code: def _cf_postprocess(extracts: types.Extracts) -> types.Extracts:
      """Postprocesses the result of applying a CF prediction ptransform.
  
      This method takes in an Extracts instance that has been prepocessed by
      _preprocess_cf and has had a prediction PTransform applied, and makes it look
      as if just a non-CF prediction PTransform had been applied.
  
      Args:
        extracts: An Extracts instance which has been preprocessed by _preprocess_cf
          and gone through a prediction PTransform.
  
      Returns:
        An Extracts instance which appears to have been produced by a standard
        predictions PTransform.
      """
      extracts = extracts.copy()
      extracts[constants.INPUT_KEY] = extracts[_TEMP_ORIG_INPUT_KEY]
      del extracts[_TEMP_ORIG_INPUT_KEY]
      return extracts
  
file_path: model-analysis/tensorflow_model_analysis/extractors/counterfactual_predictions_extractor.py
imports: from typing import Dict, Iterable, Mapping, Optional
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.extractors import extractor
  from tensorflow_model_analysis.extractors import predictions_extractor
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 5 for calling a global function with example usage: _cf_postprocess(extracts) and returns: extracts