# -*- coding: utf-8 -*-
# Copyright (C) 2016-2023 PyThaiNLP Project
#
# 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.
from pythainlp.augment.word2vec.core import Word2VecAug
from pythainlp.corpus import get_corpus_path
from pythainlp.tokenize import THAI2FIT_TOKENIZER
from typing import List, Tuple
[docs]class Thai2fitAug:
"""
Text Augment using word2vec from Thai2Fit
Thai2Fit:
`github.com/cstorm125/thai2fit <https://github.com/cstorm125/thai2fit>`_
"""
[docs] def __init__(self):
self.thai2fit_wv = get_corpus_path("thai2fit_wv")
self.load_w2v()
[docs] def tokenizer(self, text: str) -> List[str]:
"""
:param str text: thai text
:rtype: List[str]
"""
return THAI2FIT_TOKENIZER.word_tokenize(text)
[docs] def load_w2v(self):
"""
Load thai2fit word2vec model
"""
self.aug = Word2VecAug(self.thai2fit_wv, self.tokenizer, type="binary")
[docs] 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 sentence
:param float p: Probability of word
:return: list of text augment
: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)