code: def convert_examples_to_features(
      examples, label_list, max_seq_length, tokenizer
  ):
      """Convert a set of `InputExample`s to a list of `InputFeatures`."""
  
      features = []
      for ex_index, example in enumerate(examples):
          if ex_index % 10000 == 0:
              tf.logging.info(
                  "Writing example %d of %d" % (ex_index, len(examples))
              )
  
          feature = convert_single_example(
              ex_index, example, label_list, max_seq_length, tokenizer
          )
  
          features.append(feature)
      return features
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import csv
  import os
  import mesh_tensorflow
  import mesh_tensorflow.bert.bert
  import mesh_tensorflow.bert.optimization
  import mesh_tensorflow.bert.tokenization
  from six.moves import range
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 8 for calling a global function with example usage: convert_examples_to_features(examples, label_list, max_seq_length, tokenizer) and returns: features