def METHOD_NAME():
    results = []
    for i in range(20):
        test_input = torch.rand(1, 3, 224, 224).half().cuda()
        sub_label = f"[test {i}]"
        results.append(
            benchmark.Timer(
                stmt="meta_module_resnet18(test_input)",
                setup="from __main__ import meta_module_resnet18",
                globals={"test_input": test_input},
                sub_label=sub_label,
                description="tuning by meta",
            ).blocked_autorange()
        )
        results.append(
            benchmark.Timer(
                stmt="jit_module_resnet18(test_input)",
                setup="from __main__ import jit_module_resnet18",
                globals={"test_input": test_input},
                sub_label=sub_label,
                description="tuning by jit",
            ).blocked_autorange()
        )
    compare = benchmark.Compare(results)
    compare.print()