code: def get_sharding_spec(dtensor: torch.Tensor) -> ShardingSpec:
      """
      Get the sharding spec of the distributed tensor.
  
      Args:
          dtensor (torch.Tensor): The distributed tensor.
  
      Returns:
          ShardingSpec: The sharding spec of the distributed tensor.
      """
      assert is_distributed_tensor(
          dtensor
      ), "The input tensor is not a distributed tensor."
      return dtensor.dist_layout.sharding_spec
  
imports: import copy
  import operator
  from functools import reduce
  from typing import Union
  import torch
  import torch.distributed
  from torch.distributed import ProcessGroup
  from colossalai.device.device_mesh import DeviceMesh
  from .layout import Layout
  from .layout_converter import LayoutConverter
  from .sharding_spec import ShardingSpec
label_desc: Use image node_id 19 for calling a global function with example usage: get_sharding_spec(dtensor) and returns: dtensor