code: def manual_verify(
      batch_size,
      inp,
      output,
      in_idx_l,
      in_anchors_l,
      shapes_l,
      out_anchors_l,
      out_size_l,
      dtype,
  ):
      for i in range(batch_size):
          ref_source_info = ";".join(
              [inp[idx].source_info() for idx in in_idx_l[i]]
          )
          assert (
              output[i].source_info() == ref_source_info
          ), f"{output[i].source_info()} == {ref_source_info}"
          out = output.at(i)
          out_size = out_size_l[i]
          assert out.shape == out_size
          ref = np.zeros(out.shape)
          for j, idx in enumerate(in_idx_l[i]):
              roi_start = in_anchors_l[i][j]
              roi_end = roi_start + shapes_l[i][j]
              out_start = out_anchors_l[i][j]
              out_end = out_start + shapes_l[i][j]
              ref[
                  out_start[0] : out_end[0], out_start[1] : out_end[1]
              ] = inp.at(idx)[
                  roi_start[0] : roi_end[0], roi_start[1] : roi_end[1]
              ]
          ref = ref.astype(np_type_map[dtype])
          if DEBUG_LVL > 0 and not np.array_equal(out, ref):
              print(f"Error on image {i}")
              import PIL.Image
  
              PIL.Image.fromarray(out).save("multipaste_out.png")
              PIL.Image.fromarray(ref).save("multipaste_ref.png")
          assert np.array_equal(out, ref)
  
file_path: DALI/dali/test/python/operator_1/test_multipaste.py
imports: from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.fn
  import nvidia.dali.types
  import numpy
  import os
  from test_utils import get_dali_extra_path
label_desc: Use image node_id 5 for calling a global function with example usage: manual_verify(batch_size, inp, output, in_idx_l, in_anchors_l, shapes_l, out_anchors_l, out_size_l, dtype) without return types