code: def test_tl_from_list_of_tensors_same_shape():
      for shape in [(10, 1), (4, 5, 6), (13, 1), (1, 1)]:
          arr = np.random.rand(*shape)
  
          tl_cpu_from_np = TensorListCPU(arr)
          tl_cpu_from_tensors = TensorListCPU(
              [TensorCPU(a) for a in arr]
          )
          np.testing.assert_array_equal(
              tl_cpu_from_np.as_array(), tl_cpu_from_tensors.as_array()
          )
  
          tl_gpu_from_np = tl_cpu_from_np._as_gpu()
          tl_gpu_from_tensors = TensorListGPU(
              [TensorCPU(a)._as_gpu() for a in arr]
          )
          np.testing.assert_array_equal(
              tl_gpu_from_np.as_cpu().as_array(),
              tl_gpu_from_tensors.as_cpu().as_array(),
          )
  
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 19 for calling a global function with example usage: test_tl_from_list_of_tensors_same_shape() without return types