code: def get_window_sizes(window_size, smoothing_size, axes):
      window_sizes = spread_values(window_size, axes)
      if len(smoothing_size.reshape(-1)) == 0:
          return [[window_sizes[i]] * axes for i in range(axes)]
      else:
          smoothing_sizes = spread_values(smoothing_size, axes)
          return [
              [
                  window_sizes[j] if i == j else smoothing_sizes[j]
                  for j in range(axes)
              ]
              for i in range(axes)
          ]
  
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 16 for calling a global function with example usage: get_window_sizes(window_size, smoothing_size, axes) and returns: unknown, unknown