def run(v): np.random.seed(v['seed']) env_maker = EnvMaker('Pendulum-v0') env = env_maker.make() policy = GaussianMLPPolicy( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec, hidden_sizes=(64, 64), hidden_nonlinearity=chainer.functions.tanh, ) if v['baseline'] == 'mlp': baseline = MLPBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec, hidden_sizes=(64, 64), hidden_nonlinearity=chainer.functions.tanh, ) elif v['baseline'] == 'time_dependent': baseline = TimeDependentBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec, ) elif v['baseline'] == 'linear_feature': baseline = LinearFeatureBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec, ) else: raise ValueError trpo( env=env, env_maker=env_maker, n_envs=16, policy=policy, baseline=baseline, batch_size=10000, n_iters=100, snapshot_saver=SnapshotSaver(logger.get_dir()), )
def run(v): np.random.seed(v['seed']) env_maker = EnvMaker('CartPole-v0') env = env_maker.make() policy = CategoricalMLPPolicy( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) baseline = MLPBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) trpo( env=env, env_maker=env_maker, n_envs=16, policy=policy, baseline=baseline, batch_size=2000, n_iters=100, snapshot_saver=SnapshotSaver(logger.get_dir()) )
log_dir = "data/local/trpo-cartpole" np.random.seed(42) # Clean up existing logs os.system("rm -rf {}".format(log_dir)) with logger.session(log_dir): env_maker = EnvMaker('CartPole-v0') env = env_maker.make() policy = CategoricalMLPPolicy( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) baseline = MLPBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) trpo( env=env, env_maker=env_maker, n_envs=16, policy=policy, baseline=baseline, batch_size=2000, n_iters=100, snapshot_saver=SnapshotSaver(log_dir) )
log_dir = "data/local/trpo-cartpole" np.random.seed(42) # Clean up existing logs os.system("rm -rf {}".format(log_dir)) with logger.session(log_dir): env_maker = EnvMaker('CartPole-v0') env = env_maker.make() policy = CategoricalMLPPolicy( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) baseline = MLPBaseline( observation_space=env.observation_space, action_space=env.action_space, env_spec=env.spec ) trpo( env=env, env_maker=env_maker, n_envs=16, policy=policy, baseline=baseline, batch_size=2000, n_iters=100, snapshot_saver=SnapshotSaver(log_dir) )