如何在python Keras中实现自定义指标“负预测值”？

import keras.backend as K

def neg_pred(y_true, y_pred):
    # 将预测值转换为二分类结果（0或1）
    y_pred_binary = K.round(y_pred)

    # 计算负预测值
    neg_pred_value = K.sum(1 - y_pred_binary) / K.sum(K.ones_like(y_pred_binary))

    return neg_pred_value

from keras.models import Sequential
from keras.layers import Dense

model = Sequential()
model.add(Dense(64, activation='relu', input_dim=100))
model.add(Dense(1, activation='sigmoid'))

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=[neg_pred])