自定义keras真正指标应该总是返回一个整数吗？

import tensorflow as tf
from tensorflow import keras

class CustomAccuracy(keras.metrics.Metric):
    def __init__(self, name='custom_accuracy', **kwargs):
        super(CustomAccuracy, self).__init__(name=name, **kwargs)
        self.correct_count = self.add_weight(name='correct_count', initializer='zeros')
        self.total_count = self.add_weight(name='total_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 *= sample_weight
        self.correct_count.assign_add(tf.reduce_sum(values))
        self.total_count.assign_add(tf.cast(tf.shape(y_true)[0], tf.float32))

    def result(self):
        return tf.math.divide_no_nan(self.correct_count, self.total_count)

    def reset_states(self):
        self.correct_count.assign(0.0)
        self.total_count.assign(0.0)

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=[CustomAccuracy()])