making the expert demonstration processor go through all agents in order when producing a single (default) trajectory file, using a randomized agent environment in optionsgail, starting function to process and store all expert data

This commit is contained in:
Arec
2021-10-13 11:20:40 -07:00
parent 70e55327dc
commit 415d607418
9 changed files with 900 additions and 0 deletions

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import stable_baselines3 as sb3
from intersim.envs.intersimple import NRasterized
def render_env(model_name='gail_image_multiagent_nocollision', agent=51, environment=NRasterized):
"""
Render a video from an model, agent, and environment
Args:
model_name (str): name of the model
agent (int): agent to start the video from
environment (gym.Env): gym environment class to render environment on
"""
model = sb3.PPO.load(model_name)
env = environment(stop_on_collision=False, width=36, height=36, m_per_px=2, agent=agent)
obs = env.reset()
i=0
while True and i < 600:
i+=1
action, _states = model.predict(obs)
obs, rewards, done, info = env.step(action)
env.render(mode='post')
if done:
break
env.close(filestr='render/'+model_name+'_agent%i'%(agent))
if __name__ == '__main__':
import fire
fire.Fire(render_env)