code: def __init__(self):
      super().__init__()
      torch.manual_seed(0)
      self.net1 = nn.Linear(5, 10)
      self.relu = nn.ReLU()
      self.net2 = nn.Linear(10, 15)
      self.net3 = nn.Linear(15, 30)
      self.net4 = nn.Linear(30, 5)
  
imports: import io
  from copy import deepcopy
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  from torch.distributed._tensor import DTensor, init_device_mesh, Replicate, Shard
  from torch.distributed.checkpoint.state_dict import get_optimizer_state_dict, set_optimizer_state_dict
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed.fsdp._common_utils import _get_module_fsdp_state, clean_tensor_name
  from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, RowwiseParallel
  from torch.distributed.tensor.parallel.fsdp import DTensorExtensions
  from torch.distributed.tensor.parallel.input_reshard import input_reshard
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, with_comms
label_desc: Use image node_id 1 to create a new SimpleModelUneven object from inherited base classes: nn with example: obj = SimpleModelUneven()