class_docstr: Implementation of control theory augment.
class_docstr_tok: ["Implementation","of","control","theory","augment","."]
docstr: Returns augmenter state to save in checkpoint or for debugging.
docstr_tok: ["Returns","augmenter","state","to","save","in","checkpoint","or","for","debugging","."]
code: def get_augmenter_state(self):
      """Returns augmenter state to save in checkpoint or for debugging."""
      return dict(
          ct_augment_rate=self.rates, ct_augment_probs=self.probs
      )
  
imports: from typing import Optional
  import tensorflow
  from .randaugment import augment_ops
label_desc: Use image node_id 4 for calling the CTAugment obj's underlying member method code with example usage: obj.get_augmenter_state() and returns: dict