code: def testToTensor():
      transform = transforms.ToTensor()
      benchmark(transform, "ToTensor", 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 8 for calling a global function with example usage: testToTensor() without return types