def METHOD_NAME(self):
    fp32_model = copy.deepcopy(self.model)
    model1 = rtn_quantize(fp32_model, num_bits=3, group_size=-1)
    self.assertTrue(isinstance(model1.fc1, torch.nn.Linear))
    weight_config = {
        # 'op_name': (bit, group_size, scheme)
        "fc1": {"bits": 8, "group_size": -1, "scheme": "sym"},
        "fc2": {
            "bits": 4,
            "group_size": 32,
            "scheme": "asym",
            "quantile": 0.95,  # not required.
        },
    }
    model2 = rtn_quantize(fp32_model, weight_config=weight_config)
    model2 = rtn_quantize(fp32_model, weight_config=weight_config, return_int=True)
    self.assertTrue(isinstance(model2.fc1, WeightOnlyLinear))