repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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|---|---|---|---|---|---|---|
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_pickle_dataset.py | import ctypes
import io
import multiprocessing
import os
import pickle
import platform
import sys
import unittest
import mock
from chainer import datasets
from chainer.datasets import pickle_dataset
from chainer import testing
from chainer import utils
class ReaderMock(object):
def __init__(self, io_):
... | 3,912 | 26.556338 | 78 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_dict_dataset.py | import unittest
import numpy
from chainer.backends import cuda
from chainer import datasets
from chainer import testing
from chainer.testing import attr
class TestDictDataset(unittest.TestCase):
def setUp(self):
self.x = numpy.random.rand(3, 4)
self.y = numpy.random.rand(3, 5)
self.z = ... | 1,790 | 28.360656 | 73 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_cifar.py | import os
import unittest
import mock
import numpy
from chainer.dataset import download
from chainer.datasets import get_cifar10
from chainer.datasets import get_cifar100
from chainer.datasets import tuple_dataset
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
... | 2,815 | 32.927711 | 78 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_transform_dataset.py | import unittest
import numpy
from chainer import datasets
from chainer import testing
def _create_list_tuples(shape1, shape2, length):
return [(numpy.random.uniform(shape1), numpy.random.uniform(shape2)) for
_ in range(length)]
@testing.parameterize(
{'dataset': numpy.random.uniform(size=(2, 3... | 1,491 | 29.44898 | 76 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_mnist.py | import importlib
import os
import unittest
import mock
import numpy
from chainer.dataset import download
from chainer.datasets import get_fashion_mnist
from chainer.datasets import get_fashion_mnist_labels
from chainer.datasets import get_kuzushiji_mnist
from chainer.datasets import get_kuzushiji_mnist_labels
from ch... | 5,935 | 40.222222 | 79 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_sub_dataset.py | import unittest
from chainer import datasets
from chainer import testing
class TestSubDataset(unittest.TestCase):
def test_sub_dataset(self):
original = [1, 2, 3, 4, 5]
subset = datasets.SubDataset(original, 1, 4)
self.assertEqual(len(subset), 3)
self.assertEqual(subset[0], 2)
... | 9,204 | 36.267206 | 79 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_image_dataset.py | import os
import pickle
import unittest
import numpy
from chainer import datasets
from chainer.datasets import image_dataset
from chainer import testing
@testing.parameterize(*testing.product({
'dtype': [numpy.float32, numpy.int32],
}))
@unittest.skipUnless(image_dataset.available, 'image_dataset is not availab... | 5,975 | 33.148571 | 79 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_svhn.py | import os
import unittest
import mock
import numpy
from chainer.dataset import download
from chainer.datasets import get_svhn
from chainer.datasets import tuple_dataset
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
'withlabel': [True, False],
'scale': ... | 2,326 | 33.220588 | 77 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/test_concatenated_dataset.py | import unittest
import numpy as np
import six
from chainer.datasets import ConcatenatedDataset
from chainer import testing
@testing.parameterize(
# basic usage
{'datasets': (
np.random.uniform(size=(5, 3, 48, 32)),
np.random.uniform(size=(15, 3, 64, 48)),
)},
# more than two datasets... | 1,854 | 27.538462 | 75 | py |
chainer | chainer-master/tests/chainer_tests/datasets_tests/image_dataset/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/training_tests/test_trainer.py | import time
import traceback
import unittest
from chainer import testing
from chainer import training
class DummyExtension(training.extension.Extension):
def __init__(self, test_case):
self.is_called = False
self.is_finalized = False
self._test_case = test_case
def __call__(self, tr... | 7,997 | 28.843284 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/test_extension.py | import unittest
import pytest
from chainer import testing
from chainer import training
class TestExtension(unittest.TestCase):
def test_raise_error_if_call_not_implemented(self):
class MyExtension(training.Extension):
pass
ext = MyExtension()
trainer = testing.get_trainer_w... | 2,203 | 29.191781 | 77 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_plot_report.py | import unittest
import warnings
import pytest
from chainer import testing
from chainer.training import extensions
try:
import matplotlib
_available = True
except ImportError:
_available = False
class TestPlotReport(unittest.TestCase):
def test_available(self):
if _available:
s... | 1,638 | 31.78 | 77 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_fail_on_nonnumber.py | import os
import shutil
import tempfile
import unittest
import warnings
import numpy
import chainer
from chainer import links
from chainer import testing
from chainer.testing import attr
from chainer import training
class Model(chainer.Chain):
def __init__(self):
super(Model, self).__init__()
w... | 3,042 | 27.980952 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_linear_shift.py | import unittest
import mock
from chainer import testing
from chainer import training
from chainer.training import extensions
class TestLinearShift(unittest.TestCase):
value_range = (2.0, 6.0)
time_range = (1, 3)
expect = [2.0, 2.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0, 6.0, 6.0]
def setUp(self):
s... | 2,245 | 30.194444 | 77 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_print_report.py | import tempfile
import unittest
import mock
from chainer import testing
from chainer.training import extensions
class TestPrintReport(unittest.TestCase):
def _setup(self, stream=None, delete_flush=False):
self.logreport = mock.MagicMock(spec=extensions.LogReport(
['epoch'], trigger=(1, 'iter... | 1,568 | 31.6875 | 66 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_evaluator.py | import unittest
import numpy
import chainer
from chainer import backend
from chainer.backends import _cpu
from chainer import dataset
from chainer import iterators
from chainer import testing
from chainer.training import extensions
class DummyModel(chainer.Chain):
def __init__(self, test):
super(DummyM... | 9,832 | 32.332203 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_snapshot.py | import glob
import itertools
import os
import shutil
import tempfile
import time
import unittest
import mock
import pytest
from chainer import testing
from chainer import training
from chainer.training import extensions
from chainer.training.extensions._snapshot import _find_latest_snapshot
from chainer.training.exte... | 9,566 | 34.172794 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py | import re
import time
import unittest
import mock
import six
import chainer
from chainer import backend
from chainer import testing
from chainer import training
from chainer.training import extensions
def _get_mocked_trainer(links, stop_trigger=(10, 'iteration')):
updater = mock.Mock()
optimizer = mock.Mock... | 5,565 | 29.415301 | 78 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_polynomial_shift.py | import unittest
import mock
from chainer import testing
from chainer.training import extensions
from chainer.training import util
@testing.parameterize(
{'init': 2.0, 'rate': 0.5, 'max_count': 10, 'target': None,
'expect': [2.0, 1.8973665961010275, 1.7888543819998317]},
{'init': 2.0, 'rate': 0.5, 'max_... | 3,445 | 35.659574 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_computational_graph.py | import os
import shutil
import tempfile
import unittest
import numpy
import chainer
from chainer import configuration
from chainer import links
from chainer import testing
from chainer import training
from chainer.training.extensions import computational_graph as c
class Function1(chainer.FunctionNode):
def fo... | 3,109 | 25.355932 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_step_shift.py | import unittest
import mock
from chainer import testing
from chainer import training
from chainer.training import extensions
@testing.parameterize(
{'init': 2.0, 'gamma': 0.5, 'step': 2, 'target': None,
'expect': [2.0, 2.0, 1.0, 1.0, 0.5, 0.5]},
{'init': 2.0, 'gamma': 0.5, 'step': 2, 'target': 1.2,
... | 3,172 | 34.651685 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_exponential_shift.py | import unittest
import mock
from chainer import testing
from chainer.training import extensions
from chainer.training import util
@testing.parameterize(
{'init': 2.0, 'rate': 0.5, 'target': None, 'expect': [2.0, 1.0, 0.5]},
{'init': 2.0, 'rate': 0.5, 'target': 1.2, 'expect': [2.0, 1.2, 1.2]},
{'init': -... | 3,169 | 33.835165 | 78 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_warmup_shift.py | import unittest
import mock
from chainer import testing
from chainer.training import extensions
from chainer.training import util
@testing.parameterize(
{'init': 1, 'warmup_start': 0.1,
'warmup_iter': 100, 'expect': [0.1, 0.991, 1, 1]},
{'init': 0.1, 'warmup_start': 1,
'warmup_iter': 10, 'expect':... | 2,688 | 33.922078 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_inverse_shift.py | import unittest
import mock
from chainer import testing
from chainer.training import extensions
from chainer.training import util
@testing.parameterize(
{'init': 3.0, 'gamma': 1.0, 'power': 1.0, 'target': None,
'expect': [3.0, 1.5, 1.0]},
{'init': 3.0, 'gamma': 1.0, 'power': 1.0, 'target': 1.8,
'e... | 3,344 | 33.132653 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_multistep_shift.py | import unittest
import mock
from chainer import testing
from chainer.training import extensions
from chainer.training import util
@testing.parameterize(
{'init': 2.0, 'gamma': 0.1, 'step_value': [1, 3, 5],
'expect': [2.0, 0.2, 0.2, 0.02, 0.02, 0.002]},
{'init': -2.0, 'gamma': 0.1, 'step_value': [1, 3, ... | 2,641 | 35.191781 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_variable_statistics_plot.py | import os
import unittest
import numpy
import six
import chainer
from chainer import testing
from chainer.training import extensions
try:
import matplotlib
_available = True
except ImportError:
_available = False
class TestVariableStatisticsPlot(unittest.TestCase):
def setUp(self):
stop_t... | 3,260 | 30.970588 | 77 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/extensions_tests/test_snapshot_writers.py | import multiprocessing
import threading
import unittest
import mock
from chainer import testing
from chainer.training.extensions import snapshot_writers
from chainer import utils
snapshot_writers_path = 'chainer.training.extensions.snapshot_writers'
class TestSimpleWriter(unittest.TestCase):
def test_call(se... | 3,292 | 30.970874 | 72 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/test_multiprocess_parallel_updater.py | import copy
import os
import subprocess
import sys
import unittest
import numpy
import chainer
from chainer.backends import cuda
import chainer.functions.math.minmax
from chainer import initializers
import chainer.reporter
from chainer import testing
from chainer.testing import attr
import chainer.training.updaters.m... | 7,820 | 33.152838 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/test_standard_updater.py | import contextlib
import unittest
import mock
import numpy
import pytest
import chainer
from chainer import backend
from chainer.backends import _cpu
from chainer.backends import cuda
from chainer import dataset
from chainer import testing
from chainer.testing import attr
from chainer import training
class DummyIte... | 23,542 | 31.031293 | 78 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/snippets/cuda_init.py | import multiprocessing
import sys
import numpy
import chainer
from chainer.backends import cuda
import chainer.training.updaters.multiprocess_parallel_updater as mpu
class SimpleNetChild(chainer.Chain):
def __init__(self):
super(SimpleNetChild, self).__init__()
with self.init_scope():
... | 1,831 | 25.550725 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/snippets/raw_array.py | import sys
import numpy
import chainer
from chainer import testing
import chainer.training.updaters.multiprocess_parallel_updater as mpu
class SimpleNetRawArray(chainer.Chain):
def __init__(self):
super(SimpleNetRawArray, self).__init__()
with self.init_scope():
self.conv = chainer.... | 1,736 | 24.925373 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/updaters_tests/snippets/child_reporter.py | import sys
import numpy
import chainer
from chainer.training import trainer
import chainer.training.updaters.multiprocess_parallel_updater as mpu
class SimpleNetChild(chainer.Chain):
def __init__(self):
super(SimpleNetChild, self).__init__()
with self.init_scope():
self.conv = chain... | 1,953 | 25.767123 | 76 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py | from __future__ import division
import random
import tempfile
import unittest
import numpy as np
from chainer import serializers
from chainer import testing
from chainer.testing import condition
from chainer import training
@testing.parameterize(
# iteration
{
'iter_per_epoch': 5, 'interval': (2, '... | 5,498 | 38.847826 | 71 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_once_trigger.py | from __future__ import division
import random
import tempfile
import unittest
import numpy as np
from chainer import serializers
from chainer import testing
from chainer.testing import condition
from chainer import training
@testing.parameterize(
# basic
{
'iter_per_epoch': 5, 'call_on_resume': Fal... | 6,616 | 43.113333 | 79 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py | from __future__ import division
import random
import tempfile
import unittest
import numpy as np
import six
from chainer import serializers
from chainer import testing
from chainer.testing import condition
from chainer import training
def expected_finished(pos, num):
return [i >= pos for i in six.moves.range(n... | 7,675 | 42.613636 | 77 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_minmax_trigger.py | import tempfile
import unittest
from chainer import serializers
from chainer import testing
from chainer.training import triggers
class BestValueTriggerTester(object):
def _test_trigger(self, trigger, key, accuracies, expected,
resume=None, save=None):
trainer = testing.get_trainer_... | 5,906 | 32.948276 | 78 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_time_trigger.py | import io
import unittest
import chainer
from chainer import testing
class DummyTrainer(object):
def __init__(self):
self.elapsed_time = 0
class TestTimeTrigger(unittest.TestCase):
def setUp(self):
self.trigger = chainer.training.triggers.TimeTrigger(1)
self.trainer = DummyTrainer... | 1,301 | 25.04 | 74 | py |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/training_tests/triggers_tests/test_early_stopping_trigger.py | import unittest
import numpy
import pytest
import chainer
from chainer import testing
from chainer.training import triggers
from chainer.training import util
def _test_trigger(self, trigger, key, accuracies, expected):
trainer = testing.training.get_trainer_with_mock_updater(
stop_trigger=None, iter_per... | 3,914 | 35.588785 | 78 | py |
chainer | chainer-master/tests/chainer_tests/link_hooks_tests/test_spectral_normalization.py | import copy
import os
import unittest
import numpy
import pytest
import chainer
from chainer.backends import _cpu
from chainer.link_hooks.spectral_normalization import SpectralNormalization
import chainer.links as L
from chainer import serializers
from chainer import testing
from chainer.testing import attr
from chai... | 13,406 | 34.468254 | 75 | py |
chainer | chainer-master/tests/chainer_tests/link_hooks_tests/test_timer.py | import re
import unittest
import numpy
import six
import chainer
from chainer.backends import cuda
from chainer import link_hooks
from chainer import testing
from chainer.testing import attr
class MyModel(chainer.Chain):
def __init__(self):
super(MyModel, self).__init__()
with self.init_scope()... | 2,553 | 27.065934 | 73 | py |
chainer | chainer-master/tests/chainer_tests/link_hooks_tests/test_weight_standardization.py | import unittest
import numpy
import pytest
import chainer
from chainer.backends import cuda
from chainer.link_hooks.weight_standardization import WeightStandardization
import chainer.links as L
from chainer import testing
from chainer.testing import attr
class TestExceptions(unittest.TestCase):
def setUp(self)... | 5,969 | 31.445652 | 75 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/test_convert.py | import pickle
import sys
import unittest
import numpy
import pytest
from chainer import backend
from chainer.backends import cuda
from chainer import dataset
from chainer import testing
from chainer.testing import attr
import chainer.testing.backend # NOQA
import chainerx
_inject_backend_tests = testing.backend.in... | 16,187 | 36.299539 | 79 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/test_dataset_mixin.py | import unittest
import numpy
from chainer import dataset
from chainer import testing
class SimpleDataset(dataset.DatasetMixin):
def __init__(self, values):
self.values = values
def __len__(self):
return len(self.values)
def get_example(self, i):
return self.values[i]
class T... | 3,128 | 36.25 | 70 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/dataset_tests/test_download.py | import os
import shutil
import tempfile
import unittest
import mock
from chainer import dataset
from chainer import testing
class TestGetSetDatasetRoot(unittest.TestCase):
def test_set_dataset_root(self):
orig_root = dataset.get_dataset_root()
new_root = '/tmp/dataset_root'
try:
... | 4,757 | 29.305732 | 75 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_join.py | import unittest
import numpy as np
import six
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
def _filter_params(params):
for param in params:
key_size = 0
key_size += 3 if param['mode_a'] else 1
key_size += 2 if param['mode_... | 3,492 | 30.1875 | 78 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_tabular_dataset.py | import unittest
import numpy as np
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
@testing.parameterize(*testing.product({
'mode': [tuple, dict, None],
'return_array': [True, False],
}))
class TestTabularDataset(unittest.TestCase):
def test_fetch(self):
... | 3,126 | 30.908163 | 78 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_slice.py | import unittest
import warnings
import numpy as np
import six
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
def _filter_params(params):
for param in params:
if 'expected_len' in param and \
isinstance(param['get_examples_indices... | 6,953 | 35.6 | 78 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_concat.py | import operator
import unittest
import numpy as np
import six
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
@testing.parameterize(*testing.product_dict(
testing.product({
'mode_a': [tuple, dict, None],
'mode_b': [tuple, dict, None]... | 3,352 | 31.872549 | 68 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_transform.py | import unittest
import numpy as np
import six
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
# filter out invalid combinations of params
def _filter_params(params):
for param in params:
if param['out_mode'] is None and \
isinstan... | 5,484 | 30.705202 | 76 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/dummy_dataset.py | import numpy as np
import chainer
from chainer import testing
class DummyDataset(chainer.dataset.TabularDataset):
def __init__(
self, size=10, keys=('a', 'b', 'c'), mode=tuple,
return_array=False, callback=None, convert=False):
if mode is None:
keys = keys[0],
... | 1,382 | 22.844828 | 62 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_with_converter.py | import unittest
import numpy as np
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
@testing.parameterize(
{'mode': tuple},
{'mode': dict},
{'mode': None},
)
class TestWithConverter(unittest.TestCase):
def test_with_converter(self):
... | 1,413 | 30.422222 | 76 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_asmode.py | import unittest
import chainer
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
@testing.parameterize(
{'mode': tuple},
{'mode': dict},
{'mode': None},
)
class TestAstuple(unittest.TestCase):
def test_astuple(self):
dataset = dummy_dataset.Dummy... | 1,451 | 29.893617 | 76 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_from_data.py | import unittest
import numpy as np
import chainer
from chainer.dataset import tabular
from chainer import testing
class TestFromData(unittest.TestCase):
def test_unary_array(self):
dataset = tabular.from_data(np.arange(10))
self.assertIsInstance(dataset, chainer.dataset.TabularDataset)
... | 12,247 | 38.25641 | 79 | py |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/dataset_tests/tabular_tests/test_delegate_dataset.py | import unittest
import chainer
from chainer.dataset import tabular
from chainer import testing
from chainer_tests.dataset_tests.tabular_tests import dummy_dataset
@testing.parameterize(
{'mode': tuple},
{'mode': dict},
{'mode': None},
)
class TestDelegateDataset(unittest.TestCase):
def test_delegat... | 826 | 26.566667 | 70 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_condition.py | import unittest
import pytest
from chainer import testing
from chainer.testing import condition
SKIP_REASON = 'test skip reason'
# The test fixtures of this TestCase is used to be decorated by
# decorator in test. So we do not run them alone.
class MockUnitTest(unittest.TestCase):
failure_case_counter = 0
... | 7,056 | 31.37156 | 78 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_training.py | from __future__ import division
import math
import unittest
from chainer import testing
def _dummy_extension(trainer):
pass
@testing.parameterize(*testing.product({
'stop_trigger': [(5, 'iteration'), (5, 'epoch')],
'iter_per_epoch': [0.5, 1, 1.5, 5],
'extensions': [[], [_dummy_extension]]
}))
clas... | 1,768 | 28.983051 | 77 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_unary_math_function_test.py | import unittest
from chainer import function_node
from chainer import testing
def dummy():
pass
class TestNoNumpyFunction(unittest.TestCase):
def test_no_numpy_function(self):
with self.assertRaises(ValueError):
testing.unary_math_function_unittest(dummy) # no numpy.dummy
class Dumm... | 809 | 18.285714 | 73 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_parameterized.py | import unittest
from chainer import testing
@testing.parameterize(
{'actual': {'a': [1, 2], 'b': [3, 4, 5]},
'expect': [{'a': 1, 'b': 3}, {'a': 1, 'b': 4}, {'a': 1, 'b': 5},
{'a': 2, 'b': 3}, {'a': 2, 'b': 4}, {'a': 2, 'b': 5}]},
{'actual': {'a': [1, 2]}, 'expect': [{'a': 1}, {'a': 2}]},... | 2,822 | 29.031915 | 79 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_matrix.py | import unittest
import numpy
from chainer import testing
from chainer.testing import matrix
@testing.parameterize(*testing.product({
'dtype': [
numpy.float16, numpy.float32, numpy.float64,
numpy.complex64, numpy.complex128,
],
'x_s_shapes': [
((0, 0), (0,)),
((2, 2), (2,)... | 2,480 | 28.535714 | 79 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_array.py | import unittest
import numpy
import pytest
from chainer import testing
# TODO(niboshi): Add more assert_allclose tests
class TestAssertAllClose(unittest.TestCase):
def test_no_zero_division(self):
# No zero-division should occur when the relative error is inf (y=0).
# That would cause Floatin... | 663 | 24.538462 | 77 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_serializer.py | import unittest
from chainer.serializers import hdf5
from chainer import testing
class Serializable(object):
def __init__(self, value):
self.value = value
def serialize(self, serializer):
self.value = serializer('value', self.value)
class TestSaveAndLoad(unittest.TestCase):
def setUp... | 782 | 22.727273 | 66 | py |
chainer | chainer-master/tests/chainer_tests/testing_tests/test_function_link.py | import unittest
import numpy
import pytest
import six
import chainer
from chainer import initializers
from chainer import testing
from chainer import utils
import chainerx
# Utilities for contiguousness tests.
#
# These tests checks incoming array contiguousness.
# As it's not possible to assume contiguousness of i... | 30,426 | 32.036916 | 79 | py |
chainer | chainer-master/tests/chainer_tests/exporters_tests/test_caffe.py | import os
import unittest
import warnings
import numpy
import chainer
import chainer.functions as F
import chainer.links as L
from chainer import testing
# The caffe submodule relies on protobuf which under protobuf==3.7.0 and
# Python 3.7 raises a DeprecationWarning from the collections module.
with warnings.catch... | 4,411 | 28.218543 | 78 | py |
chainer | chainer-master/tests/chainer_tests/exporters_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_categorical.py | import numpy
from chainer import cuda
from chainer import distributions
from chainer import testing
from chainer.testing import array
@testing.parameterize(*testing.product({
'shape': [(3, 2), (1,)],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
# 'extreme_values': [True, False],
'e... | 4,637 | 35.234375 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_one_hot_categorical.py | import numpy
from chainer import cuda
from chainer import distributions
from chainer import testing
def _numpy_stack(xs, axis):
try:
return numpy.stack(xs, axis)
except AttributeError:
# in case numpy<1.10, which does not have numpy.stack
return numpy.concatenate(
[numpy.e... | 2,892 | 30.445652 | 78 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_normal.py | import numpy
from chainer import distributions
from chainer import testing
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
'log_scale_option': [True, False],
}))
@testing.fix_random()
@testing.with_r... | 1,680 | 31.960784 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_independent.py | import functools
import itertools
import operator
import numpy
from chainer import distributions
from chainer import testing
from chainer.testing import array
from chainer.testing import attr
from chainer import utils
def skip_not_in_params(property):
def decorator(f):
@functools.wraps(f)
def ne... | 4,547 | 30.365517 | 76 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_cauchy.py | import numpy
from chainer.backends import cuda
from chainer import distributions
from chainer import testing
from chainer.testing import array
from chainer.testing import attr
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_s... | 3,681 | 31.298246 | 77 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_chisquare.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestChisquare(testing.distribution_unittes... | 1,045 | 24.512195 | 73 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_laplace.py | import unittest
import numpy
from chainer.backends import cuda
from chainer import distributions
from chainer import gradient_check
from chainer import testing
from chainer.testing import attr
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, Fal... | 3,310 | 29.657407 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_poisson.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestLogNormal(testing.distribution_unittes... | 1,072 | 25.170732 | 77 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_beta.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestBeta(testing.distribution_unittest):
... | 1,105 | 25.97561 | 73 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_bernoulli.py | import unittest
import numpy
from chainer import backend
from chainer.backends import cuda
from chainer import distributions
from chainer import gradient_check
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
'shape': [(3, 2), (1,)],
'is_variable': [True,... | 5,780 | 31.477528 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_gamma.py | import numpy
from chainer import distributions
from chainer import testing
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestGamma(testin... | 1,236 | 26.488889 | 73 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_dirichlet.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestDirichlet(testing.distribution_unittes... | 1,151 | 26.428571 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_exponential.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestLogNormal(testing.distribution_unittes... | 1,128 | 25.880952 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_pareto.py | import numpy
from chainer import cuda
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestPareto(testin... | 2,040 | 29.924242 | 77 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_kldivergence.py | import unittest
import numpy
import chainer
from chainer.backends import cuda
from chainer import distributions
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
'shape': [(3, 2), (1,)],
'is_variable': [True, False],
}))
@testing.fix_random()
class TestKLD... | 13,849 | 37.049451 | 78 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_uniform.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
'use_loc_scale': [True, False],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestUn... | 1,626 | 30.288462 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_gumbel.py | import numpy
from chainer import distributions
from chainer import testing
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestGumbel(testi... | 1,210 | 27.833333 | 75 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_log_normal.py | import numpy
from chainer import distributions
from chainer import testing
from chainer import utils
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestLogNormal(te... | 1,258 | 27.613636 | 74 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_multivariate_normal.py | import unittest
import numpy
from chainer import cuda
from chainer import distributions
from chainer import gradient_check
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
'shape': [(3, 2), (1,)],
'is_variable': [True, False],
'sample_shape': [(3, 2),... | 4,670 | 30.77551 | 79 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_geometric.py | import numpy
from chainer import distributions
from chainer import testing
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'is_variable': [True, False],
'sample_shape': [(3, 2), ()],
}))
@testing.fix_random()
@testing.with_requires('scipy')
class TestGeometric(testing.distribution_unittes... | 1,055 | 24.756098 | 72 | py |
chainer | chainer-master/tests/chainer_tests/distributions_tests/test_utils.py | import unittest
import numpy
import chainer
from chainer.backends import cuda
from chainer import distributions
from chainer import gradient_check
from chainer import testing
from chainer.testing import attr
@testing.parameterize(*testing.product({
'shape': [(2, 3), ()],
'dtype': [numpy.float32, numpy.float... | 2,540 | 31.164557 | 77 | py |
chainer | chainer-master/tests/chainer_tests/iterators_tests/test_iterator_compatibility.py | from __future__ import division
import itertools
import unittest
from chainer import iterators
from chainer import serializers
from chainer import testing
@testing.parameterize(*testing.product({
'n_prefetch': [1, 2],
'shared_mem': [None, 1000000],
}))
class TestIteratorCompatibility(unittest.TestCase):
... | 2,074 | 31.936508 | 79 | py |
chainer | chainer-master/tests/chainer_tests/iterators_tests/test_multiprocess_iterator.py | from __future__ import division
import copy
import errno
import os
import pickle
import platform
import signal
import subprocess
import sys
import tempfile
import threading
import time
import unittest
import numpy
import six
from chainer import iterators
from chainer import serializers
from chainer import testing
fro... | 32,393 | 36.755245 | 78 | py |
chainer | chainer-master/tests/chainer_tests/iterators_tests/test_serial_iterator.py | from __future__ import division
import unittest
import numpy
from chainer import iterators
from chainer import serializers
from chainer import testing
class TestSerialIterator(unittest.TestCase):
def test_iterator_repeat(self):
dataset = [1, 2, 3, 4, 5, 6]
it = iterators.SerialIterator(dataset,... | 15,833 | 39.70437 | 78 | py |
chainer | chainer-master/tests/chainer_tests/iterators_tests/test_multithread_iterator.py | from __future__ import division
import copy
import unittest
import numpy
import six
from chainer import iterators
from chainer import serializers
from chainer import testing
@testing.parameterize(*testing.product({
'n_threads': [1, 2],
'order_sampler': [
None, lambda order, _: numpy.random.permutati... | 14,934 | 37.002545 | 76 | py |
chainer | chainer-master/tests/chainer_tests/iterators_tests/__init__.py | 0 | 0 | 0 | py |
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