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Testing SACs ability to solve EasierObstacles-v0

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This commit is contained in:
Dominik Moritz Roth 2022-06-21 15:15:38 +02:00
parent 13d335f856
commit 84b3710850
1 changed files with 22 additions and 9 deletions
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31
test.py
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@ -12,19 +12,30 @@ from sb3_trl.trl_pg import TRL_PG
import columbus import columbus
def main(env_name='ColumbusEasyObstacles-v0'): def main(env_name='ColumbusEasierObstacles-v0'):
env = gym.make(env_name) env = gym.make(env_name)
ppo_latent_sde = PPO( ppo_latent_sde = PPO(
"MlpPolicy", "MlpPolicy",
env, env,
verbose=1, verbose=0,
tensorboard_log="./logs_tb/"+env_name+"/ppo_latent_sde/", tensorboard_log="./logs_tb/"+env_name+"/ppo_latent_sde/",
use_sde=True, use_sde=True,
sde_sample_freq=30*15, sde_sample_freq=30*15,
ent_coef=0.0032, ent_coef=0.0016/1.25, #0.0032
vf_coef=0.0005, vf_coef=0.00025/2, #0.0005
gamma=0.95, gamma=0.99, # 0.95
learning_rate=0.02 learning_rate=0.005/5 # 0.015
)
sac_latent_sde = SAC(
"MlpPolicy",
env,
verbose=0,
tensorboard_log="./logs_tb/"+env_name+"/sac_latent_sde/",
use_sde=True,
sde_sample_freq=30*15,
ent_coef=0.0016, #0.0032
gamma=0.99, # 0.95
learning_rate=0.001 # 0.015
) )
#trl = TRL_PG( #trl = TRL_PG(
# "MlpPolicy", # "MlpPolicy",
@ -33,8 +44,10 @@ def main(env_name='ColumbusEasyObstacles-v0'):
# tensorboard_log="./logs_tb/"+env_name+"/trl_pg/", # tensorboard_log="./logs_tb/"+env_name+"/trl_pg/",
#) #)
print('PPO_LATENT_SDE:') #print('PPO_LATENT_SDE:')
testModel(ppo_latent_sde, 100000, showRes = True, saveModel=True, n_eval_episodes=0) #testModel(ppo_latent_sde, 1000000, showRes = True, saveModel=True, n_eval_episodes=3)
print('SAC_LATENT_SDE:')
testModel(ppo_latent_sde, 250000, showRes = True, saveModel=True, n_eval_episodes=0)
#print('TRL_PG:') #print('TRL_PG:')
#testModel(trl) #testModel(trl)
@ -45,7 +58,7 @@ def testModel(model, timesteps=150000, showRes=False, saveModel=False, n_eval_ep
if saveModel: if saveModel:
now = datetime.datetime.now().strftime('%d.%m.%Y-%H:%M') now = datetime.datetime.now().strftime('%d.%m.%Y-%H:%M')
model.save(model.tensorboard_log.replace('./logs_tb/','').replace('/','_')+now+'.zip') model.save('models/'+model.tensorboard_log.replace('./logs_tb/','').replace('/','_')+now+'.zip')
if n_eval_episodes: if n_eval_episodes:
mean_reward, std_reward = evaluate_policy(model, env, n_eval_episodes=n_eval_episodes, deterministic=False) mean_reward, std_reward = evaluate_policy(model, env, n_eval_episodes=n_eval_episodes, deterministic=False)