code: def test_tl_from_list_of_tensors_different_dtypes():
      np_types = [
          np.float32,
          np.float16,
          np.int16,
          np.int8,
          np.uint16,
          np.uint8,
      ]
      for dtypes in np.random.choice(
          np_types, size=(3, 2), replace=False
      ):
          t1 = TensorCPU(np.zeros((1), dtype=dtypes[0]))
          t2 = TensorCPU(np.zeros((1), dtype=dtypes[1]))
          with assert_raises(
              TypeError,
              glob=(
                  "Tensors cannot have different data types."
                  " Tensor at position 1 has type '*' expected to have type '*'."
              ),
          ):
              TensorListCPU([t1, t2])
  
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 23 for calling a global function with example usage: test_tl_from_list_of_tensors_different_dtypes() without return types