code: def _get_ort_device_type(device_type: str):
      if device_type == "cuda":
          return ORTC.OrtDevice.cuda()
      if device_type == "cpu":
          return ORTC.OrtDevice.cpu()
      # ort pytorch device is mapped to NPU OrtDevice type
      if device_type == "ort":
          return ORTC.OrtDevice.npu()
      raise ValueError("Unsupported device type: " + device_type)
  
imports: import dataclasses
  import importlib
  import logging
  from typing import Any, Dict, Final, List, Mapping, Optional, Sequence, Set, Tuple, Union
  from typing_extensions import TypeAlias
  import torch
  import torch._C
  import torch._ops
  import torch._prims.executor
  import torch.fx
  from torch._subclasses.fake_tensor import FakeTensor
  from torch.fx._compatibility import compatibility
  from torch.fx.passes.fake_tensor_prop import FakeTensorProp
  from torch.fx.passes.operator_support import OperatorSupport
  from torch.fx.passes.tools_common import CALLABLE_NODE_OPS
  from torch.utils import _pytree
label_desc: Use image node_id 5 for calling a global function with example usage: _get_ort_device_type(device_type) and returns: ORTC, ORTC, ORTC