code: def test_save_load_strict(self):
      config, _ = self.model_tester.prepare_config_and_inputs()
      model = FastSpeech2ConformerModel(config)
  
      with tempfile.TemporaryDirectory() as tmpdirname:
          model.save_pretrained(tmpdirname)
          _, info = FastSpeech2ConformerModel.from_pretrained(
              tmpdirname, output_loading_info=True
          )
      self.assertEqual(info["missing_keys"], [])
  
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 7 for calling the FastSpeech2ConformerModelTest obj's underlying member method code with example usage: obj.test_save_load_strict() without return types