code: def testImgPilToMulticrop():
      transform = ImgPilToMultiCrop(
          total_num_crops=8,
          num_crops=[2, 6],
          size_crops=[224, 96],
          crop_scales=[[0.14, 1], [0.05, 0.14]],
      )
  
      benchmark(transform, "MultiCrop", requires_pil=True)
  
imports: import time
  from typing import Callable, List
  import torch
  import torchvision.transforms
  from PIL import Image
  from vissl.data.ssl_transforms.img_cv_color_distortion import ColorDistortionSettings, ImgOpenCVColorDistortion
  from vissl.data.ssl_transforms.img_pil_color_distortion import ImgPilColorDistortion
  from vissl.data.ssl_transforms.img_pil_gaussian_blur import ImgPilGaussianBlur
  from vissl.data.ssl_transforms.img_pil_random_photometric import ImgPilRandomPhotometric
  from vissl.data.ssl_transforms.img_pil_to_lab_tensor import ImgPil2LabTensor
  from vissl.data.ssl_transforms.img_pil_to_multicrop import ImgPilToMultiCrop
  from vissl.data.ssl_transforms.img_pil_to_patches_and_image import ImgPilToPatchesAndImage
  from vissl.data.ssl_transforms.img_pil_to_tensor import ImgToTensor
  from vissl.data.ssl_transforms.img_rotate_pil import ImgRotatePil
label_desc: Use image node_id 12 for calling a global function with example usage: testImgPilToMulticrop() without return types