Work in progress Dockerfile to create a GPU enabled Ray runtime with Nvidia Docker.
Uses the environment variable RAY_CLUSTER to connect to an existing Ray cluster (given its Redis location).
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November 23, 2020 14:20
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``nvidia-docker`` compatible ``Dockerfile`` for ``ray``
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| FROM nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 | |
| # At build time we might require a proxy, depending on our network configuration | |
| ARG http_proxy | |
| ARG https_proxy | |
| ENV http_proxy=$http_proxy | |
| ENV https_proxy=$https_proxy | |
| ENV HTTP_PROXY=$http_proxy | |
| ENV HTTPS_PROXY=$https_proxy | |
| ENV DEBIAN_FRONTEND noninteractive | |
| ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda-10.0/compat/ | |
| RUN apt-get update && apt-get install -y --fix-missing \ | |
| nano \ | |
| wget \ | |
| python3.7 \ | |
| python3-distutils \ | |
| python3-dev | |
| RUN wget -O get-pip.py 'https://bootstrap.pypa.io/get-pip.py'; | |
| RUN python3.7 get-pip.py \ | |
| --disable-pip-version-check \ | |
| --no-cache-dir | |
| RUN python3.7 -m pip install ray | |
| CMD python3.7 -c "import os; import ray; ray.init(redis_address=os.environ.get('RAY_CLUSTER') or None)" |
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