def test_transpose(self):
"""Test that Transpose can be invoked."""
in_dim_1 = 2
in_dim_2 = 7
batch_size = 10
in_tensor = np.random.rand(batch_size, in_dim_1, in_dim_2)
with self.session() as sess:
in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)
out_tensor = Transpose((0, 2, 1))(in_tensor)
out_tensor = out_tensor.eval()
assert out_tensor.shape == (batch_size, in_dim_2, in_dim_1)
def test_transpose(self):
"""Test that Transpose can be invoked."""
in_dim_1 = 2
in_dim_2 = 7
batch_size = 10
in_tensor = np.random.rand(batch_size, in_dim_1, in_dim_2)
with self.session() as sess:
in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)
out_tensor = Transpose((0, 2, 1))(in_tensor)
out_tensor = out_tensor.eval()
assert out_tensor.shape == (batch_size, in_dim_2, in_dim_1)
def test_Transpose_pickle(): tg = TensorGraph() feature = Feature(shape=(tg.batch_size, 1)) layer = Transpose(perm=(1, 0), in_layers=feature) tg.add_output(layer) tg.set_loss(layer) tg.build() tg.save()
