def test_value_cifar_c(self, split):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig(
split, corruption_value=.25, corruption_type='brightness')
dataset = data_lib.build_dataset(config)
image_shape = next(iter(dataset))[0].numpy().shape
self.assertEqual(image_shape, data_lib.CIFAR_SHAPE)
def test_array_cifar_c(self, split):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig(
split, corruption_level=4, corruption_type='glass_blur')
dataset = data_lib.build_dataset(config)
image_shape = next(iter(dataset))[0].numpy().shape
self.assertEqual(image_shape, data_lib.CIFAR_SHAPE)
def test_roll_pixels(self, split):
config = image_data_utils.DataConfig(split, roll_pixels=5)
if not flags.FLAGS.fake_data:
dataset = data_lib.build_dataset(config, BATCH_SIZE)
image = next(iter(dataset))[0].numpy()
self.assertEqual(image.shape, BATCHED_IMAGES_SHAPE)
self.assertAllInRange(image, 0., 1.)
self.assertTrue((image > 1. / 255).any())
def test_fake_data(self, split):
# config is ignored for fake data
config = image_data_utils.DataConfig(split)
dataset = data_lib.build_dataset(config, BATCH_SIZE, fake_data=True)
image = next(iter(dataset))[0].numpy()
self.assertEqual(image.shape, BATCHED_IMAGES_SHAPE)
self.assertAllInRange(image, 0., 1.)
self.assertTrue((image > 1. / 255).any())
def test_alt_dataset(self):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig('test', alt_dataset_name='celeb_a')
dataset = data_lib.build_dataset(config, BATCH_SIZE)
image = next(iter(dataset))[0].numpy()
self.assertEqual(image.shape, BATCHED_IMAGES_SHAPE)
self.assertAllInRange(image, 0., 1.)
self.assertTrue((image > 1./255).any())
def test_value_imagenet_c(self, split):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig(
split, corruption_value=.25, corruption_type='brightness')
dataset = data_lib.build_dataset(config, BATCH_SIZE)
image = next(iter(dataset))[0].numpy()
self.assertEqual(image.shape, BATCHED_IMAGES_SHAPE)
self.assertAllInRange(image, 0., 1.)
self.assertTrue((image > 1./255).any())
def test_static_cifar_c(self, split):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig(
split, corruption_static=True, corruption_level=3,
corruption_type='pixelate')
if split in ['train', 'valid']:
with self.assertRaises(ValueError):
data_lib.build_dataset(config)
else:
dataset = data_lib.build_dataset(config)
image_shape = next(iter(dataset))[0].numpy().shape
self.assertEqual(image_shape, data_lib.CIFAR_SHAPE)
def test_static_imagenet_c(self, split):
if not flags.FLAGS.fake_data:
config = image_data_utils.DataConfig(
split, corruption_static=True, corruption_level=3,
corruption_type='pixelate')
if split in ['train', 'valid']:
with self.assertRaises(ValueError):
data_lib.build_dataset(config, BATCH_SIZE)
else:
dataset = data_lib.build_dataset(config, BATCH_SIZE)
image = next(iter(dataset))[0].numpy()
self.assertEqual(image.shape, BATCHED_IMAGES_SHAPE)
self.assertAllInRange(image, 0., 1.)
self.assertTrue((image > 1./255).any())
def test_roll_pixels(self, split):
config = image_data_utils.DataConfig(split, roll_pixels=5)
if not flags.FLAGS.fake_data:
dataset = data_lib.build_dataset(config)
image_shape = next(iter(dataset))[0].numpy().shape
self.assertEqual(image_shape, data_lib.CIFAR_SHAPE)
def test_fake_data(self, split):
# config is ignored for fake data
config = image_data_utils.DataConfig(split)
dataset = data_lib.build_dataset(config, fake_data=True)
image_shape = next(iter(dataset))[0].numpy().shape
self.assertEqual(image_shape, data_lib.CIFAR_SHAPE)
