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# -*- coding: utf-8 -*- # SPDX-FileCopyrightText: 2016-2024 PyThaiNLP Project # SPDX-License-Identifier: Apache-2.0 from typing import List, Tuple from pythainlp.augment.word2vec.core import Word2VecAug from pythainlp.corpus import get_corpus_path from pythainlp.tokenize import THAI2FIT_TOKENIZER class Thai2fitAug: """ Text Augment using word2vec from Thai2Fit Thai2Fit: `github.com/cstorm125/thai2fit <https://github.com/cstorm125/thai2fit>`_ """ def __init__(self): self.thai2fit_wv = get_corpus_path("thai2fit_wv") self.load_w2v() def tokenizer(self, text: str) -> List[str]: """ :param str text: Thai text :rtype: List[str] """ return THAI2FIT_TOKENIZER.word_tokenize(text) def load_w2v(self): """ Load Thai2Fit's word2vec model """ self.aug = Word2VecAug(self.thai2fit_wv, self.tokenizer, type="binary") def augment( self, sentence: str, n_sent: int = 1, p: float = 0.7 ) -> List[Tuple[str]]: """ Text Augment using word2vec from Thai2Fit :param str sentence: Thai sentence :param int n_sent: number of sentence :param float p: probability of word :return: list of text augmented :rtype: List[Tuple[str]] :Example: :: from pythainlp.augment.word2vec import Thai2fitAug aug = Thai2fitAug() aug.augment("ผมเรียน", n_sent=2, p=0.5) # output: [('พวกเรา', 'เรียน'), ('ฉัน', 'เรียน')] """ return self.aug.augment(sentence, n_sent, p)
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