trpo_swimmer_tf.py

from sandbox.rocky.tf.algos.trpo import TRPO
from rllab.baselines.linear_feature_baseline import LinearFeatureBaseline
from rllab.envs.mujoco.swimmer_env import SwimmerEnv
from rllab.envs.normalized_env import normalize
from sandbox.rocky.tf.policies.gaussian_mlp_policy import GaussianMLPPolicy
from sandbox.rocky.tf.envs.base import TfEnv
from rllab.misc.instrument import stub, run_experiment_lite

def run_task(*_):
    env = TfEnv(normalize(SwimmerEnv()))

    ## ==================
    policy_parameters = {
        "name": "policy",
        "env_spec": env.spec,
        "policy_type": GaussianMLPPolicy,
        "hidden_sizes": (32, 32)
    }
    ## ==================

    policy = GaussianMLPPolicy(policy_parameters)

    baseline = LinearFeatureBaseline(env_spec=env.spec)

    algo = TRPO(
        env=env,
        policy=policy,
        policy_parameters=policy_parameters,
        baseline=baseline,
        batch_size=4000,
        max_path_length=500,
        n_itr=40,
        discount=0.99,
        step_size=0.01,
        plot=True,
    )
    algo.train()

run_experiment_lite(
    run_task,
    n_parallel=4,
    snapshot_mode="last",
    seed=1,
    plot=True,
)