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

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

        Returns
        -------
        step_output : NDArray or Symbol
            The output of the decoder. Shape is (batch_size, C_out)
        new_states: list
            Includes

            - rnn_states : list of NDArray or Symbol
            - attention_vec : NDArray or Symbol, Shape (batch_size, C_memory)
            - mem_value : NDArray
            - mem_masks : NDArray, optional

        step_additional_outputs : list
            Either be an empty list or contains the attention weights in this step.
            The attention weights will have shape (batch_size, 1, mem_length) or
            (batch_size, num_heads, 1, mem_length)