code: def init_as_dtensor(
      tensor: torch.Tensor,
      device_mesh: DeviceMesh,
      sharding_spec: ShardingSpec,
      global_shape: torch.Size,
  ) -> torch.Tensor:
      assert not is_distributed_tensor(
          tensor
      ), "The input tensor is already a distributed tensor."
      dist_layout = Layout(
          device_mesh=device_mesh,
          sharding_spec=sharding_spec,
          global_shape=global_shape,
      )
  
      # shard tensor
      tensor.dist_layout = dist_layout
  
      # hack some tensor methods
      _hijack_detach_and_clone(tensor)
  
      return tensor
  
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 8 for calling a global function with example usage: init_as_dtensor(tensor, device_mesh, sharding_spec, global_shape) and returns: tensor