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FROM tensorflow/tensorflow:2.2.0-gpu
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# why 2.3 ? I looked it up on stack overflow
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# https://stackoverflow.com/questions/50622525/which-tensorflow-and-cuda-version-combinations-are-compatible
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# here is a nice list, which tf version is compatible with which cuda
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# from the cmmand docker run --runtime=nvidia --rm nvidia/cuda:9.0-base nvidia-smi
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# you get your installed cuda version running
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#RUN useradd -ms /bin/bash pluritonian
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#USER pluritonian
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WORKDIR /home/pluritonian/Prototyp
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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RUN apt-get update && apt-get install nano
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RUN pip install joblib scikit-learn==0.20.0 hickle==3.4.9
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RUN pip install idna==2.9 python-multipart==0.0.5
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RUN pip install nltk==3.4.1 spacy==2.0.18 pandas==0.23.4 ipywidgets==7.5.1 beautifulsoup4==4.6.3
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RUN python -m spacy download de_core_news_sm
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RUN pip install --upgrade pip && pip install fastapi uvicorn[standard] httpx asyncio
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#COPY Prototyp/* /home/pluritonian/
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# to let the container running:
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CMD python -m uvicorn fastapi_server:app --reload --host 0.0.0.0 --port 8000
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#CMD /bin/sh -c "while true; do sleep 30; done"
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#ENTRYPOINT ["tail"]
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#CMD ["-f","/dev/null"]
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