import tensorflow as tf

                    self.update_params_op = OPT.apply_gradients(zip(grads, globalAC.var_list))
                    # 其中传送的是local—net的actor和critic的参数梯度grads,具体计算在上面定义
                    # apply_gradients是tf.train.Optimizer中自带的功能函数，将求得的梯度参数更新到global中
            self.inc_step = self.global_step.assign_add(tf.shape(self.obs)[0])
            self.train_op = tf.group(self.update_params_op, self.inc_step)
            # GLOBALE_STEP += tf.shape(self.obs)[0]

    def build_model(self):
