def decode_seq(self, inputs, states, valid_length=None):
        """Decode given the input sequence.

        Parameters
        ----------
        inputs : NDArray
        states : list of NDArrays
        valid_length : NDArray or None, default None

        Returns
        -------
        output : NDArray
            The output of the decoder. Shape is (batch_size, length, tgt_word_num)
        states: list
            The new states of the decoder
        additional_outputs : list
            Additional outputs of the decoder, e.g, the attention weights
        """
        outputs, states, additional_outputs =\
            self.decoder.decode_seq(inputs=self.tgt_embed(inputs),
                                    states=states,
                                    valid_length=valid_length)
        outputs = self.tgt_proj(outputs)
        return outputs, states, additional_outputs
def decode_seq ( self , inputs , states , valid_length = None ) : outputs , states , additional_outputs = self . decoder . decode_seq ( inputs = self . tgt_embed ( inputs ) , states = states , valid_length = valid_length ) outputs = self . tgt_proj ( outputs ) return outputs , states , additional_outputs
Decode given the input sequence.

        Parameters
        ----------
        inputs : NDArray
        states : list of NDArrays
        valid_length : NDArray or None, default None

        Returns
        -------
        output : NDArray
            The output of the decoder. Shape is (batch_size, length, tgt_word_num)
        states: list
            The new states of the decoder
        additional_outputs : list
            Additional outputs of the decoder, e.g, the attention weights