original_docstring: tf.transform's callback function for preprocessing inputs.
      Args:
        inputs: map from feature keys to raw not-yet-transformed features.
        custom_config:
          timesteps: The number of timesteps in the look back window
          features: Which of the features from the TF.Example to use in the model.
      Returns:
        Map from string feature key to transformed feature operations.
      
docstring: tf.transform's callback function for preprocessing inputs.
docstring_tokens: tf . transform ' s callback function for preprocessing inputs .
code: def preprocessing_fn(inputs: Dict[Text, Any], custom_config) -> Dict[Text, Any]:
      """tf.transform's callback function for preprocessing inputs.
      Args:
        inputs: map from feature keys to raw not-yet-transformed features.
        custom_config:
          timesteps: The number of timesteps in the look back window
          features: Which of the features from the TF.Example to use in the model.
      Returns:
        Map from string feature key to transformed feature operations.
      """
      feature_columns = sorted(custom_config["feature_columns"])
      features = {}
  
      for feature in feature_columns:
          if feature not in inputs.keys():
              raise ValueError(
                  f"Input is missing required feature {feature}. Input has: {inputs.keys()}"
              )
  
          features[f"{feature}"] = tft.scale_to_z_score(inputs[feature])
  
      return features
code_tokens: def preprocessing_fn ( inputs : Dict [ Text , Any ] , custom_config ) -> Dict [ Text , Any ] : feature_columns = sorted ( custom_config [ "feature_columns" ] ) features = { } for feature in feature_columns : if feature not in inputs . keys ( ) : raise ValueError ( f"Input is missing required feature {feature}. Input has: {inputs.keys()}" ) features [ f"{feature}" ] = tft . scale_to_z_score ( inputs [ feature ] ) return features
short_docstring: tf.transform's callback function for preprocessing inputs.
short_docstring_tokens: tf . transform ' s callback function for preprocessing inputs .
comment: """tf.transform's callback function for preprocessing inputs.
      Args:
        inputs: map from feature keys to raw not-yet-transformed features.
        custom_config:
          timesteps: The number of timesteps in the look back window
          features: Which of the features from the TF.Example to use in the model.
      Returns:
        Map from string feature key to transformed feature operations.
      """