You are part of an AI team at an automobile company working on developing a visual defect detection model. This model is being built using TensorFlow and Keras. To enhance the performance of your model, you aim to include several image augmentation techniques, such as translation, cropping, and contrast adjustments. These functions should be applied randomly to each batch of training data. Your goal is to optimize the data processing pipeline for both runtime efficiency and optimal utilization of compute resources. What approach would you take?