code: def test_color_jitter(brightness, contrast, saturation, hue):
      np.random.seed(0)
      img = np.random.randint(0, 256, [100, 100, 3], dtype=np.uint8)
      pil_image = Image.fromarray(img)
  
      transform = A.Compose(
          [
              A.ColorJitter(
                  brightness=[brightness, brightness],
                  contrast=[contrast, contrast],
                  saturation=[saturation, saturation],
                  hue=[hue, hue],
                  p=1,
              )
          ]
      )
  
      pil_transform = ColorJitter(
          brightness=[brightness, brightness],
          contrast=[contrast, contrast],
          saturation=[saturation, saturation],
          hue=[hue, hue],
      )
  
      res1 = transform(image=img)["image"]
      res2 = np.array(pil_transform(pil_image))
  
      _max = np.abs(res1.astype(np.int16) - res2.astype(np.int16)).max()
      assert _max <= 2, "Max: {}".format(_max)
  
file_path: albumentations/tests/test_pytorch.py
imports: import pytest
  import numpy
  import torch
  from PIL import Image
  from torchvision.transforms import ColorJitter
  import albumentations
  from albumentations.pytorch.transforms import ToTensor, ToTensorV2
label_desc: Use image node_id 8 for calling a global function with example usage: test_color_jitter(brightness, contrast, saturation, hue) without return types