | func_call | tests/unit/small_text/initialization/test_strategies.py | test_random_initialization | RandomInitializationTest | 22 | null |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_UNLABELED
from small_text.data.datasets import is_multi_label
from small_text.data.datasets import (
SklearnDataset,
DatasetView,
Te... | ds.y) | self.assertIsNotNone | complex_expr | tests/unit/small_text/data/test_datasets.py | test_get_features | _DatasetTest | 112 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.data import balanced_sampling, stratified_sampling
from small_text.data.sampling import _get_class_histogram
from small_text.utils.labels import list_to_csr
class StratifiedSamplingTest... | counts[0]) | self.assertEqual | complex_expr | tests/unit/small_text/data/test_sampling.py | test_stratified_sampling | StratifiedSamplingTest | 50 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import Mock, patch
from numpy.testing import assert_array_equal
from sklearn.preprocessing import normalize
from small_text.classifiers import ConfidenceEnhancedLinearSVC
from small_text.query_strategies import (
LeastConfidence,
AnchorSubs... | y) | assert_* | variable | tests/integration/small_text/query_strategies/test_subsampling.py | test_query_when_unlabeled_pool_is_smaller_than_k | AnchorSubsamplingTest | 135 | null |
webis-de/small-text | import unittest
from packaging import version
from unittest.mock import patch
from small_text.utils.annotations import (
deprecated,
experimental,
DeprecationError,
ExperimentalWarning
)
class DeprecationUtilsTest(unittest.TestCase):
def test_deprecate_function(self):
from small_text.uti... | myfunc('foo')) | self.assertTrue | func_call | tests/unit/small_text/utils/test_annotations.py | test_deprecate_function | DeprecationUtilsTest | 67 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
from importlib import reload
from packaging.version import parse, Version
from unittest.mock import patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_QUIET, VERBOSITY_MORE_VERBOSE
... | args.max_steps) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_setfit.py | test_setfit_model_arguments_init_default | TestSetFitModelArguments | 42 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class PytorchTextClassificationDatasetTest(unittest.TestCase):
def test_dataset_to(self):
ds = random_text_classification_dataset(10)
tensor_is_on_cpu = [item[PytorchText... | np.all(tensor_is_on_cpu)) | self.assertTrue | func_call | tests/integration/small_text/integrations/pytorch/test_datasets.py | test_dataset_to | PytorchTextClassificationDatasetTest | 24 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.utils.classification import empty_result, prediction_result
from tests.utils.testing import assert_csr_matrix_equal
class ClassificationUtilsTest(unittest.TestCase):
def test_empt... | proba.shape) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_classification.py | test_empty_result_single_label_proba | ClassificationUtilsTest | 133 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.misc import increase_dense_labels_safe
from test... | ds_cloned.x) | assert_* | complex_expr | tests/unit/small_text/integrations/transformers/test_datasets.py | test_clone | _TransformersDatasetTest | 196 | null |
webis-de/small-text | import pytest
import unittest
from unittest.mock import Mock, patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.training.model_selection import NoopModelSelection
from tests.utils.datasets import random_text_classification_dataset
class SimplePytorchClassifierTest(unit... | clf.multi_label) | self.assertFalse | complex_expr | tests/unit/small_text/integrations/pytorch/classifiers/test_base.py | test_default_init | SimplePytorchClassifierTest | 126 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import create_autospec, patch
from scipy.sparse import issparse, csr_matrix
from small_text.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.datasets import t... | np.int64) | self.assertEqual | complex_expr | tests/integration/small_text/integrations/transformers/classifiers/test_setfit.py | test_fit_and_predict | _ClassificationTest | 56 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.data.datasets import TextDataset
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class SetFitUtilsTest(unittest.TestCase):
def test_truncate_texts(self):
model_args = SetFitModelArguments('sentence-transformers/p... | len(result_datasets)) | self.assertEqual | func_call | tests/integration/small_text/integrations/transformers/utils/test_setfit.py | test_truncate_texts | SetFitUtilsTest | 40 | null |
webis-de/small-text | import unittest
import numpy as np
from copy import copy
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.base import LABEL_UNLABELED
from small_text.data.datasets import is_multi_label
from small_text.data.datasets import (
SklearnDataset,
DatasetView,
Te... | ds.x) | assert_* | complex_expr | tests/unit/small_text/data/test_datasets.py | test_get_features | _TextDatasetTest | 483 | null |
webis-de/small-text | import unittest
import numpy as np
from small_text.stopping_criteria.uncertainty import OverallUncertainty
class OverallUncertaintyTest(unittest.TestCase):
def test_first_stop_call(self):
stopping_criterion = OverallUncertainty(2)
proba = np.array([
[0.5, 0.5]
])
sto... | stop) | self.assertFalse | variable | tests/unit/small_text/stopping_criteria/test_uncertainty.py | test_first_stop_call | OverallUncertaintyTest | 39 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from abc import abstractmethod
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.data.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.excep... | len(ds.x)) | self.assertEqual | func_call | tests/unit/small_text/integrations/pytorch/test_datasets.py | test_get_features | _PytorchTextClassificationDatasetTest | 110 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.utils.classification import empty_result, prediction_result
from tests.utils.testing import assert_csr_matrix_equal
class ClassificationUtilsTest(unittest.TestCase):
def test_pred... | result) | assert_* | variable | tests/unit/small_text/utils/test_classification.py | test_prediction_result | ClassificationUtilsTest | 23 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from packaging.version import parse, Version
from unittest.mock import patch
from unittest import mock
from unittest.mock import Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_... | loss >= 0) | self.assertTrue | complex_expr | tests/integration/small_text/integrations/pytorch/classifiers/test_kimcnn.py | test_fit_and_validate | _KimCNNClassifierTest | 157 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from unittest.mock import create_autospec, patch
from scipy.sparse import issparse, csr_matrix
from small_text.exceptions import UnsupportedOperationException
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.datasets import t... | amp_args.use_amp) | self.assertFalse | complex_expr | tests/integration/small_text/integrations/transformers/classifiers/test_setfit.py | test_with_no_amp_args_configured | SetFitClassificationAMPArgumentsTest | 269 | null |
webis-de/small-text | import pytest
import unittest
from unittest.mock import Mock, patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.training.model_selection import NoopModelSelection
from tests.utils.datasets import random_text_classification_dataset
class AMPArgumentsTest(unittest.TestCa... | amp_args.dtype) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/pytorch/classifiers/test_base.py | test_init_default | AMPArgumentsTest | 41 | null |
webis-de/small-text | import unittest
import warnings
import numpy as np
from small_text.classifiers import ConfidenceEnhancedLinearSVC
from small_text.query_strategies.bayesian import BALD, _bald
from tests.utils.datasets import random_sklearn_dataset
from tests.utils.testing import assert_array_equal
class BALDHelperTest(unittest.TestC... | result) | assert_* | variable | tests/unit/small_text/query_strategies/test_bayesian.py | test_bald_with_only_zeros | BALDHelperTest | 17 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from small_text.utils.classification import empty_result, prediction_result
from tests.utils.testing import assert_csr_matrix_equal
class ClassificationUtilsTest(unittest.TestCase):
def test_empt... | prediction.shape) | self.assertEqual | complex_expr | tests/unit/small_text/utils/test_classification.py | test_empty_result_single_label_prediction | ClassificationUtilsTest | 125 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from scipy.sparse import csr_matrix
from numpy.testing import assert_array_equal
from small_text.base import LABEL_UNLABELED
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from tests.utils.misc import increase_dense_labels_safe
from test... | ds.y) | assert_* | complex_expr | tests/unit/small_text/integrations/transformers/test_datasets.py | test_get_labels | _TransformersDatasetTest | 125 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest.mock import patch
from scipy.sparse import csr_matrix
from small_text.data import balanced_sampling, stratified_sampling
from small_text.initialization import random_initialization, \
random_initialization_stratified, random_initialization_balanced
from tests.util... | len(indices)) | self.assertEqual | func_call | tests/unit/small_text/initialization/test_strategies.py | test_random_initialization | RandomInitializationTest | 21 | null |
webis-de/small-text | import unittest
import tempfile
import pytest
import numpy as np
from numpy.testing import assert_array_equal
from small_text.active_learner import PoolBasedActiveLearner
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.query_strategies import RandomSampling
from tests.ut... | len(weights_after)) | self.assertEqual | func_call | tests/integration/small_text/integrations/pytorch/test_serialization.py | test_and_load_with_file_str | SerializationTest | 55 | null |
webis-de/small-text | import os
import unittest
from unittest.mock import patch
from small_text.utils.system import (
OFFLINE_MODE_VARIABLE,
PROGRESS_BARS_VARIABLE,
TMP_DIR_VARIABLE,
get_offline_mode,
get_show_progress_bar_default,
get_tmp_dir_base
)
class SystemUtilsTest(unittest.TestCase):
def test_get_tmp_... | get_tmp_dir_base()) | self.assertIsNone | func_call | tests/unit/small_text/utils/test_system.py | test_get_tmp_dir_base | SystemUtilsTest | 41 | null |
webis-de/small-text | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from small_text.stopping_criteria.kappa import KappaAverage, _adapted_cohen_kappa_score
class KappaAverageTest(unittest.TestCase):
def test_first_stop_call(self):
stopping_criterion = KappaAverage(2)
predictions = n... | stop) | self.assertFalse | variable | tests/unit/small_text/stopping_criteria/test_kappa.py | test_first_stop_call | KappaAverageTest | 103 | null |
webis-de/small-text | import unittest
import numpy as np
from unittest import mock
from small_text import (
ConfidenceEnhancedLinearSVC,
RandomSampling,
SklearnClassifier,
SklearnDataset
)
from small_text.data.sampling import _get_class_histogram
from small_text.query_strategies.class_balancing import ClassBalancer, _get_r... | str(strategy)) | self.assertEqual | func_call | tests/unit/small_text/query_strategies/test_class_balancing.py | test_class_balancer_str | ClassBalancerTest | 190 | null |
webis-de/small-text | import numpy as np
class VectorIndexesTest(object):
def get_vector_index(self):
"""
Defines the vector index to be used for these test cases.
"""
raise NotImplementedError
def _get_random_data(self, n=20, d=4):
return np.random.rand(n, d).astype(np.float32)
def te... | indices.shape) | self.assertEqual | complex_expr | tests/integration/small_text/vector_indexes/test_base.py | test_search_with_ids | VectorIndexesTest | 61 | null |
webis-de/small-text | import os
import unittest
import pytest
import small_text
from importlib import reload
from packaging.version import parse, Version
from unittest.mock import patch
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.utils.logging import VERBOSITY_QUIET, VERBOSITY_MORE_VERBOSE
... | clf.device) | self.assertIsNone | complex_expr | tests/unit/small_text/integrations/transformers/classifiers/test_setfit.py | test_init | _SetFitClassification | 272 | null |
webis-de/small-text | import unittest
import pytest
import warnings
import numpy as np
from packaging.version import parse, Version
from unittest import mock
from unittest.mock import patch, Mock
from scipy.sparse import issparse, csr_matrix
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
from small_text.trai... | issparse(y_pred)) | self.assertTrue | func_call | tests/integration/small_text/integrations/transformers/classifiers/test_classification.py | test_fit_and_predict | _TransformerBasedClassificationTest | 141 | null |
webis-de/small-text | import unittest
import pytest
import numpy as np
from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
class ExpectedGradientLengthTest(unittest.TestCase):
def test_init_default(self):
strategy = ExpectedGradientLength(2)
self.assertEqual(2, strategy.num_classes)
s... | strategy.device) | self.assertEqual | complex_expr | tests/unit/small_text/integrations/pytorch/test_strategies.py | test_init_default | ExpectedGradientLengthTest | 47 | null |
explosion/thinc | import numpy
import pytest
from thinc.api import (
SGD,
ArgsKwargs,
CupyOps,
Linear,
MPSOps,
NumpyOps,
PyTorchWrapper,
PyTorchWrapper_v2,
PyTorchWrapper_v3,
Relu,
chain,
get_current_ops,
torch2xp,
use_ops,
xp2torch,
)
from thinc.backends import context_pools
... | (nN, nI) | assert | collection | thinc/tests/layers/test_pytorch_wrapper.py | test_pytorch_wrapper | 95 | null | |
explosion/thinc | import numpy
import pytest
from numpy.testing import assert_allclose
from thinc.types import Pairs, Ragged
def ragged():
data = numpy.zeros((20, 4), dtype="f")
lengths = numpy.array([4, 2, 8, 1, 4], dtype="i")
data[0] = 0
data[1] = 1
data[2] = 2
data[3] = 3
data[4] = 4
data[5] = 5
... | (1, 45) | assert | collection | thinc/tests/test_indexing.py | test_pairs_arrays | 65 | null | |
explosion/thinc | import math
import numpy
import pytest
from thinc.api import SGD, SparseLinear, SparseLinear_v2, to_categorical
def instances():
lengths = numpy.asarray([5, 4], dtype="int32")
keys = numpy.arange(9, dtype="uint64")
values = numpy.ones(9, dtype="float32")
X = (keys, values, lengths)
y = numpy.asar... | (2, 3) | assert | collection | thinc/tests/layers/test_sparse_linear.py | test_init | 45 | null | |
explosion/thinc | import numpy
import pytest
from thinc.api import reduce_first, reduce_last, reduce_max, reduce_mean, reduce_sum
from thinc.types import Ragged
def Xs():
seqs = [numpy.zeros((10, 8), dtype="f"), numpy.zeros((4, 8), dtype="f")]
for x in seqs:
x[0] = 1
x[1] = 2 # so max != first
x[-1] = ... | list(Xs[0][1]) | assert | func_call | thinc/tests/layers/test_reduce.py | test_reduce_max | 74 | null | |
explosion/thinc | import numpy
import pytest
from thinc.api import NumpyOps, Ragged, registry, strings2arrays
from ..util import get_data_checker
def shapes(request):
return request.param
def ops():
return NumpyOps()
def list_data(shapes):
return [numpy.zeros(shape, dtype="f") for shape in shapes]
def ragged_data(ops, ... | len(strings) | assert | func_call | thinc/tests/layers/test_transforms.py | test_strings2arrays | 78 | null | |
explosion/thinc | import platform
import threading
import time
from collections import Counter
import numpy
import pytest
from thinc.api import (
Adam,
CupyOps,
Dropout,
Linear,
Model,
Relu,
Shim,
Softmax,
chain,
change_attr_values,
concatenate,
set_dropout_rate,
use_ops,
with_de... | 4 | assert | numeric_literal | thinc/tests/model/test_model.py | test_maybe_methods | 192 | null | |
explosion/thinc | import pytest
import srsly
from thinc.api import (
Linear,
Maxout,
Model,
Shim,
chain,
deserialize_attr,
serialize_attr,
with_array,
)
def linear():
return Linear(5, 3)
def test_simple_model_roundtrip_bytes_serializable_attrs():
fwd = lambda model, X, is_train: (X, lambda dY: ... | "foo" | assert | string_literal | thinc/tests/test_serialize.py | test_simple_model_roundtrip_bytes_serializable_attrs | 82 | null |
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