code: def test_advanced_blur_float_uint8_diff_less_than_two(val_uint8):
      x_uint8 = np.zeros((5, 5)).astype(np.uint8)
      x_uint8[2, 2] = val_uint8
  
      x_float32 = np.zeros((5, 5)).astype(np.float32)
      x_float32[2, 2] = val_uint8 / 255.0
  
      adv_blur = A.AdvancedBlur(blur_limit=(3, 5), always_apply=True)
  
      set_seed(0)
      adv_blur_uint8 = adv_blur(image=x_uint8)["image"]
  
      set_seed(0)
      adv_blur_float32 = adv_blur(image=x_float32)["image"]
  
      # Before comparison, rescale the adv_blur_float32 to [0, 255]
      diff = np.abs(adv_blur_uint8 - adv_blur_float32 * 255)
  
      # The difference between the results of float32 and uint8 will be at most 2.
      assert np.all(diff <= 2.0)
  
imports: import random
  from functools import partial
  import cv2
  import numpy
  import pytest
  import albumentations
  import albumentations.augmentations.functional
  import albumentations.augmentations.geometric.functional
  from albumentations.augmentations.blur.functional import gaussian_blur
  from .utils import get_dual_transforms, get_image_only_transforms, get_transforms
label_desc: Use image node_id 45 for calling a global function with example usage: test_advanced_blur_float_uint8_diff_less_than_two(val_uint8) without return types