code: def __init__(self):
      super().__init__()
      self.layers = nn.ModuleList(
          [nn.Linear(DIM, DIM) for _ in range(NUM_LAYER)]
      )
  
imports: import copy
  from functools import partial
  from types import MethodType
  import pytest
  import torch
  import torch.distributed
  import torch.nn
  import colossalai
  from colossalai.cluster import ProcessGroupMesh
  from colossalai.interface import OptimizerWrapper
  from colossalai.pipeline.schedule.one_f_one_b import OneForwardOneBackwardSchedule
  from colossalai.pipeline.stage_manager import PipelineStageManager
  from colossalai.testing import rerun_if_address_is_in_use, spawn
  from colossalai.testing.random import seed_all
label_desc: Use image node_id 1 to create a new MlpModel object from inherited base classes: nn with example: obj = MlpModel()