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98 lines (80 loc) · 3.84 KB
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# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Evalation plays games between two neural nets."""
import os
import time
from absl import flags
from tensorflow import gfile
from strategies import MCTSPlayer
import sgf_wrapper
def play_match(black_net, white_net, games, sgf_dir, verbosity):
"""Plays matches between two neural nets.
black_net: Instance of minigo.DualNetwork, a wrapper around a tensorflow
convolutional network.
white_net: Instance of the minigo.DualNetwork.
games: number of games to play. We play all the games at the same time.
sgf_dir: directory to write the sgf results.
"""
readouts = flags.FLAGS.num_readouts # Flag defined in strategies.py
black = MCTSPlayer(
black_net, verbosity=verbosity, two_player_mode=True)
white = MCTSPlayer(
white_net, verbosity=verbosity, two_player_mode=True)
black_name = os.path.basename(black_net.save_file)
white_name = os.path.basename(white_net.save_file)
for i in range(games):
num_move = 0 # The move number of the current game
for player in [black, white]:
player.initialize_game()
first_node = player.root.select_leaf()
prob, val = player.network.run(first_node.position)
first_node.incorporate_results(prob, val, first_node)
while True:
start = time.time()
active = white if num_move % 2 else black
inactive = black if num_move % 2 else white
current_readouts = active.root.N
while active.root.N < current_readouts + readouts:
active.tree_search()
# print some stats on the search
if verbosity >= 3:
print(active.root.position)
# First, check the roots for hopeless games.
if active.should_resign(): # Force resign
active.set_result(-1 *
active.root.position.to_play, was_resign=True)
inactive.set_result(
active.root.position.to_play, was_resign=True)
if active.is_done():
fname = "{:d}-{:s}-vs-{:s}-{:d}.sgf".format(int(time.time()),
white_name, black_name, i)
with gfile.GFile(os.path.join(sgf_dir, fname), 'w') as _file:
sgfstr = sgf_wrapper.make_sgf(active.position.recent,
active.result_string, black_name=black_name,
white_name=white_name)
_file.write(sgfstr)
print("Finished game", i, active.result_string)
break
move = active.pick_move()
active.play_move(move)
inactive.play_move(move)
dur = time.time() - start
num_move += 1
if (verbosity > 1) or (verbosity == 1 and num_move % 10 == 9):
timeper = (dur / readouts) * 100.0
print(active.root.position)
print("%d: %d readouts, %.3f s/100. (%.2f sec)" % (num_move,
readouts,
timeper,
dur))