src/transformers/models/gpt2/modeling_tf_gpt2.py/TFGPT2LMHeadModel/serving_output
class TFGPT2LMHeadModel:    def serving_output(self, output):
        pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None
        hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
        attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
        cross_attns = (
            tf.convert_to_tensor(output.cross_attentions)
            if self.config.output_attentions
            and self.config.add_cross_attention
            and output.cross_attentions is not None
            else None
        )

        return TFCausalLMOutputWithCrossAttentions(
            logits=output.logits, past_key_values=pkv, hidden_states=hs, attentions=attns, cross_attentions=cross_attns
        )