Deploy to GitHub Pages: d65316f8

develop/doc/_sources/getstarted/build_and_install/docker_install_en.rst.txt

@@ -122,7 +122,7 @@ GPU driver installed before move on.
 
   .. code-block:: bash
 
-     nvidia-docker run -it -v $PWD:/work paddledev/paddle:latest-gpu /bin/bash
+     nvidia-docker run -it -v $PWD:/work paddlepaddle/paddle:latest-gpu /bin/bash
 
 **NOTE: If you don't have nvidia-docker installed, try the following method to mount CUDA libs and devices into the container.**
 
@@ -130,7 +130,7 @@ GPU driver installed before move on.
 
      export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
      export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
-     docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:latest-gpu
+     docker run ${CUDA_SO} ${DEVICES} -it paddlepaddle/paddle:latest-gpu
 
 **About AVX:**
 

develop/doc/getstarted/build_and_install/docker_install_en.html

@@ -310,7 +310,7 @@ dig deeper into deep learning, PaddlePaddle Book definitely is your best choice.
 to run GPU training jobs. Please ensure you have latest
 GPU driver installed before move on.</p>
 <blockquote>
-<div><div class="highlight-bash"><div class="highlight"><pre><span></span>nvidia-docker run -it -v <span class="nv">$PWD</span>:/work paddledev/paddle:latest-gpu /bin/bash
+<div><div class="highlight-bash"><div class="highlight"><pre><span></span>nvidia-docker run -it -v <span class="nv">$PWD</span>:/work paddlepaddle/paddle:latest-gpu /bin/bash
 </pre></div>
 </div>
 </div></blockquote>
@@ -318,7 +318,7 @@ GPU driver installed before move on.</p>
 <blockquote>
 <div><div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">CUDA_SO</span><span class="o">=</span><span class="s2">&quot;</span><span class="k">$(</span><span class="se">\l</span>s /usr/lib64/libcuda* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2"> </span><span class="k">$(</span><span class="se">\l</span>s /usr/lib64/libnvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2">&quot;</span>
 <span class="nb">export</span> <span class="nv">DEVICES</span><span class="o">=</span><span class="k">$(</span><span class="se">\l</span>s /dev/nvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;--device {}:{}&#39;</span><span class="k">)</span>
-docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddledev/paddle:latest-gpu
+docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddlepaddle/paddle:latest-gpu
 </pre></div>
 </div>
 </div></blockquote>

develop/doc_cn/_sources/faq/build_and_install/index_cn.rst.txt

@@ -14,7 +14,7 @@
 
     $ export CUDA_SO="$(\ls usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
     $ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
-    $ docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddlepaddle:latest-gpu
+    $ docker run ${CUDA_SO} ${DEVICES} -it paddlepaddle/paddle:latest-gpu
 
 更多关于Docker的安装与使用, 请参考 `PaddlePaddle Docker 文档 <http://www.paddlepaddle.org/doc_cn/build_and_install/install/docker_install.html>`_ 。
 

develop/doc_cn/_sources/getstarted/build_and_install/docker_install_cn.rst.txt

@@ -114,7 +114,7 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note
 
   .. code-block:: bash
 
-     nvidia-docker run -it -v $PWD:/work paddledev/paddle:latest-gpu /bin/bash
+     nvidia-docker run -it -v $PWD:/work paddlepaddle/paddle:latest-gpu /bin/bash
 
 **注: 如果没有安装nvidia-docker，可以尝试以下的方法，将CUDA库和Linux设备挂载到Docker容器内：**
 
@@ -122,7 +122,7 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note
 
      export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
      export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
-     docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:latest-gpu
+     docker run ${CUDA_SO} ${DEVICES} -it paddlepaddle/paddle:latest-gpu
 
 **关于AVX：**
 

develop/doc_cn/faq/build_and_install/index_cn.html

@@ -232,7 +232,7 @@
 具体的解决方法是：</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>$ <span class="nb">export</span> <span class="nv">CUDA_SO</span><span class="o">=</span><span class="s2">&quot;</span><span class="k">$(</span><span class="se">\l</span>s usr/lib64/libcuda* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2"> </span><span class="k">$(</span><span class="se">\l</span>s /usr/lib64/libnvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2">&quot;</span>
 $ <span class="nb">export</span> <span class="nv">DEVICES</span><span class="o">=</span><span class="k">$(</span><span class="se">\l</span>s /dev/nvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;--device {}:{}&#39;</span><span class="k">)</span>
-$ docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddledev/paddlepaddle:latest-gpu
+$ docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddlepaddle/paddle:latest-gpu
 </pre></div>
 </div>
 <p>更多关于Docker的安装与使用, 请参考 <a class="reference external" href="http://www.paddlepaddle.org/doc_cn/build_and_install/install/docker_install.html">PaddlePaddle Docker 文档</a> 。</p>

develop/doc_cn/getstarted/build_and_install/docker_install_cn.html

@@ -304,7 +304,7 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note
 <a class="reference external" href="https://github.com/NVIDIA/nvidia-docker">nvidia-docker</a> 来运行镜像。
 请不要忘记提前在物理机上安装GPU最新驱动。</p>
 <blockquote>
-<div><div class="highlight-bash"><div class="highlight"><pre><span></span>nvidia-docker run -it -v <span class="nv">$PWD</span>:/work paddledev/paddle:latest-gpu /bin/bash
+<div><div class="highlight-bash"><div class="highlight"><pre><span></span>nvidia-docker run -it -v <span class="nv">$PWD</span>:/work paddlepaddle/paddle:latest-gpu /bin/bash
 </pre></div>
 </div>
 </div></blockquote>
@@ -312,7 +312,7 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note
 <blockquote>
 <div><div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">CUDA_SO</span><span class="o">=</span><span class="s2">&quot;</span><span class="k">$(</span><span class="se">\l</span>s /usr/lib64/libcuda* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2"> </span><span class="k">$(</span><span class="se">\l</span>s /usr/lib64/libnvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;-v {}:{}&#39;</span><span class="k">)</span><span class="s2">&quot;</span>
 <span class="nb">export</span> <span class="nv">DEVICES</span><span class="o">=</span><span class="k">$(</span><span class="se">\l</span>s /dev/nvidia* <span class="p">|</span> xargs -I<span class="o">{}</span> <span class="nb">echo</span> <span class="s1">&#39;--device {}:{}&#39;</span><span class="k">)</span>
-docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddledev/paddle:latest-gpu
+docker run <span class="si">${</span><span class="nv">CUDA_SO</span><span class="si">}</span> <span class="si">${</span><span class="nv">DEVICES</span><span class="si">}</span> -it paddlepaddle/paddle:latest-gpu
 </pre></div>
 </div>
 </div></blockquote>