code: def __init__(self, stage_id, actual_stage_num, feat_num, h) -> None:
      super().__init__()
      self.rank = stage_id
      self.is_last_rank = stage_id == actual_stage_num - 1
      self.linear_name = f"linear_{stage_id}"
  
      if stage_id == 0:
          linear = nn.Linear(feat_num, h)
      elif stage_id == actual_stage_num - 1:
          linear = nn.Linear(h, 1)
      else:
          linear = nn.Linear(h, h)
  
      setattr(self, self.linear_name, linear)
  
imports: import argparse
  import os
  import warnings
  import torch
  import torch.distributed.rpc
  import torch.multiprocessing
  from torch import nn
  from torch._C._distributed_rpc import _is_current_rpc_agent_set
  from colossalai.legacy import launch
  from colossalai.legacy.pipeline.pipeline_process_group import ppg
  from colossalai.logging import disable_existing_loggers
label_desc: Use image node_id 1 to create a new RpcTestModel object from inherited base classes: nn with example: obj = RpcTestModel(stage_id, actual_stage_num, feat_num, h)