tfpolicy.py 文件源码

def initialize(self):
        if self.summarize:
            bs = tf.to_float(tf.shape(self.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.scalar("model/grad_gnorm", tf.global_norm(self.grads))
            tf.summary.scalar("model/var_gnorm", tf.global_norm(self.var_list))
            self.summary_op = tf.summary.merge_all()

        self.sess = tf.Session(graph=self.g, config=tf.ConfigProto(
            intra_op_parallelism_threads=1, inter_op_parallelism_threads=2))
        self.variables = ray.experimental.TensorFlowVariables(self.loss,
                                                              self.sess)
        self.sess.run(tf.global_variables_initializer())