def test_make_sgf(self):
all_positions = list(replay_sgf(NO_HANDICAP_SGF))
last_position, _, metadata = all_positions[-1]
back_to_sgf = make_sgf(
last_position.recent,
last_position.score(),
boardsize=metadata.board_size,
komi=last_position.komi,
)
reconstructed_positions = list(replay_sgf(back_to_sgf))
last_position2, _, _ = reconstructed_positions[-1]
self.assertEqualPositions(last_position, last_position2)
def test_make_sgf(self):
all_positions = list(replay_sgf(NO_HANDICAP_SGF))
last_position, _, metadata = all_positions[-1]
back_to_sgf = make_sgf(
last_position.recent,
last_position.score(),
boardsize=metadata.board_size,
komi=last_position.komi,
)
reconstructed_positions = list(replay_sgf(back_to_sgf))
last_position2, _, _ = reconstructed_positions[-1]
self.assertEqualPositions(last_position, last_position2)
def test_make_sgf(self):
all_pwcs = list(replay_sgf(NO_HANDICAP_SGF))
second_last_position, last_move, _ = all_pwcs[-1]
last_position = second_last_position.play_move(last_move)
back_to_sgf = make_sgf(
last_position.recent,
last_position.score(),
komi=last_position.komi,
)
reconstructed_positions = list(replay_sgf(back_to_sgf))
second_last_position2, last_move2, _ = reconstructed_positions[-1]
last_position2 = second_last_position2.play_move(last_move2)
self.assertEqualPositions(last_position, last_position2)
def test_make_sgf(self):
all_pwcs = list(replay_sgf(NO_HANDICAP_SGF))
second_last_position, last_move, _ = all_pwcs[-1]
last_position = second_last_position.play_move(last_move)
back_to_sgf = make_sgf(
last_position.recent,
last_position.score(),
komi=last_position.komi,
)
reconstructed_positions = list(replay_sgf(back_to_sgf))
second_last_position2, last_move2, _ = reconstructed_positions[-1]
last_position2 = second_last_position2.play_move(last_move2)
self.assertEqualPositions(last_position, last_position2)
def analyze_symmetries(sgf_file, dual_network):
with open(sgf_file) as f:
sgf_contents = f.read()
iterator = sgf_wrapper.replay_sgf(sgf_contents)
differences = []
stddevs = []
# For every move in the game, get the corresponding network values for all
# eight symmetries.
for i, pwc in enumerate(iterator):
feats = features.extract_features(pwc.position)
variants = [symmetries.apply_symmetry_feat(s, feats)
for s in symmetries.SYMMETRIES]
values = dual_network.sess.run(
dual_network.inference_output['value_output'],
feed_dict={dual_network.inference_input: variants})
# Get the difference between the maximum and minimum outputs of the
# value network over all eight symmetries; also get the standard
# deviation of the eight values.
differences.append(max(values) - min(values))
stddevs.append(np.std(values))
differences.sort()
percentiles = [differences[i * len(differences) // 100] for i in range(100)]
worst = differences[-1]
avg_stddev = np.mean(stddevs)
return (percentiles, worst, avg_stddev)
def test_replay_position(self):
sgf_positions = list(replay_sgf(NO_HANDICAP_SGF))
initial = sgf_positions[0]
self.assertEqual(initial.metadata.result, 'W+1.5')
self.assertEqual(initial.metadata.board_size, 9)
self.assertEqual(initial.position.komi, 6.5)
final = sgf_positions[-1].position
# sanity check to ensure we're working with the right position
final_board = load_board('''
.OXX.....
O.OX.X...
.OOX.....
OOOOXXXXX
XOXXOXOOO
XOOXOO.O.
XOXXXOOXO
XXX.XOXXO
X..XOO.O.
''')
expected_final_position = go.Position(final_board,
n=62,
komi=6.5,
caps=(3, 2),
ko=None,
recent=tuple(),
to_play=go.BLACK)
self.assertEqualPositions(expected_final_position, final)
self.assertEqual(final.n, len(final.recent))
replayed_positions = list(replay_position(final))
for sgf_pos, replay_pos in zip(sgf_positions, replayed_positions):
self.assertEqualPositions(sgf_pos.position, replay_pos.position)
def cmd_loadsgf(self, arguments):
args = arguments.split()
if len(args) == 2:
file_, movenum = args
movenum = int(movenum)
print("movenum =", movenum, file=sys.stderr)
else:
file_ = args[0]
movenum = None
try:
with open(file_, 'r') as f:
contents = f.read()
except:
raise ValueError("Unreadable file: " + file_)
try:
# This is kinda bad, because replay_sgf is already calling
# 'play move' on its internal position objects, but we really
# want to advance the engine along with us rather than try to
# push in some finished Position object.
for idx, p in enumerate(sgf_wrapper.replay_sgf(contents)):
print("playing #", idx, p.next_move, file=sys.stderr)
self._game.play_move(p.next_move)
if movenum and idx == movenum:
break
except:
raise
def test_replay_position(self):
sgf_positions = list(sgf_wrapper.replay_sgf(NO_HANDICAP_SGF))
initial = sgf_positions[0]
self.assertEqual(initial.result, go.WHITE)
final = sgf_positions[-1].position.play_move(
sgf_positions[-1].next_move)
# sanity check to ensure we're working with the right position
final_board = test_utils.load_board('''
.OXX.....
O.OX.X...
.OOX.....
OOOOXXXXX
XOXXOXOOO
XOOXOO.O.
XOXXXOOXO
XXX.XOXXO
X..XOO.O.
''')
expected_final_position = go.Position(
final_board,
n=62,
komi=6.5,
caps=(3, 2),
ko=None,
recent=tuple(),
to_play=go.BLACK
)
self.assertEqualPositions(expected_final_position, final)
self.assertEqual(final.n, len(final.recent))
replayed_positions = list(go.replay_position(final, 1))
for sgf_pos, replay_pos in zip(sgf_positions, replayed_positions):
self.assertEqualPositions(sgf_pos.position, replay_pos.position)
def test_replay_position(self):
sgf_positions = list(sgf_wrapper.replay_sgf(NO_HANDICAP_SGF))
initial = sgf_positions[0]
self.assertEqual(initial.result, go.WHITE)
final = sgf_positions[-1].position.play_move(
sgf_positions[-1].next_move)
# sanity check to ensure we're working with the right position
final_board = test_utils.load_board('''
.OXX.....
O.OX.X...
.OOX.....
OOOOXXXXX
XOXXOXOOO
XOOXOO.O.
XOXXXOOXO
XXX.XOXXO
X..XOO.O.
''')
expected_final_position = go.Position(final_board,
n=62,
komi=6.5,
caps=(3, 2),
ko=None,
recent=tuple(),
to_play=go.BLACK)
self.assertEqualPositions(expected_final_position, final)
self.assertEqual(final.n, len(final.recent))
replayed_positions = list(go.replay_position(final))
for sgf_pos, replay_pos in zip(sgf_positions, replayed_positions):
self.assertEqualPositions(sgf_pos.position, replay_pos.position)
def cmd_loadsgf(self, arguments):
args = arguments.split()
if len(args) == 2:
file_, movenum = args
movenum = int(movenum)
print("movenum =", movenum, file=sys.stderr)
else:
file_ = args[0]
movenum = None
try:
with open(file_, 'r') as f:
contents = f.read()
except:
raise ValueError("Unreadable file: " + file_)
try:
# This is kinda bad, because replay_sgf is already calling
# 'play move' on its internal position objects, but we really
# want to advance the engine along with us rather than try to
# push in some finished Position object.
for idx, p in enumerate(sgf_wrapper.replay_sgf(contents)):
print("playing #", idx, p.next_move, file=sys.stderr)
self._game.play_move(p.next_move)
if movenum and idx == movenum:
break
except:
raise
def predict_move(filename, network, tries_per_move=1, readouts=1000):
replay = []
if filename not in REPLAY_CACHE:
with open(filename) as f:
text = f.read()
for position_w_context in sgf_wrapper.replay_sgf(text):
replay.append(position_w_context)
REPLAY_CACHE[filename] = replay
replay = REPLAY_CACHE[filename]
black_net = network
player = MCTSPlayer(
black_net, verbosity=0, two_player_mode=True, num_parallel=4)
tried = 0
correct = 0
move_ratings = []
for position_w_context in replay:
if position_w_context.next_move is None:
continue
num_correct = 0
for i in range(tries_per_move):
move, correct_move, is_correct = predict_position(position_w_context, player, readouts=readouts)
if is_correct:
num_correct += 1
move_ratings.append(num_correct * 1.0 / tries_per_move)
print('RATING: ', sum(move_ratings) / len(move_ratings))
return move_ratings
def main(argv):
# It takes a couple of seconds to import anything from tensorflow, so only
# do it if we need to read from GCS.
path = argv[1]
if path.startswith('gs://'):
from tensorflow import gfile
f = gfile.GFile(path, 'r')
else:
f = open(path, 'r')
contents = f.read()
f.close()
# Determine the board size before importing any Minigo libraries because
# require that the BOARD_SIZE environment variable is set correctly before
# import.
m = re.search(r'SZ\[([^]]+)', contents)
if not m:
print('Couldn\'t find SZ node, assuming 19x19 board')
board_size = 19
else:
board_size = int(m.group(1))
# Set the board size and import the Minigo libs.
os.environ['BOARD_SIZE'] = str(board_size)
import coords
import go
import sgf_wrapper
# Replay the game.
for x in sgf_wrapper.replay_sgf(contents):
to_play = 'B' if x.position.to_play == 1 else 'W'
print('{}>> {}: {}\n'.format(x.position, to_play,
coords.to_gtp(x.next_move)))
def get_positions_from_sgf(file):
try:
with open(file) as f:
for position_w_context in replay_sgf(f.read()):
if position_w_context.is_usable():
yield position_w_context
except:
return
def test_chinese_handicap_handling(self):
intermediate_board = utils_test.load_board('''
.........
.........
......X..
.........
.........
.........
.........
.........
.........
''')
intermediate_position = go.Position(
utils_test.BOARD_SIZE,
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.BLACK, coords.from_kgs(
utils_test.BOARD_SIZE, 'G7')),),
to_play=go.BLACK,
)
final_board = utils_test.load_board('''
....OX...
.O.OOX...
O.O.X.X..
.OXXX....
OX...XX..
.X.XXO...
X.XOOXXX.
XXXO.OOX.
.XOOX.O..
''')
final_position = go.Position(
utils_test.BOARD_SIZE,
final_board,
n=50,
komi=5.5,
caps=(7, 2),
ko=None,
recent=(
go.PlayerMove(
go.WHITE, coords.from_kgs(utils_test.BOARD_SIZE, 'E9')),
go.PlayerMove(
go.BLACK, coords.from_kgs(utils_test.BOARD_SIZE, 'F9')),),
to_play=go.WHITE
)
positions_w_context = list(replay_sgf(
utils_test.BOARD_SIZE, CHINESE_HANDICAP_SGF))
self.assertEqualPositions(
intermediate_position, positions_w_context[1].position)
self.assertEqual(
positions_w_context[1].next_move, coords.from_kgs(
utils_test.BOARD_SIZE, 'C3'))
final_replayed_position = positions_w_context[-1].position.play_move(
positions_w_context[-1].next_move)
self.assertEqualPositions(final_position, final_replayed_position)
def initialize_game(sgf_file, load_file, move=1):
with open(sgf_file) as f:
sgf_contents = f.read()
iterator = sgf_wrapper.replay_sgf(sgf_contents)
for i in range(move):
position_w_context = next(iterator)
player = strategies.MCTSPlayerMixin(dual_net.DualNetwork(load_file))
player.initialize_game(position_w_context.position)
return player
def get_positions_from_sgf(file): #取得行棋位置
print("正在处理棋谱文件：%s"%file)
#auto_play.game().__init__()
with open(file) as t: #打开一个文件到内存
ft=replay_sgf(t.read())
auto_play.game().run(ft,file) #自动显示棋谱
with open(file) as f: #打开一个文件到内存(上面已经打开过 要重新打开)
for i,position_w_context in enumerate(replay_sgf(f.read())): #循环打开棋谱文件，得到棋谱数据 使用枚举得到坐标
#print("正在处理第%s手"%(i+1))
#print(position_w_context.next_move) #sgf坐标 横坐标（从左到右） 从a到s 纵坐标：从上到下a到s 现在使用数字坐标先是纵坐票0到18 后是横从坐票0到18
if position_w_context.is_usable():
yield position_w_context
def test_chinese_handicap_handling(self):
intermediate_board = utils_test.load_board('''
.........
.........
......X..
.........
.........
.........
.........
.........
.........
''')
intermediate_position = go.Position(
utils_test.BOARD_SIZE,
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.BLACK,
coords.from_kgs(utils_test.BOARD_SIZE,
'G7')), ),
to_play=go.BLACK,
)
final_board = utils_test.load_board('''
....OX...
.O.OOX...
O.O.X.X..
.OXXX....
OX...XX..
.X.XXO...
X.XOOXXX.
XXXO.OOX.
.XOOX.O..
''')
final_position = go.Position(
utils_test.BOARD_SIZE,
final_board,
n=50,
komi=5.5,
caps=(7, 2),
ko=None,
recent=(
go.PlayerMove(go.WHITE,
coords.from_kgs(utils_test.BOARD_SIZE, 'E9')),
go.PlayerMove(go.BLACK,
coords.from_kgs(utils_test.BOARD_SIZE, 'F9')),
),
to_play=go.WHITE)
positions_w_context = list(
replay_sgf(utils_test.BOARD_SIZE, CHINESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position,
positions_w_context[1].position)
self.assertEqual(positions_w_context[1].next_move,
coords.from_kgs(utils_test.BOARD_SIZE, 'C3'))
final_replayed_position = positions_w_context[-1].position.play_move(
positions_w_context[-1].next_move)
self.assertEqualPositions(final_position, final_replayed_position)
def initialize_game(sgf_file, load_file, move=1):
with open(sgf_file) as f:
sgf_contents = f.read()
iterator = sgf_wrapper.replay_sgf(sgf_contents)
for i in range(move):
position_w_context = next(iterator)
player = strategies.MCTSPlayerMixin(dual_net.DualNetwork(load_file))
player.initialize_game(position_w_context.position)
return player
def test_japanese_handicap_handling(self):
intermediate_board = utils_test.load_board('''
.........
.........
......X..
.........
....O....
.........
..X......
.........
.........
''')
intermediate_position = go.Position(
utils_test.BOARD_SIZE,
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.WHITE,
coords.from_kgs(utils_test.BOARD_SIZE,
'E5')), ),
to_play=go.BLACK,
)
final_board = utils_test.load_board('''
.........
.........
......X..
.........
....O....
.........
..XX.....
.........
.........
''')
final_position = go.Position(
utils_test.BOARD_SIZE,
final_board,
n=2,
komi=5.5,
caps=(0, 0),
recent=(
go.PlayerMove(go.WHITE,
coords.from_kgs(utils_test.BOARD_SIZE, 'E5')),
go.PlayerMove(go.BLACK,
coords.from_kgs(utils_test.BOARD_SIZE, 'D3')),
),
to_play=go.WHITE,
)
positions_w_context = list(
replay_sgf(utils_test.BOARD_SIZE, JAPANESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position,
positions_w_context[1].position)
final_replayed_position = positions_w_context[-1].position.play_move(
positions_w_context[-1].next_move)
self.assertEqualPositions(final_position, final_replayed_position)
def predict_move(filename, network):
# Strategies: def initialize_game(self, position=None):
#filename = '/usr/local/google/home/vbittorf/projects/minigo/benchmark_sgf/prob_0001.sgf'
replay = []
with open(filename) as f:
text = f.read()
print(text)
for position_w_context in sgf_wrapper.replay_sgf(text):
replay.append(position_w_context)
print(replay)
# model_path = '/usr/local/google/home/vbittorf/Documents/minigo/rl_pipeline/models/000003-leopard'
#model_path = '/usr/local/google/home/vbittorf/Documents/minigo/20hour1000game/models/000002-nassau'
#white_net = dual_net.DualNetwork(model_path)
#black_net = dual_net.DualNetwork(model_path)
#print(evaluation.play_match(white_net, black_net, 1, 50, "/tmp/sgf", 0))
black_net = network
player = MCTSPlayer(
black_net, verbosity=0, two_player_mode=True, num_parallel=4)
readouts = 361 * 10
tried = 0
correct = 0
for position_w_context in replay:
if position_w_context.next_move is None:
continue
player.initialize_game(position_w_context.position)
current_readouts = player.root.N
while player.root.N < current_readouts + readouts:
player.tree_search()
move = player.pick_move()
#if player.should_resign(): # Force resign
# move = 'R'
#else:
# move = player.suggest_move(position_w_context.position)
tried += 1
if move == position_w_context.next_move:
correct += 1
player.play_move(move)
print(player.root.position)
print(move, position_w_context.next_move)
return move, position_w_context.next_move, move == position_w_context.next_move
print('Correct: ', correct * 1.0 / tried)
def predict_move(filename, network):
# Strategies: def initialize_game(self, position=None):
#filename = '/usr/local/google/home/vbittorf/projects/minigo/benchmark_sgf/prob_0001.sgf'
replay = []
with open(filename) as f:
text = f.read()
print(text)
for position_w_context in sgf_wrapper.replay_sgf(text):
replay.append(position_w_context)
print(replay)
# model_path = '/usr/local/google/home/vbittorf/Documents/minigo/rl_pipeline/models/000003-leopard'
#model_path = '/usr/local/google/home/vbittorf/Documents/minigo/20hour1000game/models/000002-nassau'
#white_net = dual_net.DualNetwork(model_path)
#black_net = dual_net.DualNetwork(model_path)
#print(evaluation.play_match(white_net, black_net, 1, 50, "/tmp/sgf", 0))
black_net = network
player = MCTSPlayer(black_net,
verbosity=0,
two_player_mode=True,
num_parallel=4)
readouts = 361 * 10
tried = 0
correct = 0
for position_w_context in replay:
if position_w_context.next_move is None:
continue
player.initialize_game(position_w_context.position)
current_readouts = player.root.N
while player.root.N < current_readouts + readouts:
player.tree_search()
move = player.pick_move()
# if player.should_resign(): # Force resign
# move = 'R'
# else:
# move = player.suggest_move(position_w_context.position)
tried += 1
if move == position_w_context.next_move:
correct += 1
player.play_move(move)
print(player.root.position)
print(move, position_w_context.next_move)
return move, position_w_context.next_move, move == position_w_context.next_move
print('Correct: ', correct * 1.0 / tried)
def test_japanese_handicap_handling(self):
intermediate_board = utils_test.load_board('''
.........
.........
......X..
.........
....O....
.........
..X......
.........
.........
''')
intermediate_position = go.Position(
utils_test.BOARD_SIZE,
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.WHITE, coords.from_kgs(
utils_test.BOARD_SIZE, 'E5')),),
to_play=go.BLACK,
)
final_board = utils_test.load_board('''
.........
.........
......X..
.........
....O....
.........
..XX.....
.........
.........
''')
final_position = go.Position(
utils_test.BOARD_SIZE,
final_board,
n=2,
komi=5.5,
caps=(0, 0),
recent=(
go.PlayerMove(go.WHITE, coords.from_kgs(
utils_test.BOARD_SIZE, 'E5')),
go.PlayerMove(go.BLACK, coords.from_kgs(
utils_test.BOARD_SIZE, 'D3')),),
to_play=go.WHITE,
)
positions_w_context = list(replay_sgf(
utils_test.BOARD_SIZE, JAPANESE_HANDICAP_SGF))
self.assertEqualPositions(
intermediate_position, positions_w_context[1].position)
final_replayed_position = positions_w_context[-1].position.play_move(
positions_w_context[-1].next_move)
self.assertEqualPositions(final_position, final_replayed_position)
def parse_sgf(sgf_path):
with open(sgf_path) as f:
sgf_contents = f.read()
collection = sgf.parse(sgf_contents)
game = collection.children[0]
props = game.root.properties
assert int(sgf_prop(props.get('GM', ['1']))) == 1, "Not a Go SGF!"
result = utils.parse_game_result(sgf_prop(props.get('RE')))
positions, moves = zip(*[(p.position, p.next_move) for p in sgf_wrapper.replay_sgf(sgf_contents)])
return positions, moves, result, props
def test_chinese_handicap_handling(self):
intermediate_board = load_board('''
.........
.........
......X..
.........
.........
.........
.........
.........
.........
''')
intermediate_position = go.Position(
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.BLACK, pc('G7')), ),
to_play=go.BLACK,
)
final_board = load_board('''
....OX...
.O.OOX...
O.O.X.X..
.OXXX....
OX...XX..
.X.XXO...
X.XOOXXX.
XXXO.OOX.
.XOOX.O..
''')
final_position = go.Position(final_board,
n=50,
komi=5.5,
caps=(7, 2),
ko=None,
recent=(
go.PlayerMove(go.WHITE, pc('E9')),
go.PlayerMove(go.BLACK, pc('F9')),
),
to_play=go.WHITE)
positions_w_context = list(replay_sgf(CHINESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position,
positions_w_context[1].position)
self.assertEqual(positions_w_context[1].next_move, pc('C3'))
self.assertEqualPositions(final_position,
positions_w_context[-1].position)
self.assertFalse(positions_w_context[-1].is_usable())
self.assertTrue(positions_w_context[-2].is_usable())
def parse_sgf(sgf_path):
# TODO(sethtroisi): Replace uses with call to sgf_wrapper.
with open(sgf_path) as f:
sgf_contents = f.read()
collection = sgf.parse(sgf_contents)
game = collection.children[0]
props = game.root.properties
assert int(sgf_prop_get(props, 'GM', '1')) == 1, "Not a Go SGF!"
result = parse_game_result(sgf_prop_get(props, 'RE', ''))
positions, moves = zip(*[(p.position, p.next_move)
for p in replay_sgf(sgf_contents)])
return positions, moves, result, props
def test_japanese_handicap_handling(self):
intermediate_board = load_board('''
.........
.........
......X..
.........
....O....
.........
..X......
.........
.........
''')
intermediate_position = go.Position(
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.WHITE, pc('E5')), ),
to_play=go.BLACK,
)
final_board = load_board('''
.........
.........
......X..
.........
....O....
.........
..XX.....
.........
.........
''')
final_position = go.Position(
final_board,
n=2,
komi=5.5,
caps=(0, 0),
recent=(
go.PlayerMove(go.WHITE, pc('E5')),
go.PlayerMove(go.BLACK, pc('D3')),
),
to_play=go.WHITE,
)
positions_w_context = list(replay_sgf(JAPANESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position,
positions_w_context[1].position)
self.assertEqualPositions(final_position,
positions_w_context[-1].position)
def cmd_loadsgf(self, filename: str, movenum=0):
try:
with open(filename, 'r') as f:
contents = f.read()
except:
raise ValueError("Unreadable file: " + filename)
# This is kinda bad, because replay_sgf is already calling
# 'play move' on its internal position objects, but we really
# want to advance the engine along with us rather than try to
# push in some finished Position object.
for idx, p in enumerate(sgf_wrapper.replay_sgf(contents)):
print("playing #", idx, p.next_move, file=sys.stderr)
self._player.play_move(p.next_move)
if movenum and idx == movenum:
break
def test_chinese_handicap_handling(self):
intermediate_board = load_board('''
.........
.........
......X..
.........
.........
.........
.........
.........
.........
''')
intermediate_position = go.Position(
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.BLACK, pc('G7')),),
to_play=go.BLACK,
)
final_board = load_board('''
....OX...
.O.OOX...
O.O.X.X..
.OXXX....
OX...XX..
.X.XXO...
X.XOOXXX.
XXXO.OOX.
.XOOX.O..
''')
final_position = go.Position(
final_board,
n=50,
komi=5.5,
caps=(7, 2),
ko=None,
recent=(go.PlayerMove(go.WHITE, pc('E9')),
go.PlayerMove(go.BLACK, pc('F9')),),
to_play=go.WHITE
)
positions_w_context = list(replay_sgf(CHINESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position, positions_w_context[1].position)
self.assertEqual(positions_w_context[1].next_move, pc('C3'))
self.assertEqualPositions(final_position, positions_w_context[-1].position)
self.assertFalse(positions_w_context[-1].is_usable())
self.assertTrue(positions_w_context[-2].is_usable())
def test_japanese_handicap_handling(self):
intermediate_board = load_board('''
.........
.........
......X..
.........
....O....
.........
..X......
.........
.........
''')
intermediate_position = go.Position(
intermediate_board,
n=1,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.WHITE, pc('E5')),),
to_play=go.BLACK,
)
final_board = load_board('''
.........
.........
......X..
.........
....O....
.........
..XX.....
.........
.........
''')
final_position = go.Position(
final_board,
n=2,
komi=5.5,
caps=(0, 0),
recent=(go.PlayerMove(go.WHITE, pc('E5')),
go.PlayerMove(go.BLACK, pc('D3')),),
to_play=go.WHITE,
)
positions_w_context = list(replay_sgf(JAPANESE_HANDICAP_SGF))
self.assertEqualPositions(intermediate_position, positions_w_context[1].position)
self.assertEqualPositions(final_position, positions_w_context[-1].position)
def analyze_symmetries(sgf_file, load_file):
with open(sgf_file) as f:
sgf_contents = f.read()
iterator = sgf_wrapper.replay_sgf(sgf_contents)
net = dual_net.DualNetwork(load_file)
for i, pwc in enumerate(iterator):
if i < 200:
continue
feats = features.extract_features(pwc.position)
variants = [symmetries.apply_symmetry_feat(s, feats) for s in symmetries.SYMMETRIES]
values = net.sess.run(
net.inference_output['value_output'],
feed_dict={net.inference_input['pos_tensor']: variants})
mean = np.mean(values)
stdev = np.std(values)
all_vals = sorted(zip(values, symmetries.SYMMETRIES))
print("{:3d} {:.3f} +/- {:.3f} min {:.3f} {} max {:.3f} {}".format(
i, mean, stdev, *all_vals[0], *all_vals[-1]))
def cmd_loadsgf(self, filename: str, movenum=0):
try:
with open(filename, 'r') as f:
contents = f.read()
except:
raise ValueError("Unreadable file: " + filename)
# Clear the board before replaying sgf
# TODO: should this use the sgfs komi?
self._player.initialize_game(go.Position())
# This is kinda bad, because replay_sgf is already calling
# 'play move' on its internal position objects, but we really
# want to advance the engine along with us rather than try to
# push in some finished Position object.
for idx, p in enumerate(sgf_wrapper.replay_sgf(contents)):
dbg("playing #", idx, p.next_move)
self._player.play_move(p.next_move)
if movenum and idx == movenum:
break
def analyze_symmetries(sgf_file, load_file):
with open(sgf_file) as f:
sgf_contents = f.read()
iterator = sgf_wrapper.replay_sgf(sgf_contents)
net = dual_net.DualNetwork(load_file)
for i, pwc in enumerate(iterator):
if i < 200:
continue
feats = features.extract_features(pwc.position)
variants = [
symmetries.apply_symmetry_feat(s, feats)
for s in symmetries.SYMMETRIES
]
values = net.sess.run(
net.inference_output['value_output'],
feed_dict={net.inference_input['pos_tensor']: variants})
mean = np.mean(values)
stdev = np.std(values)
all_vals = sorted(zip(values, symmetries.SYMMETRIES))
print("{:3d} {:.3f} +/- {:.3f} min {:.3f} {} max {:.3f} {}".format(
i, mean, stdev, *all_vals[0], *all_vals[-1]))
def test_replay_position(self):
sgf_positions = list(replay_sgf(NO_HANDICAP_SGF))
initial = sgf_positions[0]
self.assertEqual(initial.metadata.result, 'W+1.5')
self.assertEqual(initial.metadata.board_size, 9)
self.assertEqual(initial.position.komi, 6.5)
final = sgf_positions[-1].position
# sanity check to ensure we're working with the right position
final_board = load_board('''
.OXX.....
O.OX.X...
.OOX.....
OOOOXXXXX
XOXXOXOOO
XOOXOO.O.
XOXXXOOXO
XXX.XOXXO
X..XOO.O.
''')
expected_final_position = go.Position(
final_board,
n=62,
komi=6.5,
caps=(3, 2),
ko=None,
recent=tuple(),
to_play=go.BLACK
)
self.assertEqualPositions(expected_final_position, final)
self.assertEqual(final.n, len(final.recent))
replayed_positions = list(replay_position(final))
for sgf_pos, replay_pos in zip(sgf_positions, replayed_positions):
self.assertEqualPositions(sgf_pos.position, replay_pos.position)
def get_positions_from_sgf(file):
with open(file) as f:
for position_w_content in replay_sgf(f.read()):
if position_w_content.is_usable():
yield position_w_content
def test_sgf_props(self): sgf_replayer = replay_sgf(utils_test.BOARD_SIZE, CHINESE_HANDICAP_SGF) initial = next(sgf_replayer) self.assertEqual(initial.result, go.BLACK) self.assertEqual(initial.position.komi, 5.5)
def test_sgf_props(self):
sgf_replayer = replay_sgf(utils_test.BOARD_SIZE, CHINESE_HANDICAP_SGF)
initial = next(sgf_replayer)
self.assertEqual(initial.result, go.BLACK)
self.assertEqual(initial.position.komi, 5.5)
def test_sgf_props(self):
sgf_replayer = replay_sgf(CHINESE_HANDICAP_SGF)
initial = next(sgf_replayer)
self.assertEqual(initial.metadata.result, 'B+39.50')
self.assertEqual(initial.metadata.board_size, 9)
self.assertEqual(initial.position.komi, 5.5)
def parse_sgf(sgf_path):
with open(sgf_path) as f:
sgf_contents = f.read()
return zip(*[(p.position, p.next_move, p.result)
for p in sgf_wrapper.replay_sgf(sgf_contents)])
def get_positions_from_sgf(file):
with open(file) as f:
for position_w_context in replay_sgf(f.read()):
if position_w_context.is_usable():
yield position_w_context
def test_sgf_props(self):
sgf_replayer = replay_sgf(CHINESE_HANDICAP_SGF)
initial = next(sgf_replayer)
self.assertEqual(go.BLACK, initial.result)
self.assertEqual(5.5, initial.position.komi)
def test_sgf_props(self):
sgf_replayer = replay_sgf(CHINESE_HANDICAP_SGF)
initial = next(sgf_replayer)
self.assertEqual(initial.metadata.result, 'B+39.50')
self.assertEqual(initial.metadata.board_size, 9)
self.assertEqual(initial.position.komi, 5.5)
