215 lines
9.4 KiB
Python
215 lines
9.4 KiB
Python
import copy
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import json
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import random
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import re
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import shlex
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import subprocess
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import sys
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import threading
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import time
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from queue import Queue
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from kivy.storage.jsonstore import JsonStore
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from kivy.uix.gridlayout import GridLayout
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from board import Board, IllegalMoveException, Move
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config_file = sys.argv[1] if len(sys.argv) > 1 else "config.json"
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print(f"Using config file {config_file}")
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Config = JsonStore(config_file)
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class EngineControls(GridLayout):
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def __init__(self, **kwargs):
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super(EngineControls, self).__init__(**kwargs)
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self.command = shlex.split(Config.get("engine")["command"])
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analysis_settings = Config.get("analysis")
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self.visits = [[analysis_settings["pass_visits"], analysis_settings["visits"]], [analysis_settings["pass_visits_fast"], analysis_settings["visits_fast"]]]
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self.train_settings = Config.get("trainer")
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self.debug = Config.get("debug")["level"]
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self.board_size = Config.get("board")["size"]
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self.ready = False
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self.message_queue = None
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self.board = Board(self.board_size)
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self.komi = 6.5 # loaded from config in init
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self.outstanding_analysis_queries = [] # allows faster interaction while kata is starting
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self.kata = None
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def redraw(self, include_board=False):
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if include_board:
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self.parent.board.draw_board()
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self.parent.board.redraw()
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def restart(self, board_size=None):
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self.ready = False
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if not self.message_queue:
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self.message_queue = Queue()
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self.engine_thread = threading.Thread(target=self._engine_thread, daemon=True).start()
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else:
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with self.message_queue.mutex:
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self.message_queue.queue.clear()
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self.action("init", board_size or self.board_size)
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def action(self, message, *args):
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self.message_queue.put([message, *args])
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# engine main loop
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def _engine_thread(self):
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self.kata = subprocess.Popen(self.command, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
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self.analysis_thread = threading.Thread(target=self._analysis_read_thread, daemon=True).start()
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msg, *args = self.message_queue.get()
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while True:
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try:
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if self.debug:
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print("MESSAGE", msg, args)
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getattr(self, f"_do_{msg.replace('-','_')}")(*args)
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except Exception as e:
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self.info.text = f"Exception in Engine thread: {e}"
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raise
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msg, *args = self.message_queue.get()
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def play(self, move):
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try:
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mr = self.board.play(move)
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except IllegalMoveException as e:
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self.info.text = f"Illegal move: {str(e)}"
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return
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if not mr.analysis_ready: # replayed old move
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self._request_analysis(mr)
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return mr
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# handles showing completed analysis and triggered actions like auto undo and ai move
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def update_evaluation(self, undo_triggered=False):
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current_move = self.board.current_move
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self.score.set_prisoners(self.board.prisoner_count)
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if self.eval.active(current_move.player):
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self.info.text = current_move.comment(eval=self.eval.active(current_move.player), hints=self.hints.active(current_move.player))
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self.evaluation.text = ""
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if current_move.analysis_ready and self.eval.active(current_move.player):
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self.score.text = current_move.format_score().replace("-", "\u2013")
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self.temperature.text = f"{current_move.temperature_stats[2]:.1f}"
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if current_move.parent and current_move.parent.analysis_ready:
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self.evaluation.text = f"{100 * current_move.evaluation:.1f}%"
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if current_move.analysis_ready and current_move.parent and current_move.parent.analysis_ready and not current_move.children:
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# handle automatic undo
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if self.auto_undo.active(current_move.player) and not self.ai_auto.active(current_move.player) and not current_move.auto_undid:
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ts = self.train_settings
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# TODO: is this overly generous wrt low visit outdated evaluations?
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eval = max(current_move.evaluation, current_move.outdated_evaluation or 0)
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points_lost = (current_move.parent or current_move).temperature_stats[2] * (1 - eval)
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if eval < ts["undo_eval_threshold"] and points_lost >= ts["undo_point_threshold"]:
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current_move.auto_undid = True
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self.board.undo()
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undo_triggered = True
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if len(current_move.parent.children) >= ts["num_undo_prompts"] + 1:
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best_move = sorted([m for m in current_move.parent.children], key=lambda m: -(m.evaluation_info[0] or 0))[0]
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best_move.x_comment = f"Automatically played as best option after max. {ts['num_undo_prompts']} undo(s).\n"
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self.board.play(best_move)
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self.update_evaluation(undo_triggered=True)
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# ai player doesn't technically need parent ready, but don't want to override waiting for undo
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elif self.ai_auto.active(1 - current_move.player) and not current_move.children and not undo_triggered and not self.board.game_ended:
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self._do_aimove()
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# engine action functions
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def _do_play(self, *args):
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self.play(Move(player=self.board.current_player, coords=args[0]))
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self.redraw()
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def _do_aimove(self):
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ts = self.train_settings
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while not self.board.current_move.analysis_ready:
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self.info.text = "Thinking..."
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time.sleep(0.05)
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# select move
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current_move = self.board.current_move
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pos_moves = [(d["move"], float(d["scoreMean"]), d["evaluation"]) for d in current_move.ai_moves if int(d["visits"]) >= ts["balance_play_min_visits"]]
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sel_moves = pos_moves[:1]
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# don't play suicidal to balance score - pass when it's best
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if self.ai_balance.active and pos_moves[0][0] != "pass":
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sel_moves = [
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(move, score, eval)
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for move, score, eval in pos_moves
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if eval > ts["balance_play_randomize_eval"]
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and -current_move.player_sign * score > 0
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or eval > ts["balance_play_min_eval"]
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and -current_move.player_sign * score > ts["balance_play_target_score"]
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] or sel_moves
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aimove = Move(player=self.board.current_player, gtpcoords=random.choice(sel_moves)[0], robot=True)
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if len(sel_moves) > 1:
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aimove.x_comment = "AI Balance on, moves considered: " + ", ".join(f"{move} ({aimove.format_score(score)})" for move, score, _ in sel_moves) + "\n"
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self.play(aimove)
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def _do_undo(self):
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if (
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self.ai_lock.active
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and self.auto_undo.active(self.board.current_move.parent.player)
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and len(self.board.current_move.parent.player.children) > self.train_settings["num_undo_prompts"]
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):
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self.info.text = f"Can't undo more than {self.train_settings['num_undo_prompts']} time(s) when locked"
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return
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self.board.undo()
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def _do_init(self, board_size):
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self.board_size = board_size
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self.komi = Config.get("board")[f"komi_{board_size}"]
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self.board = Board(board_size)
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self._request_analysis(self.board.root)
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self.redraw(include_board=True)
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self.ready = True
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def _do_analyze_sgf(self, sgf):
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self._do_init(self.board_size)
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sgfmoves = re.findall(r"([BW])\[([a-z]{2})\]", sgf)
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moves = [Move(player=Move.PLAYERS.index(p.upper()), sgfcoords=(mv, self.board_size)) for p, mv in sgfmoves]
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for move in moves:
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self.play(move)
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# analysis thread
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def _analysis_read_thread(self):
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while True:
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while self.outstanding_analysis_queries:
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self._send_analysis_query(self.outstanding_analysis_queries.pop(0))
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line = self.kata.stdout.readline()
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if self.debug:
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print("KATA ANALYSIS RECEIVED:", line[:50])
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self.board.store_analysis(json.loads(line))
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self.update_evaluation()
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self.redraw(include_board=False)
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def _send_analysis_query(self, query):
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if self.kata:
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self.kata.stdin.write((json.dumps(query) + "\n").encode())
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self.kata.stdin.flush()
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else: # early on / root / etc
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self.outstanding_analysis_queries.append(copy.copy(query))
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def _request_analysis(self, move):
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move_id = move.id
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moves = self.board.moves
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fast = self.ai_fast.active
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query = {
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"id": str(move_id),
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"moves": [[m.bw_player(), m.gtp()] for m in moves],
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"rules": "japanese",
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"komi": self.komi,
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"boardXSize": self.board_size,
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"boardYSize": self.board_size,
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"analyzeTurns": [len(moves)],
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"includeOwnership": True,
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"maxVisits": self.visits[fast][1],
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}
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if self.debug:
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print(f"query for {move_id}")
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self._send_analysis_query(query)
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query.update({"id": f"PASS_{move_id}", "maxVisits": self.visits[fast][0], "includeOwnership": False})
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query["moves"] += [[move.bw_player(next_move=True), "pass"]]
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query["analyzeTurns"][0] += 1
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self._send_analysis_query(query)
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def output_sgf(self):
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return self.board.write_sgf(self.komi, self.train_settings)
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