model.py 文件源码

def build_model(self):

        Z = tf.placeholder(tf.float32, [self.batch_size, self.dim_z])
        Y = tf.placeholder(tf.float32, [self.batch_size, self.dim_y])

        image_real = tf.placeholder(tf.float32, [self.batch_size]+self.image_shape)
        h4 = self.generate(Z,Y)
        #image_gen comes from sigmoid output of generator
        image_gen = tf.nn.sigmoid(h4)

        raw_real2 = self.discriminate(image_real, Y)
        #p_real = tf.nn.sigmoid(raw_real)
        p_real=tf.reduce_mean(raw_real2)

        raw_gen2 = self.discriminate(image_gen, Y)
        #p_gen = tf.nn.sigmoid(raw_gen)
        p_gen = tf.reduce_mean(raw_gen2)

        discrim_cost = tf.reduce_sum(raw_real2) - tf.reduce_sum(raw_gen2)
        gen_cost = -tf.reduce_mean(raw_gen2)

        return Z, Y, image_real, discrim_cost, gen_cost, p_real, p_gen