How to inference with data parallelism and model parallelism[BUG]

Describe the bug
I try to use inference with model parallelism and data parallelism, but it seems something wrong

logger.info("DeepSpeed Inference Initialization")
model = LlamaForCausalLM.from_pretrained(ckpt_path, device_map='cpu', torch_dtype=model_dtype)
if is_pipeline:
       model = pipeline("text-generation",
       model=model,
       tokenizer=tokenizer,
       torch_dtype=model_dtype)
       model.model = deepspeed.init_inference(
              model.model,
              mp_size = model_parallel_size,
              dtype=model_dtype,
              replace_with_kernel_inject=False
       )
       model.device = torch.device(f"cuda:{int(os.environ.get('LOCAL_RANK', 0))}")

command line: deepspeed --include localhost:4,5,6,7 --master_addr=127.0.0.1 --master_port=29501 run_inference_model_parallelism.py

The text above is main code. model_parallel_size is 2, and num_gpus is 4.

Got the warning below:
/anaconda3/lib/python3.9/site-packages/torch/distributed/distributed_c10d.py:278: UserWarning: Running all_reduce on global rank 3 which does not belong to the given group.
/anaconda3/lib/python3.9/site-packages/torch/distributed/distributed_c10d.py:278: UserWarning: Running all_reduce on global rank 2 which does not belong to the given group.

Start by reproducing the shown inference setup with model_parallel_size=2 on GPUs 4–7 using the provided DeepSpeed command. Inspect how ranks are assigned to the model-parallel group around the reported all_reduce warnings; done means the configuration runs without warnings and performs inference as intended.