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""" |
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Custom Chess Tokenizer for the Chess Challenge. |
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This tokenizer treats each move as a single token using the extended UCI notation |
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from the Lichess dataset (e.g., WPe2e4, BNg8f6). |
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The dataset format uses: |
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- W/B prefix for White/Black |
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- Piece letter: P=Pawn, N=Knight, B=Bishop, R=Rook, Q=Queen, K=King |
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- Source and destination squares (e.g., e2e4) |
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- Special suffixes: (x)=capture, (+)=check, (+*)=checkmate, (o)/(O)=castling |
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""" |
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from __future__ import annotations |
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import json |
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import os |
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from pathlib import Path |
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from typing import Dict, List, Optional |
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import re |
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from transformers import PreTrainedTokenizer |
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class ChessTokenizer(PreTrainedTokenizer): |
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model_input_names = ["input_ids", "attention_mask"] |
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PAD_TOKEN = "[PAD]" |
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BOS_TOKEN = "[BOS]" |
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EOS_TOKEN = "[EOS]" |
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UNK_TOKEN = "[UNK]" |
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def __init__( |
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self, |
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vocab_file: Optional[str] = None, |
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vocab: Optional[Dict[str, int]] = None, |
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**kwargs, |
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): |
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self._pad_token = self.PAD_TOKEN |
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self._bos_token = self.BOS_TOKEN |
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self._eos_token = self.EOS_TOKEN |
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self._unk_token = self.UNK_TOKEN |
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kwargs.pop("pad_token", None) |
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kwargs.pop("bos_token", None) |
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kwargs.pop("eos_token", None) |
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kwargs.pop("unk_token", None) |
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self.token_pattern = re.compile(r'[a-h][1-8]|[qrbn]') |
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if vocab is not None: |
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self._vocab = vocab |
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elif vocab_file is not None and os.path.exists(vocab_file): |
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with open(vocab_file, "r", encoding="utf-8") as f: |
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self._vocab = json.load(f) |
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else: |
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self._vocab = self._create_default_vocab() |
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self._ids_to_tokens = {v: k for k, v in self._vocab.items()} |
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super().__init__( |
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pad_token=self._pad_token, |
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bos_token=self._bos_token, |
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eos_token=self._eos_token, |
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unk_token=self._unk_token, |
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**kwargs, |
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) |
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def _create_default_vocab(self) -> Dict[str, int]: |
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special_tokens = [self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN] |
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vocab = {token: idx for idx, token in enumerate(special_tokens)} |
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idx = len(vocab) |
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for f in 'abcdefgh': |
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for r in '12345678': |
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vocab[f"{f}{r}"] = idx |
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idx += 1 |
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for p in ['q', 'r', 'b', 'n']: |
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vocab[p] = idx |
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idx += 1 |
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return vocab |
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def _tokenize(self, text: str) -> List[str]: |
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""" |
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Tokenizes text by first normalizing specific chess patterns |
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and then extracting squares/promotions. |
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""" |
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text = (text.replace("(Q)", "q") |
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.replace("(R)", "r") |
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.replace("(B)", "b") |
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.replace("(N)", "n")) |
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return self.token_pattern.findall(text) |
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def _convert_token_to_id(self, token: str) -> int: |
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"""Convert a token to its ID.""" |
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return self._vocab.get(token, self._vocab.get(self.UNK_TOKEN, 0)) |
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def _convert_id_to_token(self, index: int) -> str: |
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"""Convert an ID to its token.""" |
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return self._ids_to_tokens.get(index, self.UNK_TOKEN) |
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def convert_tokens_to_string(self, tokens: List[str]) -> str: |
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"""Reconstructs standard UCI string (e.g. "e2e4 a7a8q")""" |
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special = {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN} |
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clean_tokens = [t for t in tokens if t not in special] |
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output = [] |
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for token in clean_tokens: |
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if token in ['q', 'r', 'b', 'n'] and output: |
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output[-1] += token |
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elif output and len(output[-1]) == 2 and output[-1][0] in 'abcdefgh': |
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output[-1] += token |
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else: |
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output.append(token) |
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return " ".join(output) |
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def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> tuple: |
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if not os.path.isdir(save_directory): |
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os.makedirs(save_directory, exist_ok=True) |
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vocab_file = os.path.join( |
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save_directory, (filename_prefix + "-" if filename_prefix else "") + "vocab.json" |
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) |
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with open(vocab_file, "w", encoding="utf-8") as f: |
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json.dump(self._vocab, f, ensure_ascii=False, indent=2) |
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return (vocab_file,) |
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@classmethod |
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def build_vocab_from_iterator(cls, iterator, min_frequency=1): |
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return cls() |
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@classmethod |
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def build_vocab_from_dataset(cls, **kwargs): |
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return cls() |
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@property |
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def vocab_size(self) -> int: |
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return len(self._vocab) |
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def get_vocab(self) -> Dict[str, int]: |
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return dict(self._vocab) |
