如何重置Keras指标？

import tensorflow as tf
from tensorflow import keras

class CustomAccuracy(keras.metrics.Metric):
    def __init__(self, name='accuracy', **kwargs):
        super(CustomAccuracy, 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):
        y_pred = tf.argmax(y_pred, axis=-1)
        values = tf.cast(tf.equal(y_true, y_pred), tf.float32)
        if sample_weight is not None:
            sample_weight = tf.cast(sample_weight, tf.float32)
            values = tf.multiply(values, sample_weight)
        self.total.assign_add(tf.reduce_sum(values))
        self.count.assign_add(tf.cast(tf.size(values), tf.float32))

    def result(self):
        return self.total / self.count

    def reset_states(self):
        self.total.assign(0.0)
        self.count.assign(0.0)

# 创建模型
model = keras.models.Sequential([...])

# 编译模型并指定自定义指标
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=[CustomAccuracy()])

# 训练模型
model.fit([...])

# 重置指标
model.metrics[-1].reset_states()