# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # The MIT License (MIT) # Copyright (c) 2016 The-Orizon # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # The detokenize function is based on : https://github.com/The-Orizon/nlputils/blob/master/detokenizer.py import re from typing import List import jieba import opencc from pangu import spacing class ChineseProcessor: """ Tokenizer, Detokenizer and Normalizer utilities for Chinese. """ def __init__(self): self.normalizer = opencc.OpenCC('t2s.json') def normalize(self, text: str) -> str: return self.normalizer.convert(text) def detokenize(self, text: List[str]) -> str: RE_WS_IN_FW = re.compile( r'([\u2018\u2019\u201c\u201d\u2e80-\u312f\u3200-\u32ff\u3400-\u4dbf\u4e00-\u9fff\uf900-\ufaff\uff00-\uffef])\s+(?=[\u2018\u2019\u201c\u201d\u2e80-\u312f\u3200-\u32ff\u3400-\u4dbf\u4e00-\u9fff\uf900-\ufaff\uff00-\uffef])' ) detokenize = lambda s: spacing(RE_WS_IN_FW.sub(r'\1', s)).strip() return detokenize(' '.join(text)) def tokenize(self, text: str) -> str: text = jieba.cut(text) return ' '.join(text)