GMAN.py 文件源码

def add_summaries(self):
        self.min_Df = tf.reduce_min(self.Df)
        self.max_Df = tf.reduce_max(self.Df)
        self.min_Dr = tf.reduce_min(self.Dr)
        self.max_Dr = tf.reduce_max(self.Dr)
        tf.summary.scalar('D_0_z', tf.reduce_mean(self.Df[0]))
        tf.summary.scalar('min_D_z', self.min_Df)
        tf.summary.scalar('max_D_z', self.max_Df)
        tf.summary.scalar('D_0_x', tf.reduce_mean(self.Dr[0]))
        tf.summary.scalar('min_D_x', self.min_Dr)
        tf.summary.scalar('max_D_x', self.max_Dr)
        tf.summary.histogram('D_f', self.Df)
        tf.summary.histogram('D_r', self.Dr)
        for ind in range(len(self.D_losses)):
            tf.summary.scalar('D_%d_Loss' % ind, self.D_losses[ind])
        tf.summary.scalar('G_loss', self.G_loss)
        for ind in range(len(self.V_D)):
            tf.summary.scalar('V_D_%d' % ind, self.V_D[ind])
        tf.summary.scalar('V_G', self.V_G)