def METHOD_NAME():
    # Same params
    scale_and_zp = {
        "lhs_scale": 0.125,
        "lhs_zp": 0,
        "rhs_scale": 0.125,
        "rhs_zp": 0,
        "output_scale": 0.125,
        "output_zp": 0,
    }
    x_data = [np.array((255, 1, 1, 0)).reshape((1, 4))]
    y_data = [np.array((255, 255, 128, 0)).reshape((1, 4))]
    golden_output = [np.array((0, 0, 0, 0)).reshape((1, 4))]
    qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)
    # Same params, different scale
    scale_and_zp = {
        "lhs_scale": 0.125,
        "lhs_zp": 0,
        "rhs_scale": 0.125,
        "rhs_zp": 0,
        "output_scale": 0.25,
        "output_zp": 0,
    }
    x_data = [np.array((255, 1, 200, 0)).reshape((1, 4))]
    y_data = [np.array((255, 255, 127, 0)).reshape((1, 4))]
    golden_output = [np.array((0, 0, 36, 0)).reshape((1, 4))]
    qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)
    # All params different
    scale_and_zp = {
        "lhs_scale": 0.5,
        "lhs_zp": 0,
        "rhs_scale": 0.25,
        "rhs_zp": 0,
        "output_scale": 0.125,
        "output_zp": 0,
    }
    x_data = [np.array((255, 0, 1, 0)).reshape((1, 4))]
    y_data = [np.array((0, 128, 64, 0)).reshape((1, 4))]
    golden_output = [np.array((255, 0, 0, 0)).reshape((1, 4))]
    qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)