class_docstr: Base default handler to set up rpc workers for PiPPy large model inference
code: def initialize(self, ctx):
      self.local_rank = int(os.environ["LOCAL_RANK"])
      self.world_size = int(os.environ["WORLD_SIZE"])
      n_devs = torch.cuda.device_count()
      self.device = self.local_rank % n_devs
      initialize_rpc_workers(self.local_rank, self.world_size, ctx)
  
file_path: serve/ts/torch_handler/distributed/base_pippy_handler.py
imports: import os
  from abc import ABC
  import torch
  from ts.handler_utils.distributed.pt_pippy import initialize_rpc_workers
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 1 for calling the BasePippyHandler obj's underlying member method code with example usage: obj.initialize(ctx) without return types