transformer
Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.
파일 탐색기
최종 버전 다운로드 (.zip)- theme_modifs.css
- training_2019_12_03__170100.ipynb
- training_2019_12_03__172753.ipynb
- training_2019_12_03__173205.ipynb
- training_2019_12_04__132557.ipynb
- training_2019_12_06__114703.ipynb
- training_2019_12_06__123805.ipynb
- training_2019_12_15__152700.ipynb
- training_2019_12_15__164718.ipynb
- training_2019_12_15__172952.ipynb
- training_2019_12_20__112013.ipynb
- training_2019_12_20__172758.ipynb
- training_2019_12_23__173446.ipynb
- training_2019_12_23__194258.ipynb
- training_2019_12_24__132610.ipynb
- training_2019_12_25__114022.ipynb
- training_2019_12_28__110648.ipynb
- training_2019_12_28__174445.ipynb
- training_2019_12_29__143613.ipynb
- training_2020_01_03__133337.ipynb
- training_2020_01_06__190627.ipynb
- training_2020_01_07__172923.ipynb
- training_2020_01_10__114522.ipynb
- training_2020_01_31__144602.ipynb
- training_2020_02_25__224128.ipynb
- training_2020_03_04__202641.ipynb
- training_2020_03_05__080607.ipynb
- training_2020_03_12__195104.ipynb
- training_2020_03_31__163536.ipynb
- training_2020_04_01__193853.ipynb
- training_2020_04_14__143020.ipynb
- training_2020_04_27__093505.ipynb
- training_2020_06_27__164648.ipynb
- 2989283.png
- closing.png
- conso30.png
- consoclim.png
- consocpcu.png
- consocta.png
- deltaT.png
- dispersiontemperature.png
- horaires.png
- demonstrateur.ipynb
- demonstrateur_oze.ipynb
- demonstrateur_oze_3.ipynb
- visu_2020_03_28__120412.ipynb
- conf.py
- decoder.rst
- encoder.rst
- index.rst
- loss.rst
- modules.rst
- multiHeadAttention.rst
- positionwiseFeedForward.rst
- README.md
- trainings.rst
- transformer.rst
- utils.rst
- visualizations.rst
- Makefile
- requirements.txt
- training.ipynb
- __init__.py
- search.py
- utils.py
- __init__.py
- plot_functions.py
- utils.py
- benchmark.py
- dataset.py
- metrics.py
- __init__.py
- decoder.py
- encoder.py
- loss.py
- multiHeadAttention.py
- positionwiseFeedForward.py
- transformer.py
- utils.py
- .gitignore
- benchmark.ipynb
- cross_validation.py
- export_doc.py
- labels.json
- learning_curve.py
- LICENSE
- README.md
- requirements.txt
- search.py
- setup.py
- training.ipynb
- training.py
- visualization.ipynb
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/maxjcohen/transformer
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd transformer
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Python
쉬움 추천사전 준비물
$ pip3 install --upgrade --user pip virtualenv
requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.
(.env) $ pip install -r requirements.txt
requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
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