code: def __init__(self, in_features):
      super().__init__()
      self.linear_1 = torch.nn.Linear(
          in_features, 4 * in_features, bias=False
      )
      self.linear_2 = torch.nn.Linear(
          4 * in_features, in_features, bias=False
      )
  
file_path: ColossalAI/tests/test_auto_parallel/test_tensor_shard/test_compatibility_with_ddp.py
imports: import copy
  import pytest
  import torch
  from torch.nn.parallel import DistributedDataParallel
  from colossalai.device.device_mesh import DeviceMesh
  from colossalai.initialize import launch
  from colossalai.logging import disable_existing_loggers
  from colossalai.testing import assert_close, rerun_if_address_is_in_use, run_on_environment_flag, spawn
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: torch.nn with example: obj = MLP(in_features)