PPO playing HalfCheetahBulletEnv-v0 from https://github.com/sgoodfriend/rl-algo-impls/tree/2067e21d62fff5db60168687e7d9e89019a8bfc0
6f3bdf9
import gym | |
import numpy as np | |
from typing import Any, Dict, Tuple, Union | |
from rl_algo_impls.wrappers.vectorable_wrapper import VecotarableWrapper | |
ObsType = Union[np.ndarray, dict] | |
ActType = Union[int, float, np.ndarray, dict] | |
class InitialStepTruncateWrapper(VecotarableWrapper): | |
def __init__(self, env: gym.Env, initial_steps_to_truncate: int) -> None: | |
super().__init__(env) | |
self.initial_steps_to_truncate = initial_steps_to_truncate | |
self.initialized = initial_steps_to_truncate == 0 | |
self.steps = 0 | |
def step(self, action: ActType) -> Tuple[ObsType, float, bool, Dict[str, Any]]: | |
obs, rew, done, info = self.env.step(action) | |
if not self.initialized: | |
self.steps += 1 | |
if self.steps >= self.initial_steps_to_truncate: | |
print(f"Truncation at {self.steps} steps") | |
done = True | |
self.initialized = True | |
return obs, rew, done, info | |