datamllab / rlcard / 317

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Build # 317

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CaoYuanpu

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<a href="https://github.com/datamllab/rlcard/commit/<a class=hub.com/datamllab/rlcard/commit/<a class="double-link" href="https://git"><a class=hub.com/datamllab/rlcard/commit/c22766bf31008720d7eee13201062209c50d3a79">c22766bf3<a href="https://github.com/datamllab/rlcard/commit/c22766bf31008720d7eee13201062209c50d3a79">&lt;a href=&quot;https://github.com/datamllab/rlcard/commit/c22766bf31008720d7eee13201062209c50d3a79">&quot;&gt;test decode


Former-commit-id: &lt;/a&gt;&lt;a class=&quot;double-link&quot; href=&quot;https://github.com/datamllab/rlcard/commit/&lt;a class=&quot;double-link&quot; href=&quot;https://github.com/datamllab/rlcard/commit/48ed65a9686aa64b4408199b39f99ad7e9f5db9b">48ed65a96</a>">48ed65a96</a><a href="https://github.com/datamllab/rlcard/commit/c22766bf31008720d7eee13201062209c50d3a79"> [formerly </a><a class="double-link" href="https://github.com/datamllab/rlcard/commit/<a class="double-link" href="https://github.com/datamllab/rlcard/commit/26d3a48660c71821356a576586f2bdf40e6f0274">26d3a4866</a>">26d3a4866</a><a href="https://github.com/datamllab/rlcard/commit/c22766bf31008720d7eee13201062209c50d3a79">]
Former-commit-id: c7c4b91d0">c7c4b91d0</a>

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97.5

/rlcard/envs/leducholdem.py

import json
import os
import numpy as np

import rlcard
from rlcard.envs.env import Env
from rlcard.games.leducholdem.game import LeducholdemGame as Game
from rlcard.utils.utils import *
from rlcard import models


class LeducholdemEnv(Env):
    ''' Leduc Hold'em Environment
    '''

    def __init__(self, allow_step_back=False):
        ''' Initialize the Limitholdem environment
        '''
        super().__init__(Game(allow_step_back), allow_step_back)
        self.actions = ['call', 'raise', 'fold', 'check']
        self.state_shape = [6]

        with open(os.path.join(rlcard.__path__[0], 'games/leducholdem/card2index.json'), 'r') as file:
            self.card2index = json.load(file)

    def print_state(self, player):
        ''' Print out the state of a given player

        Args:
            player (int): Player id
        '''
        state = self.game.get_state(player)
        print('\n=============== Community Card ===============')
        print_card(state['public_card'])
        print('===============   Your Hand    ===============')
        print_card(state['hand'])
        print('===============     Chips      ===============')
        print('Yours:   ', end='')
        for _ in range(state['my_chips']):
            print('+', end='')
        print('')
        for i in range(self.player_num):
            if i != self.active_player:
                print('Agent {}: '.format(i) , end='')
                for _ in range(state['all_chips'][i]):
                    print('+', end='')
        print('\n=========== Actions You Can Choose ===========')
        print(', '.join([str(self.actions.index(action)) + ': ' + action for action in state['legal_actions']]))
        print('')

    def print_result(self, player):
        ''' Print the game result when the game is over

        Args:
            player (int): The human player id
        '''
        payoffs = self.get_payoffs()
        hands = [self.game.players[i].hand.get_index() for i in range(self.player_num)]
        print('')

        if not self.game.players[self.active_player].status == 'folded':
            for i in range(self.player_num):
                if i != self.active_player:
                    if not self.game.players[i].status == 'fold':
                        print('===============     Agent {}    ==============='.format(i))
                        print_card(hands[i])

        print('===============     Result     ===============')
        if payoffs[player] > 0:
            print('You win {} chips!'.format(payoffs[player]))
        elif payoffs[player] == 0:
            print('It is a tie.')
        else:
            print('You lose {} chips!'.format(-payoffs[player]))
        print('')

    @staticmethod
    def print_action(action):
        ''' Print out an action in a nice form

        Args:
            action (str): A string a action
        '''
        print(action, end='')

    def load_model(self):
        ''' Load pretrained/rule model

        Returns:
            model (Model): A Model object
        '''
        return models.load('leduc-holdem-nfsp')

    def get_legal_actions(self):
        ''' Get all leagal actions

        Returns:
            encoded_action_list (list): return encoded legal action list (from str to int)
        '''
        return self.game.get_legal_actions()

    def extract_state(self, state):
        ''' Extract the state representation from state dictionary for agent

        Note: Currently the use the hand cards and the public cards. TODO: encode the states

        Args:
            state (dict): Original state from the game

        Returns:
            observation (list): combine the player's score and dealer's observable score for observation
        '''
        processed_state = {}

        legal_actions = [self.actions.index(a) for a in state['legal_actions']]
        processed_state['legal_actions'] = legal_actions

        public_card = state['public_card']
        hand = state['hand']
        cards = [] + [hand]
        if public_card:
            cards.append(public_card)
        idx = [self.card2index[card] for card in cards]
        obs = np.zeros(6)
        obs[idx] = 1
        processed_state['obs'] = obs

        return processed_state

    def get_payoffs(self):
        ''' Get the payoff of a game

        Returns:
           payoffs (list): list of payoffs
        '''
        return self.game.get_payoffs()

    def decode_action(self, action_id):
        ''' Decode the action for applying to the game

        Args:
            action id (int): action id

        Returns:
            action (str): action for the game
        '''
        legal_actions = self.game.get_legal_actions()
        if self.actions[action_id] not in legal_actions:
            if 'check' in legal_actions:
                return 'check'
            else:
                return 'fold'
        return self.actions[action_id]

1	import json	1✔
2	import os	1✔
3	import numpy as np	1✔
4
5	import rlcard	1✔
6	from rlcard.envs.env import Env	1✔
7	from rlcard.games.leducholdem.game import LeducholdemGame as Game	1✔
8	from rlcard.utils.utils import *	1✔
9	from rlcard import models	1✔
10
11
12	class LeducholdemEnv(Env):	1✔
13	''' Leduc Hold'em Environment
14	'''
15
16	def __init__(self, allow_step_back=False):	1✔
17	''' Initialize the Limitholdem environment
18	'''
19	super().__init__(Game(allow_step_back), allow_step_back)	1✔
20	self.actions = ['call', 'raise', 'fold', 'check']	1✔
21	self.state_shape = [6]	1✔
22
23	with open(os.path.join(rlcard.__path__[0], 'games/leducholdem/card2index.json'), 'r') as file:	1✔
24	self.card2index = json.load(file)	1✔
25
26	def print_state(self, player):	1✔
27	''' Print out the state of a given player
28
29	Args:
30	player (int): Player id
31	'''
32	state = self.game.get_state(player)	1✔
33	print('\n=============== Community Card ===============')	1✔
34	print_card(state['public_card'])	1✔
35	print('=============== Your Hand ===============')	1✔
36	print_card(state['hand'])	1✔
37	print('=============== Chips ===============')	1✔
38	print('Yours: ', end='')	1✔
39	for _ in range(state['my_chips']):	1✔
40	print('+', end='')	1✔
41	print('')	1✔
42	for i in range(self.player_num):	1✔
43	if i != self.active_player:	1✔
44	print('Agent {}: '.format(i) , end='')	1✔
45	for _ in range(state['all_chips'][i]):	1✔
46	print('+', end='')	1✔
47	print('\n=========== Actions You Can Choose ===========')	1✔
48	print(', '.join([str(self.actions.index(action)) + ': ' + action for action in state['legal_actions']]))	1✔
49	print('')	1✔
50
51	def print_result(self, player):	1✔
52	''' Print the game result when the game is over
53
54	Args:
55	player (int): The human player id
56	'''
57	payoffs = self.get_payoffs()	1✔
58	hands = [self.game.players[i].hand.get_index() for i in range(self.player_num)]	1✔
59	print('')	1✔
60
61	if not self.game.players[self.active_player].status == 'folded':	1✔
62	for i in range(self.player_num):	1✔
63	if i != self.active_player:	1✔
64	if not self.game.players[i].status == 'fold':	1✔
65	print('=============== Agent {} ==============='.format(i))	1✔
66	print_card(hands[i])	1✔
67
68	print('=============== Result ===============')	1✔
69	if payoffs[player] > 0:	1✔
70	print('You win {} chips!'.format(payoffs[player]))	1✔
71	elif payoffs[player] == 0:	1✔
72	print('It is a tie.')	×
73	else:
74	print('You lose {} chips!'.format(-payoffs[player]))	1✔
75	print('')	1✔
76
77	@staticmethod	1✔
78	def print_action(action):
79	''' Print out an action in a nice form
80
81	Args:
82	action (str): A string a action
83	'''
84	print(action, end='')	1✔
85
86	def load_model(self):	1✔
87	''' Load pretrained/rule model
88
89	Returns:
90	model (Model): A Model object
91	'''
92	return models.load('leduc-holdem-nfsp')	1✔
93
94	def get_legal_actions(self):	1✔
95	''' Get all leagal actions
96
97	Returns:
98	encoded_action_list (list): return encoded legal action list (from str to int)
99	'''
100	return self.game.get_legal_actions()	1✔
101
102	def extract_state(self, state):	1✔
103	''' Extract the state representation from state dictionary for agent
104
105	Note: Currently the use the hand cards and the public cards. TODO: encode the states
106
107	Args:
108	state (dict): Original state from the game
109
110	Returns:
111	observation (list): combine the player's score and dealer's observable score for observation
112	'''
113	processed_state = {}	1✔
114
115	legal_actions = [self.actions.index(a) for a in state['legal_actions']]	1✔
116	processed_state['legal_actions'] = legal_actions	1✔
117
118	public_card = state['public_card']	1✔
119	hand = state['hand']	1✔
120	cards = [] + [hand]	1✔
121	if public_card:	1✔
122	cards.append(public_card)	1✔
123	idx = [self.card2index[card] for card in cards]	1✔
124	obs = np.zeros(6)	1✔
125	obs[idx] = 1	1✔
126	processed_state['obs'] = obs	1✔
127
128	return processed_state	1✔
129
130	def get_payoffs(self):	1✔
131	''' Get the payoff of a game
132
133	Returns:
134	payoffs (list): list of payoffs
135	'''
136	return self.game.get_payoffs()	1✔
137
138	def decode_action(self, action_id):	1✔
139	''' Decode the action for applying to the game
140
141	Args:
142	action id (int): action id
143
144	Returns:
145	action (str): action for the game
146	'''
147	legal_actions = self.game.get_legal_actions()	1✔
148	if self.actions[action_id] not in legal_actions:	1✔
149	if 'check' in legal_actions:	1✔
150	return 'check'	1✔
151	else:
152	return 'fold'	×
153	return self.actions[action_id]	1✔

datamllab / rlcard / 317

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