code: def test_tensorlist_getitem_cpu():
      arr = np.random.rand(3, 5, 6)
      tensorlist = TensorListCPU(arr, "NHWC")
      list_of_tensors = [x for x in tensorlist]
  
      assert type(tensorlist.at(0)) is np.ndarray
      assert type(tensorlist[0]) is not np.ndarray
      assert type(tensorlist[0]) is TensorCPU
      assert type(tensorlist[-3]) is TensorCPU
      assert len(list_of_tensors) == len(tensorlist)
      with assert_raises(IndexError, glob="out of range"):
          tensorlist[len(tensorlist)]
      with assert_raises(IndexError, glob="out of range"):
          tensorlist[-len(tensorlist) - 1]
  
imports: import numpy
  import nvidia.dali.fn
  import nvidia.dali.types
  import warnings
  from numpy.testing import assert_array_equal
  from nvidia.dali import pipeline_def
  from nvidia.dali.backend_impl import TensorCPU, TensorListCPU, TensorListGPU
  from nvidia.dali.backend_impl import types
  import nvidia.dali
  from nose_utils import assert_raises
  from nose import SkipTest
  from test_utils import dali_type_to_np, py_buffer_from_address, get_device_memory_info
label_desc: Use image node_id 8 for calling a global function with example usage: test_tensorlist_getitem_cpu() without return types