dqn-Acrobot-v1 / ppo /policy.py
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DQN playing Acrobot-v1 from https://github.com/sgoodfriend/rl-algo-impls/tree/1d4094fbcc9082de7f53f4348dd4c7c354152907
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from stable_baselines3.common.vec_env.base_vec_env import VecEnv
from typing import Optional, Sequence
from gym.spaces import Box, Discrete
from shared.policy.on_policy import ActorCritic
class PPOActorCritic(ActorCritic):
def __init__(
self,
env: VecEnv,
pi_hidden_sizes: Optional[Sequence[int]] = None,
v_hidden_sizes: Optional[Sequence[int]] = None,
**kwargs,
) -> None:
obs_space = env.observation_space
if isinstance(obs_space, Box):
if len(obs_space.shape) == 3:
pi_hidden_sizes = pi_hidden_sizes or []
v_hidden_sizes = v_hidden_sizes or []
elif len(obs_space.shape) == 1:
pi_hidden_sizes = pi_hidden_sizes or [64, 64]
v_hidden_sizes = v_hidden_sizes or [64, 64]
else:
raise ValueError(f"Unsupported observation space: {obs_space}")
elif isinstance(obs_space, Discrete):
pi_hidden_sizes = pi_hidden_sizes or [64]
v_hidden_sizes = v_hidden_sizes or [64]
else:
raise ValueError(f"Unsupported observation space: {obs_space}")
super().__init__(
env,
pi_hidden_sizes,
v_hidden_sizes,
**kwargs,
)