def METHOD_NAME(self):
    from neural_compressor.config import PostTrainingQuantConfig
    from neural_compressor.data import DATALOADERS, Datasets
    from neural_compressor.quantization import fit
    # dataset and dataloader
    dataset = Datasets("tensorflow")["dummy"](((100, 3, 3, 1)))
    dataloader = DATALOADERS["tensorflow"](dataset)
    # tuning and accuracy criterion
    conf = PostTrainingQuantConfig(diagnosis=True)
    q_model = fit(model=self.constant_graph, conf=conf, calib_dataloader=dataloader, eval_func=lambda model: 1)
    self.assertEqual(os.path.exists(os.path.join(self.workspace, "inspect_saved/fp32/inspect_result.pkl")), True)
    self.assertEqual(os.path.exists(os.path.join(self.workspace, "inspect_saved/quan/inspect_result.pkl")), True)