class_docstr: Normalizes feature names to 'inputs' and 'targets'.
class_docstr_tok: ["Normalizes","feature","names","to","'inputs","'","and","'targets","'","."]
code: def __init__(
      self, ds_info: tfds.core.DatasetInfo, reverse_translation: bool
  ):
      self.input_lang, self.target_lang = ds_info.supervised_keys
      if reverse_translation:
          self.input_lang, self.target_lang = (
              self.target_lang,
              self.input_lang,
          )
  
file_path: flax/examples/wmt/input_pipeline.py
imports: import os
  from typing import Dict, Optional, List, Union
  from clu import deterministic_data
  import ml_collections
  import tensorflow
  import tensorflow_datasets
  import tokenizer
label_desc: Use image node_id 1 to create a new NormalizeFeatureNamesOp object  with example: obj = NormalizeFeatureNamesOp(ds_info, reverse_translation)