A training job reads the same large immutable dataset each epoch and repeatedly waits on remote input. Which approach best fits?

1. Evaluate a supported model-parallel or sharded training strategy.
2. Profile and optimize the input pipeline with suitable caching and parallelism.
3. Evaluate data-parallel distributed training.
4. Use a bounded, tracked hyperparameter tuning strategy.