class_docstr: Lime: Explaining the predictions of any machine learning classifier
  https://github.com/marcotcr/lime
code: def batch_predict(self, images):
      (images, _, _) = utils.dataset.normalize_images(
          images, self._normalize_mean, self._normalize_std
      )
  
      self._model.eval()
  
      images = images.to(self.device)
      logits = self._model(images).to(self.device)
  
      return probs.detach().cpu().numpy()
  
imports: from lime import lime_image
  from skimage.segmentation import mark_boundaries
  from singa_auto.model import utils
label_desc: Use image node_id 2 for calling the Lime obj's underlying member method code with example usage: obj.batch_predict(images) and returns: probs