code: def test_question_answering_forward(self):
      config, input_ids, batch_size = self._get_config_and_data()
      sequence_labels = ids_tensor([batch_size], 2).to(torch_device)
      model = MvpForQuestionAnswering(config)
      model.to(torch_device)
      outputs = model(
          input_ids=input_ids,
          start_positions=sequence_labels,
          end_positions=sequence_labels,
      )
  
      self.assertEqual(outputs["start_logits"].shape, input_ids.shape)
      self.assertEqual(outputs["end_logits"].shape, input_ids.shape)
      self.assertIsInstance(outputs["loss"].item(), float)
  
imports: import copy
  import tempfile
  import unittest
  import timeout_decorator
  from transformers import MvpConfig, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 3 for calling the MvpHeadTests obj's underlying member method code with example usage: obj.test_question_answering_forward() without return types