docker run -it -v ~/workspace:/workspace -v $(pwd):/paddle paddlepaddle/paddle:0.10.0rc2-dev /bin/bash
# now we are inside docker container
- or, we can run it as a daemon container
.. code-block:: bash
# use nvidia-docker instead of docker if you need to use GPU
The above command will compile PaddlePaddle and create a Dockerfile for building production image. All the generated files are in the build directory. "WITH_GPU" controls if the generated production image supports GPU. "WITH_AVX" controls if the generated production image supports AVX. "WITH_TEST" controls if the unit test will be generated.
<h2>Usage of CPU-only and GPU Images<aclass="headerlink"href="#usage-of-cpu-only-and-gpu-images"title="Permalink to this headline">¶</a></h2>
<h2>Usage of CPU-only and GPU Images<aclass="headerlink"href="#usage-of-cpu-only-and-gpu-images"title="Permalink to this headline">¶</a></h2>
<p>For each version of PaddlePaddle, we release two types of Docker images:
<p>We package PaddlePaddle’s compile environment into a Docker image,
development image and production image. Production image includes
called the develop image, it contains all compiling tools that
CPU-only version and a CUDA GPU version and their no-AVX versions. We
PaddlePaddle needs. We package compiled PaddlePaddle program into a
put the docker images on <aclass="reference external"href="https://hub.docker.com/r/paddledev/paddle/">dockerhub.com</a>. You can find the
Docker image as well, called the production image, it contains all
latest versions under “tags” tab at dockerhub.com</p>
runtime environment that running PaddlePaddle needs. For each version
of PaddlePaddle, we release both of them. Production image includes
CPU-only version and a CUDA GPU version and their no-AVX versions.</p>
<p>We put the docker images on <aclass="reference external"href="https://hub.docker.com/r/paddledev/paddle/">dockerhub.com</a>. You can find the
latest versions under “tags” tab at dockerhub.com. If you are in
China, you can use our Docker image registry mirror to speed up the
download process. To use it, please replace all paddlepaddle/paddle in
the commands to docker.paddlepaddle.org/paddle.</p>
<olclass="arabic">
<olclass="arabic">
<li><pclass="first">Production images, this image might have multiple variants:</p>
<li><pclass="first">Production images, this image might have multiple variants:</p>
<ulclass="simple">
<ulclass="simple">
...
@@ -359,49 +366,33 @@ python example.py
...
@@ -359,49 +366,33 @@ python example.py
<h2>Develop PaddlePaddle or Train Model Using C++ API<aclass="headerlink"href="#develop-paddlepaddle-or-train-model-using-c-api"title="Permalink to this headline">¶</a></h2>
<h2>Develop PaddlePaddle or Train Model Using C++ API<aclass="headerlink"href="#develop-paddlepaddle-or-train-model-using-c-api"title="Permalink to this headline">¶</a></h2>
<p>We will be using PaddlePaddle development image since it contains all
<p>We will be using PaddlePaddle development image since it contains all
<p>and SSH to this container using password <codeclass="code docutils literal"><spanclass="pre">root</span></code>:</p>
<p>The above command will compile PaddlePaddle and create a Dockerfile for building production image. All the generated files are in the build directory. “WITH_GPU” controls if the generated production image supports GPU. “WITH_AVX” controls if the generated production image supports AVX. “WITH_TEST” controls if the unit test will be generated.</p>
PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统（包括Linux，Mac OS X和Windows）上运行。 请注意，您需要更改 `Dockers设置 <https://github.com/PaddlePaddle/Paddle/issues/627>`_ 才能充分利用Mac OS X和Windows上的硬件资源。
PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统（包括Linux，Mac OS X和Windows）上运行。 请注意，您需要更改 `Dockers设置 <https://github.com/PaddlePaddle/Paddle/issues/627>`_ 才能充分利用Mac OS X和Windows上的硬件资源。
<p>PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统（包括Linux，Mac OS X和Windows）上运行。 请注意，您需要更改 <aclass="reference external"href="https://github.com/PaddlePaddle/Paddle/issues/627">Dockers设置</a> 才能充分利用Mac OS X和Windows上的硬件资源。</p>
<p>PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统（包括Linux，Mac OS X和Windows）上运行。 请注意，您需要更改 <aclass="reference external"href="https://github.com/PaddlePaddle/Paddle/issues/627">Dockers设置</a> 才能充分利用Mac OS X和Windows上的硬件资源。</p>
docker run <spanclass="si">${</span><spanclass="nv">CUDA_SO</span><spanclass="si">}</span><spanclass="si">${</span><spanclass="nv">DEVICES</span><spanclass="si">}</span> -it paddledev/paddle:<version>-gpu
docker run <spanclass="si">${</span><spanclass="nv">CUDA_SO</span><spanclass="si">}</span><spanclass="si">${</span><spanclass="nv">DEVICES</span><spanclass="si">}</span> -it paddledev/paddle:<version>-gpu
