• 运行make_datafiles的过程


    1。 第一个bug

    运行

    echo "Please tokenize this text." | java edu.stanford.nlp.process.PTBTokenizer 后显示。提示:

    - -bash: java: command not found。

    那我就觉得可能是java没安装。然后,我就去官网

    下载的是放到了/data 目录下,然后解压,

    解压完成后,vim ./bashrc,打开,然后输入如下的内容。

    保存退出,source ~/.bashrc 一下。

    这时候再 echo "Please tokenize this text." | java edu.stanford.nlp.process.PTBTokenizer就可以了。

    2.  第二个bug  UnicodeDecodeError: 'ascii' codec can't decode byte 0xe2 in position 858: ordinal not in range(128) 这个bug

    (jjenv_pytorch) root@032ba38f2b6e:/data/rl_abs_other/cnn-dailymail# ls
    README.md  make_datafiles.py  url_lists
    (jjenv_pytorch) root@032ba38f2b6e:/data/rl_abs_other/cnn-dailymail# 
    (jjenv_pytorch) root@032ba38f2b6e:/data/rl_abs_other/cnn-dailymail# python make_datafiles.py /data/rl_abs_other/data/cnn/stories /data/rl_abs_other/data/dailymail/stories
    Preparing to tokenize /data/rl_abs_other/data/cnn/stories to cnn_stories_tokenized...
    Making list of files to tokenize...
    Tokenizing 92579 files in /data/rl_abs_other/data/cnn/stories and saving in cnn_stories_tokenized...
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+20A9, decimal: 8361)
    Untokenizable: ? (U+F06E, decimal: 61550)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+F022, decimal: 61474)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    PTBTokenizer tokenized 80043350 tokens at 42671.94 tokens per second.
    Stanford CoreNLP Tokenizer has finished.
    Successfully finished tokenizing /data/rl_abs_other/data/cnn/stories to cnn_stories_tokenized.
    
    Preparing to tokenize /data/rl_abs_other/data/dailymail/stories to dm_stories_tokenized...
    Making list of files to tokenize...
    Tokenizing 219506 files in /data/rl_abs_other/data/dailymail/stories and saving in dm_stories_tokenized...
    Untokenizable: ? (U+FFFC, decimal: 65532)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202D, decimal: 8237)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+2012, decimal: 8210)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202D, decimal: 8237)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202B, decimal: 8235)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202D, decimal: 8237)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
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    Untokenizable: ? (U+FFFD, decimal: 65533)
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    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+F001, decimal: 61441)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+F001, decimal: 61441)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+70E, decimal: 1806)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202F, decimal: 8239)
    Untokenizable: ? (U+2010, decimal: 8208)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202C, decimal: 8236)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+206E, decimal: 8302)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+200D, decimal: 8205)
    Untokenizable: ? (U+202A, decimal: 8234)
    Untokenizable: ? (U+FFFD, decimal: 65533)
    Untokenizable: ? (U+202C, decimal: 8236)
    PTBTokenizer tokenized 203118231 tokens at 32507.27 tokens per second.
    Stanford CoreNLP Tokenizer has finished.
    Successfully finished tokenizing /data/rl_abs_other/data/dailymail/stories to dm_stories_tokenized.
    
    Making bin file for URLs listed in url_lists/all_test.txt...
    Writing story 0 of 11490; 0.00 percent done
    Traceback (most recent call last):
      File "make_datafiles.py", line 253, in <module>
        write_to_tar(all_test_urls, os.path.join(finished_files_dir, "test.tar"))
      File "make_datafiles.py", line 182, in write_to_tar
        article_sents, abstract_sents = get_art_abs(story_file)
      File "make_datafiles.py", line 106, in get_art_abs
        lines = read_story_file(story_file)
      File "make_datafiles.py", line 78, in read_story_file
        lines = f.read().split('
    
    ')
      File "/root/anaconda3/envs/jjenv_pytorch/lib/python3.6/encodings/ascii.py", line 26, in decode
        return codecs.ascii_decode(input, self.errors)[0]
    UnicodeDecodeError: 'ascii' codec can't decode byte 0xe2 in position 858: ordinal not in range(128)
    (jjenv_pytorch) root@032ba38f2b6e:/data/rl_abs_other/cnn-dailymail# 

    然后我以为是编码问题,就去 make_datafiles.py 的文件开头加上 # coding: utf-8 ,但是没有解决问题,后来参考了一篇帖子https://blog.csdn.net/qq_36847641/article/details/78414718

    所以就把我自己的代码,做如下更改,就可以了。

    但是,

     然后我就继续运行make_datafiles.py文件,然后一路都顺利直到完成。

    (jjenv_pytorch) root@032ba38f2b6e:/data/rl_abs_other/cnn-dailymail# python make_datafiles.py /data/rl/rl_abs_other/data/dailymail/stories
    Making bin file for URLs listed in url_lists/all_test.txt...
    Writing story 0 of 11490; 0.00 percent done
    Writing story 1000 of 11490; 8.70 percent done
    Writing story 2000 of 11490; 17.41 percent done
    Writing story 3000 of 11490; 26.11 percent done
    Writing story 4000 of 11490; 34.81 percent done
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    Writing story 11000 of 11490; 95.74 percent done
    Finished writing file finished_files/test.tar
    
    Making bin file for URLs listed in url_lists/all_val.txt...
    Writing story 0 of 13368; 0.00 percent done
    Writing story 1000 of 13368; 7.48 percent done
    Writing story 2000 of 13368; 14.96 percent done
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    Finished writing file finished_files/val.tar
    
    Making bin file for URLs listed in url_lists/all_train.txt...
    Writing story 0 of 287227; 0.00 percent done
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    Writing story 225000 of 287227; 78.34 percent done
    Writing story 226000 of 287227; 78.68 percent done
    Writing story 227000 of 287227; 79.03 percent done
    Writing story 228000 of 287227; 79.38 percent done
    Writing story 229000 of 287227; 79.73 percent done
    Writing story 230000 of 287227; 80.08 percent done
    Writing story 231000 of 287227; 80.42 percent done
    Writing story 232000 of 287227; 80.77 percent done
    Writing story 233000 of 287227; 81.12 percent done
    Writing story 234000 of 287227; 81.47 percent done
    Writing story 235000 of 287227; 81.82 percent done
    Writing story 236000 of 287227; 82.16 percent done
    Writing story 237000 of 287227; 82.51 percent done
    Writing story 238000 of 287227; 82.86 percent done
    Writing story 239000 of 287227; 83.21 percent done
    Writing story 240000 of 287227; 83.56 percent done
    Writing story 241000 of 287227; 83.91 percent done
    Writing story 242000 of 287227; 84.25 percent done
    Writing story 243000 of 287227; 84.60 percent done
    Writing story 244000 of 287227; 84.95 percent done
    Writing story 245000 of 287227; 85.30 percent done
    Writing story 246000 of 287227; 85.65 percent done
    Writing story 247000 of 287227; 85.99 percent done
    Writing story 248000 of 287227; 86.34 percent done
    Writing story 249000 of 287227; 86.69 percent done
    Writing story 250000 of 287227; 87.04 percent done
    Writing story 251000 of 287227; 87.39 percent done
    Writing story 252000 of 287227; 87.74 percent done
    Writing story 253000 of 287227; 88.08 percent done
    Writing story 254000 of 287227; 88.43 percent done
    Writing story 255000 of 287227; 88.78 percent done
    Writing story 256000 of 287227; 89.13 percent done
    Writing story 257000 of 287227; 89.48 percent done
    Writing story 258000 of 287227; 89.82 percent done
    Writing story 259000 of 287227; 90.17 percent done
    Writing story 260000 of 287227; 90.52 percent done
    Writing story 261000 of 287227; 90.87 percent done
    Writing story 262000 of 287227; 91.22 percent done
    Writing story 263000 of 287227; 91.57 percent done
    Writing story 264000 of 287227; 91.91 percent done
    Writing story 265000 of 287227; 92.26 percent done
    Writing story 266000 of 287227; 92.61 percent done
    Writing story 267000 of 287227; 92.96 percent done
    Writing story 268000 of 287227; 93.31 percent done
    Writing story 269000 of 287227; 93.65 percent done
    Writing story 270000 of 287227; 94.00 percent done
    Writing story 271000 of 287227; 94.35 percent done
    Writing story 272000 of 287227; 94.70 percent done
    Writing story 273000 of 287227; 95.05 percent done
    Writing story 274000 of 287227; 95.39 percent done
    Writing story 275000 of 287227; 95.74 percent done
    Writing story 276000 of 287227; 96.09 percent done
    Writing story 277000 of 287227; 96.44 percent done
    Writing story 278000 of 287227; 96.79 percent done
    Writing story 279000 of 287227; 97.14 percent done
    Writing story 280000 of 287227; 97.48 percent done
    Writing story 281000 of 287227; 97.83 percent done
    Writing story 282000 of 287227; 98.18 percent done
    Writing story 283000 of 287227; 98.53 percent done
    Writing story 284000 of 287227; 98.88 percent done
    Writing story 285000 of 287227; 99.22 percent done
    Writing story 286000 of 287227; 99.57 percent done
    Writing story 287000 of 287227; 99.92 percent done
    Finished writing file finished_files/train.tar
    
    Writing vocab file...
    Finished writing vocab file
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  • 原文地址:https://www.cnblogs.com/www-caiyin-com/p/10187985.html
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