Source code for jaclearn.rl.envs.gym_adapter

#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File   : gym_adapter.py
# Author : Jiayuan Mao
# Email  : maojiayuan@gmail.com
# Date   : 02/17/2018
#
# This file is part of Jacinle.
# Distributed under terms of the MIT license.

# https://github.com/openai/gym/blob/26556f99fe09332771ea619ed0a56bcfc75a3b99/gym/spaces/multi_discrete.py

# Adapters

from gym.spaces import Discrete, MultiDiscrete

Error = Exception


[docs] class DiscreteToMultiDiscrete(Discrete): """ Adapter that adapts the MultiDiscrete action space to a Discrete action space of any size The converted action can be retrieved by calling the adapter with the discrete action discrete_to_multi_discrete = DiscreteToMultiDiscrete(multi_discrete) discrete_action = discrete_to_multi_discrete.sample() multi_discrete_action = discrete_to_multi_discrete(discrete_action) It can be initialized using 3 configurations: Configuration 1) - DiscreteToMultiDiscrete(multi_discrete) [2nd param is empty] Would adapt to a Discrete action space of size (1 + nb of discrete in MultiDiscrete) where - 0 returns NOOP [ 0, 0, 0, ...] - 1 returns max for the first discrete space [max, 0, 0, ...] - 2 returns max for the second discrete space [ 0, max, 0, ...] - etc. Configuration 2) - DiscreteToMultiDiscrete(multi_discrete, list_of_discrete) [2nd param is a list] Would adapt to a Discrete action space of size (1 + nb of items in list_of_discrete) e.g. if list_of_discrete = [0, 2] - 0 returns NOOP [ 0, 0, 0, ...] - 1 returns max for first discrete in list [max, 0, 0, ...] - 2 returns max for second discrete in list [ 0, 0, max, ...] - etc. Configuration 3) - DiscreteToMultiDiscrete(multi_discrete, discrete_mapping) [2nd param is a dict] Would adapt to a Discrete action space of size (nb_keys in discrete_mapping) where discrete_mapping is a dictionnary in the format { discrete_key: multi_discrete_mapping } e.g. for the Nintendo Game Controller [ [0,4], [0,1], [0,1] ] a possible mapping might be; > mapping = { > 0: [0, 0, 0], # NOOP > 1: [1, 0, 0], # Up > 2: [3, 0, 0], # Down > 3: [2, 0, 0], # Right > 4: [2, 1, 0], # Right + A > 5: [2, 0, 1], # Right + B > 6: [2, 1, 1], # Right + A + B > 7: [4, 0, 0], # Left > 8: [4, 1, 0], # Left + A > 9: [4, 0, 1], # Left + B > 10: [4, 1, 1], # Left + A + B > 11: [0, 1, 0], # A only > 12: [0, 0, 1], # B only, > 13: [0, 1, 1], # A + B > } """
[docs] def __init__(self, multi_discrete, options=None): super().__init__(0) assert isinstance(multi_discrete, MultiDiscrete) self.multi_discrete = multi_discrete self.num_discrete_space = self.multi_discrete.num_discrete_space # Config 1 if options is None: self.n = self.num_discrete_space + 1 # +1 for NOOP at beginning self.mapping = {i: [0] * self.num_discrete_space for i in range(self.n)} for i in range(self.num_discrete_space): self.mapping[i + 1][i] = self.multi_discrete.high[i] # Config 2 elif isinstance(options, list): assert len(options) <= self.num_discrete_space self.n = len(options) + 1 # +1 for NOOP at beginning self.mapping = {i: [0] * self.num_discrete_space for i in range(self.n)} for i, disc_num in enumerate(options): assert disc_num < self.num_discrete_space self.mapping[i + 1][disc_num] = self.multi_discrete.high[disc_num] # Config 3 elif isinstance(options, dict): self.n = len(list(options.keys())) self.mapping = options for i, key in enumerate(options.keys()): if i != key: raise Error('DiscreteToMultiDiscrete must contain ordered keys. ' \ 'Item {0} should have a key of "{0}", but key "{1}" found instead.'.format(i, key)) if not self.multi_discrete.contains(options[key]): raise Error('DiscreteToMultiDiscrete mapping for key {0} is ' \ 'not contained in the underlying MultiDiscrete action space. ' \ 'Invalid mapping: {1}'.format(key, options[key])) # Unknown parameter provided else: raise Error('DiscreteToMultiDiscrete - Invalid parameter provided.')
[docs] def __call__(self, discrete_action): return self.mapping[discrete_action]