

def standardize_X(shape, X):
    if (not numpy_array(X)):
        X = np.asarray(X)
    if ((len(shape) == 4) and (len(shape.shape) == 2)):
        return X.reshape((- 1), shape[2], shape[3], shape[1]).transpose(0, 3, 1, 2)
    else:
        return X

dataset/ETHPy150Open IndicoDataSolutions/Foxhound/foxhound/preprocessing.py standardize_X/VarMisuse@47/52 `X`->`shape`