code: def get_data_parallel_rank() -> int:
      """Return my rank for the data parallel group."""
      return torch.distributed.get_rank(group=get_data_parallel_group())
  
file_path: fairscale/fairscale/nn/model_parallel/initialize.py
imports: from typing import List, Optional
  import torch
  from .utils import ensure_divisibility
label_desc: Use image node_id 11 for calling a global function with example usage: get_data_parallel_rank() and returns: torch