class_docstr: Base class for `neural (or range) augmentation <https://arxiv.org/abs/2212.10553>`_
class_docstr_tok: ["Base","class","for","`","neural","(","or","range",")","augmentation","<","https",":","\/\/arxiv.org\/abs\/2212.10553",">","`","_"]
code: def __repr__(self):
      aug_str = "{}(".format(self.__class__.__name__)
  
      if self.brightness is not None:
          aug_str += "\n\tBrightness={}, ".format(
              self.brightness.data.shape
              if isinstance(self.brightness, nn.Parameter)
              else self.brightness
          )
  
      if self.contrast is not None:
          aug_str += "\n\tContrast={}, ".format(
              self.contrast.data.shape
              if isinstance(self.contrast, nn.Parameter)
              else self.contrast
          )
  
      if self.noise is not None:
          aug_str += "\n\tNoise={}, ".format(
              self.noise.data.shape
              if isinstance(self.noise, nn.Parameter)
              else self.noise
          )
  
      aug_str += self.extra_repr()
      aug_str += ")"
      return aug_str
  
imports: import argparse
  import random
  from typing import List, Optional
  import torch
  from torch import Tensor, nn
  from cvnets.misc.common import parameter_list
  from cvnets.neural_augmentor.utils.neural_aug_utils import Clip, FixedSampler, UniformSampler, random_brightness, random_contrast, random_noise
  from utils import logger
label_desc: Use image node_id 4 for calling the BaseNeuralAugmentor obj's underlying member method code with example usage: obj.__repr__() and returns: aug_str