code: def test_vs_scipy():
      batch_size = 10
      for device in ["cpu", "gpu"]:
          for num_dims in [1, 2, 3]:
              # scipy simply wraps integers instead of saturating them, so uint8 inputs won't match
              for in_type in [np.int16, np.int32, np.int64, np.float32]:
                  output_types = (
                      [None]
                      if in_type == np.float32
                      else [None, np.float32]
                  )
                  for out_type in output_types:
                      yield _test_vs_scipy, device, batch_size, num_dims, in_type, out_type
  
imports: from nvidia.dali.pipeline import pipeline_def
  import nvidia.dali.types
  import nvidia.dali.fn
  import numpy
  import cv2
  from scipy.ndimage import convolve1d, filters
  import os
  from nose_utils import assert_raises
  from nose.plugins.attrib import attr
  from sequences_test_utils import video_suite_helper, ArgCb
  from test_utils import get_dali_extra_path, check_batch, RandomlyShapedDataIterator
label_desc: Use image node_id 12 for calling a global function with example usage: test_vs_scipy() without return types