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import gymnasium as gym
import numpy as np
import random
from utils import MiniGridShieldHandler, create_shield_query
class MiniGridSbShieldingWrapper(gym.core.Wrapper):
def __init__(self,
env,
shield_creator : MiniGridShieldHandler,
shield_query_creator,
create_shield_at_reset = True,
mask_actions=True,
):
super(MiniGridSbShieldingWrapper, self).__init__(env)
self.max_available_actions = env.action_space.n
self.observation_space = env.observation_space.spaces["image"]
self.shield_creator = shield_creator
self.mask_actions = mask_actions
self.shield_query_creator = shield_query_creator
def create_action_mask(self):
if not self.mask_actions:
return np.array([1.0] * self.max_available_actions, dtype=np.int8)
cur_pos_str = self.shield_query_creator(self.env)
allowed_actions = []
# Create the mask
# If shield restricts actions, mask only valid actions with 1.0
# else set all actions valid
mask = np.array([0.0] * self.max_available_actions, dtype=np.int8)
if cur_pos_str in self.shield and self.shield[cur_pos_str]:
allowed_actions = self.shield[cur_pos_str]
for allowed_action in allowed_actions:
index = get_action_index_mapping(allowed_action.labels)
if index is None:
assert(False)
mask[index] = random.choices([0.0, 1.0], weights=(1 - allowed_action.prob, allowed_action.prob))[0]
else:
for index, x in enumerate(mask):
mask[index] = 1.0
front_tile = self.env.grid.get(self.env.front_pos[0], self.env.front_pos[1])
if front_tile and front_tile.type == "door":
mask[Actions.toggle] = 1.0
return mask
def reset(self, *, seed=None, options=None):
obs, infos = self.env.reset(seed=seed, options=options)
shield = self.shield_creator.create_shield(env=self.env)
self.shield = shield
return obs["image"], infos
def step(self, action):
orig_obs, rew, done, truncated, info = self.env.step(action)
obs = orig_obs["image"]
return obs, rew, done, truncated, info