[BUG] Pipeline Dataloader Sampler: `shuffle=False`

Describe the bug
When I read the source code of building the dataloader in PipelineEngine. I find shuffle=False in the sampler. Code:

sampler = torch.utils.data.distributed.DistributedSampler(dataset,
                                                                  num_replicas=self.dp_world_size,
                                                                  rank=self.mpu.get_data_parallel_rank(),
                                                                  shuffle=False)

I want to know why you set shuffle to False, not True.
The code is in deepspeed/runtime/pipe/engine.py, Pipeline Engine class, def _build_data_iter.

deepspeed version: 0.12.4

To Reproduce
Steps to reproduce the behavior:

1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error

Expected behavior
A clear and concise description of what you expected to happen.

ds_report output
Please run ds_report to give us details about your setup.

Screenshots
If applicable, add screenshots to help explain your problem.

System info (please complete the following information):

• OS: [e.g. Ubuntu 18.04]
• GPU count and types [e.g. two machines with x8 A100s each]
• Interconnects (if applicable) [e.g., two machines connected with 100 Gbps IB]
• Python version
• Any other relevant info about your setup

Launcher context
Are you launching your experiment with the deepspeed launcher, MPI, or something else?

Docker context
Are you using a specific docker image that you can share?

Additional context
Add any other context about the problem here.