src/transformers/models/blenderbot/modeling_flax_blenderbot.py/FlaxBlenderbotModule/__call__
class FlaxBlenderbotModule:    def __call__(
        self,
        input_ids,
        attention_mask,
        decoder_input_ids,
        decoder_attention_mask,
        position_ids,
        decoder_position_ids,
        output_attentions: bool = False,
        output_hidden_states: bool = False,
        return_dict: bool = True,
        deterministic: bool = True,
    ):
        encoder_outputs = self.encoder(
            input_ids=input_ids,
            attention_mask=attention_mask,
            position_ids=position_ids,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
            deterministic=deterministic,
        )

        decoder_outputs = self.decoder(
            input_ids=decoder_input_ids,
            attention_mask=decoder_attention_mask,
            position_ids=decoder_position_ids,
            encoder_hidden_states=encoder_outputs[0],
            encoder_attention_mask=attention_mask,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
            deterministic=deterministic,
        )

        if not return_dict:
            return decoder_outputs + encoder_outputs

        return FlaxSeq2SeqModelOutput(
            last_hidden_state=decoder_outputs.last_hidden_state,
            decoder_hidden_states=decoder_outputs.hidden_states,
            decoder_attentions=decoder_outputs.attentions,
            cross_attentions=decoder_outputs.cross_attentions,
            encoder_last_hidden_state=encoder_outputs.last_hidden_state,
            encoder_hidden_states=encoder_outputs.hidden_states,
            encoder_attentions=encoder_outputs.attentions,
        )