202 lines
7.2 KiB
Python
202 lines
7.2 KiB
Python
import os, sys
|
|
|
|
sys.path.append(os.path.join(os.path.dirname(__file__), os.path.pardir))
|
|
import numpy as np
|
|
import utils
|
|
import time
|
|
import copy
|
|
import network_small
|
|
import tensorflow as tf
|
|
from collections import deque
|
|
from tianshou.core.mcts.mcts import MCTS
|
|
|
|
NEIGHBOR_OFFSET = [[1, 0], [-1, 0], [0, -1], [0, 1]]
|
|
CORNER_OFFSET = [[-1, -1], [-1, 1], [1, 1], [1, -1]]
|
|
|
|
class GoEnv:
|
|
def __init__(self, **kwargs):
|
|
self.game = kwargs['game']
|
|
self.simulate_board = [utils.EMPTY] * (self.game.size ** 2)
|
|
self.simulate_latest_boards = deque(maxlen=8)
|
|
|
|
def _find_group(self, start):
|
|
color = self.simulate_board[self.game._flatten(start)]
|
|
# print ("color : ", color)
|
|
chain = set()
|
|
frontier = [start]
|
|
has_liberty = False
|
|
while frontier:
|
|
current = frontier.pop()
|
|
# print ("current : ", current)
|
|
chain.add(current)
|
|
for n in self._neighbor(current):
|
|
# print n, self._flatten(n), self.board[self._flatten(n)],
|
|
if self.simulate_board[self.game._flatten(n)] == color and not n in chain:
|
|
frontier.append(n)
|
|
if self.simulate_board[self.game._flatten(n)] == utils.EMPTY:
|
|
has_liberty = True
|
|
return has_liberty, chain
|
|
|
|
def _is_suicide(self, color, vertex):
|
|
self.simulate_board[self.game._flatten(vertex)] = color # assume that we already take this move
|
|
suicide = False
|
|
|
|
has_liberty, group = self._find_group(vertex)
|
|
if not has_liberty:
|
|
suicide = True # no liberty, suicide
|
|
for n in self._neighbor(vertex):
|
|
if self.simulate_board[self.game._flatten(n)] == utils.another_color(color):
|
|
opponent_liberty, group = self._find_group(n)
|
|
if not opponent_liberty:
|
|
suicide = False # this move is able to take opponent's stone, not suicide
|
|
|
|
self.simulate_board[self.game._flatten(vertex)] = utils.EMPTY # undo this move
|
|
return suicide
|
|
|
|
def _check_global_isomorphous(self, color, vertex):
|
|
##backup
|
|
_board = copy.copy(self.simulate_board)
|
|
self.simulate_board[self.game._flatten(vertex)] = color
|
|
self._process_board(color, vertex)
|
|
if self.simulate_board in self.game.history:
|
|
res = True
|
|
else:
|
|
res = False
|
|
|
|
self.simulate_board = _board
|
|
return res
|
|
|
|
def _in_board(self, vertex):
|
|
x, y = vertex
|
|
if x < 1 or x > self.game.size: return False
|
|
if y < 1 or y > self.game.size: return False
|
|
return True
|
|
|
|
def _neighbor(self, vertex):
|
|
x, y = vertex
|
|
nei = []
|
|
for d in NEIGHBOR_OFFSET:
|
|
_x = x + d[0]
|
|
_y = y + d[1]
|
|
if self._in_board((_x, _y)):
|
|
nei.append((_x, _y))
|
|
return nei
|
|
|
|
def _corner(self, vertex):
|
|
x, y = vertex
|
|
corner = []
|
|
for d in CORNER_OFFSET:
|
|
_x = x + d[0]
|
|
_y = y + d[1]
|
|
if self._in_board((_x, _y)):
|
|
corner.append((_x, _y))
|
|
return corner
|
|
|
|
def _process_board(self, color, vertex):
|
|
nei = self._neighbor(vertex)
|
|
for n in nei:
|
|
if self.simulate_board[self.game._flatten(n)] == utils.another_color(color):
|
|
has_liberty, group = self._find_group(n)
|
|
if not has_liberty:
|
|
for b in group:
|
|
self.simulate_board[self.game._flatten(b)] = utils.EMPTY
|
|
|
|
def _is_eye(self, color, vertex):
|
|
nei = self._neighbor(vertex)
|
|
cor = self._corner(vertex)
|
|
ncolor = {color == self.simulate_board[self.game._flatten(n)] for n in nei}
|
|
if False in ncolor:
|
|
# print "not all neighbors are in same color with us"
|
|
return False
|
|
_, group = self._find_group(nei[0])
|
|
if set(nei) < group:
|
|
# print "all neighbors are in same group and same color with us"
|
|
return True
|
|
else:
|
|
opponent_number = [self.simulate_board[self.game._flatten(c)] for c in cor].count(-color)
|
|
opponent_propotion = float(opponent_number) / float(len(cor))
|
|
if opponent_propotion < 0.5:
|
|
# print "few opponents, real eye"
|
|
return True
|
|
else:
|
|
# print "many opponents, fake eye"
|
|
return False
|
|
|
|
def knowledge_prunning(self, color, vertex):
|
|
### check if it is an eye of yourself
|
|
### assumptions : notice that this judgement requires that the state is an endgame
|
|
if self._is_eye(color, vertex):
|
|
return False
|
|
return True
|
|
|
|
def simulate_is_valid(self, state, action):
|
|
# State is the play board, the shape is [1, self.game.size, self.game.size, 17].
|
|
# Action is an index
|
|
# We need to transfer the (state, action) pair into (color, vertex) pair to simulate the move
|
|
if action == self.game.size ** 2:
|
|
vertex = (0, 0)
|
|
else:
|
|
vertex = self.game._deflatten(action)
|
|
if state[0, 0, 0, -1] == utils.BLACK:
|
|
color = utils.BLACK
|
|
else:
|
|
color = utils.WHITE
|
|
self.simulate_latest_boards.clear()
|
|
for i in range(8):
|
|
self.simulate_latest_boards.append((state[:, :, :, i] - state[:, :, :, i + 8]).reshape(-1).tolist())
|
|
self.simulate_board = copy.copy(self.simulate_latest_boards[-1])
|
|
|
|
### in board
|
|
if not self._in_board(vertex):
|
|
return False
|
|
|
|
### already have stone
|
|
if not self.simulate_board[self.game._flatten(vertex)] == utils.EMPTY:
|
|
# print(np.array(self.board).reshape(9, 9))
|
|
# print(vertex)
|
|
return False
|
|
|
|
### check if it is suicide
|
|
if self._is_suicide(color, vertex):
|
|
return False
|
|
|
|
### forbid global isomorphous
|
|
if self._check_global_isomorphous(color, vertex):
|
|
return False
|
|
|
|
if not self.knowledge_prunning(color, vertex):
|
|
return False
|
|
|
|
return True
|
|
|
|
def simulate_do_move(self, color, vertex):
|
|
if vertex == utils.PASS:
|
|
return True
|
|
|
|
id_ = self.game._flatten(vertex)
|
|
if self.simulate_board[id_] == utils.EMPTY:
|
|
self.simulate_board[id_] = color
|
|
return True
|
|
else:
|
|
return False
|
|
|
|
def simulate_step_forward(self, state, action):
|
|
if state[0, 0, 0, -1] == 1:
|
|
color = utils.BLACK
|
|
else:
|
|
color = utils.WHITE
|
|
if action == self.game.size ** 2:
|
|
vertex = utils.PASS
|
|
else:
|
|
vertex = self.game._deflatten(action)
|
|
# print(vertex)
|
|
# print(self.board)
|
|
self.simulate_board = (state[:, :, :, 7] - state[:, :, :, 15]).reshape(-1).tolist()
|
|
self.simulate_do_move(color, vertex)
|
|
new_state = np.concatenate(
|
|
[state[:, :, :, 1:8], (np.array(self.simulate_board) == utils.BLACK).reshape(1, self.game.size, self.game.size, 1),
|
|
state[:, :, :, 9:16], (np.array(self.simulate_board) == utils.WHITE).reshape(1, self.game.size, self.game.size, 1),
|
|
np.array(1 - state[:, :, :, -1]).reshape(1, self.game.size, self.game.size, 1)],
|
|
axis=3)
|
|
return new_state, 0
|