class_docstr: Squad with question and context concatenated, multi-lingual vocabulary.
class_docstr_tok: ["Squad","with","question","and","context","concatenated",",","multi-lingual","vocabulary","."]
code: def preprocess_example(
      self, example, unused_mode, unused_model_hparams
  ):
      sep = tf.convert_to_tensor(
          [self.QUESTION_SEPARATOR_ID], dtype=example["inputs"].dtype
      )
      example["inputs"] = tf.concat(
          [example["inputs"], sep, example["context"]], 0
      )
      example.pop("context")
      return example
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.data_generators import wiki_lm
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the SquadConcatMulti64k obj's underlying member method code with example usage: obj.preprocess_example(example, unused_mode, unused_model_hparams) and returns: example