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- FROM tensorflow/tensorflow:2.2.0-gpu
-
- # why 2.3 ? I looked it up on stack overflow
- # https://stackoverflow.com/questions/50622525/which-tensorflow-and-cuda-version-combinations-are-compatible
- # here is a nice list, which tf version is compatible with which cuda
- # from the cmmand docker run --runtime=nvidia --rm nvidia/cuda:9.0-base nvidia-smi
- # you get your installed cuda version running
-
- #RUN useradd -ms /bin/bash pluritonian
-
-
- #USER pluritonian
-
- WORKDIR /home/pluritonian/Prototyp
-
- RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
-
- RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
-
- RUN apt-get update && apt-get install nano
-
- RUN pip install joblib scikit-learn==0.20.0 hickle==3.4.9
-
- RUN pip install idna==2.9 python-multipart==0.0.5
-
- RUN pip install nltk==3.4.1 spacy==2.0.18 pandas==0.23.4 ipywidgets==7.5.1 beautifulsoup4==4.6.3
-
- RUN python -m spacy download de_core_news_sm
-
- RUN pip install --upgrade pip && pip install fastapi uvicorn[standard]
-
- #COPY Prototyp/* /home/pluritonian/
-
-
- # to let the container running:
-
- CMD uvicorn --host 0.0.0.0 fastapi_server:app
-
- #ENTRYPOINT ["tail"]
- #CMD ["-f","/dev/null"]
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