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)
    from neural_compressor.metric import METRICS
    metrics = METRICS("tensorflow")
    top1 = metrics["topk"]()
    # tuning and accuracy criterion
    conf = PostTrainingQuantConfig()
    q_model = fit(
        model=self.constant_graph,
        conf=conf,
        calib_dataloader=dataloader,
        eval_dataloader=dataloader,
        eval_metric=top1,
    )