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84 lines
2.6 KiB
84 lines
2.6 KiB
PaddlePaddle in Docker Containers
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=================================
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Docker container is currently the only officially-supported way to
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running PaddlePaddle. This is reasonable as Docker now runs on all
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major operating systems including Linux, Mac OS X, and Windows.
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Please be aware that you will need to change `Dockers settings
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<https://github.com/PaddlePaddle/Paddle/issues/627>`_ to make full use
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of your hardware resource on Mac OS X and Windows.
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CPU-only and GPU Images
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-----------------------
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For each version of PaddlePaddle, we release 2 Docker images, a
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CPU-only one and a CUDA GPU one. We do so by configuring
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`dockerhub.com <https://hub.docker.com/r/paddledev/paddle/>`_
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automatically runs the following commands:
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.. code-block:: base
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docker build -t paddle:cpu-noavx -f paddle/scripts/docker/Dockerfile .
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docker build -t paddle:gpu-noavx -f paddle/scripts/docker/Dockerfile.gpu .
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To run the CPU-only image as an interactive container:
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.. code-block:: bash
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docker run -it --rm paddledev/paddle:cpu-latest /bin/bash
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or, we can run it as a daemon container
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.. code-block:: bash
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docker run -d -p 2202:22 paddledev/paddle:cpu-latest
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and SSH to this container using password :code:`root`:
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.. code-block:: bash
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ssh -p 2202 root@localhost
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An advantage of using SSH is that we can connect to PaddlePaddle from
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more than one terminals. For example, one terminal running vi and
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another one running Python interpreter. Another advantage is that we
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can run the PaddlePaddle container on a remote server and SSH to it
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from a laptop.
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Above methods work with the GPU image too -- just please don't forget
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to install CUDA driver and let Docker knows about it:
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.. code-block:: bash
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export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
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export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
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docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
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Non-AVX Images
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--------------
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Please be aware that the CPU-only and the GPU images both use the AVX
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instruction set, but old computers produced before 2008 do not support
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AVX. The following command checks if your Linux computer supports
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AVX:
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.. code-block:: bash
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if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi
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If it doesn't, we will need to build non-AVX images manually from
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source code:
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.. code-block:: bash
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cd ~
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git clone github.com/PaddlePaddle/Paddle
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cd Paddle
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docker build --build-arg WITH_AVX=OFF -t paddle:cpu-noavx -f paddle/scripts/docker/Dockerfile .
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docker build --build-arg WITH_AVX=OFF -t paddle:gpu-noavx -f paddle/scripts/docker/Dockerfile.gpu .
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