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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 word_tokenize class LTW2VAug: """ Text Augment using word2vec from LTW2V LTW2V: `github.com/PyThaiNLP/large-thaiword2vec <https://github.com/PyThaiNLP/large-thaiword2vec>`_ """ def __init__(self): self.ltw2v_wv = get_corpus_path("ltw2v") self.load_w2v() def tokenizer(self, text: str) -> List[str]: """ :param str text: Thai text :rtype: List[str] """ return word_tokenize(text, engine="newmm") def load_w2v(self): # insert substitute """ Load LTW2V's word2vec model """ self.aug = Word2VecAug(self.ltw2v_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 LTW2VAug aug = LTW2VAug() aug.augment("ผมเรียน", n_sent=2, p=0.5) # output: [('เขา', 'เรียนหนังสือ'), ('เขา', 'สมัครเรียน')] """ return self.aug.augment(sentence, n_sent, p)
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