def METHOD_NAME(cfg, rec_val, batch_size=1, original=False):
    qconfig = qtz.qconfig(
        skip_conv_layers=[0],
        skip_dense_layer=False,
        nbit_input=cfg.nbit_input,
        nbit_weight=cfg.nbit_input,
        dtype_input=cfg.dtype_input,
        dtype_weight=cfg.dtype_input,
        dtype_activation=cfg.dtype_output,
        debug_enabled_ops=None,
        calibrate_mode="percentile",
        calibrate_chunk_by=8,
    )
    dataset = list(calibrate_dataset(cfg.model, rec_val, batch_size, 64))
    model, params, logfile = get_onnx_model(
        cfg.model, batch_size, qconfig, original=original, dataset=dataset
    )
    val_data, batch_fn = get_val_data(cfg.model, rec_val=rec_val, batch_size=batch_size)
    with tvm.autotvm.apply_history_best(logfile):
        acc = eval_acc(model, params, val_data, batch_fn, log_interval=1000)
    assert acc > cfg.expected_acc
    return acc