class_docstr: Creates an adapter to make logging for multiple processes cleaner
class_docstr_tok: ["Creates","an","adapter","to","make","logging","for","multiple","processes","cleaner"]
code: def process(
      self, msg: str, kwargs: Any
  ) -> Tuple[str, MutableMapping[str, Any]]:
      # use process_num from kwargs or the default given on instantiation
      process_num = kwargs.pop("process_num", self.extra["process_num"])
      return f"process: {process_num} {msg}", kwargs
  
file_path: fairscale/fairscale/experimental/nn/data_parallel/gossip/utils/helpers.py
imports: import collections
  import logging
  import sys
  from typing import Any, Dict, List, MutableMapping, Set, Tuple
  import torch
  import torch.distributed
label_desc: Use image node_id 1 for calling the MultiProcessAdapter obj's underlying member method code with example usage: obj.process(msg, kwargs) and returns: str, process_num, str, msg,  kwargs