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docker

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    Cyprien Noel authored
    4db619ae
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    cpu
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    README.md

    Running an official image

    You can run one of the automatic builds. E.g. for the CPU version:

    docker run -ti bvlc/caffe:cpu caffe --version

    or for GPU support (You need a CUDA 8.0 capable driver and nvidia-docker):

    nvidia-docker run -ti bvlc/caffe:gpu caffe --version

    You might see an error about libdc1394, ignore it.

    Docker run options

    By default caffe runs as root, thus any output files, e.g. snapshots, will be owned by root. It also runs by default in a container-private folder.

    You can change this using flags, like user (-u), current directory, and volumes (-w and -v). E.g. this behaves like the usual caffe executable:

    docker run --rm -u $(id -u):$(id -g) -v $(pwd):$(pwd) -w $(pwd) bvlc/caffe:cpu caffe train --solver=example_solver.prototxt

    Containers can also be used interactively, specifying e.g. bash or ipython instead of caffe.

    docker run -ti bvlc/caffe:cpu ipython
    import caffe
    ...

    The caffe build requirements are included in the container, so this can be used to build and run custom versions of caffe. Also, caffe/python is in PATH, so python utilities can be used directly, e.g. draw_net.py, classify.py, or detect.py.

    Building images yourself

    Examples:

    docker build -t caffe:cpu cpu

    docker build -t caffe:gpu gpu

    You can also build Caffe and run the tests in the image:

    docker run -ti caffe:cpu bash -c "cd /opt/caffe/build; make runtest"