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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
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