code: def test_csc_sampling_graph_to_device(device):
      # Construct FusedCSCSamplingGraph.
      graph = create_fused_csc_sampling_graph()
  
      # Copy to device.
      graph2 = graph.to(device)
  
      if device == "cuda":
          is_graph_on_device_type(graph2, "cuda")
      elif device == "pinned":
          is_graph_on_device_type(graph2, "cpu")
          is_graph_pinned(graph2)
  
      # The original variable should be untouched.
      is_graph_on_device_type(graph, "cpu")
  
imports: import os
  import pickle
  import re
  import tempfile
  import unittest
  import backend
  import dgl
  import dgl.graphbolt
  import pytest
  import torch
  import torch.multiprocessing
  from dgl.graphbolt.base import etype_str_to_tuple
  from scipy import sparse
  from ..None import gb_test_utils
label_desc: Use image node_id 31 for calling a global function with example usage: test_csc_sampling_graph_to_device(device) without return types