39a28aba95b0d8eeb56f7a17b7dad140e601b591,agents/clipped_ppo_agent.py,ClippedPPOAgent,choose_action,#ClippedPPOAgent#Any#Any#,180

Before Change

    def choose_action(self, curr_state, phase=RunPhase.TRAIN):
        // convert to batch so we can run it through the network
        observation = curr_state["observation"]
        observation = np.expand_dims(np.array(observation), 0)

        if self.env.discrete_controls:
            // DISCRETE

After Change

    def choose_action(self, current_state, phase=RunPhase.TRAIN):
        if self.env.discrete_controls:
            // DISCRETE
            _, action_values = self.main_network.online_network.predict(self.tf_input_state(current_state))
            action_values = action_values.squeeze()

            if phase == RunPhase.TRAIN:
                action = self.exploration_policy.get_action(action_values)
            else:
                action = np.argmax(action_values)
            action_info = {"action_probability": action_values[action]}
            // self.entropy.add_sample(-np.sum(action_values * np.log(action_values)))
        else:
            // CONTINUOUS
            _, action_values_mean, action_values_std = self.main_network.online_network.predict(self.tf_input_state(current_state))
            action_values_mean = action_values_mean.squeeze()
            action_values_std = action_values_std.squeeze()
            if phase == RunPhase.TRAIN:

Instances