如何实现精确匹配/子集精度作为Keras的度量标准？

from keras import backend as K
from keras.metrics import Metric

class ExactMatch(Metric):
    def __init__(self, name='exact_match', **kwargs):
        super(ExactMatch, self).__init__(name=name, **kwargs)
        self.total = self.add_weight(name='total', initializer='zeros')
        self.count = self.add_weight(name='count', initializer='zeros')
    
    def update_state(self, y_true, y_pred, sample_weight=None):
        # 实现度量标准的更新逻辑
        exact_match = K.cast(K.all(K.equal(y_true, y_pred), axis=-1), K.floatx())
        self.total.assign_add(K.cast(K.shape(y_true)[0], K.floatx()))
        self.count.assign_add(K.sum(exact_match))
    
    def result(self):
        # 返回最终的度量结果
        return self.count / self.total
    
    def reset_states(self):
        # 重置度量状态
        self.total.assign(0.0)
        self.count.assign(0.0)

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