def main(run_args):
with open(os.path.join(run_args.logdir, 'hyps.json'), 'r') as f:
hyps = json.load(f)
args = namedtuple('Args', hyps.keys())(**hyps)
env_fn = make_env_fn(args)
model_fn = make_model_fn(args)
time.sleep(1)
alg = Algorithm(run_args.logdir,
env_fn,
model_fn,
args.nenv,
args.rollout_length,
args.batchsize,
epochs_per_iter=args.epochs,
lr=args.lr,
momentum=args.momentum,
ent_coef=args.entcoeff,
gamma=args.gamma,
lambda_=args.lmbda,
clip_norm=args.grad_clip_norm,
clip_param=args.ppo_clip_param,
robot_lr=args.robot_lr,
robot_momentum=args.robot_momentum,
fixed_robot=args.fixed_robot,
steps_before_robot_update=args.steps_before_robot_update,
steps_after_robot_update=args.steps_after_robot_update,
chop_freq=args.chop_freq,
tmax=args.maxtimesteps)
alg.train(args.maxtimesteps, run_args.maxseconds, run_args.save_freq)
alg.close()
