code: def test_duration_energy_pitch_output(self):
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
      config.return_dict = True
  
      seq_len = self.model_tester.seq_length
      for model_class in self.all_model_classes:
          model = model_class(config)
          model.to(torch_device)
          model.eval()
          with torch.no_grad():
              outputs = model(
                  **self._prepare_for_class(inputs_dict, model_class)
              )
  
          # duration
          self.assertListEqual(
              list(outputs.duration_outputs.shape),
              [self.model_tester.batch_size, seq_len],
          )
          # energy
          self.assertListEqual(
              list(outputs.energy_outputs.shape),
              [self.model_tester.batch_size, seq_len, 1],
          )
          # pitch
          self.assertListEqual(
              list(outputs.pitch_outputs.shape),
              [self.model_tester.batch_size, seq_len, 1],
          )
  
imports: import inspect
  import tempfile
  import unittest
  from transformers import FastSpeech2ConformerConfig, FastSpeech2ConformerHifiGanConfig, FastSpeech2ConformerTokenizer, FastSpeech2ConformerWithHifiGanConfig, is_torch_available
  from transformers.testing_utils import require_g2p_en, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, ids_tensor
label_desc: Use image node_id 5 for calling the FastSpeech2ConformerModelTest obj's underlying member method code with example usage: obj.test_duration_energy_pitch_output() without return types