def generate_game(board_size, rounds, max_moves, temperature):
boards, moves = [], []
encoder = get_encoder_by_name('oneplane', board_size)
game = goboard.GameState.new_game(board_size)
bot = mcts.MCTSAgent(rounds, temperature)
num_moves = 0
while not game.is_over():
print_board(game.board)
move = bot.select_move(game) # <5>
if move.is_play:
boards.append(encoder.encode(game)) # <6>
move_one_hot = np.zeros(encoder.num_points())
move_one_hot[encoder.encode_point(move.point)] = 1
moves.append(move_one_hot) # <7>
print_move(game.next_player, move)
game = game.apply_move(move) # <8>
num_moves += 1
if num_moves > max_moves: # <9>
break
return np.array(boards), np.array(moves)
def __init__(self,
encoder='simple',
data_directory='data',
count_stones_debute=None,
count_stones_middle=None,
count_stones_end=None):
self.encoder_string = encoder
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
self.count_stones_debute = count_stones_debute # Nail counts stones on board debute
self.count_stones_middle = count_stones_middle # Nail counts stones on board middle
self.count_stones_end = count_stones_end # Nail counts stones on board end
def generate_game(board_size, rounds, max_moves, temperature):
# In `boards` we store encoded board state, `moves` is for encoded moves.
boards, moves = [], []
# We initialize a OnePlaneEncoder by name with given board size.
encoder = get_encoder_by_name('oneplane', board_size)
# An new game of size `board_size` is instantiated.
game = goboard.GameState.new_game(board_size)
# A Monte Carlo tree search agent with specified number of rounds and temperature will serve as our bot.
bot = mcts.MCTSAgent(rounds, temperature)
num_moves = 0
while not game.is_over():
print_board(game.board)
# The next move is selected by the bot.
move = bot.select_move(game)
if move.is_play:
boards.append(encoder.encode(
game)) # The encoded board situation is appended to `boards`.
move_one_hot = np.zeros(encoder.num_points())
move_one_hot[encoder.encode_point(move.point)] = 1
moves.append(
move_one_hot
) # The one-hot-encoded next move is appended to `moves`.
print_move(game.next_player, move)
game = game.apply_move(
move) # Afterwards the bot move is applied to the board.
num_moves += 1
if num_moves > max_moves: # continue with the next move, unless the maximum number of moves has been reached
break
return np.array(boards), np.array(moves)
def __init__(self, encoder='train', data_directory='data'):
self.encoder_string = encoder
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
def __init__(
self,
encoder='oneplane',
data_directory='D:\\CODE\\Python\\Go\\code\\dlgo\\data\\tarfiles'):
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
def __init__(self, encoder='simple', data_directory='data'):
self.encoder_string = encoder
self.encoder = get_encoder_by_name(encoder, 19)
fpath = os.path.join(CODE_ROOT_DIR, data_directory)
self.data_dir = fpath
def __init__(self, encoder='oneplane', data_directory=DATA_DIRECTORY):
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
def __init__(self, encoder='oneplane', data_directory='data'):
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
def __init__(self, encoder='simple', data_directory='datasets'):
self.encoder_string = encoder
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
def __init__(self, encoder='simple', data_directory=DATA_DIRECTORY):
# process_zipを行い，ファイルを特徴量とラベルに変換するエンコーダ
self.encoder_string = encoder
self.encoder = get_encoder_by_name(encoder, 19)
self.data_dir = data_directory
