code: def split_test(split_dict):
      if "test" not in split_dict:
          assert "test-whole" in split_dict
          assert "test-dev" in split_dict
          assert "test-challenge" in split_dict
          return
  
      if isinstance(split_dict["test"], torch.Tensor):
          idx = torch.arange(len(split_dict["test"]))
          dev_idx = torch.nonzero(idx % 5 < 3, as_tuple=True)[0]
          challenge_idx = torch.nonzero(~(idx % 5 < 3), as_tuple=True)[
              0
          ]
      else:
          idx = np.arange(len(split_dict["test"]))
          dev_idx = np.nonzero(idx % 5 < 3)[0]
          challenge_idx = np.nonzero(~(idx % 5 < 3))[0]
  
      split_dict["test-whole"] = split_dict["test"]
      split_dict["test-dev"] = split_dict["test-whole"][dev_idx]
      split_dict["test-challenge"] = split_dict["test-whole"][
          challenge_idx
      ]
  
      assert len(split_dict["test-dev"]) + len(
          split_dict["test-whole"][challenge_idx]
      ) == len(split_dict["test"])
  
      del split_dict["test"]
  
label_desc: Use image node_id 1 for calling a global function with example usage: split_test(split_dict) without return types