如何创建自定义keras层"min pooling“而忽略零？

import tensorflow as tf
from tensorflow.keras.layers import Layer

class MinPooling(Layer):
    def __init__(self, pool_size=(2, 2), **kwargs):
        super(MinPooling, self).__init__(**kwargs)
        self.pool_size = pool_size

    def call(self, inputs):
        return tf.where(inputs != 0, tf.nn.pool(inputs, window_shape=self.pool_size, pooling_type='MIN', padding='SAME'), inputs)

    def get_config(self):
        config = super(MinPooling, self).get_config()
        config.update({'pool_size': self.pool_size})
        return config

# 创建模型
model = tf.keras.Sequential()
model.add(MinPooling(pool_size=(2, 2)))
# 添加其他层和配置...

# 编译和训练模型...