class_docstr: Add random uniform noise to integer values.
class_docstr_tok: ["Add","random","uniform","noise","to","integer","values","."]
code: def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
      super().__init__(opts=opts, *args, **kwargs)
      self.opts = opts
  
      self.width_range = getattr(
          opts, "image_augmentation.random_uniform.width_range"
      )
  
imports: import argparse
  import io
  from typing import Dict, Union
  import numpy
  import torch
  from PIL import Image
  from data.transforms import TRANSFORMATIONS_REGISTRY, BaseTransformation
label_desc: Use image node_id 1 to create a new RandomUniformNoise object from inherited base classes: BaseTransformation with example: obj = RandomUniformNoise(opts)