You are in the process of creating an ML model that aims to classify X-ray images to assess the risk of bone fractures. You've already trained a ResNet model on Vertex AI using a TPU as an accelerator, but you're not satisfied with the training time and memory usage. Your goal is to rapidly iterate on the training code with minimal code modifications and without significantly affecting the model's accuracy. What steps should you take to achieve this?