code: def _preprocess_transform(self):
      transf = transforms.Compose(
          [
              transforms.ToTensor(),
              imagenet_utils.get_normalize_transform(),
          ]
      )
  
      return transf
  
file_path: tensorwatch/tensorwatch/saliency/lime_image_explainer.py
imports: from skimage.segmentation import mark_boundaries
  from torchvision import transforms
  import torch
  from .lime import lime_image
  import numpy
  from ..None import imagenet_utils, pytorch_utils, utils
label_desc: Use image node_id 2 for calling the LimeImagenetExplainer obj's underlying member method code with example usage: obj._preprocess_transform() and returns: transf