def play(env, act, stochastic, video_path):
    num_episodes = 0
    video_recorder = None
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)
    obs = env.reset()
    if args.visual:
        action_names = distdeepq.actions_from_env(env)
        plot_machine = distdeepq.PlotMachine(dist_params, env.action_space.n,
                                             action_names)
    while True:
        env.unwrapped.render()
        video_recorder.capture_frame()
        action = act(np.array(obs)[None], stochastic=stochastic)[0]
        obs, rew, done, info = env.step(action)
        if args.visual:
            plot_machine.plot_distribution(np.array(obs)[None])

        if done:
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print(info["rewards"][-1])
            num_episodes = len(info["rewards"])
Exemple #2
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def play(env, act, stochastic, video_path):
    num_episodes = 0
    video_recorder = None
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)
    obs = env.reset()
    X = []
    while True:
        env.unwrapped.render()
        video_recorder.capture_frame()
        action = act(np.array(obs)[None], stochastic=stochastic)[0]
        obs, rew, done, info = env.step(action)
        if done:
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print("Score in this episode: " + str(info["rewards"][-1]))
            X.append(info["rewards"][-1])
            num_episodes = len(info["rewards"])
            print("Average Score so far: " + str(sum(X) / float(num_episodes)))
Exemple #3
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def play(env, act, stochastic, video_path):
    num_episodes = 0
    video_recorder = None
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)
    obs = env.reset()
    if args.show_observation:
        fig = plt.figure()
        im = plt.imshow(obs._frames[-1].reshape((84, 84)), cmap='Greys')
        plt.show(False)
    while True:
        env.unwrapped.render()
        if args.show_observation:
            im.set_data(obs._frames[-1].reshape((84, 84)))
            fig.canvas.draw()
        video_recorder.capture_frame()
        action = act(np.array(obs)[None], stochastic=stochastic)[0]
        obs, rew, done, info = env.step(action)
        if done:
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print(info["rewards"][-1])
            num_episodes = len(info["rewards"])
Exemple #4
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def play(env, act, stochastic, video_path, clipped, num_trials=10):
    num_episodes = 0
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)
    obs = env.reset()
    reward = 0
    num_played = 0
    rewardArray = []
    while num_played < num_trials:
        env.unwrapped.render()
        video_recorder.capture_frame()
        action = act(np.array(obs)[None], stochastic=stochastic)[0]
        obs, rew, done, info = env.step(action)
        if clipped:
            rew = clip_score(rew)
        reward += rew
        if done:
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print(info["rewards"][-1])
            rewardArray.append(reward)
            reward = 0
            num_played += 1
            num_episodes = len(info["rewards"])
    return {"Nonclipped": info["rewards"], "Clipped": rewardArray}
Exemple #5
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def play(
    env,
    act,
    craft_adv_obs,
    craft_adv_obs2,
    stochastic,
    video_path,
    attack,
    m_target,
    m_adv,
):
    num_episodes = 0
    num_moves = 0
    num_transfer = 0

    video_recorder = None
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)
    obs = env.reset()
    while True:
        env.unwrapped.render()
        video_recorder.capture_frame()

        # V: Attack #
        if attack is not None:
            # Craft adv. examples
            with m_adv.get_session().as_default():
                adv_obs = craft_adv_obs(np.array(obs)[None],
                                        stochastic_adv=stochastic)[0]
            with m_target.get_session().as_default():
                action = act(np.array(adv_obs)[None], stochastic=stochastic)[0]
                action2 = act(np.array(obs)[None], stochastic=stochastic)[0]
                num_moves += 1
                if action != action2:
                    num_transfer += 1
        else:
            # Normal
            action = act(np.array(obs)[None], stochastic=stochastic)[0]

        obs, rew, done, info = env.step(action)
        if done:
            obs = env.reset()

        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print("Reward: " + str(info["rewards"][-1]))
            num_episodes = len(info["rewards"])
            print("Episode: " + str(num_episodes))
            success = float(num_transfer / num_moves) * 100.0
            print("Percentage of successful attacks: " + str(success))
            num_moves = 0
            num_transfer = 0
def play(env, act, craft_adv_obs, stochastic, video_path, game_name, attack,
         defense):
    if defense == 'foresight':
        vf, game_screen_mean = load_visual_foresight(game_name)
        pred_obs = deque(maxlen=4)

    num_episodes = 0
    video_recorder = None
    video_recorder = VideoRecorder(env,
                                   video_path,
                                   enabled=video_path is not None)

    t = 0
    obs = env.reset()
    while True:
        #env.unwrapped.render()
        video_recorder.capture_frame()

        # Attack
        if craft_adv_obs != None:
            # Craft adv. examples
            adv_obs = craft_adv_obs(np.array(obs)[None],
                                    stochastic=stochastic)[0]
            action = act(np.array(adv_obs)[None], stochastic=stochastic)[0]
        else:
            # Normal
            action = act(np.array(obs)[None], stochastic=stochastic)[0]

# Defense
        if t > 4 and defense == 'foresight':
            pred_obs.append(
                foresee(U.get_session(), old_obs, old_action, np.array(obs),
                        game_screen_mean, vf, env.action_space.n, t))
            if len(pred_obs) == 4:
                action = act(np.stack(pred_obs, axis=2)[None],
                             stochastic=stochastic)[0]

        old_obs = obs
        old_action = action

        # RL loop
        obs, rew, done, info = env.step(action)
        t += 1
        if done:
            t = 0
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print(info["rewards"][-1])
            num_episodes = len(info["rewards"])
Exemple #7
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def play(env, act, craft_adv_obs, craft_adv_obs2, stochastic, video_path,
         attack, m_target, m_adv):
    num_episodes = 0
    num_moves = 0
    num_transfer = 0

    video_recorder = None
    video_recorder = VideoRecorder(
        env, video_path, enabled=video_path is not None)
    obs = env.reset()
    while True:
        env.unwrapped.render()
        video_recorder.capture_frame()

        # V: Attack #
        if attack is not None:
            # Craft adv. examples
            with m_adv.get_session().as_default():
                adv_obs = \
                    craft_adv_obs(np.array(obs)[None],
                                  stochastic_adv=stochastic)[0]
            with m_target.get_session().as_default():
                action = act(np.array(adv_obs)[None],
                             stochastic=stochastic)[0]
                action2 = act(np.array(obs)[None], stochastic=stochastic)[0]
                num_moves += 1
                if action != action2:
                    num_transfer += 1
        else:
            # Normal
            action = act(np.array(obs)[None], stochastic=stochastic)[0]

        obs, rew, done, info = env.step(action)
        if done:
            obs = env.reset()

        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print('Reward: ' + str(info["rewards"][-1]))
            num_episodes = len(info["rewards"])
            print('Episode: ' + str(num_episodes))
            success = float(num_transfer / num_moves) * 100.0
            print("Percentage of successful attacks: " + str(success))
            num_moves = 0
            num_transfer = 0
Exemple #8
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def play(env, act, stochastic, video_path):
    num_episodes = 0
    video_recorder = None
    video_recorder = VideoRecorder(
        env, video_path, enabled=video_path is not None)
    obs = env.reset()
    while True:
        env.unwrapped.render()
        video_recorder.capture_frame()
        action = act(np.array(obs)[None], stochastic=stochastic)[0]
        obs, rew, done, info = env.step(action)
        if done:
            obs = env.reset()
        if len(info["rewards"]) > num_episodes:
            if len(info["rewards"]) == 1 and video_recorder.enabled:
                # save video of first episode
                print("Saved video.")
                video_recorder.close()
                video_recorder.enabled = False
            print(info["rewards"][-1])
            num_episodes = len(info["rewards"])
Exemple #9
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                              batch_size=BATCH_SIZE,
                              shuffle=True)

match_env(env_real, env_sim)
video_recorder = VideoRecorder(env_real, 'real.mp4', enabled=True)
video_recorder2 = VideoRecorder(env_sim, 'sim.mp4', enabled=True)

for i, data in enumerate(dataloader_train):
    for j in range(50):
        env_sim.render()
        env_real.render()

        action = data["actions"][0, j].numpy()

        video_recorder.capture_frame()
        video_recorder2.capture_frame()

        obs_real, _, _, _ = env_real.step(action.copy())
        obs_simp, _, _, _ = env_sim.step(action.copy())

    env_real.reset()
    env_sim.reset()
    match_env(env_real, env_sim)
    if i == 10:
        break

video_recorder.close()
video_recorder.enabled = False
video_recorder2.close()
video_recorder2.enabled = False