code: def test_torch_transform():
      torchvision = pytest.importorskip("torchvision")
  
      red = np.zeros([10, 10, 3], np.uint8)
      red[..., 0] = 255
      red = Image.fromarray(red)
  
      p = Augmentor.Pipeline()
  
      # include multiple transforms to test integration
      p.greyscale(probability=1)
      p.zoom(probability=1, min_factor=1.0, max_factor=1.0)
      p.rotate_random_90(probability=1)
  
      transforms = torchvision.transforms.Compose([p.torch_transform()])
  
      assert red != transforms(red)
  
      # assert that all operations were correctly applied
      result = red
      for op in p.operations:
          result = op.perform_operation([result])[0]
      assert transforms(red) == result
  
imports: import pytest
  import numpy
  import PIL.Image
  import Augmentor
label_desc: Use image node_id 1 for calling a global function with example usage: test_torch_transform() without return types