class_docstr: Normalizes feature names to 'inputs' and 'targets'.
class_docstr_tok: ["Normalizes","feature","names","to","'inputs","'","and","'targets","'","."]
code: def __call__(self, features: Features) -> Features:
      features["inputs"] = features.pop("text")
      # Unnecessary step used for uniformizing with examples/wmt.
      features["targets"] = features["inputs"]
      return features
  
file_path: flax/examples/lm1b/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 2 for calling the NormalizeFeatureNamesOp obj's underlying member method code with example usage: obj.__call__(features) and returns: features