def __call__(self, step_input, states): 
return super(TransformerDecoder, self).__call__(step_input, states)<EOL>
One-step-ahead decoding of the Transformer decoder.

        Parameters
        ----------
        step_input : NDArray
        states : list of NDArray

        Returns
        -------
        step_output : NDArray
            The output of the decoder.
            In the train mode, Shape is (batch_size, length, C_out)
            In the test mode, Shape is (batch_size, C_out)
        new_states: list
            Includes
            - last_embeds : NDArray or None
                It is only given during testing
            - mem_value : NDArray
            - mem_masks : NDArray, optional

        step_additional_outputs : list of list
            Either be an empty list or contains the attention weights in this step.
            The attention weights will have shape (batch_size, length, mem_length) or
            (batch_size, num_heads, length, mem_length)