code: def test_map_on_task_template(self):
      info = DatasetInfo(task_templates=QuestionAnsweringExtractive())
      dataset = Dataset.from_dict(
          {
              k: [v]
              for k, v in SAMPLE_QUESTION_ANSWERING_EXTRACTIVE.items()
          },
          info=info,
      )
      assert isinstance(dataset.info.task_templates, list)
      assert len(dataset.info.task_templates) == 1
  
      def keep_task(x):
          return x
  
      def dont_keep_task(x):
          out = deepcopy(SAMPLE_QUESTION_ANSWERING_EXTRACTIVE)
          out["answers"]["foobar"] = 0
          return out
  
      mapped_dataset = dataset.map(keep_task)
      assert (
          mapped_dataset.info.task_templates
          == dataset.info.task_templates
      )
      # reload from cache
      mapped_dataset = dataset.map(keep_task)
      assert (
          mapped_dataset.info.task_templates
          == dataset.info.task_templates
      )
  
      mapped_dataset = dataset.map(dont_keep_task)
      assert mapped_dataset.info.task_templates == []
      # reload from cache
      mapped_dataset = dataset.map(dont_keep_task)
      assert mapped_dataset.info.task_templates == []
  
imports: from copy import deepcopy
  from unittest.case import TestCase
  import pytest
  from datasets.arrow_dataset import Dataset
  from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value
  from datasets.info import DatasetInfo
  from datasets.tasks import AudioClassification, AutomaticSpeechRecognition, ImageClassification, LanguageModeling, QuestionAnsweringExtractive, Summarization, TextClassification, task_template_from_dict
  from datasets.utils.py_utils import asdict
label_desc: Use image node_id 1 for calling the DatasetWithTaskProcessingTest obj's underlying member method code with example usage: obj.test_map_on_task_template() and returns: x, out