class_docstr: SquadConcat with targets in format of answer position + answer length.
class_docstr_tok: ["SquadConcat","with","targets","in","format","of","answer","position","+","answer","length","."]
code: def generate_encoded_samples(self, data_dir, tmp_dir, dataset_split):
      samples = super(
          SquadConcatPositioned, self
      ).generate_encoded_samples(data_dir, tmp_dir, dataset_split)
      for sample in samples:
          sample["targets"] = self.generate_targets(
              sample["targets"], sample["context"]
          )
          if sample["targets"]:
              yield sample
  
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 SquadConcatPositioned obj's underlying member method code with example usage: obj.generate_encoded_samples(data_dir, tmp_dir, dataset_split) without return types