카카오브레인 pororo, conda 가상환경에 설치하는 방법

# pororo는 pytorch 1.6 이 선행되어야 함. 이를 위해 python-3.6 버전으로 가상환경 생성
conda create -n pororo_test python=3.6
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch

# pip 유저 옵션 - 권한 문제 해결
python -m pip install -U pip --user
# 여기까지 참고: https://kangaroo-dev.tistory.com/1

# pororo git
git clone https://github.com/kakaobrain/pororo.git
ls
cd pororo
conda install -e .

1. pip install pororo를 했더니 ImportError: cannot import name 'Pororo’ 에러가 떴다.
   • 설치 시 커맨드 창

     Successfully built pororo
     Installing collected packages: pororo
       Attempting uninstall: pororo
         Found existing installation: pororo 0.4.2
         Uninstalling pororo-0.4.2:
           Successfully uninstalled pororo-0.4.2
     Successfully installed pororo-0.4.1

   • 실패

     $python pororo.py
     Traceback (most recent call last):
      File "pororo.py", line 1, in <module>
        from pororo import Pororo
      File "/pororo.py", line 1, in <module>
        from pororo import Pororo
      ImportError: cannot import name 'Pororo'

2. pororo git을 clone하여 직접 conda install -e . 해주어야 한다. 그리고 이때 가상환경을 새로 생성해주어 pytorch 1.6을 꼭! 먼저 설치해 주어야 한다.
   • 설치 시 커맨드 창

     Installing collected packages: pororo
       Attempting uninstall: pororo
         Found existing installation: pororo 0.4.1
         Uninstalling pororo-0.4.1:
           Successfully uninstalled pororo-0.4.1
       Running setup.py develop for pororo
     Successfully installed pororo-0.4.1

   • 성공

     $python
     >>> from pororo import Pororo
     >>> Pororo.available_tasks()
     "Available tasks are ['mrc', 'rc', 'qa', 'question_answering', 'machine_reading_comprehension', 'reading_comprehension', 'sentiment', 'sentiment_analysis', 'nli', 'natural_language_inference', 'inference', 'fill', 'fill_in_blank', 'fib', 'para', 'pi', 'cse', 'contextual_subword_embedding', 'similarity', 'sts', 'semantic_textual_similarity', 'sentence_similarity', 'sentvec', 'sentence_embedding', 'sentence_vector', 'se', 'inflection', 'morphological_inflection', 'g2p', 'grapheme_to_phoneme', 'grapheme_to_phoneme_conversion', 'w2v', 'wordvec', 'word2vec', 'word_vector', 'word_embedding', 'tokenize', 'tokenise', 'tokenization', 'tokenisation', 'tok', 'segmentation', 'seg', 'mt', 'machine_translation', 'translation', 'pos', 'tag', 'pos_tagging', 'tagging', 'const', 'constituency', 'constituency_parsing', 'cp', 'pg', 'collocation', 'collocate', 'col', 'word_translation', 'wt', 'summarization', 'summarisation', 'text_summarization', 'text_summarisation', 'summary', 'gec', 'review', 'review_scoring', 'lemmatization', 'lemmatisation', 'lemma', 'ner', 'named_entity_recognition', 'entity_recognition', 'zero-topic', 'dp', 'dep_parse', 'caption', 'captioning', 'asr', 'speech_recognition', 'st', 'speech_translation', 'tts', 'text_to_speech', 'speech_synthesis', 'ocr', 'srl', 'semantic_role_labeling', 'p2g', 'aes', 'essay', 'qg', 'question_generation', 'age_suitability', 'wsd']"
     >>>