merge gtp
This commit is contained in:
rtz19970824
parent
e8c05c21cc
commit
13738f13c4
@ -3,6 +3,7 @@ import time
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import sys
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import numpy as np
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import time
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import tensorflow as tf
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import tensorflow.contrib.layers as layers
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@ -49,33 +50,37 @@ def value_heads(input, is_training):
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return h
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x = tf.placeholder(tf.float32, shape=[None, 19, 19, 17])
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is_training = tf.placeholder(tf.bool, shape=[])
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z = tf.placeholder(tf.float32, shape=[None, 1])
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pi = tf.placeholder(tf.float32, shape=[None, 362])
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class Network(object):
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def __init__(self):
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self.x = tf.placeholder(tf.float32, shape=[None, 19, 19, 17])
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self.is_training = tf.placeholder(tf.bool, shape=[])
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self.z = tf.placeholder(tf.float32, shape=[None, 1])
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self.pi = tf.placeholder(tf.float32, shape=[None, 362])
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self.build_network()
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h = layers.conv2d(x, 256, kernel_size=3, stride=1, activation_fn=tf.nn.relu, normalizer_fn=layers.batch_norm,
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normalizer_params={'is_training': is_training, 'updates_collections': tf.GraphKeys.UPDATE_OPS},
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def build_network(self):
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h = layers.conv2d(self.x, 256, kernel_size=3, stride=1, activation_fn=tf.nn.relu, normalizer_fn=layers.batch_norm,
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normalizer_params={'is_training': self.is_training,
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'updates_collections': tf.GraphKeys.UPDATE_OPS},
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weights_regularizer=layers.l2_regularizer(1e-4))
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for i in range(19):
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h = residual_block(h, is_training)
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v = value_heads(h, is_training)
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p = policy_heads(h, is_training)
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h = residual_block(h, self.is_training)
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self.v = value_heads(h, self.is_training)
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self.p = policy_heads(h, self.is_training)
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# loss = tf.reduce_mean(tf.square(z-v)) - tf.multiply(pi, tf.log(tf.clip_by_value(tf.nn.softmax(p), 1e-8, tf.reduce_max(tf.nn.softmax(p)))))
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value_loss = tf.reduce_mean(tf.square(z - v))
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policy_loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=pi, logits=p))
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self.value_loss = tf.reduce_mean(tf.square(self.z - self.v))
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self.policy_loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=self.pi, logits=self.p))
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reg = tf.add_n(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES))
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total_loss = value_loss + policy_loss + reg
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self.reg = tf.add_n(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES))
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self.total_loss = self.value_loss + self.policy_loss + self.reg
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# train_op = tf.train.MomentumOptimizer(1e-4, momentum=0.9, use_nesterov=True).minimize(total_loss)
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update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
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with tf.control_dependencies(update_ops):
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train_op = tf.train.RMSPropOptimizer(1e-4).minimize(total_loss)
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var_list = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
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saver = tf.train.Saver(max_to_keep=10, var_list=var_list)
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self.update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
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with tf.control_dependencies(self.update_ops):
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self.train_op = tf.train.RMSPropOptimizer(1e-4).minimize(self.total_loss)
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self.var_list = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
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self.saver = tf.train.Saver(max_to_keep=10, var_list=self.var_list)
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def train():
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def train(self):
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data_path = "/home/tongzheng/data/"
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data_name = os.listdir("/home/tongzheng/data/")
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epochs = 100
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@ -87,7 +92,7 @@ def train():
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ckpt_file = tf.train.latest_checkpoint(result_path)
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if ckpt_file is not None:
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print('Restoring model from {}...'.format(ckpt_file))
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saver.restore(sess, ckpt_file)
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self.saver.restore(sess, ckpt_file)
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for epoch in range(epochs):
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for name in data_name:
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data = np.load(data_path + name)
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@ -105,14 +110,15 @@ def train():
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regs = []
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time_train = -time.time()
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for iter in range(batch_num):
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lv, lp, r, value, prob, _ = sess.run([value_loss, policy_loss, reg, v, tf.nn.softmax(p), train_op],
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feed_dict={x: boards[
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lv, lp, r, value, prob, _ = sess.run(
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[self.value_loss, self.policy_loss, self.reg, self.v, tf.nn.softmax(p), self.train_op],
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feed_dict={self.x: boards[
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index[iter * batch_size:(iter + 1) * batch_size]],
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z: wins[index[
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self.z: wins[index[
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iter * batch_size:(iter + 1) * batch_size]],
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pi: ps[index[
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self.pi: ps[index[
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iter * batch_size:(iter + 1) * batch_size]],
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is_training: True})
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self.is_training: True})
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value_losses.append(lv)
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policy_losses.append(lp)
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regs.append(r)
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@ -127,7 +133,7 @@ def train():
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regs = []
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if iter % 20 == 0:
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save_path = "Epoch{}.Part{}.Iteration{}.ckpt".format(epoch, name, iter)
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saver.save(sess, result_path + save_path)
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self.saver.save(sess, result_path + save_path)
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del data, boards, wins, ps
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@ -179,21 +185,27 @@ def train():
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# # np.savetxt(pv_file, res[1][0], fmt="%.6f", newline=" ")
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# return res
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def forward(state):
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def forward(self):
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checkpoint_path = "/home/tongzheng/tianshou/AlphaGo/checkpoints/"
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with multi_gpu.create_session() as sess:
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sess = multi_gpu.create_session()
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sess.run(tf.global_variables_initializer())
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ckpt_file = tf.train.latest_checkpoint(checkpoint_path)
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if ckpt_file is not None:
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print('Restoring model from {}...'.format(ckpt_file))
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saver.restore(sess, ckpt_file)
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self.saver.restore(sess, ckpt_file)
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print('Successfully loaded')
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else:
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raise ValueError("No model loaded")
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prior, value = sess.run([tf.nn.softmax(p), v], feed_dict={x: state, is_training: False})
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return prior, value
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# prior, value = sess.run([tf.nn.softmax(p), v], feed_dict={x: state, is_training: False})
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# return prior, value
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return sess
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if __name__ == '__main__':
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np.set_printoptions(threshold='nan')
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# time.sleep(2)
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forward(sys.argv[1])
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state = np.random.randint(0, 1, [1, 19, 19, 17])
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net = Network()
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sess = net.forward()
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start = time.time()
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for i in range(100):
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sess.run([tf.nn.softmax(net.p), net.v], feed_dict={net.x: state, net.is_training: False})
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print("Step {}, Cumulative time {}".format(i, time.time() - start))
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197
AlphaGo/game.py
197
AlphaGo/game.py
@ -1,15 +1,138 @@
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# -*- coding: utf-8 -*-
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# vim:fenc=utf-8
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# $File: game.py
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# $Date: Fri Nov 17 15:0745 2017 +0800
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# $Date: Tue Nov 28 14:4726 2017 +0800
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# $Author: renyong15 © <mails.tsinghua.edu.cn>
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#
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import numpy as np
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from __future__ import print_function
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import utils
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import copy
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import tensorflow as tf
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from collections import deque
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import Network
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from strategy import strategy
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from collections import deque
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'''
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(1, 1) is considered as the upper left corner of the board,
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(size, 1) is the lower left
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'''
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DELTA = [[1, 0], [-1, 0], [0, -1], [0, 1]]
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class Executor:
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def __init__(self, **kwargs):
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self.game = kwargs['game']
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def _bfs(self, vertex, color, block, status, alive_break):
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block.append(vertex)
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status[self.game._flatten(vertex)] = True
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nei = self._neighbor(vertex)
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for n in nei:
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if not status[self.game._flatten(n)]:
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if self.game.board[self.game._flatten(n)] == color:
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self._bfs(n, color, block, status, alive_break)
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def _find_block(self, vertex, alive_break=False):
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block = []
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status = [False] * (self.game.size * self.game.size)
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color = self.game.board[self.game._flatten(vertex)]
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self._bfs(vertex, color, block, status, alive_break)
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for b in block:
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for n in self._neighbor(b):
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if self.game.board[self.game._flatten(n)] == utils.EMPTY:
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return False, block
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return True, block
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def _is_qi(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.game.board[self.game._flatten(n)] == utils.EMPTY:
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return True
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self.game.board[self.game._flatten(vertex)] = color
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for n in nei:
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if self.game.board[self.game._flatten(n)] == utils.another_color(color):
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can_kill, block = self._find_block(n)
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if can_kill:
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self.game.board[self.game._flatten(vertex)] = utils.EMPTY
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return True
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### can not suicide
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can_kill, block = self._find_block(vertex)
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if can_kill:
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self.game.board[self.game._flatten(vertex)] = utils.EMPTY
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return False
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self.game.board[self.game._flatten(vertex)] = utils.EMPTY
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return True
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def _check_global_isomorphous(self, color, vertex):
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##backup
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_board = copy.copy(self.game.board)
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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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if self.game.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.game.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 _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.game.board[self.game._flatten(n)] == utils.another_color(color):
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can_kill, block = self._find_block(n, alive_break=True)
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if can_kill:
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for b in block:
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self.game.board[self.game._flatten(b)] = utils.EMPTY
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def is_valid(self, color, vertex):
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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.game.board[self.game._flatten(vertex)] == utils.EMPTY:
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return False
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### check if it is qi
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if not self._is_qi(color, vertex):
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return False
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if self._check_global_isomorphous(color, vertex):
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return False
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return True
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def do_move(self, color, vertex):
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if not self.is_valid(color, vertex):
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return False
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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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return True
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class Game:
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@ -17,14 +140,16 @@ class Game:
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self.size = size
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self.komi = 6.5
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self.board = [utils.EMPTY] * (self.size * self.size)
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self.strategy = strategy(Network.forward)
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self.history = deque(maxlen=8)
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self.strategy = strategy()
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self.executor = Executor(game=self)
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self.history = []
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self.past = deque(maxlen=8)
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for i in range(8):
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self.history.append(self.board)
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self.past.append(self.board)
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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 (y - 1) * self.size + (x - 1)
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def clear(self):
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self.board = [utils.EMPTY] * (self.size * self.size)
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@ -36,34 +161,42 @@ class Game:
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def set_komi(self, k):
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self.komi = k
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def check_valid(self, vertex):
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return True
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def 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._flatten(vertex)
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if self.board[id_] == utils.EMPTY:
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self.board[id_] = color
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self.history.append(self.board)
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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 = 1
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else:
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color = -1
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if action == 361:
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vertex = (0, 0)
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else:
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vertex = (action / 19 + 1, action % 19)
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self.do_move(color, vertex)
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new_state = np.concatenate([state[:, :, :, 1:8], self.board == 1, state[:, :, :, 9:16], 1 - state[:, :, :, -1]],
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axis=3)
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return new_state, 0
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res = self.executor.do_move(color, vertex)
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return res
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def gen_move(self, color):
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move = self.strategy.gen_move(self.history, color)
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# move = self.strategy.gen_move(color)
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# return move
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move = self.strategy.gen_move(self.past, color)
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self.do_move(color, move)
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return move
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# return utils.PASS
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def status2symbol(self, s):
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pool = {utils.WHITE: '#', utils.EMPTY: '.', utils.BLACK: '*', utils.FILL: 'F', utils.UNKNOWN: '?'}
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return pool[s]
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def show_board(self):
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row = [i for i in range(1, 20)]
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col = ' abcdefghijklmnopqrstuvwxyz'
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print(' ', end='')
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for j in range(self.size + 1):
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print(col[j], end=' ')
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print('')
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for i in range(self.size):
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print(row[i], end=' ')
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if row[i] < 10:
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print(' ', end='')
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for j in range(self.size):
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print(self.status2symbol(self.board[self._flatten((j + 1, i + 1))]), end=' ')
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print('')
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if __name__ == "__main__":
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g = Game()
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g.show_board()
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@ -1,5 +1,8 @@
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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 Network
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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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@ -47,9 +50,12 @@ class GoEnv:
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class strategy(object):
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def __init__(self, evaluator):
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def __init__(self):
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self.simulator = GoEnv()
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self.evaluator = evaluator
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self.net = Network.Network()
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self.sess = self.net.forward()
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self.evaluator = lambda state: self.sess.run([tf.nn.softmax(self.net.p), self.net.v],
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feed_dict={self.net.x: state, self.net.is_training: False})
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def data_process(self, history, color):
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state = np.zeros([1, 19, 19, 17])
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@ -67,7 +73,7 @@ class strategy(object):
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self.simulator.board = history[-1]
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state = self.data_process(history, color)
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prior = self.evaluator(state)[0]
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mcts = MCTS(self.simulator, self.evaluator, state, 362, prior, inverse=True, max_step=20)
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mcts = MCTS(self.simulator, self.evaluator, state, 362, prior, inverse=True, max_step=100)
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temp = 1
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p = mcts.root.N ** temp / np.sum(mcts.root.N ** temp)
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choice = np.random.choice(362, 1, p=p).tolist()[0]
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217
AlphaGo/test.py
217
AlphaGo/test.py
@ -33,112 +33,127 @@ print(res)
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res = e.run_cmd('7 play BLACK C3')
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print(res)
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res = e.run_cmd('play BLACK C4')
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res = e.run_cmd('play BLACK C5')
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res = e.run_cmd('play BLACK C6')
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res = e.run_cmd('play BLACK D3')
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print(res)
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# res = e.run_cmd('play BLACK C4')
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# res = e.run_cmd('play BLACK C5')
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# res = e.run_cmd('play BLACK C6')
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# res = e.run_cmd('play BLACK D3')
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# print(res)
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res = e.run_cmd('8 genmove BLACK')
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||||
print(res)
|
||||
|
||||
<<<<<<< HEAD:AlphaGo/test.py
|
||||
res = e.run_cmd('9 genmove WHITE')
|
||||
res = e.run_cmd('8 genmove WHITE')
|
||||
print(res)
|
||||
=======
|
||||
g.show_board()
|
||||
|
||||
# res = e.run_cmd('8 genmove BLACK')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
print(g.check_valid((10, 9)))
|
||||
print(g.executor._neighbor((1,1)))
|
||||
print(g.do_move(utils.WHITE, (4, 6)))
|
||||
#
|
||||
# res = e.run_cmd('8 genmove WHITE')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('8 genmove BLACK')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('8 genmove WHITE')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
# #g.show_board()
|
||||
# print(g.check_valid((10, 9)))
|
||||
# print(g.executor._neighbor((1,1)))
|
||||
# print(g.do_move(utils.WHITE, (4, 6)))
|
||||
# #g.show_board()
|
||||
#
|
||||
#
|
||||
# res = e.run_cmd('play BLACK L10')
|
||||
# res = e.run_cmd('play BLACK L11')
|
||||
# res = e.run_cmd('play BLACK L12')
|
||||
# res = e.run_cmd('play BLACK L13')
|
||||
# res = e.run_cmd('play BLACK L14')
|
||||
# res = e.run_cmd('play BLACK m15')
|
||||
# res = e.run_cmd('play BLACK m9')
|
||||
# res = e.run_cmd('play BLACK C9')
|
||||
# res = e.run_cmd('play BLACK D9')
|
||||
# res = e.run_cmd('play BLACK E9')
|
||||
# res = e.run_cmd('play BLACK F9')
|
||||
# res = e.run_cmd('play BLACK G9')
|
||||
# res = e.run_cmd('play BLACK H9')
|
||||
# res = e.run_cmd('play BLACK I9')
|
||||
#
|
||||
# res = e.run_cmd('play BLACK N9')
|
||||
# res = e.run_cmd('play BLACK N15')
|
||||
# res = e.run_cmd('play BLACK O10')
|
||||
# res = e.run_cmd('play BLACK O11')
|
||||
# res = e.run_cmd('play BLACK O12')
|
||||
# res = e.run_cmd('play BLACK O13')
|
||||
# res = e.run_cmd('play BLACK O14')
|
||||
# res = e.run_cmd('play BLACK M12')
|
||||
#
|
||||
# res = e.run_cmd('play WHITE M10')
|
||||
# res = e.run_cmd('play WHITE M11')
|
||||
# res = e.run_cmd('play WHITE N10')
|
||||
# res = e.run_cmd('play WHITE N11')
|
||||
#
|
||||
# res = e.run_cmd('play WHITE M13')
|
||||
# res = e.run_cmd('play WHITE M14')
|
||||
# res = e.run_cmd('play WHITE N13')
|
||||
# res = e.run_cmd('play WHITE N14')
|
||||
# print(res)
|
||||
#
|
||||
# res = e.run_cmd('play BLACK N12')
|
||||
# print(res)
|
||||
# #g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play BLACK P16')
|
||||
# res = e.run_cmd('play BLACK P17')
|
||||
# res = e.run_cmd('play BLACK P18')
|
||||
# res = e.run_cmd('play BLACK P19')
|
||||
# res = e.run_cmd('play BLACK Q16')
|
||||
# res = e.run_cmd('play BLACK R16')
|
||||
# res = e.run_cmd('play BLACK S16')
|
||||
#
|
||||
# res = e.run_cmd('play WHITE S18')
|
||||
# res = e.run_cmd('play WHITE S17')
|
||||
# res = e.run_cmd('play WHITE Q19')
|
||||
# res = e.run_cmd('play WHITE Q18')
|
||||
# res = e.run_cmd('play WHITE Q17')
|
||||
# res = e.run_cmd('play WHITE R18')
|
||||
# res = e.run_cmd('play WHITE R17')
|
||||
# res = e.run_cmd('play BLACK S19')
|
||||
# print(res)
|
||||
# #g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play WHITE R19')
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play BLACK S19')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play BLACK S19')
|
||||
# print(res)
|
||||
#
|
||||
#
|
||||
# res = e.run_cmd('play BLACK E17')
|
||||
# res = e.run_cmd('play BLACK F16')
|
||||
# res = e.run_cmd('play BLACK F18')
|
||||
# res = e.run_cmd('play BLACK G17')
|
||||
# res = e.run_cmd('play WHITE G16')
|
||||
# res = e.run_cmd('play WHITE G18')
|
||||
# res = e.run_cmd('play WHITE H17')
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play WHITE F17')
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play BLACK G17')
|
||||
# print(res)
|
||||
# g.show_board()
|
||||
#
|
||||
# res = e.run_cmd('play BLACK G19')
|
||||
# res = e.run_cmd('play BLACK G17')
|
||||
# g.show_board()
|
||||
|
||||
|
||||
res = e.run_cmd('play BLACK L10')
|
||||
res = e.run_cmd('play BLACK L11')
|
||||
res = e.run_cmd('play BLACK L12')
|
||||
res = e.run_cmd('play BLACK L13')
|
||||
res = e.run_cmd('play BLACK L14')
|
||||
res = e.run_cmd('play BLACK m15')
|
||||
res = e.run_cmd('play BLACK m9')
|
||||
res = e.run_cmd('play BLACK C9')
|
||||
res = e.run_cmd('play BLACK D9')
|
||||
res = e.run_cmd('play BLACK E9')
|
||||
res = e.run_cmd('play BLACK F9')
|
||||
res = e.run_cmd('play BLACK G9')
|
||||
res = e.run_cmd('play BLACK H9')
|
||||
res = e.run_cmd('play BLACK I9')
|
||||
|
||||
res = e.run_cmd('play BLACK N9')
|
||||
res = e.run_cmd('play BLACK N15')
|
||||
res = e.run_cmd('play BLACK O10')
|
||||
res = e.run_cmd('play BLACK O11')
|
||||
res = e.run_cmd('play BLACK O12')
|
||||
res = e.run_cmd('play BLACK O13')
|
||||
res = e.run_cmd('play BLACK O14')
|
||||
res = e.run_cmd('play BLACK M12')
|
||||
|
||||
res = e.run_cmd('play WHITE M10')
|
||||
res = e.run_cmd('play WHITE M11')
|
||||
res = e.run_cmd('play WHITE N10')
|
||||
res = e.run_cmd('play WHITE N11')
|
||||
|
||||
res = e.run_cmd('play WHITE M13')
|
||||
res = e.run_cmd('play WHITE M14')
|
||||
res = e.run_cmd('play WHITE N13')
|
||||
res = e.run_cmd('play WHITE N14')
|
||||
print(res)
|
||||
|
||||
res = e.run_cmd('play BLACK N12')
|
||||
print(res)
|
||||
#g.show_board()
|
||||
|
||||
res = e.run_cmd('play BLACK P16')
|
||||
res = e.run_cmd('play BLACK P17')
|
||||
res = e.run_cmd('play BLACK P18')
|
||||
res = e.run_cmd('play BLACK P19')
|
||||
res = e.run_cmd('play BLACK Q16')
|
||||
res = e.run_cmd('play BLACK R16')
|
||||
res = e.run_cmd('play BLACK S16')
|
||||
|
||||
res = e.run_cmd('play WHITE S18')
|
||||
res = e.run_cmd('play WHITE S17')
|
||||
res = e.run_cmd('play WHITE Q19')
|
||||
res = e.run_cmd('play WHITE Q18')
|
||||
res = e.run_cmd('play WHITE Q17')
|
||||
res = e.run_cmd('play WHITE R18')
|
||||
res = e.run_cmd('play WHITE R17')
|
||||
res = e.run_cmd('play BLACK S19')
|
||||
print(res)
|
||||
#g.show_board()
|
||||
|
||||
res = e.run_cmd('play WHITE R19')
|
||||
g.show_board()
|
||||
|
||||
res = e.run_cmd('play BLACK S19')
|
||||
print(res)
|
||||
g.show_board()
|
||||
|
||||
res = e.run_cmd('play BLACK S19')
|
||||
print(res)
|
||||
|
||||
|
||||
res = e.run_cmd('play BLACK E17')
|
||||
res = e.run_cmd('play BLACK F16')
|
||||
res = e.run_cmd('play BLACK F18')
|
||||
res = e.run_cmd('play BLACK G17')
|
||||
res = e.run_cmd('play WHITE G16')
|
||||
res = e.run_cmd('play WHITE G18')
|
||||
res = e.run_cmd('play WHITE H17')
|
||||
g.show_board()
|
||||
|
||||
res = e.run_cmd('play WHITE F17')
|
||||
g.show_board()
|
||||
|
||||
res = e.run_cmd('play BLACK G17')
|
||||
print(res)
|
||||
g.show_board()
|
||||
|
||||
res = e.run_cmd('play BLACK G19')
|
||||
res = e.run_cmd('play BLACK G17')
|
||||
g.show_board()
|
||||
>>>>>>> gtp:GTP/test.py
|
||||
|
||||
131
AlphaGo/utils.py
131
AlphaGo/utils.py
@ -1,137 +1,20 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
# vim:fenc=utf-8
|
||||
# $File: utils.py
|
||||
# $Date: Fri Nov 17 10:2407 2017 +0800
|
||||
# $Date: Mon Nov 27 18:2755 2017 +0800
|
||||
# $Author: renyong15 © <mails.tsinghua.edu.cn>
|
||||
#
|
||||
|
||||
WHITE = -1
|
||||
BLACK = +1
|
||||
EMPTY = 0
|
||||
BLACK = +1
|
||||
FILL = +2
|
||||
KO = +3
|
||||
UNKNOWN = +4
|
||||
|
||||
PASS = (0,0)
|
||||
RESIGN = "resign"
|
||||
|
||||
from collections import defaultdict
|
||||
import functools
|
||||
import itertools
|
||||
import operator
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
|
||||
import gtp
|
||||
import go
|
||||
|
||||
KGS_COLUMNS = 'ABCDEFGHJKLMNOPQRST'
|
||||
SGF_COLUMNS = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
|
||||
|
||||
|
||||
def parse_sgf_to_flat(sgf):
|
||||
return flatten_coords(parse_sgf_coords(sgf))
|
||||
|
||||
|
||||
def flatten_coords(c):
|
||||
return go.N * c[0] + c[1]
|
||||
|
||||
|
||||
def unflatten_coords(f):
|
||||
return divmod(f, go.N)
|
||||
|
||||
|
||||
def parse_sgf_coords(s):
|
||||
'Interprets coords. aa is top left corner; sa is top right corner'
|
||||
if s is None or s == '':
|
||||
return None
|
||||
return SGF_COLUMNS.index(s[1]), SGF_COLUMNS.index(s[0])
|
||||
|
||||
|
||||
def unparse_sgf_coords(c):
|
||||
if c is None:
|
||||
return ''
|
||||
return SGF_COLUMNS[c[1]] + SGF_COLUMNS[c[0]]
|
||||
|
||||
|
||||
def parse_kgs_coords(s):
|
||||
'Interprets coords. A1 is bottom left; A9 is top left.'
|
||||
if s == 'pass':
|
||||
return None
|
||||
s = s.upper()
|
||||
col = KGS_COLUMNS.index(s[0])
|
||||
row_from_bottom = int(s[1:]) - 1
|
||||
return go.N - row_from_bottom - 1, col
|
||||
|
||||
|
||||
def parse_pygtp_coords(vertex):
|
||||
'Interprets coords. (1, 1) is bottom left; (1, 9) is top left.'
|
||||
if vertex in (gtp.PASS, gtp.RESIGN):
|
||||
return None
|
||||
return go.N - vertex[1], vertex[0] - 1
|
||||
|
||||
|
||||
def unparse_pygtp_coords(c):
|
||||
if c is None:
|
||||
return gtp.PASS
|
||||
return c[1] + 1, go.N - c[0]
|
||||
|
||||
|
||||
def parse_game_result(result):
|
||||
if re.match(r'[bB]\+', result):
|
||||
return go.BLACK
|
||||
elif re.match(r'[wW]\+', result):
|
||||
return go.WHITE
|
||||
else:
|
||||
return None
|
||||
|
||||
|
||||
def product(numbers):
|
||||
return functools.reduce(operator.mul, numbers)
|
||||
|
||||
|
||||
def take_n(n, iterable):
|
||||
return list(itertools.islice(iterable, n))
|
||||
|
||||
|
||||
def iter_chunks(chunk_size, iterator):
|
||||
while True:
|
||||
next_chunk = take_n(chunk_size, iterator)
|
||||
# If len(iterable) % chunk_size == 0, don't return an empty chunk.
|
||||
if next_chunk:
|
||||
yield next_chunk
|
||||
else:
|
||||
break
|
||||
|
||||
|
||||
def shuffler(iterator, pool_size=10 ** 5, refill_threshold=0.9):
|
||||
yields_between_refills = round(pool_size * (1 - refill_threshold))
|
||||
# initialize pool; this step may or may not exhaust the iterator.
|
||||
pool = take_n(pool_size, iterator)
|
||||
while True:
|
||||
random.shuffle(pool)
|
||||
for i in range(yields_between_refills):
|
||||
yield pool.pop()
|
||||
next_batch = take_n(yields_between_refills, iterator)
|
||||
if not next_batch:
|
||||
break
|
||||
pool.extend(next_batch)
|
||||
# finish consuming whatever's left - no need for further randomization.
|
||||
yield pool
|
||||
|
||||
|
||||
class timer(object):
|
||||
all_times = defaultdict(float)
|
||||
|
||||
def __init__(self, label):
|
||||
self.label = label
|
||||
|
||||
def __enter__(self):
|
||||
self.tick = time.time()
|
||||
|
||||
def __exit__(self, type, value, traceback):
|
||||
self.tock = time.time()
|
||||
self.all_times[self.label] += self.tock - self.tick
|
||||
|
||||
@classmethod
|
||||
def print_times(cls):
|
||||
for k, v in cls.all_times.items():
|
||||
print("%s: %.3f" % (k, v))
|
||||
def another_color(color):
|
||||
return color * -1
|
||||
|
||||
27
GTP/game.py
27
GTP/game.py
@ -4,7 +4,7 @@
|
||||
# $Date: Tue Nov 28 14:4726 2017 +0800
|
||||
# $Author: renyong15 © <mails.tsinghua.edu.cn>
|
||||
#
|
||||
|
||||
from __future__ import print_function
|
||||
import utils
|
||||
import copy
|
||||
|
||||
@ -173,15 +173,20 @@ class Game:
|
||||
def show_board(self):
|
||||
row = [i for i in range(1, 20)]
|
||||
col = ' abcdefghijklmnopqrstuvwxyz'
|
||||
|
||||
for i in range(self.size):
|
||||
print(row[i])
|
||||
if row[i] < 10:
|
||||
print(' ')
|
||||
for j in range(self.size):
|
||||
print(self.status2symbol(self.board[self._flatten((j + 1, i + 1))]))
|
||||
print('\n')
|
||||
print(' ')
|
||||
print(' ', end='')
|
||||
for j in range(self.size + 1):
|
||||
print(col[j])
|
||||
print(col[j], end=' ')
|
||||
|
||||
print('\n')
|
||||
for i in range(self.size):
|
||||
print(row[i], end=' ')
|
||||
if row[i] < 10:
|
||||
print(' ', end='')
|
||||
for j in range(self.size):
|
||||
print(self.status2symbol(self.board[self._flatten((j + 1, i + 1))]), end=' ')
|
||||
print('\n')
|
||||
|
||||
|
||||
if __name__=="__main__":
|
||||
g = Game()
|
||||
g.show_board()
|
||||
@ -17,6 +17,3 @@ RESIGN = "resign"
|
||||
|
||||
def another_color(color):
|
||||
return color * -1
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user