code: def _decode_record(record, name_to_features):
      """Decodes a record to a TensorFlow example."""
      example = tf.parse_single_example(record, name_to_features)
  
      # tf.Example only supports tf.int64, but the TPU only supports tf.int32.
      # So cast all int64 to int32.
      for name in list(example.keys()):
          t = example[name]
          if t.dtype == tf.int64:
              t = tf.to_int32(t)
          example[name] = t
  
      return example
  
file_path: BigDL/python/orca/example/learn/tf/bert/run_pretraining.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import absl
  import sys
  import modeling
  import optimization
  import tensorflow.compat.v1
  from bigdl.orca.learn.tf.tf_estimator import TFEstimator
label_desc: Use image node_id 6 for calling a global function with example usage: _decode_record(record, name_to_features) and returns: example