train.py 文件源码

def f1_score(confusion):
    tps = np.diagonal(confusion)
    supports = confusion.sum(axis=1)
    # TODO remove this ignore divide by 0, shouldn't happen
    with np.errstate(divide='ignore', invalid='ignore'):
        precisions = np.true_divide(tps, confusion.sum(axis=0))
        recalls = np.true_divide(tps, supports)
        f1s = 2*np.true_divide((precisions*recalls),(precisions+recalls))
        f1s[f1s == np.inf] = 0
        f1s = np.nan_to_num(f1s)
    f1 = np.average(f1s, weights=supports)
    return f1

# TODO remove duplicated code, same as intent model utils