code: def __eq__(self, __o: object) -> bool:
      if not (
          isinstance(__o, DTensorSpec)
          and self.mesh == __o.mesh
          and self.placements == __o.placements
      ):
          return False
      if self.tensor_meta is None or __o.tensor_meta is None:
          return self.tensor_meta == __o.tensor_meta
  
      return (
          self.tensor_meta.shape == __o.tensor_meta.shape  # type: ignore[union-attr]
          and self.tensor_meta.stride == __o.tensor_meta.stride  # type: ignore[union-attr]
          and self.tensor_meta.dtype == __o.tensor_meta.dtype  # type: ignore[union-attr]
      )
  
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 5 for calling the DTensorSpec obj's underlying member method code with example usage: obj.__eq__(__o) and returns: unknown, False, unknown