code: def get_gaussian_pipe(batch_size, sigma, window_size, op_type):
      pipe = Pipeline(batch_size=batch_size, num_threads=4, device_id=0)
      with pipe:
          input, _ = fn.readers.file(
              file_root=images_dir, shard_id=0, num_shards=1
          )
          decoded = fn.decoders.image(
              input, device="cpu", output_type=types.RGB
          )
          if op_type == "gpu":
              decoded = decoded.gpu()
          blurred = fn.gaussian_blur(
              decoded,
              device=op_type,
              sigma=sigma,
              window_size=window_size,
          )
          pipe.set_outputs(blurred, decoded)
      return pipe
  
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 6 for calling a global function with example usage: get_gaussian_pipe(batch_size, sigma, window_size, op_type) and returns: pipe