code: def test_save_load_strict(self):
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs()
      for model_class in self.all_model_classes:
          model = model_class(config)
  
          with tempfile.TemporaryDirectory() as tmpdirname:
              model.save_pretrained(tmpdirname)
              model2, info = model_class.from_pretrained(
                  tmpdirname, output_loading_info=True
              )
          self.assertEqual(info["missing_keys"], [])
  
imports: import copy
  import tempfile
  import unittest
  from transformers import M2M100Config, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, require_torch_fp16, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the M2M100ModelTest obj's underlying member method code with example usage: obj.test_save_load_strict() without return types