VideoAI stores 40 TB of raw video frames in S3 and trains on GPU instances that have only 1 TB of instance storage. Their training loop reads the dataset sequentially for several epochs and can stream records from stdin-compatible interfaces. Which SageMaker input mode should they choose and why?

Pipe mode (InputMode='Pipe') is the correct choice because it allows the training container to stream data directly from S3. This is crucial when the dataset (40 TB) is significantly larger than the instance storage (1 TB), preventing out-of-disk errors. Since the training loop reads data sequentially and the algorithm supports streaming, Pipe mode efficiently delivers data without needing to download the entire dataset upfront. File mode (InputMode='File') is incorrect because it downloads the entire dataset to the instance storage before training, which would fail given the size mismatch. SageMaker does not automatically extend instance disk for File mode to accommodate datasets larger than the instance store. Setting EBSVolumeSize to 50 TB with Pipe mode is unnecessary and inefficient; Pipe mode's benefit is streaming, not persistent storage on the instance for the entire dataset. Mounting S3 as a POSIX filesystem is not a standard SageMaker input mode and would still involve data transfer overhead, potentially impacting performance.