code: def __init__(self, rank=None):
      super().__init__()
      # Use same seed.
      torch.manual_seed(0)
      self.linear1 = torch.nn.Linear(17, 12)
      self.linear2 = torch.nn.Linear(12, 29)
      self.gelu = torch.nn.GELU()
  
      if rank:
          self.linear1.cuda(rank)
          self.linear2.cuda(rank)
  
imports: import torch
  import torch.optim
  from torch.distributed._shard import sharded_tensor, shard_parameter
  from copy import deepcopy
  from torch.distributed._shard.sharding_spec import ChunkShardingSpec
  from torch.distributed._shard.sharded_optim import ShardedOptimizer
  from torch.testing._internal.common_distributed import requires_nccl, skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._shard.sharded_tensor import ShardedTensorTestBase, with_comms
label_desc: Use image node_id 1 to create a new MyShardedLinear object from inherited base classes: torch.nn with example: obj = MyShardedLinear(rank)