Method load_weights

examples/reinforcement_learning/tutorial_SAC.py:347–355

(self)

        np.save(extend_path('log_alpha.npy'), self.log_alpha.numpy())  # save log_alpha variable

    def load_weights(self):  # load trained weights
        path = os.path.join('model', '_'.join([ALG_NAME, ENV_ID]))
        extend_path = lambda s: os.path.join(path, s)
        tl.files.load_and_assign_npz(extend_path('model_q_net1.npz'), self.soft_q_net1)
        tl.files.load_and_assign_npz(extend_path('model_q_net2.npz'), self.soft_q_net2)
        tl.files.load_and_assign_npz(extend_path('model_target_q_net1.npz'), self.target_soft_q_net1)
        tl.files.load_and_assign_npz(extend_path('model_target_q_net2.npz'), self.target_soft_q_net2)
        tl.files.load_and_assign_npz(extend_path('model_policy_net.npz'), self.policy_net)
        self.log_alpha.assign(np.load(extend_path('log_alpha.npy')))  # load log_alpha variable


if __name__ == '__main__':