src/transformers/models/regnet/modeling_tf_regnet.py/TFRegNetModel/serving_output
class TFRegNetModel:    def serving_output(
        self, output: TFBaseModelOutputWithPoolingAndNoAttention
    ) -> TFBaseModelOutputWithPoolingAndNoAttention:
        # hidden_states not converted to Tensor with tf.convert_to_tensor as they are all of different dimensions
        return TFBaseModelOutputWithPoolingAndNoAttention(
            last_hidden_state=output.last_hidden_state,
            pooler_output=output.pooler_output,
            hidden_states=output.hidden_states,
        )