code: def test_cpu_cuda(dtype):
      kwargs = dict(dtype=dtype)
      adj = EdgeIndex([[0, 1, 1, 2], [1, 0, 2, 1]], **kwargs)
  
      out = adj.cuda()
      assert isinstance(out, EdgeIndex)
      assert out.is_cuda
  
      out = out.cpu()
      assert isinstance(out, EdgeIndex)
      assert not out.is_cuda
  
imports: import os.path
  import warnings
  from typing import List, Optional
  import pytest
  import torch
  from torch import Tensor, tensor
  import torch_geometric
  from torch_geometric import EdgeIndex
  from torch_geometric.edge_index import SUPPORTED_DTYPES, ReduceType, SortReturnType, _scatter_spmm, _torch_sparse_spmm, _TorchSPMM, set_tuple_item
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import onlyCUDA, onlyLinux, withCUDA, withoutExtensions, withPackage
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import scatter
label_desc: Use image node_id 10 for calling a global function with example usage: test_cpu_cuda(dtype) without return types