0. code refactor, try to merge Go and GoEnv
This commit is contained in:
Dong Yan
parent
431f551ce9
commit
e10acf5130
@ -31,14 +31,14 @@ class Game:
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self.komi = komi
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self.board = [utils.EMPTY] * (self.size * self.size)
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self.history = []
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self.past = deque(maxlen=8)
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self.latest_boards = deque(maxlen=8)
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for _ in range(8):
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self.past.append(self.board)
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self.latest_boards.append(self.board)
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self.executor = go.Go(game=self)
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#self.strategy = strategy(checkpoint_path)
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self.simulator = strategy.GoEnv()
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self.simulator = strategy.GoEnv(game=self)
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self.net = network_small.Network()
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self.sess = self.net.forward(checkpoint_path)
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self.evaluator = lambda state: self.sess.run([tf.nn.softmax(self.net.p), self.net.v],
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@ -57,7 +57,7 @@ class Game:
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self.board = [utils.EMPTY] * (self.size * self.size)
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self.history = []
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for _ in range(8):
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self.past.append(self.board)
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self.latest_boards.append(self.board)
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def set_size(self, n):
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self.size = n
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@ -66,29 +66,29 @@ class Game:
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def set_komi(self, k):
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self.komi = k
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def data_process(self, history, color):
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state = np.zeros([1, self.simulator.size, self.simulator.size, 17])
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def generate_nn_input(self, history, color):
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state = np.zeros([1, self.size, self.size, 17])
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for i in range(8):
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state[0, :, :, i] = np.array(np.array(history[i]) == np.ones(self.simulator.size ** 2)).reshape(self.simulator.size, self.simulator.size)
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state[0, :, :, i + 8] = np.array(np.array(history[i]) == -np.ones(self.simulator.size ** 2)).reshape(self.simulator.size, self.simulator.size)
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state[0, :, :, i] = np.array(np.array(history[i]) == np.ones(self.size ** 2)).reshape(self.size, self.size)
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state[0, :, :, i + 8] = np.array(np.array(history[i]) == -np.ones(self.size ** 2)).reshape(self.size, self.size)
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if color == utils.BLACK:
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state[0, :, :, 16] = np.ones([self.simulator.size, self.simulator.size])
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state[0, :, :, 16] = np.ones([self.size, self.size])
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if color == utils.WHITE:
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state[0, :, :, 16] = np.zeros([self.simulator.size, self.simulator.size])
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state[0, :, :, 16] = np.zeros([self.size, self.size])
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return state
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def strategy_gen_move(self, history, color):
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self.simulator.history = copy.copy(history)
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self.simulator.board = copy.copy(history[-1])
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state = self.data_process(self.simulator.history, color)
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mcts = MCTS(self.simulator, self.evaluator, state, self.simulator.size ** 2 + 1, inverse=True, max_step=10)
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def strategy_gen_move(self, latest_boards, color):
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self.simulator.latest_boards = copy.copy(latest_boards)
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self.simulator.board = copy.copy(latest_boards[-1])
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nn_input = self.generate_nn_input(self.simulator.latest_boards, color)
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mcts = MCTS(self.simulator, self.evaluator, nn_input, self.size ** 2 + 1, inverse=True, max_step=1)
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temp = 1
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prob = mcts.root.N ** temp / np.sum(mcts.root.N ** temp)
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choice = np.random.choice(self.simulator.size ** 2 + 1, 1, p=prob).tolist()[0]
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if choice == self.simulator.size ** 2:
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choice = np.random.choice(self.size ** 2 + 1, 1, p=prob).tolist()[0]
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if choice == self.size ** 2:
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move = utils.PASS
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else:
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move = (choice % self.simulator.size + 1, choice / self.simulator.size + 1)
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move = (choice % self.size + 1, choice / self.size + 1)
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return move, prob
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def do_move(self, color, vertex):
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@ -100,7 +100,7 @@ class Game:
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def gen_move(self, color):
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# move = self.strategy.gen_move(color)
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# return move
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move, self.prob = self.strategy_gen_move(self.past, color)
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move, self.prob = self.strategy_gen_move(self.latest_boards, color)
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self.do_move(color, move)
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return move
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@ -127,3 +127,6 @@ class Game:
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if __name__ == "__main__":
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g = Game()
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g.show_board()
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#file = open("debug.txt", "a")
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#file.write("mcts check\n")
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#file.close()
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@ -135,7 +135,7 @@ class Go:
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self.game.board[self.game._flatten(vertex)] = color
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self._process_board(color, vertex)
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self.game.history.append(copy.copy(self.game.board))
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self.game.past.append(copy.copy(self.game.board))
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self.game.latest_boards.append(copy.copy(self.game.board))
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return True
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def _find_empty(self):
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@ -87,8 +87,8 @@ if __name__ == '__main__':
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score = player[turn].run_cmd(str(num) + ' get_score')
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print "Finished : ", score.split(" ")[1]
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player[0].run_cmd(str(num) + ' clear_board')
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player[1].run_cmd(str(num) + ' clear_board')
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game_num += 1
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player[1].run_cmd(str(num) + ' clear_board')
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game_num += 1
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subprocess.call(["kill", "-9", str(agent_v0.pid)])
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subprocess.call(["kill", "-9", str(agent_v1.pid)])
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@ -14,15 +14,14 @@ 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, size=9, komi=6.5):
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self.size = size
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self.komi = komi
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self.board = [utils.EMPTY] * (self.size * self.size)
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self.history = deque(maxlen=8)
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def __init__(self, **kwargs):
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self.game = kwargs['game']
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self.board = [utils.EMPTY] * (self.game.size * self.game.size)
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self.latest_boards = deque(maxlen=8)
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def _flatten(self, vertex):
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x, y = vertex
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return (x - 1) * self.size + (y - 1)
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return (x - 1) * self.game.size + (y - 1)
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def _bfs(self, vertex, color, block, status, alive_break):
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block.append(vertex)
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@ -35,7 +34,7 @@ class GoEnv:
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def _find_block(self, vertex, alive_break=False):
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block = []
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status = [False] * (self.size * self.size)
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status = [False] * (self.game.size * self.game.size)
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color = self.board[self._flatten(vertex)]
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self._bfs(vertex, color, block, status, alive_break)
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@ -73,7 +72,7 @@ class GoEnv:
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_board = copy.copy(self.board)
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self.board[self._flatten(vertex)] = color
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self._process_board(color, vertex)
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if self.board in self.history:
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if self.board in self.latest_boards:
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res = True
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else:
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res = False
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@ -83,8 +82,8 @@ class GoEnv:
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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.size: return False
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if y < 1 or y > self.size: return False
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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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@ -151,21 +150,28 @@ class GoEnv:
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# print "many opponents, fake eye"
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return False
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# def is_valid(self, color, vertex):
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def is_valid(self, state, action):
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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, 9, 9, 17]
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if action == self.size * self.size:
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if action == self.game.size * self.game.size:
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vertex = (0, 0)
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else:
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vertex = (action / self.size + 1, action % self.size + 1)
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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.history.clear()
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self.latest_boards.clear()
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for i in range(8):
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self.history.append((state[:, :, :, i] - state[:, :, :, i + 8]).reshape(-1).tolist())
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self.board = copy.copy(self.history[-1])
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self.latest_boards.append((state[:, :, :, i] - state[:, :, :, i + 8]).reshape(-1).tolist())
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self.board = copy.copy(self.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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@ -180,12 +186,11 @@ class GoEnv:
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if not self._is_qi(color, vertex):
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return False
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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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### 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 self._check_global_isomorphous(color, vertex):
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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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@ -206,17 +211,17 @@ class GoEnv:
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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.size ** 2:
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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.size + 1, action / self.size + 1)
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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.board = (state[:, :, :, 7] - state[:, :, :, 15]).reshape(-1).tolist()
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self.do_move(color, vertex)
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new_state = np.concatenate(
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[state[:, :, :, 1:8], (np.array(self.board) == utils.BLACK).reshape(1, self.size, self.size, 1),
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state[:, :, :, 9:16], (np.array(self.board) == utils.WHITE).reshape(1, self.size, self.size, 1),
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np.array(1 - state[:, :, :, -1]).reshape(1, self.size, self.size, 1)],
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[state[:, :, :, 1:8], (np.array(self.board) == utils.BLACK).reshape(1, self.game.size, self.game.size, 1),
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state[:, :, :, 9:16], (np.array(self.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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@ -75,7 +75,7 @@ class UCTNode(MCTSNode):
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start_time = time.time()
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self.mask = []
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for act in range(self.action_num - 1):
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if not simulator.is_valid(self.state, act):
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if not simulator.simulate_is_valid(self.state, act):
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self.mask.append(act)
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self.ucb[act] = -float("Inf")
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else:
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