File size: 4,621 Bytes
84624c3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 | # src/tokenizer.py
from __future__ import annotations
import json
import os
import re
from typing import Dict, List, Optional
from transformers import PreTrainedTokenizer
class ChessTokenizer(PreTrainedTokenizer):
"""
Ultra-simple square tokenizer.
Vocab (68 tokens):
- 4 specials: [PAD] [BOS] [EOS] [UNK]
- 64 squares: a1..h8
Tokenization:
- Any text containing two squares -> emits those squares as tokens
- Accepts:
"WPe2e4(x+)" , "e2e4" , "e2 e4" -> ["e2","e4"]
- For longer histories, extracts ALL squares in order.
Decoding:
- Joins square tokens with spaces => evaluator regex sees them easily.
"""
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]"
_SQUARE_PATTERN = r"[a-h][1-8]"
_SQUARE_RE = re.compile(_SQUARE_PATTERN)
def __init__(
self,
vocab_file: Optional[str] = None,
vocab: Optional[Dict[str, int]] = None,
**kwargs,
):
self._pad_token = self.PAD_TOKEN
self._bos_token = self.BOS_TOKEN
self._eos_token = self.EOS_TOKEN
self._unk_token = self.UNK_TOKEN
kwargs.pop("pad_token", None)
kwargs.pop("bos_token", None)
kwargs.pop("eos_token", None)
kwargs.pop("unk_token", None)
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._create_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,
)
@classmethod
def _create_fixed_vocab(cls) -> Dict[str, int]:
specials = [cls.PAD_TOKEN, cls.BOS_TOKEN, cls.EOS_TOKEN, cls.UNK_TOKEN]
files = "abcdefgh"
ranks = "12345678"
squares = [f + r for r in ranks for f in files] # a1..h8
tokens = specials + squares
return {tok: i for i, tok in enumerate(tokens)}
@classmethod
def build_vocab_from_iterator(cls, iterator, **kwargs) -> "ChessTokenizer":
return cls(vocab=cls._create_fixed_vocab())
@classmethod
def build_vocab_from_dataset(cls, *args, **kwargs) -> "ChessTokenizer":
return cls(vocab=cls._create_fixed_vocab())
@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]:
text = text.strip()
if not text:
return []
# Keep BOS/EOS tokens if they appear as standalone strings
# (rare, but safe)
if text in {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN}:
return [text]
# Extract all squares in order from the text
squares = self._SQUARE_RE.findall(text)
if not squares:
# if nothing parsable, return UNK token
return [self.UNK_TOKEN]
# Filter to vocab squares only (should always be true)
out = [sq for sq in squares if sq in self._vocab]
return out if out else [self.UNK_TOKEN]
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:
# Drop special tokens; join squares with spaces so evaluator can parse.
special = {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN}
toks = [t for t in tokens if t not in special]
return " ".join(toks)
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,)
|