code: def preprocessing_fn(inputs):
      """tf.transform's callback function for preprocessing inputs.
  
      Args:
        inputs: map from feature keys to raw not-yet-transformed features.
  
      Returns:
        Map from string feature key to transformed feature operations.
      """
      outputs = {}
  
      for key in _FEATURE_KEYS:
          # Nothing to transform for the penguin dataset. This code is just to
          # show how the preprocessing function for Transform should be defined.
          # We just assign original values to the transformed feature.
          outputs[_transformed_name(key)] = inputs[key]
      # TODO(b/157064428): Support label transformation for Keras.
      # Do not apply label transformation as it will result in wrong evaluation.
      outputs[_transformed_name(_LABEL_KEY)] = inputs[_LABEL_KEY]
  
      return outputs
  
imports: import datetime
  import os
  from typing import List
  from absl import logging
  import keras_tuner
  import tensorflow
  from tensorflow import keras
  import tensorflow_transform
  import tfx.v1
  from tfx_bsl.public import tfxio
  from tensorflow_cloud.core import machine_config
  from tensorflow_cloud.tuner import tuner
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 5 for calling a global function with example usage: preprocessing_fn(inputs) and returns: outputs