code: def get_model_parallel_src_rank() -> int:
      """Calculate the global rank corresponding to a local rank zero
      in the model parallel group."""
      global_rank = torch.distributed.get_rank()
      local_world_size = get_model_parallel_world_size()
      return (global_rank // local_world_size) * local_world_size
  
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 9 for calling a global function with example usage: get_model_parallel_src_rank() and returns: unknown