code: def __init__(self, rank):
      super().__init__()
      torch.manual_seed(0)
  
      self.second = SecondTier(rank)
      self.net = nn.Sequential(nn.Linear(16, 16), nn.ReLU())
  
imports: import torch
  import torch.nn
  from torch.distributed._tensor import DTensor
  from torch.distributed.checkpoint.state_dict import get_state_dict
  from torch.distributed.device_mesh import _mesh_resources, init_device_mesh
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, skip_if_lt_x_gpu, with_comms
  from torch.testing._internal.distributed.checkpoint_utils import with_temp_dir
  from torch.testing._internal.distributed.common_state_dict import VerifyStateDictMixin
label_desc: Use image node_id 1 to create a new TopModel object from inherited base classes: nn with example: obj = TopModel(rank)