| """ |
| Custom Chess Tokenizer for the Chess Challenge. |
| |
| This tokenizer treats each move as a sequence of structured tokens derived from the |
| extended UCI notation from the Lichess dataset (e.g., WPe2e4, BNg8f6). |
| |
| The dataset format uses: |
| - W/B prefix for White/Black |
| - Piece letter: P=Pawn, N=Knight, B=Bishop, R=Rook, Q=Queen, K=King |
| - Source and destination squares (e.g., e2e4) |
| - Special suffixes: (x)=capture, (+)=check, (+*)=checkmate, (o)/(O)=castling |
| """ |
|
|
| from __future__ import annotations |
|
|
| import json |
| import os |
| import re |
| from typing import Dict, List, Optional, Sequence, Union |
|
|
| from transformers import PreTrainedTokenizer |
|
|
|
|
| _MOVE_RE = re.compile( |
| r"^(?P<side>[WB])" |
| r"(?P<piece>[PNBRQK])" |
| r"(?P<src>[a-h][1-8])" |
| r"(?P<dst>[a-h][1-8])" |
| r"(?P<rest>.*)$" |
| ) |
|
|
|
|
| class ChessTokenizer(PreTrainedTokenizer): |
| """ |
| A structured tokenizer for chess moves. |
| |
| Each move is decomposed into: |
| SIDE_(W/B), PIECE_(P/N/B/R/Q/K), SQ_<src>, SQ_<dst>, |
| and optional flags: CAPTURE, CHECK, MATE, CASTLE, PROMO_(Q/R/B/N). |
| |
| This avoids UNK explosions when using a move-as-token vocabulary. |
| """ |
|
|
| model_input_names = ["input_ids", "attention_mask"] |
| vocab_files_names = {"vocab_file": "vocab.json"} |
|
|
| |
| PAD_TOKEN = "[PAD]" |
| BOS_TOKEN = "[BOS]" |
| EOS_TOKEN = "[EOS]" |
| UNK_TOKEN = "[UNK]" |
|
|
| |
| SIDE_W = "SIDE_W" |
| SIDE_B = "SIDE_B" |
|
|
| PIECES = ["P", "N", "B", "R", "Q", "K"] |
|
|
| PROMO_PREFIX = "PROMO_" |
| CAPTURE = "CAPTURE" |
| CHECK = "CHECK" |
| MATE = "MATE" |
| CASTLE = "CASTLE" |
|
|
| def __init__( |
| self, |
| vocab_file: Optional[str] = None, |
| vocab: Optional[Dict[str, int]] = None, |
| **kwargs, |
| ): |
| kwargs.pop("pad_token", None) |
| kwargs.pop("bos_token", None) |
| kwargs.pop("eos_token", None) |
| kwargs.pop("unk_token", None) |
|
|
| self._pad_token = self.PAD_TOKEN |
| self._bos_token = self.BOS_TOKEN |
| self._eos_token = self.EOS_TOKEN |
| self._unk_token = self.UNK_TOKEN |
|
|
| if vocab is not None: |
| self._vocab = vocab |
| elif vocab_file is not None and os.path.exists(vocab_file): |
| with open(vocab_file, "r", encoding="utf-8") as f: |
| self._vocab = json.load(f) |
| else: |
| self._vocab = self._build_fixed_vocab() |
|
|
| self._ids_to_tokens = {v: k for k, v in self._vocab.items()} |
|
|
| super().__init__( |
| pad_token=self._pad_token, |
| bos_token=self._bos_token, |
| eos_token=self._eos_token, |
| unk_token=self._unk_token, |
| **kwargs, |
| ) |
|
|
| def _build_fixed_vocab(self) -> Dict[str, int]: |
| special = [self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN] |
| sides = [self.SIDE_W, self.SIDE_B] |
| pieces = [f"PIECE_{p}" for p in self.PIECES] |
| squares = [f"SQ_{file}{rank}" for file in "abcdefgh" for rank in "12345678"] |
| promos = [f"{self.PROMO_PREFIX}{p}" for p in ["Q", "R", "B", "N"]] |
| flags = [self.CAPTURE, self.CHECK, self.MATE, self.CASTLE] |
| tokens = special + sides + pieces + squares + promos + flags |
| return {tok: i for i, tok in enumerate(tokens)} |
|
|
| @classmethod |
| def build_vocab_from_dataset(cls, *args, **kwargs) -> "ChessTokenizer": |
| """ |
| Kept for API compatibility with the template training script. |
| This tokenizer uses a fixed vocabulary (no dataset-dependent pruning). |
| """ |
| return cls() |
|
|
| @classmethod |
| def build_vocab_from_iterator(cls, *args, **kwargs) -> "ChessTokenizer": |
| """ |
| Kept for API compatibility. This tokenizer uses a fixed vocabulary. |
| """ |
| return cls() |
|
|
| @property |
| def vocab_size(self) -> int: |
| return len(self._vocab) |
|
|
| def get_vocab(self) -> Dict[str, int]: |
| return dict(self._vocab) |
|
|
| def _tokenize(self, text: str) -> List[str]: |
| tokens: List[str] = [] |
| moves = text.strip().split() |
| for mv in moves: |
| tokens.extend(self._tokenize_move(mv)) |
| return tokens |
|
|
| def _tokenize_move(self, move: str) -> List[str]: |
| m = _MOVE_RE.match(move) |
| if not m: |
| return [self.UNK_TOKEN] |
|
|
| side = m.group("side") |
| piece = m.group("piece") |
| src = m.group("src") |
| dst = m.group("dst") |
| rest = m.group("rest") or "" |
|
|
| out: List[str] = [] |
| out.append(self.SIDE_W if side == "W" else self.SIDE_B) |
| out.append(f"PIECE_{piece}") |
| out.append(f"SQ_{src}") |
| out.append(f"SQ_{dst}") |
|
|
| promo = self._parse_promotion(rest) |
| if promo is not None: |
| out.append(f"{self.PROMO_PREFIX}{promo}") |
|
|
| if "(x)" in rest or "x" in rest: |
| out.append(self.CAPTURE) |
|
|
| if "(+*)" in rest or "++" in rest or "#" in rest: |
| out.append(self.MATE) |
| elif "(+)" in rest or "+" in rest: |
| out.append(self.CHECK) |
|
|
| if "(o)" in rest or "(O)" in rest or "O-O" in rest: |
| out.append(self.CASTLE) |
|
|
| return out |
|
|
| def _parse_promotion(self, rest: str) -> Optional[str]: |
| m = re.search(r"=([QRBNqrbn])", rest) |
| if m: |
| return m.group(1).upper() |
| return None |
|
|
| def _convert_token_to_id(self, token: str) -> int: |
| return self._vocab.get(token, self._vocab[self.UNK_TOKEN]) |
|
|
| def _convert_id_to_token(self, index: int) -> str: |
| return self._ids_to_tokens.get(index, self.UNK_TOKEN) |
|
|
| def convert_tokens_to_string(self, tokens: List[str]) -> str: |
| special = {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN} |
| out: List[str] = [] |
| for t in tokens: |
| if t in special: |
| continue |
| out.append(t) |
| return " ".join(out) |
|
|
| def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> tuple: |
| if not os.path.isdir(save_directory): |
| os.makedirs(save_directory, exist_ok=True) |
|
|
| vocab_file = os.path.join( |
| save_directory, |
| (filename_prefix + "-" if filename_prefix else "") + "vocab.json", |
| ) |
| with open(vocab_file, "w", encoding="utf-8") as f: |
| json.dump(self._vocab, f, ensure_ascii=False, indent=2) |
|
|
| return (vocab_file,) |
|
|
| def decode(self, token_ids: Union[int, Sequence[int]], skip_special_tokens: bool = False, **kwargs) -> str: |
| if isinstance(token_ids, int): |
| ids = [token_ids] |
| elif "torch" in str(type(token_ids)): |
| ids = token_ids.detach().cpu().flatten().tolist() |
| else: |
| ids = list(token_ids) |
|
|
| toks = [self._convert_id_to_token(i) for i in ids] |
| if skip_special_tokens: |
| special = {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN} |
| toks = [t for t in toks if t not in special] |
| return self.convert_tokens_to_string(toks) |
|
|
