def test_none_channels_mean():
# 3-D image
fn = mean_filter2d.get_concrete_function(
tf.TensorSpec(dtype=tf.dtypes.float32, shape=(3, 3, None)))
fn(tf.ones(shape=(3, 3, 1)))
fn(tf.ones(shape=(3, 3, 3)))
# 4-D image
fn = mean_filter2d.get_concrete_function(
tf.TensorSpec(dtype=tf.dtypes.float32, shape=(1, 3, 3, None)))
fn(tf.ones(shape=(1, 3, 3, 1)))
fn(tf.ones(shape=(1, 3, 3, 3)))
def test_unknown_shape_mean(shape):
fn = mean_filter2d.get_concrete_function(
tf.TensorSpec(shape=None, dtype=tf.dtypes.float32),
padding="CONSTANT",
constant_values=1.0,
)
image = tf.ones(shape=shape)
np.testing.assert_equal(image.numpy(), fn(image).numpy())
def test_unknown_shape(self):
fn = mean_filter2d.get_concrete_function(tf.TensorSpec(
shape=None, dtype=tf.dtypes.float32),
padding="CONSTANT",
constant_values=1.)
for shape in [(3, 3), (3, 3, 3), (1, 3, 3, 3)]:
image = tf.ones(shape=shape)
self.assertAllEqual(self.evaluate(image), self.evaluate(fn(image)))
