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