code: def __init__(self, spec=None, group=None, init_rrefs=True) -> None:
      super().__init__()
      if spec is not None:
          self.sharded_tensor2 = sharded_tensor.rand(
              spec, 10, 20, process_group=group, init_rrefs=init_rrefs
          )
      else:
          self.sharded_tensor2 = None
      self.random_tensor2 = torch.nn.Parameter(torch.rand(2, 2))
  
file_path: pytorch/torch/testing/_internal/distributed/_shard/sharded_tensor/_test_st_common.py
imports: import copy
  import random
  import torch
  from torch.distributed._shard import sharded_tensor
  from torch.distributed._shard.sharding_spec import ChunkShardingSpec
label_desc: Use image node_id 1 to create a new MyShardedModel2 object from inherited base classes: torch.nn with example: obj = MyShardedModel2(spec, group, init_rrefs)