def METHOD_NAME(self):
    finetune_model = build_model(self.model_config)
    finetune_model.eval()
    test_sample = Sample()
    test_sample.input_ids = torch.randint(low=0, high=30255, size=(128,)).long()
    test_sample.input_mask = torch.ones(128).long()
    test_sample.segment_ids = torch.zeros(128).long()
    test_sample.image = torch.rand((3, 300, 300)).float()
    test_sample_list = SampleList([test_sample.copy()])
    with torch.no_grad():
        model_output = finetune_model.model(test_sample_list)
    test_sample_list = SampleList([test_sample])
    script_model = torch.jit.script(finetune_model.model)
    with torch.no_grad():
        script_output = script_model(test_sample_list)
    self.assertTrue(torch.equal(model_output["scores"], script_output["scores"]))