def METHOD_NAME(self):
    import time
    from jittor.models import resnet
    im=np.random.rand(100,3,224,224).astype(np.float32)
    net = resnet.Resnet34()
    net.eval()
    # warm up
    x = jt.array(im).stop_grad()
    for i in range(10):
        a = net(x)
        a.sync()
    jt.sync(device_sync=True)
    # pure compute
    time_start=time.time()
    x = jt.array(im).stop_grad()
    for i in range(10):
        a = net(x)
        a.sync()
    jt.sync(device_sync=True)
    t1 = time.time() - time_start
    # warm up
    for i in range(3):
        x = jt.array(im)
        b = net(x)
        b.fetch(lambda b: None)
        b.sync()
    jt.sync(device_sync=True)
    # overlap
    time_start=time.time()
    results = []
    for i in range(10):
        x = jt.array(im)
        b = net(x)
        b.fetch(lambda b: results.append(b))
        b.sync()
        # del c
    jt.sync(device_sync=True)
    t2 = time.time() - time_start
    assert t2-t1 < 0.010, (t2, t1, t2-t1)
    assert np.allclose(a.data, b.data)
    assert len(results) == 10
    for v in results:
        assert np.allclose(a.data, v), (v.shape, a.data.shape)
    jt.LOG.v(f"pure compute: {t1}, overlap: {t2}")