code: def run(self, library, imgs):
      transform = getattr(self, f"{library}_pipeline")
      for img in imgs:
          if library == "albumentations":
              transform(image=img)
          elif library == "solt":
              transform(img, return_torch=True, normalize=True)
          else:
              transform(img)
  
imports: import cv2
  import Augmentor
  import albumentations
  from albumentations.pytorch import ToTensor
  import solt
  import solt.transforms
  from torchvision import transforms
label_desc: Use image node_id 5 for calling the BenchmarkTest obj's underlying member method code with example usage: obj.run(library, imgs) without return types