docstr: Scales a field by constant factors. For example, for mean-variance normalization.
  
  Specifically: input[field] = (input[field] + add_value) / div_value
  
  Args:
      field: Field to scale
      add_value: Constant float value to add to feature.
      div_value: Constant float value to divide feature by.
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code: def __init__(
      self, field: str, add_value: float = 0.0, div_value: float = 1.0
  ):
      """
      Scales a field by constant factors. For example, for mean-variance normalization.
  
      Specifically: input[field] = (input[field] + add_value) / div_value
  
      Args:
          field: Field to scale
          add_value: Constant float value to add to feature.
          div_value: Constant float value to divide feature by.
      """
      self.field = field
      self.add_value = add_value
      self.div_value = div_value
  
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 1 to create a new FeatureScaler object from inherited base classes: FeatureProcessor with example: obj = FeatureScaler(field, add_value, div_value)