code: def test_contains_tensor():
      t = torch.tensor([0])
      assert contains_tensor(t)
      assert contains_tensor([1, 2, 3, t, 5, 6])
      assert contains_tensor([1, 2, 3, {"dict": t}, 5, 6])
      assert contains_tensor({"outer": [1, 2, 3, {"dict": t}, 5, 6]})
      assert contains_tensor({t: [1, 2, 3, {"dict": 2}, 5, 6]})
      assert not contains_tensor([4, 5, 6])
  
file_path: ray/python/ray/train/tests/test_torch_utils.py
imports: import numpy
  import pandas
  import pytest
  import torch
  from ray.air._internal.torch_utils import contains_tensor, convert_pandas_to_torch_tensor, load_torch_model
  from ray.util.debug import _test_some_code_for_memory_leaks
label_desc: Use image node_id 1 for calling a global function with example usage: test_contains_tensor() without return types