55 lines
2.1 KiB
Python
55 lines
2.1 KiB
Python
# -*- coding: UTF-8 -*-
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# !/usr/bin/python
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# @time :2019/4/4 10:00
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# @author :Mo
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# @function :
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from __future__ import print_function
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from utils.text_tools import txtRead, txtWrite
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from gensim.models.word2vec import LineSentence
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from gensim.models import Word2Vec
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import multiprocessing
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import logging
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import sys
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import os
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def train_word2vec_by_word():
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logging.basicConfig(format='%(asctime)s: %(levelname)s: %(message)s')
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logging.root.setLevel(level=logging.INFO)
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logging.info("running")
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inp = "Y:/BaiduNetdiskDownload/cut_zhwiki_wiki_parse/cut_zhwiki_wiki_parse.txt"
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outp1 = "w2v_model_wiki.model"
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outp2 = "w2v_model_wiki_word.vec"
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model = Word2Vec(LineSentence(inp), size=300, window=5, min_count=5, workers=multiprocessing.cpu_count())
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model.save(outp1)
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model.wv.save_word2vec_format(outp2, binary=False)
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def train_word2vec_by_char():
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logging.basicConfig(format='%(asctime)s: %(levelname)s: %(message)s')
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logging.root.setLevel(level=logging.INFO)
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logging.info("running")
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inp = "Y:/BaiduNetdiskDownload/cut_zhwiki_wiki_parse/cut_zhwiki_wiki_parse_char.txt"
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outp1 = "w2v_model_wiki.model"
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outp2 = "w2v_model_wiki_char.vec"
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model = Word2Vec(LineSentence(inp), size=300, window=5, min_count=5, workers=multiprocessing.cpu_count())
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model.save(outp1)
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model.wv.save_word2vec_format(outp2, binary=False)
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if __name__ == '__main__':
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train_word2vec_by_word()
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# train_word2vec_by_char()
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# inp = "Y:/BaiduNetdiskDownload/cut_zhwiki_wiki_parse/cut_zhwiki_wiki_parse.txt"
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# sentences_char = []
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# sentences = txtRead(inp)
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# for sentences_one in sentences:
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# sentences_one_replace = sentences_one.strip().replace(" ", "")
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# sentences_one_replace_all = []
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# for sentences_one_replace_one in sentences_one_replace:
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# sentences_one_replace_all.append(sentences_one_replace_one)
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# sentences_char.append(" ".join(sentences_one_replace_all) + "\n")
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# txtWrite(sentences_char, "Y:/BaiduNetdiskDownload/cut_zhwiki_wiki_parse/cut_zhwiki_wiki_parse_char.txt")
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# gg = 0 |