def test_per_pixel_conditional_conv_depth3(self):
# From the paper https://arxiv.org/abs/2003.05664
out = deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, 10)), tf.zeros((10, 169)), 8, 3)
self.assertEqual(out.shape, (10, 32, 32, 1))
def test_per_pixel_conditional_conv_depth2(self):
num_params = (
7 * 9 + 9 + # layer 1
9 + 1) # layer 2
out = deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, 7)), tf.zeros((10, num_params)), 9, 2)
self.assertEqual(out.shape, (10, 32, 32, 1))
def test_per_pixel_conditional_conv_shape(self, num_input_channels,
instance_embedding_dim, channels,
depth):
out = deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, num_input_channels)),
tf.zeros((10, instance_embedding_dim)), channels, depth)
self.assertEqual(out.shape, (10, 32, 32, 1))
def test_per_pixel_conditional_conv_value_depth2_single(self):
input_tensor = tf.constant(np.array([2]))
input_tensor = tf.reshape(input_tensor, (1, 1, 1, 1))
instance_embedding = tf.constant(np.array([-2, 3, 100, 5]))
instance_embedding = tf.reshape(instance_embedding, (1, 4))
out = deepmac_meta_arch.per_pixel_conditional_conv(input_tensor,
instance_embedding,
channels=1,
depth=2)
expected_output = np.array([5])
expected_output = np.reshape(expected_output, (1, 1, 1, 1))
self.assertAllClose(expected_output, out)
def test_per_pixel_conditional_conv_value_depth1(self):
input_tensor = tf.constant(np.array([1, 2, 3]))
input_tensor = tf.reshape(input_tensor, (1, 1, 1, 3))
instance_embedding = tf.constant(np.array([1, 10, 100, 1000]))
instance_embedding = tf.reshape(instance_embedding, (1, 4))
out = deepmac_meta_arch.per_pixel_conditional_conv(input_tensor,
instance_embedding,
channels=3,
depth=1)
expected_output = np.array([1321])
expected_output = np.reshape(expected_output, (1, 1, 1, 1))
self.assertAllClose(expected_output, out)
def test_per_pixel_conditional_conv_value_depth2_identity(self):
input_tensor = tf.constant(np.array([1, 2]))
input_tensor = tf.reshape(input_tensor, (1, 1, 1, 2))
instance_embedding = tf.constant(
np.array([1, 0, 0, 1, 1, -3, 5, 100, -9]))
instance_embedding = tf.reshape(instance_embedding, (1, 9))
out = deepmac_meta_arch.per_pixel_conditional_conv(input_tensor,
instance_embedding,
channels=2,
depth=2)
expected_output = np.array([1])
expected_output = np.reshape(expected_output, (1, 1, 1, 1))
self.assertAllClose(expected_output, out)
def test_per_pixel_conditional_conv_depth1(self):
out = deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, 7)), tf.zeros((10, 8)), 7, 1)
self.assertEqual(out.shape, (10, 32, 32, 1))
def test_per_pixel_conditional_conv_depth1_error(self):
with self.assertRaises(ValueError):
_ = deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, 7)), tf.zeros((10, 8)), 99, 1)
def test_per_pixel_conditional_conv_error(self):
with self.assertRaises(ValueError):
deepmac_meta_arch.per_pixel_conditional_conv(
tf.zeros((10, 32, 32, 8)), tf.zeros((10, 2)), 8, 3)
