Allow manual early stopping of training (Ctrl+C)
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68
test.py
68
test.py
@ -17,75 +17,39 @@ import columbus
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root_path = '.'
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def main(env_name='ColumbusCandyland_Aux10-v0', timesteps=500000, showRes=True, saveModel=True, n_eval_episodes=0):
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def main(env_name='ColumbusCandyland_Aux10-v0', timesteps=200_000, showRes=True, saveModel=True, n_eval_episodes=0):
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env = gym.make(env_name)
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test_sde = False
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use_sde = False
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ppo = PPO(
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"MlpPolicy",
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env,
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verbose=0,
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tensorboard_log=root_path+"/logs_tb/"+env_name+"/ppo/",
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tensorboard_log=root_path+"/logs_tb/" +
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env_name+"/ppo"+(['', '_sde'][use_sde])+"/",
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learning_rate=3e-4,
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gamma=0.99,
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gae_lambda=0.95,
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normalize_advantage=True,
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ent_coef=0.1, # 0.1
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ent_coef=0.02, # 0.1
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vf_coef=0.5,
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use_sde=False, # False
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use_sde=use_sde, # False
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clip_range=0.2,
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)
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trl_pg = TRL_PG(
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"MlpPolicy",
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env,
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verbose=0,
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tensorboard_log=root_path+"/logs_tb/"+env_name+"/trl_pg/",
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tensorboard_log=root_path+"/logs_tb/"+env_name +
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"/trl_pg"+(['', '_sde'][use_sde])+"/",
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learning_rate=3e-4,
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gamma=0.99,
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gae_lambda=0.95,
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normalize_advantage=True,
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ent_coef=0.1, # 0.1
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ent_coef=0.03, # 0.1
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vf_coef=0.5,
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use_sde=False, # False
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use_sde=use_sde,
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clip_range=2, # 0.2
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)
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if test_sde:
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ppo_latent_sde = PPO(
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"MlpPolicy",
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env,
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verbose=0,
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tensorboard_log=root_path+"/logs_tb/"+env_name+"/ppo_latent_sde/",
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learning_rate=3e-4,
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gamma=0.99,
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gae_lambda=0.95,
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normalize_advantage=True,
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ent_coef=0.15, # 0.1
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vf_coef=0.5,
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use_sde=True, # False
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sde_sample_freq=30*15, # -1
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)
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trl_pg_latent_sde = TRL_PG(
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"MlpPolicy",
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env,
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verbose=0,
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tensorboard_log=root_path+"/logs_tb/"+env_name+"/trl_pg_latent_sde/",
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learning_rate=3e-4,
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gamma=0.99,
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gae_lambda=0.95,
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normalize_advantage=True,
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ent_coef=0.15, # 0.1
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vf_coef=0.5,
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use_sde=True, # False
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sde_sample_freq=30*15, # -1
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)
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# sac_latent_sde = SAC(
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# "MlpPolicy",
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# env,
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# verbose=0,
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# tensorboard_log=root_path+"/logs_tb/"+env_name+"/sac_latent_sde/",
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# use_sde=True,
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# sde_sample_freq=30*15,
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# ent_coef=0.0016, #0.0032
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# gamma=0.99, # 0.95
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# learning_rate=0.001 # 0.015
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# )
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print('TRL_PG:')
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testModel(trl_pg, timesteps, showRes,
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@ -97,13 +61,18 @@ def main(env_name='ColumbusCandyland_Aux10-v0', timesteps=500000, showRes=True,
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def testModel(model, timesteps, showRes=False, saveModel=False, n_eval_episodes=16):
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env = model.get_env()
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try:
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model.learn(timesteps)
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except KeyboardInterrupt:
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print('[!] Training Terminated')
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pass
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if saveModel:
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now = datetime.datetime.now().strftime('%d.%m.%Y-%H:%M')
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loc = root_path+'/models/' + \
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model.tensorboard_log.replace(
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root_path+'/logs_tb/', '').replace('/', '_')+now+'.zip'
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print(model.get_parameters())
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model.save(loc)
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if n_eval_episodes:
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@ -132,3 +101,6 @@ def testModel(model, timesteps, showRes=False, saveModel=False, n_eval_episodes=
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if __name__ == '__main__':
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main('LunarLanderContinuous-v2')
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#main('ColumbusJustState-v0')
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#main('ColumbusStateWithBarriers-v0')
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#main('ColumbusEasierObstacles-v0')
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