code: def num_shards(self) -> int:
      num_shards = 1
      for i, placement in enumerate(self.placements):
          if placement.is_shard():
              num_shards *= self.mesh.size(i)
      return num_shards
  
imports: from dataclasses import dataclass
  from typing import Any, cast, List, NamedTuple, Optional, Tuple
  import torch
  import torch.distributed._functional_collectives
  import torch.distributed.distributed_c10d
  from torch.distributed._tensor._collective_utils import mesh_broadcast, mesh_scatter
  from torch.distributed.device_mesh import DeviceMesh
label_desc: Use image node_id 10 for calling the DTensorSpec obj's underlying member method code with example usage: obj.num_shards() and returns: num_shards