[Edited to fix broken link]
@Angela Zhang Thanks for the question. The “score.py” exposed in trained_model_outputs is for customized deployment, only have model init and scoring logic, user can add their own pre-process and post-process code on top of that.
The scoring logic that having pre-process logic is available through Designer deployed web service, which can be on both AKS and ACI. You can follow this doc: Tutorial: Deploy ML models with the designer - Azure Machine Learning | Microsoft Learn.