You are running a machine learning model training pipeline on Vertex AI and encounter an out-of-memory error during the evaluation step. You are using TensorFlow Model Analysis (TFMA) with a standard Evaluator TensorFlow Extended (TFX) pipeline component for this evaluation. Your goal is to stabilize the pipeline without compromising evaluation quality and to minimize infrastructure overhead. What should you do to resolve the out-of-memory error?