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 Tensors.
      """
      input_word_ids, input_mask, segment_ids = _tokenize(
          inputs[_FEATURE_KEY_A], inputs[_FEATURE_KEY_B]
      )
  
      return {
          _LABEL_KEY: inputs[_LABEL_KEY],
          _INPUT_WORD_IDS: input_word_ids,
          _INPUT_MASK: input_mask,
          _SEGMENT_IDS: segment_ids,
      }
  
file_path: tfx/tfx/examples/bert/mrpc/bert_mrpc_utils.py
imports: from typing import List
  import tensorflow
  import tensorflow_data_validation
  import tensorflow_hub
  import tensorflow_transform
  from tfx import v1
  from tfx.components.transform import stats_options_util
  from tfx.examples.bert.utils.bert_models import build_and_compile_bert_classifier
  from tfx.examples.bert.utils.bert_tokenizer_utils import BertPreprocessor
  from tfx_bsl.public import tfxio
  from google.protobuf import text_format
label_desc: Use image node_id 2 for calling a global function with example usage: preprocessing_fn(inputs) and returns: dict