ray/rllib/examples/env/cartpole_crashing.py

86 lines
3.1 KiB
Python

import logging
from gym.envs.classic_control import CartPoleEnv
import numpy as np
import time
from ray.rllib.examples.env.multi_agent import make_multi_agent
from ray.rllib.utils.annotations import override
from ray.rllib.utils.error import EnvError
logger = logging.getLogger(__name__)
class CartPoleCrashing(CartPoleEnv):
"""A CartPole env that crashes from time to time.
Useful for testing faulty sub-env (within a vectorized env) handling by
RolloutWorkers.
After crashing, the env expects a `reset()` call next (calling `step()` will
result in yet another error), which may or may not take a very long time to
complete. This simulates the env having to reinitialize some sub-processes, e.g.
an external connection.
"""
def __init__(self, config=None):
super().__init__()
config = config or {}
# Crash probability (in each `step()`).
self.p_crash = config.get("p_crash", 0.005)
self.p_crash_reset = config.get("p_crash_reset", self.p_crash)
self.crash_after_n_steps = config.get("crash_after_n_steps")
# Only crash (with prob=p_crash) if on certain worker indices.
faulty_indices = config.get("crash_on_worker_indices", None)
if faulty_indices and config.worker_index not in faulty_indices:
self.p_crash = 0.0
self.p_crash_reset = 0.0
self.crash_after_n_steps = None
# Timestep counter for the ongoing episode.
self.timesteps = 0
# Time in seconds to initialize (in this c'tor).
init_time_s = config.get("init_time_s", 0)
time.sleep(init_time_s)
# Time in seconds to re-initialize, while `reset()` is called after a crash.
self.re_init_time_s = config.get("re_init_time_s", 10)
# No env pre-checking?
self._skip_env_checking = config.get("skip_env_checking", False)
# Make sure envs don't crash at the same time.
self._rng = np.random.RandomState()
@override(CartPoleEnv)
def reset(self):
# Reset timestep counter for the new episode.
self.timesteps = 0
# Should we crash?
if self._rng.rand() < self.p_crash_reset or (
self.crash_after_n_steps is not None and self.crash_after_n_steps == 0
):
raise EnvError(
"Simulated env crash in `reset()`! Feel free to use any "
"other exception type here instead."
)
return super().reset()
@override(CartPoleEnv)
def step(self, action):
# Increase timestep counter for the ongoing episode.
self.timesteps += 1
# Should we crash?
if self._rng.rand() < self.p_crash or (
self.crash_after_n_steps and self.crash_after_n_steps == self.timesteps
):
raise EnvError(
"Simulated env crash in `step()`! Feel free to use any "
"other exception type here instead."
)
# No crash.
return super().step(action)
MultiAgentCartPoleCrashing = make_multi_agent(lambda config: CartPoleCrashing(config))