83 lines
4.0 KiB
Python
83 lines
4.0 KiB
Python
# -*- coding: UTF-8 -*-
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# !/usr/bin/python
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# @time :2019/4/3 11:23
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# @author :Mo
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# @function :path
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import pathlib
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import sys
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import os
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# base dir
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projectdir = str(pathlib.Path(os.path.abspath(__file__)).parent.parent)
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sys.path.append(projectdir)
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print(projectdir)
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# stop_words_path
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stop_words_path = projectdir + '/Data/common_words/stopwords.txt'
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# corpus
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chicken_and_gossip_path = projectdir + '/Data/corpus/chicken_and_gossip.txt'
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# word2vec
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w2v_model_merge_short_path = projectdir + "/Data/chinese_vector/w2v_model_merge_short.vec"
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# tf_idf
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td_idf_cut_path = projectdir + '/Data/tf_idf/td_idf_cut.csv'
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td_idf_cut_pinyin = projectdir + '/Data/tf_idf/td_idf_cut_pinyin.csv'
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td_idf_path_pinyin = projectdir + '/Data/tf_idf/td_idf_cut_pinyin_dictionary_model.pkl'
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td_idf_path = projectdir + '/Data/tf_idf/td_idf_cut_dictionary_model.pkl'
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# word, 句向量
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w2v_model_wiki_word_path = projectdir + '/Data/chinese_vector/w2v_model_wiki_word.vec'
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matrix_ques_part_path = projectdir + '/Data/sentence_vec_encode_word/1.txt'
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# char, 句向量
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w2v_model_char_path = projectdir + '/Data/chinese_vector/w2v_model_wiki_char.vec'
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matrix_ques_part_path_char = projectdir + '/Data/sentence_vec_encode_char/1.txt'
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# word2vec select
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word2_vec_path = w2v_model_wiki_word_path if os.path.exists(w2v_model_wiki_word_path) else w2v_model_merge_short_path
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# stanford_corenlp_full_path，需要自己下载配置stanford-corenlp-full-2018-10-05
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stanford_corenlp_full_path = "Y:/segment/stanford-corenlp-full-2018-10-05"
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# corpus webbank sim data char
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train_data_web_char_dir = projectdir + '/AugmentText/augment_seq2seq/data_mid/char/'
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train_data_web_ws_anti=projectdir + '/AugmentText/augment_seq2seq/data_mid/char/train_data_web_ws_anti.pkl'
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train_data_web_xy_anti=projectdir + '/AugmentText/augment_seq2seq/data_mid/char/train_data_web_xy_anti.pkl'
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model_ckpt_web_anti=projectdir + '/AugmentText/augment_seq2seq/model_seq2seq_tp/seq2seq_char_webank/model_ckpt_char_webank.ckp'
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path_params=projectdir + '/conf/params.json'
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path_webank_sim=projectdir + '/Data/corpus/sim_webank.csv'
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# corpus webbank sim data word
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train_data_web_word_dir = projectdir + '/AugmentText/augment_seq2seq/data_mid/word/'
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train_data_web_emb_anti=projectdir + '/AugmentText/augment_seq2seq/data_mid/word/train_data_web_emb_anti.pkl'
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train_data_web_xyw_anti=projectdir + '/AugmentText/augment_seq2seq/data_mid/word/train_data_web_ws_anti.pkl'
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model_ckpt_web_anti_word=projectdir + '/AugmentText/augment_seq2seq/model_seq2seq_tp/seq2seq_word_webank/train_data_web_ws_anti.pkl'
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# chatbot data char
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chatbot_data_cg_char_dir = projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/char/'
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chatbot_data_cg_ws_anti=projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/char/train_data_web_ws_anti.pkl'
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chatbot_data_cg_xy_anti=projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/char/train_data_web_xy_anti.pkl'
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model_ckpt_cg_anti=projectdir + '/ChatBot/chatbot_generate/seq2seq/model_seq2seq_tp/seq2seq_char_cg/model_ckpt_char_cg.ckp'
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# chatbot data word
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chatbot_data_cg_word_dir = projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/word/'
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chatbot_data_cg_xyw_anti_word=projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/word/train_data_cg_word_xyw.pkl'
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chatbot_data_cg_emb_anti_word=projectdir + '/ChatBot/chatbot_generate/seq2seq/data_mid/word/train_data_cg_word_emb.pkl'
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model_ckpt_cg_anti_word=projectdir + '/ChatBot/chatbot_generate/seq2seq/model_seq2seq_tp/seq2seq_word_cg/model_ckpt_word_cg.ckp'
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# webank corpus for classify train-dev-test
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path_webank_train=projectdir + '/Data/corpus/webank/train.csv'
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path_webank_dev=projectdir + '/Data/corpus/webank/dev.csv'
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path_webank_test=projectdir + '/Data/corpus/webank/test.csv'
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# ner chinese_people_daily
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path_ner_people_train = projectdir + '/Data/corpus/ner/people_daily/people.train'
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path_ner_people_dev = projectdir + '/Data/corpus/ner/people_daily/people.dev'
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path_ner_people_test = projectdir + '/Data/corpus/ner/people_daily/people.test'
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