def test_downsample_jacobian_random(self):
"""Tests the Jacobian for random inputs."""
downsample = lambda image: pyramid.downsample(image, num_levels=_NUM_LEVELS)
tensor_shape = np.random.randint(1, 5, size=4).tolist()
image_random_init = np.random.uniform(size=tensor_shape)
for level in range(_NUM_LEVELS):
self.assert_jacobian_is_correct_fn(
lambda x, level=level: downsample(x)[level], [image_random_init])
def test_downsample_jacobian_random(self):
"""Tests the Jacobian for random inputs."""
downsample = lambda image: pyramid.downsample(image, num_levels=4)
tensor_shape = np.random.randint(1, 5, size=(4)).tolist()
image_random_init = np.random.uniform(size=tensor_shape)
image_random = tf.convert_to_tensor(value=image_random_init)
downsample_random = downsample(image_random)
for level in downsample_random:
self.assert_jacobian_is_correct(image_random, image_random_init,
level)
def test_downsample_preset(self, image_high, image_low):
"""Tests that the downsample works as expected."""
downsample = lambda image: pyramid.downsample(image, num_levels=1)
image_high = tf.expand_dims(tf.expand_dims(image_high, axis=-1), axis=0)
image_low = tf.expand_dims(tf.expand_dims(image_low, axis=-1), axis=0)
pyr = downsample(image_high)
with self.subTest(name="image_high"):
self.assertAllClose(image_high, pyr[0])
with self.subTest(name="image_low"):
self.assertAllClose(image_low, pyr[1])
def test_downsample_jacobian_random(self):
"""Tests the Jacobian for random inputs."""
downsample = lambda image: pyramid.downsample(image,
num_levels=_NUM_LEVELS)
tensor_shape = np.random.randint(1, 5, size=4).tolist()
image_random_init = np.random.uniform(size=tensor_shape)
for level in range(_NUM_LEVELS):
# We skip testing level = 0, which returns the image as is. In graph mode,
# the gradient calculation fails when there are no nodes in the graph.
if level == 0 and not tf.executing_eagerly():
continue
self.assert_jacobian_is_correct_fn(
lambda x, level=level: downsample(x)[level],
[image_random_init])
def test_downsample_exception_raised(self, error_msg, *shape):
"""Tests that the shape exceptions are properly raised."""
downsample = lambda image: pyramid.downsample(image,
num_levels=_NUM_LEVELS)
self.assert_exception_is_raised(downsample, error_msg, shape)
def test_downsample_exception_not_raised(self, *shape):
"""Tests that the shape exceptions are not raised."""
downsample = lambda image: pyramid.downsample(image,
num_levels=_NUM_LEVELS)
self.assert_exception_is_not_raised(downsample, shape)
