def create_video(py_env: py_environment.PyEnvironment,
tf_env: tf_environment.TFEnvironment,
policy: tf_py_policy.TFPyPolicy,
num_episodes=10,
max_episode_length=60 * 30,
video_filename='eval_video.mp4'):
logging.info('Generating video %s', video_filename)
py_env.reset()
with imageio.get_writer(video_filename, fps=60) as vid:
for episode in range(num_episodes):
logging.info('\tEpisode %s of %s', episode + 1, num_episodes)
frames = 0
time_step = tf_env.reset()
py_env.reset()
state = policy.get_initial_state(tf_env.batch_size)
vid.append_data(py_env.render(mode='rgb_array'))
while not time_step.is_last() and frames < max_episode_length:
if frames % 60 == 0:
logging.info('Frame %s of %s', frames, max_episode_length)
policy_step = policy.action(time_step, state)
state = policy_step.state
time_step = tf_env.step(policy_step.action)
py_env.step(policy_step.action)
vid.append_data(py_env.render(mode='rgb_array'))
frames += 1
py_env.close()
logging.info('Finished rendering video %s', video_filename)
def create_video(py_environment: PyEnvironment,
tf_environment: TFPyEnvironment,
policy: tf_policy,
num_episodes=10,
video_filename='imageio.mp4'):
print("Generating video %s" % video_filename)
with imageio.get_writer(video_filename, fps=60) as video:
for episode in range(num_episodes):
print("Generating episode %d of %d" % (episode, num_episodes))
time_step = tf_environment.reset()
video.append_data(py_environment.render())
while not time_step.is_last():
action_step = policy.action(time_step)
time_step = tf_environment.step(action_step.action)
video.append_data(py_environment.render())
def create_video(py_environment: PyEnvironment, tf_environment: TFEnvironment, policy: tf_policy.Base, num_episodes=10, video_filename='imageio.mp4'):
logging.info("Generating video %s" % video_filename)
with imageio.get_writer(video_filename, fps=60) as video:
for episode in range(num_episodes):
logging.info("Generating episode %d of %d" % (episode, num_episodes))
time_step = tf_environment.reset()
state = policy.get_initial_state(tf_environment.batch_size)
video.append_data(py_environment.render())
while not time_step.is_last():
policy_step: PolicyStep = policy.action(time_step, state)
state = policy_step.state
time_step = tf_environment.step(policy_step.action)
video.append_data(py_environment.render())
logging.info("Finished video %s" % video_filename)
def create_video(py_environment: PyEnvironment,
tf_environment: TFPyEnvironment,
policy: tf_policy,
num_episodes=10,
video_filename='imageio.mp4'):
print("Generating video %s" % video_filename)
with imageio.get_writer(video_filename, fps=60) as video:
for episode in range(num_episodes):
episode_return = 0.0
time_step = tf_environment.reset()
video.append_data(py_environment.render())
while not time_step.is_last():
action_step = policy.action(time_step)
time_step = tf_environment.step(action_step.action)
episode_return += time_step.reward
video.append_data(py_environment.render())
print(
f"Generated episode {episode} of {num_episodes}. Return:{episode_return} "
)