base.py 文件源码

def build_summary(self):
    bs = tf.to_float(tf.shape(self.local_network.x)[0])

    tf.summary.scalar("model/policy_loss", self.pi_loss / bs)
    tf.summary.scalar("model/value_loss", self.vf_loss / bs)
    tf.summary.scalar("model/entropy", self.entropy / bs)
    tf.summary.image("model/state", self.local_network.x)
    tf.summary.scalar("model/grad_global_norm", tf.global_norm(self.grads))
    tf.summary.scalar("model/var_global_norm", tf.global_norm(self.local_network.var_list))
    tf.summary.scalar("model/lr", self.lr)

    self.summary_op = tf.summary.merge_all()