code: def test_multi_problem_v2(self, schedule, num_datasets, sample_size):
      class DummyProblem(problem.Problem):
          def dataset(self, *args, **kwargs):
              return tf.data.Dataset.from_tensors({"targets": 0.0})
  
      with self.test_session() as sess:
          for mode in [
              problem.DatasetSplit.TRAIN,
              problem.DatasetSplit.EVAL,
          ]:
              p = multi_problem_v2.MultiProblemV2(
                  [DummyProblem() for _ in range(num_datasets)],
                  schedule,
              )
              global_step = tf.train.get_or_create_global_step()
              dataset = p.dataset(mode, global_step).batch(sample_size)
              iterator = dataset.make_initializable_iterator()
              features = iterator.get_next()
              sess.run(global_step.initializer)
              sess.run(iterator.initializer)
              sess.run(features)
  
file_path: tensor2tensor/tensor2tensor/data_generators/multi_problem_v2_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.data_generators import multi_problem_v2
  from tensor2tensor.data_generators import problem
  import tensorflow.compat.v1
label_desc: Use image node_id 8 for calling the MultiProblemV2Test obj's underlying member method code with example usage: obj.test_multi_problem_v2(schedule, num_datasets, sample_size) and returns: tf