code: def check_gaussian_blur(
      batch_size, sigma, window_size, op_type="cpu"
  ):
      pipe = get_gaussian_pipe(batch_size, sigma, window_size, op_type)
      pipe.build()
      for _ in range(test_iters):
          result, input = pipe.run()
          if op_type == "gpu":
              result = result.as_cpu()
              input = input.as_cpu()
          input = to_batch(input, batch_size)
          baseline_cv = [
              gaussian_cv(img, sigma, window_size) for img in input
          ]
          check_batch(
              result,
              baseline_cv,
              batch_size,
              max_allowed_error=1,
              expected_layout="HWC",
          )
  
imports: from nvidia.dali.pipeline import Pipeline, pipeline_def
  import nvidia.dali.types
  import nvidia.dali.fn
  import numpy
  import cv2
  from scipy.ndimage import convolve1d
  import os
  from nose_utils import assert_raises, 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, compare_pipelines, RandomlyShapedDataIterator, dali_type
label_desc: Use image node_id 7 for calling a global function with example usage: check_gaussian_blur(batch_size, sigma, window_size, op_type) without return types