class_docstr: Base class for translation problems.
class_docstr_tok: ["Base","class","for","translation","problems","."]
code: def example_reading_spec(self):
      data_fields = {"dist_targets": tf.VarLenFeature(tf.int64)}
  
      if self.has_inputs:
          data_fields["inputs"] = tf.VarLenFeature(tf.int64)
  
      # hack: ignoring true targets and putting dist_targets in targets
      data_items_to_decoders = {
          "inputs": contrib.slim().tfexample_decoder.Tensor("inputs"),
          "targets": contrib.slim().tfexample_decoder.Tensor(
              "dist_targets"
          ),
      }
  
      return (data_fields, data_items_to_decoders)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gzip
  import os
  import tarfile
  import zipfile
  from tensor2tensor.data_generators import cleaner_en_xx
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import bleu_hook
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import mlperf_log
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the TranslateDistillProblem obj's underlying member method code with example usage: obj.example_reading_spec() and returns: data_fields,  data_items_to_decoders