Dear Expert,

I am trying to create a custom factor using GRANT's template but I encountered the following error. Seem like having a class within a class can generate this error?

NonWindowSafeInput: Can't compute windowed expression SimpleMovingAverage([TEST(...)], 3) with windowed input TEST([NumExprFactor(...)], 252).

def preprocess(a):  
    a = a.astype(np.float64)  
    a[np.isinf(a)] = np.nan  
    a = np.nan_to_num(a - np.nanmean(a))  
    a = winsorize(a, limits=[WIN_LIMIT,WIN_LIMIT])  
    return preprocessing.scale(a)



def make_factors(rng):  
    class LastTwoQuarters(CustomFactor):  
        # Get the last 2 reported values of the given asof_date + field.  
        outputs = ['q2', 'q1']

        window_length = 130

        def compute(self, today, assets, out, asof_date, values):  
            for column_ix in range(asof_date.shape[1]):  
                _, unique_indices = np.unique(asof_date[:, column_ix], return_index=True)  
                quarterly_values = values[unique_indices, column_ix]  
                if len(quarterly_values) < 2:  
                    quarterly_values = np.hstack([  
                            np.repeat([np.nan], 2 - len(quarterly_values)),  
                            quarterly_values,  
                        ])  
                    quarterly_values = quarterly_values[-2:]  
                    out[column_ix] = quarterly_values


    class TEST(CustomFactor):  
        FCFYLD = LastTwoQuarters(inputs = [Fundamentals.fcf_yield_asof_date, Fundamentals.fcf_yield], mask=universe)  
        # FCFYLD.window_safe = True  
        # FCFYLD.q1.window_safe = True  
        FCF_YLD = FCFYLD.q1 + FCFYLD.q2  
        FCF_YLD.window_safe = True  
        inputs = [FCF_YLD]  
        window_length = 252  
        def compute(self, today, assets, out, FCF_YLD):  
            out[:] = preprocess(np.nan_to_num(FCF_YLD)) 

    factors = [  
            TEST  
        ]  
    return factors  
def make_pipeline_1():  
    universe = QTradableStocksUS()  
    factors = make_factors((0,30))  
    combined_alpha = None  
    for f in factors:  
        if combined_alpha == None:  
            combined_alpha = SimpleMovingAverage([f(mask=universe)],window_length=FACTOR_AVG_WINDOW)  
        else:  
            combined_alpha += SimpleMovingAverage([f(mask=universe)],window_length=FACTOR_AVG_WINDOW)  
    beta = SimpleBeta(target=sid(8554),regression_length=260,  
                      allowed_missing_percentage=1.0  
                     )  
    pipe = Pipeline(columns = {  
        'combined_alpha':combined_alpha,  
        'beta':beta,  
    },  
    screen = universe)  
    return pipe  

thanks