import tensorflow as tf

            return biases

    # 定义一个卷积层，命名空间为name，输入为x，卷积核为W，步长为stride,偏差为bias,激活函数默认为relu
    def conv2d(self,name, x, W, stride, bias):
        with tf.variable_scope(name) as scope:
            conv = tf.nn.conv2d(x, W, [1, stride, stride, 1], padding='SAME')
            pre_activation = tf.nn.bias_add(conv, bias)
            output = tf.nn.relu(pre_activation, name=scope.name)

            return output

    # 定义一个池化层，默认为max_pooling
