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 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"]