def outputs()

in optimum/exporters/neuron/model_configs.py [0:0]

• 18 lines of code
• 13 McCabe index (conditional complexity)

    def outputs(self) -> List[str]:
        beam_outputs = ["next_token_scores", "next_tokens", "next_indices"] if self.num_beams > 1 else ["next_tokens"]
        common_outputs = (
            beam_outputs
            + [f"past.{idx}.self.key" for idx in range(self._config.num_decoder_layers)]
            + [f"past.{idx}.self.value" for idx in range(self._config.num_decoder_layers)]
            + [f"past.{idx}.cross.key" for idx in range(self._config.num_decoder_layers)]
            + [f"past.{idx}.cross.value" for idx in range(self._config.num_decoder_layers)]
        )

        if self.output_hidden_states:
            # Flatten hidden states of all layers
            common_outputs += [
                f"decoder_hidden_state.{idx}" for idx in range(self._config.num_decoder_layers + 1)
            ]  # +1 for the embedding layer

        if self.output_attentions:
            # Flatten attentions tensors of all attention layers
            common_outputs += [f"decoder_attention.{idx}" for idx in range(self._config.num_decoder_layers)]
            if getattr(self._config, "is_encoder_decoder", False) is True:
                common_outputs += [f"cross_attention.{idx}" for idx in range(self._config.num_decoder_layers)]

        return common_outputs