code: def test_tl_from_list_of_tensors_different_backends():
      t1 = TensorCPU(np.zeros((1)))
      t2 = TensorCPU(np.zeros((1)))._as_gpu()
      with assert_raises(
          TypeError,
          glob="Object at position 1 cannot be converted to TensorCPU",
      ):
          TensorListCPU([t1, t2])
      with assert_raises(
          TypeError,
          glob="Object at position 1 cannot be converted to TensorGPU",
      ):
          TensorListGPU([t2, t1])
  
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 22 for calling a global function with example usage: test_tl_from_list_of_tensors_different_backends() without return types