import tensorflow as tf


        W_fc1 = self.weight_variable('W_fc1', [1600, 512])
        b_fc1 = self.bias_variable('b_fc1', [512])

        W_fc2 = self.weight_variable('W_fc2', [512, self.ACTIONS])
        b_fc2 = self.bias_variable('b_fc2', [self.ACTIONS])

        s = tf.placeholder("float", [None, 80, 80, 4])  # 输入层，输入图像为80x80的4通道图像

        h_conv1 = self.conv2d('h_conv1', s, W_conv1, 4, b_conv1)  # 构造第一个卷积层输出为conv1
        h_pool1 = self.max_pool_2x2('h_pool1', h_conv1)

        h_conv2 = self.conv2d('h_conv2', h_pool1, W_conv2, 2, b_conv2)

