pprett / nut Goto Github PK

Hi! There have some indent miss in the code file, when I download the entire project, like nut/bow.py L39:

    for fname in bowfnames:
        with open(fname) as f:
        for i, line in enumerate(f):
        if maxlines != -1 and i >= maxlines:
            break
        label, tokens = parse_bow(line)
        for token,freq in tokens:
            fd[token] += 1

other files have the same error:
bow.py: L63
pivotselection: L80, L102, L117, L136
util.py: L54, L71, L74

Hi! I have get the same result when training serially. However, I got ImportError when parallel training, the error as follow:

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "D:\Python27\lib\multiprocessing\forking.py", line 380, in main
    prepare(preparation_data)
  File "D:\Python27\lib\multiprocessing\forking.py", line 489, in prepare
    file, path_name, etc = imp.find_module(main_name, dirs)
ImportError: No module named clscl_train

I download your code and execute the following scirpt without run setup.py

python clscl_train en de Z:/DataDeport/cls-acl10-processed/en/books/train.processed Z:/DataDeport/cls-acl10-processed/en/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/de/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/dict/en_de_dict.txt model.bz2 --phi 30 --max-unlabeled=50000 -k 100 -m 450 --strategy=parallel

Is it the reason that I got the ImportError ?

Hi! Thanks the code of CLCSL! I found the data presented in the readme was not able to download, Could you update it? Thank you!

The data for cross-language sentiment classification that has been used in the above study can be found here [2].
...
[2] http://www.uni-weimar.de/medien/webis/research/corpora/webis-cls-10/cls-acl10-processed.tar.gz

Hi ! The data you provided is processed, do you have the original raw data? I want to use it for some comparison.

The corpora seem to be damaged, because I can only download 1MB of the archive(230MB). I can only find the "readme" in the archive. Could you check it again?

[2] http://www.webis.de/research/corpora/corpus-webis-cls-10/cls-acl10-processed.tar.gz