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| from pathlib import Path | |
| from typing import Iterable | |
| from typing import List | |
| from typing import Union | |
| import warnings | |
| import re | |
| from funasr_detach.tokenizer.abs_tokenizer import BaseTokenizer | |
| from funasr_detach.register import tables | |
| class CharTokenizer(BaseTokenizer): | |
| def __init__( | |
| self, | |
| non_linguistic_symbols: Union[Path, str, Iterable[str]] = None, | |
| space_symbol: str = "<space>", | |
| remove_non_linguistic_symbols: bool = False, | |
| split_with_space: bool = False, | |
| seg_dict: str = None, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) | |
| self.space_symbol = space_symbol | |
| if non_linguistic_symbols is None: | |
| self.non_linguistic_symbols = set() | |
| elif isinstance(non_linguistic_symbols, (Path, str)): | |
| non_linguistic_symbols = Path(non_linguistic_symbols) | |
| try: | |
| with non_linguistic_symbols.open("r", encoding="utf-8") as f: | |
| self.non_linguistic_symbols = set(line.rstrip() for line in f) | |
| except FileNotFoundError: | |
| warnings.warn(f"{non_linguistic_symbols} doesn't exist.") | |
| self.non_linguistic_symbols = set() | |
| else: | |
| self.non_linguistic_symbols = set(non_linguistic_symbols) | |
| self.remove_non_linguistic_symbols = remove_non_linguistic_symbols | |
| self.split_with_space = split_with_space | |
| self.seg_dict = None | |
| if seg_dict is not None: | |
| self.seg_dict = load_seg_dict(seg_dict) | |
| def __repr__(self): | |
| return ( | |
| f"{self.__class__.__name__}(" | |
| f'space_symbol="{self.space_symbol}"' | |
| f'non_linguistic_symbols="{self.non_linguistic_symbols}"' | |
| f")" | |
| ) | |
| def text2tokens(self, line: Union[str, list]) -> List[str]: | |
| # if self.split_with_space: | |
| if self.seg_dict is not None: | |
| tokens = line.strip().split(" ") | |
| tokens = seg_tokenize(tokens, self.seg_dict) | |
| else: | |
| tokens = [] | |
| while len(line) != 0: | |
| for w in self.non_linguistic_symbols: | |
| if line.startswith(w): | |
| if not self.remove_non_linguistic_symbols: | |
| tokens.append(line[: len(w)]) | |
| line = line[len(w) :] | |
| break | |
| else: | |
| t = line[0] | |
| if t == " ": | |
| # t = "<space>" | |
| line = line[1:] | |
| continue | |
| tokens.append(t) | |
| line = line[1:] | |
| return tokens | |
| def tokens2text(self, tokens: Iterable[str]) -> str: | |
| tokens = [t if t != self.space_symbol else " " for t in tokens] | |
| return "".join(tokens) | |
| def load_seg_dict(seg_dict_file): | |
| seg_dict = {} | |
| assert isinstance(seg_dict_file, str) | |
| with open(seg_dict_file, "r", encoding="utf8") as f: | |
| lines = f.readlines() | |
| for line in lines: | |
| s = line.strip().split() | |
| key = s[0] | |
| value = s[1:] | |
| seg_dict[key] = " ".join(value) | |
| return seg_dict | |
| def seg_tokenize(txt, seg_dict): | |
| pattern = re.compile(r"^[\u4E00-\u9FA50-9]+$") | |
| out_txt = "" | |
| for word in txt: | |
| word = word.lower() | |
| if word in seg_dict: | |
| out_txt += seg_dict[word] + " " | |
| else: | |
| if pattern.match(word): | |
| for char in word: | |
| if char in seg_dict: | |
| out_txt += seg_dict[char] + " " | |
| else: | |
| out_txt += "<unk>" + " " | |
| else: | |
| out_txt += "<unk>" + " " | |
| return out_txt.strip().split() | |