code: def process(self, training_example: dict) -> None:
      feature = training_example[self.field]
      feature = (feature + self.add_value) / self.div_value
      training_example[self.field] = feature
  
imports: import json
  from abc import ABC, abstractmethod
  from pathlib import Path
  from typing import Optional
  import torch
  from nemo.utils.decorators import experimental
label_desc: Use image node_id 2 for calling the FeatureScaler obj's underlying member method code with example usage: obj.process(training_example) without return types