rewards1 = [np.sum(epi['rews']) for epi in epis1]
rewards2 = [np.sum(epi['rews']) for epi in epis2]
mean_rew = np.mean(rewards1 + rewards2)
logger.record_tabular_misc_stat('Reward1', rewards1)
logger.record_tabular_misc_stat('Reward2', rewards2)
logger.record_results(args.log,
result_dict,
score_file,
total_epi,
step,
total_step,
rewards1 + rewards2,
plot_title='humanoid')
if mean_rew > max_rew:
torch.save(pol.state_dict(),
os.path.join(args.log, 'models', 'pol_max.pkl'))
torch.save(vf.state_dict(),
os.path.join(args.log, 'models', 'vf_max.pkl'))
torch.save(optim_pol.state_dict(),
os.path.join(args.log, 'models', 'optim_pol_max.pkl'))
torch.save(optim_vf.state_dict(),
os.path.join(args.log, 'models', 'optim_vf_max.pkl'))
max_rew = mean_rew
torch.save(pol.state_dict(),
os.path.join(args.log, 'models', 'pol_last.pkl'))
torch.save(vf.state_dict(), os.path.join(args.log, 'models',
'vf_last.pkl'))
torch.save(optim_pol.state_dict(),
os.path.join(args.log, 'models', 'optim_pol_last.pkl'))
total_epi += traj1.num_epi
step = traj1.num_step
total_step += step
rewards1 = [np.sum(epi['rews']) for epi in epis1]
rewards2 = [np.sum(epi['rews']) for epi in epis2]
mean_rew = np.mean(rewards1 + rewards2)
logger.record_tabular_misc_stat('Reward1', rewards1)
logger.record_tabular_misc_stat('Reward2', rewards2)
logger.record_results(args.log, result_dict, score_file,
total_epi, step, total_step,
rewards1 + rewards2,
plot_title='humanoid')
if mean_rew > max_rew:
torch.save(pol.state_dict(), os.path.join(
args.log, 'models', 'pol_max.pkl'))
torch.save(vf.state_dict(), os.path.join(
args.log, 'models', 'vf_max.pkl'))
torch.save(optim_pol.state_dict(), os.path.join(
args.log, 'models', 'optim_pol_max.pkl'))
torch.save(optim_vf.state_dict(), os.path.join(
args.log, 'models', 'optim_vf_max.pkl'))
max_rew = mean_rew
torch.save(pol.state_dict(), os.path.join(
args.log, 'models', 'pol_last.pkl'))
torch.save(vf.state_dict(), os.path.join(
args.log, 'models', 'vf_last.pkl'))
torch.save(optim_pol.state_dict(), os.path.join(
args.log, 'models', 'optim_pol_last.pkl'))