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未验证 提交 377f7dd7 编写于 作者: T tianshuo78520a 提交者： GitHub
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cherry-pick 2.0 doc (#2159) 

* update install doc for release/2.0

* update install doc for release/2.0

* update install doc for release/2.0

* update install doc for release/2.0

* update install doc for release/2.0
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Showing with 161 addition and 1423 deletion
doc/fluid/install/Tables.md
浏览文件 @ 377f7dd7
......@@ -228,17 +228,13 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
</thead>
<tbody>
<tr>
<td> paddlepaddle==[版本号] 例如 paddlepaddle==1.8.1 </td>
<td> paddlepaddle==[版本号] 例如 paddlepaddle==2.0.0a0 </td>
<td> 只支持CPU对应版本的PaddlePaddle，具体版本请参见<a href=https://pypi.org/project/paddlepaddle/#history>Pypi</a> </td>
</tr>
<tr>
<td> paddlepaddle-gpu==[版本号] 例如 paddlepaddle-gpu==1.8.1 </td>
<td> paddlepaddle-gpu==[版本号] 例如 paddlepaddle-gpu==2.0.0a0 </td>
<td> 默认安装支持CUDA 10.0和cuDNN 7的对应[版本号]的PaddlePaddle安装包 </td>
</tr>
<tr>
<td> paddlepaddle-gpu==[版本号].postXX 例如 paddlepaddle-gpu==1.8.1.post97 </td>
<td> 支持CUDA 9.0和cuDNN 7的对应PaddlePaddle版本的安装包</td>
</tr>
</tbody>
</table>
</p>
......@@ -246,7 +242,7 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
您可以在 [Release History](https://pypi.org/project/paddlepaddle-gpu/#history) 中找到PaddlePaddle-gpu的各个发行版本。
> 其中`postXX` 对应的是CUDA和cuDNN的版本，`postXX`之前的数字代表Paddle的版本
需要注意的是，命令中<code> paddlepaddle-gpu </code> 在windows环境下，会默认安装支持CUDA 10.0和cuDNN 7的对应[版本号]的PaddlePaddle安装包
需要注意的是，命令中<code> paddlepaddle-gpu==2.0.0a0 </code> 在windows环境下，会默认安装支持CUDA 10.0和cuDNN 7的对应[版本号]的PaddlePaddle安装包
<a name="ciwhls-release"></a>
</br></br>
......@@ -268,126 +264,65 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
<tbody>
<tr>
<td> cpu-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cpu-openblas </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cuda9-cudnn7-openblas </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cuda9-cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp27-cp27m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cuda10_cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp35-cp35m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> win_cpu_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl">
paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl">
paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl">
paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl">
paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp27-cp27m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp35-cp35m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp36-cp36m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp37-cp37m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda9_cudnn7_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda10_cudnn7_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cpu_openblas </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl">
paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl">
paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl">
paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl">
paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda9_cudnn7_openblas </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> mac_cpu </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp27-cp27m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp27-cp27m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp35-cp35m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp35-cp35m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp36-cp36m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp36-cp36m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp37-cp37m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp37-cp37m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp27-cp27m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp35-cp35m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp36-cp36m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp37-cp37m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-macosx_10_6_intel.whl</a></td>
</tr>
</tbody>
</table>
......@@ -399,12 +334,6 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
cpu-mkl: 支持CPU训练和预测，使用Intel mkl数学库
cpu-openblas: 支持CPU训练和预测，使用openblas数学库
cuda9-cudnn7-openblas: 支持GPU训练和预测，使用openblas数学库
cuda9_cudnn7-mkl: 支持GPU训练和预测，使用Intel mkl数学库
cuda10_cudnn7-mkl: 支持GPU训练和预测，使用Intel mkl数学库
......@@ -538,38 +467,6 @@ platform tag: 类似 'linux_x86_64', 'any'
</p>
<a name="ciwhls-gcc8.2-release"></a>
</br></br>
## **多版本whl包列表(gcc8.2)-release**
<p align="center">
<table>
<thead>
<tr>
<th> 版本说明 </th>
<th> cp27-cp27mu </th>
<th> cp27-cp27m </th>
<th> cp35-cp35m </th>
<th> cp36-cp36m </th>
<th> cp37-cp37m </th>
</tr>
</thead>
<tbody>
<tr>
<td> cuda10.1-cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
</tbody>
</table>
</p>
<!--TODO this part should be in a new webpage-->
......
doc/fluid/install/Tables_en.md
浏览文件 @ 377f7dd7
......@@ -225,17 +225,13 @@ PaddePaddle implements references to various BLAS/CUDA/cuDNN libraries by specif
</thead>
<tbody>
<tr>
<td> paddlepaddle==[version code] such as paddlepaddle==1.8.1 </td>
<td> paddlepaddle==[version code] such as paddlepaddle==2.0.0a0 </td>
<td> Only support the corresponding version of the CPU PaddlePaddle, please refer to <a href=https://pypi.org/project/paddlepaddle/#history>Pypi</a> for the specific version. </td>
</tr>
<tr>
<td> paddlepaddle-gpu==[version code], such as paddlepaddle-gpu==1.8.1 </td>
<td> paddlepaddle-gpu==[version code], such as paddlepaddle-gpu==2.0.0a0 </td>
<td> The default installation supports the PaddlePaddle installation package corresponding to [version number] of CUDA 10.0 and cuDNN 7 </td>
</tr>
<tr>
<td> paddlepaddle-gpu==[version code].postXX, such as paddlepaddle-gpu==1.8.1.post97 </td>
<td> Installation package supporting the corresponding PaddlePaddle version of CUDA 9.0 and cuDNN 7 </td>
</tr>
</tbody>
</table>
</p>
......@@ -243,7 +239,7 @@ PaddePaddle implements references to various BLAS/CUDA/cuDNN libraries by specif
You can find various distributions of PaddlePaddle-gpu in [the Release History](https://pypi.org/project/paddlepaddle-gpu/#history).
> 'postxx' corresponds to CUDA and cuDNN versions, and the number before 'postxx' represents the version of Paddle
Please note that: in the commands, <code> paddlepaddle-gpu </code> will install the installation package of PaddlePaddle that supports CUDA 10.0 and cuDNN 7 by default under Windows environment.
Please note that: in the commands, <code> paddlepaddle-gpu==2.0.0a0 </code> will install the installation package of PaddlePaddle that supports CUDA 10.0 and cuDNN 7 by default under Windows environment.
<a name="ciwhls-release"></a>
......@@ -254,141 +250,80 @@ Please note that: in the commands, <code> paddlepaddle-gpu </code> will install
<p align="center">
<table>
<thead>
<tr>
<th> Release Instruction </th>
<th> cp27-cp27mu </th>
<th> cp27-cp27m </th>
<th> cp35-cp35m </th>
<th> cp36-cp36m </th>
<th> cp37-cp37m </th>
</tr>
</thead>
<tbody>
<tr>
<td> cpu-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mkl/paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cpu-openblas </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-openblas/paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<thead>
<tr>
<td> cuda9-cudnn7-openblas </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
<th> Release Instruction </th>
<th> cp27-cp27mu </th>
<th> cp27-cp27m </th>
<th> cp35-cp35m </th>
<th> cp36-cp36m </th>
<th> cp37-cp37m </th>
</tr>
</thead>
<tbody>
<tr>
<td> cuda9-cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
<td> cpu-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp27-cp27m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp35-cp35m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp36-cp36m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mkl/paddlepaddle-2.0.0a0-cp37-cp37m-linux_x86_64.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> cuda10_cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.8.1.post107-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp35-cp35m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-2.0.0a0-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-2.0.0a0-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
<tr>
<td> win_cpu_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl">
paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl">
paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl">
paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl">
paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp27-cp27m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp35-cp35m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp36-cp36m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle-2.0.0a0-cp37-cp37m-win_amd64.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda9_cudnn7_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda10_cudnn7_mkl </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-mkl/paddlepaddle_gpu-1.8.1.post107-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0/win-mkl/paddlepaddle_gpu-2.0.0a0-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-2.0.0a0-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cpu_openblas </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl">
paddlepaddle-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl">
paddlepaddle-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl">
paddlepaddle-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl">
paddlepaddle-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> win_cuda9_cudnn7_openblas </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp27-cp27m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp35-cp35m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp36-cp36m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-win_amd64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1/win-open/paddlepaddle_gpu-1.8.1.post97-cp37-cp37m-win_amd64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-win_amd64.whl</a></td>
</tr>
<tr>
<td> mac_cpu </td>
<td> - </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp27-cp27m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp27-cp27m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp35-cp35m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp35-cp35m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp36-cp36m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp36-cp36m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-cpu-mac/paddlepaddle-1.8.1-cp37-cp37m-macosx_10_6_intel.whl">
paddlepaddle-1.8.1-cp37-cp37m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp27-cp27m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp27-cp27m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp35-cp35m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp35-cp35m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp36-cp36m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp36-cp36m-macosx_10_6_intel.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/2.0.0-alpha0-cpu-mac/paddlepaddle-2.0.0a0-cp37-cp37m-macosx_10_6_intel.whl">
paddlepaddle-2.0.0a0-cp37-cp37m-macosx_10_6_intel.whl</a></td>
</tr>
</tbody>
</tbody>
</table>
</p>
......@@ -399,12 +334,6 @@ Please note that: in the commands, <code> paddlepaddle-gpu </code> will install
cpu-mkl: Support CPU training and prediction, use Intel MKL math library
cpu-openblas: Support CPU training and prediction, use openblas math library
cuda9-cudnn7-openblas: Support GPU training and prediction, use openblas math library
cuda9_cudnn7-mkl: Support GPU training and prediction, use Intel MKL math library
cuda10_cudnn7-mkl: Support GPU training and prediction, use Intel MKL math library
......@@ -541,39 +470,6 @@ platform tag: similar to 'linux_x86_64', 'any'
</p>
<a name="ciwhls-gcc8.2-release"></a>
</br></br>
## **Multi-version whl package list(gcc8.2)-release**
<p align="center">
<table>
<thead>
<tr>
<th> version instruction </th>
<th> cp27-cp27mu </th>
<th> cp27-cp27m </th>
<th> cp35-cp35m </th>
<th> cp36-cp36m </th>
<th> cp37-cp37m </th>
</tr>
</thead>
<tbody>
<tr>
<td> cuda10.1-cudnn7-mkl </td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27mu-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp27-cp27m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp35-cp35m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp36-cp36m-linux_x86_64.whl</a></td>
<td> <a href="https://paddle-wheel.bj.bcebos.com/1.8.1-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl">
paddlepaddle_gpu-1.8.1-cp37-cp37m-linux_x86_64.whl</a></td>
</tr>
</tbody>
</table>
</p>
<!--TODO this part should be in a new webpage-->
</br></br>
......
doc/fluid/install/index_cn.rst
浏览文件 @ 377f7dd7
......@@ -181,20 +181,13 @@
如果您是使用 Python 2，安装CPU版本的命令为：
::
python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple
或
python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple
如果您是使用 Python 3，安装CPU版本的命令为：
::
python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple
或
python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple
如果您是使用 Python 3，请将上述命令中的 **python** 更换为 **python3** 进行安装
(2). **GPU版本** ：如果您想使用GPU版本请参考如下命令安装
......@@ -202,32 +195,14 @@
* 需要您确认您的 GPU 满足上方列出的要求
如果您是使用 Python2，请注意用以下指令安装的PaddlePaddle在Windows、Ubuntu、CentOS下默认支持CUDA10.0：
如果您是使用 Python2，请注意用以下指令安装的PaddlePaddle在Windows、Ubuntu、CentOS下只支持CUDA10.0：
::
python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple
或
python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple
如果您是使用 Python 2，CUDA 9，cuDNN 7.3+，安装GPU版本的命令为：
::
python -m pip install paddlepaddle-gpu==1.8.1.post97 -i https://mirror.baidu.com/pypi/simple
或
python -m pip install paddlepaddle-gpu==1.8.1.post97 -i https://pypi.tuna.tsinghua.edu.cn/simple
如果您是使用 Python 2，CUDA 10.0，cuDNN 7.3+，安装GPU版本的命令为：
::
python -m pip install paddlepaddle-gpu==1.8.1.post107 -i https://mirror.baidu.com/pypi/simple
或
python -m pip install paddlepaddle-gpu==1.8.1.post107 -i https://pypi.tuna.tsinghua.edu.cn/simple
python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple
如果您是使用 Python 3，请将上述命令中的 **python** 更换为 **python3** 进行安装。
......@@ -248,275 +223,10 @@
`Windows下安装 <install_Windows.html>`_
第二种安装方式：使用 conda 安装
================================
您可以选择“使用pip安装”、“使用conda安装”、“使用docker安装”、“从源码编译安装” 四种方式中的任意一种方式进行安装。
本节将介绍使用 conda 的安装方式。
1. 需要您确认您的 操作系统 满足上方列出的要求
2. 需要您确认您的 处理器 满足上方列出的要求
3. 对于国内用户无法连接到Anaconda官方源的可以按照以下命令添加清华源进行安装。
::
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/Paddle/
conda config --set show_channel_urls yes
4. 如果您需要新建 conda 的虚拟环境专门给 Paddle 使用（--name后边的环境名称，您可以自己选择）：
如果您是使用 Python2 并且在 Window 环境下
::
conda create --name paddle python=2.7
activate paddle
如果您是使用 Python2 并且在 MacOS/Linux 环境下
::
conda create --name paddle python=2.7
conda activate paddle
如果您是使用 Python3 并且在 Window 环境下，注意：python3版本可以是3.5.1+/3.6/3.7
::
conda create --name paddle python=3.7
activate paddle
如果您是使用 Python3 并且在 MacOS/Linux 环境下，注意：python3版本可以是3.5.1+/3.6/3.7
::
conda create --name paddle python=3.7
conda activate paddle
5. 确认您需要安装 PaddlePaddle 的 Python 是您预期的位置，因为您计算机可能有多个 Python，进入 Anaconda 的命令行终端，输入以下指令确认 Python 位置
如果您是使用 Python 2，使用以下命令输出 Python 路径，根据您的环境您可能需要将说明中所有命令行中的 python 替换为具体的 Python 路径
在 Windows 环境下，输出 Python 路径的命令为：
::
where python
在 MacOS/Linux 环境下，输出 Python 路径的命令为：
::
which python
如果您是使用 Python 3，使用以下命令输出 Python 路径，根据您的环境您可能需要将说明中所有命令行中的 python3 替换为 python 或者替换为具体的 Python 路径
在 Windows 环境下，输出 Python 路径的命令为：
::
where python3
在 MacOS/Linux 环境下，输出 Python 路径的命令为：
::
which python3
6. 检查 Python 的版本
如果您是使用 Python 2，使用以下命令确认是 2.7.15+
::
python --version
如果您是使用 Python 3，使用以下命令确认是 3.5.1+/3.6/3.7
::
python3 --version
7. 检查 pip 的版本，确认是 9.0.1+
如果您是使用 Python 2
::
python -m ensurepip
python -m pip --version
如果您是使用 Python 3
::
python3 -m ensurepip
python3 -m pip --version
8. 确认 Python 和 pip 是 64 bit，并且处理器架构是x86_64（或称作 x64、Intel 64、AMD64）架构，目前PaddlePaddle不支持arm64架构。下面的第一行输出的是 "64bit" ，第二行输出的是 "x86_64" 、 "x64" 或 "AMD64" 即可：
如果您是使用 Python 2
::
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
如果您是使用 Python 3
::
python3 -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
9. 如果您希望使用 conda 进行安装PaddlePaddle可以直接使用以下命令:
(1). **CPU版本** ：如果您只是想安装CPU版本请参考如下命令安装
::
conda install paddlepaddle
(2). **GPU版本** ：如果您想使用GPU版本请参考如下命令安装
注意：
* 需要您确认您的 GPU 满足上方列出的要求
如果您是使用 CUDA 8，cuDNN 7.1+，安装GPU版本的命令为：
::
conda install paddlepaddle-gpu cudatoolkit=8.0
如果您是使用 CUDA 9，cuDNN 7.3+，安装GPU版本的命令为：
::
conda install paddlepaddle-gpu cudatoolkit=9.0
如果您是使用 CUDA 10.0，cuDNN 7.3+，安装GPU版本的命令为：
::
conda install paddlepaddle-gpu cudatoolkit=10.0
10. 验证安装
使用 python 或 python3 进入python解释器，输入import paddle.fluid ，再输入 paddle.fluid.install_check.run_check()。
如果出现 Your Paddle Fluid is installed succesfully!，说明您已成功安装。
11. 更多帮助信息请参考：
`conda下安装 <install_Conda.html>`_
第三种安装方式：使用 docker 安装
================================
您可以选择“使用pip安装”、“使用conda安装”、“使用docker安装”、“从源码编译安装” 四种方式中的任意一种方式进行安装。
本节将介绍使用 docker 的安装方式。
如果您希望使用 `docker <https://www.docker.com>`_ 安装PaddlePaddle，可以使用以下命令:
1. **CPU 版本**
(1). 首先需要安装 `docker <https://www.docker.com>`_
注意：
* CentOS 6 不支持 docker 方式安装
* 处理器需要支持 MKL
(2). 拉取预安装 PaddlePaddle 的镜像：
::
docker pull hub.baidubce.com/paddlepaddle/paddle:1.8.1
(3). 用镜像构建并进入Docker容器：
::
docker run --name paddle -it -v dir1:dir2 hub.baidubce.com/paddlepaddle/paddle:1.8.1 /bin/bash
> --name [Name of container] 设定Docker的名称；
> -it 参数说明容器已和本机交互式运行；
> -v 参数用于宿主机与容器里文件共享；其中dir1为宿主机目录，dir2为挂载到容器内部的目录，用户可以通过设定dir1和dir2自定义自己的挂载目录；例如：$PWD:/paddle 指定将宿主机的当前路径（Linux中PWD变量会展开为当前路径的绝对路径）挂载到容器内部的 /paddle 目录；
> hub.baidubce.com/paddlepaddle/paddle:1.8.1 是需要使用的image名称；/bin/bash是在Docker中要执行的命令
2. **GPU 版本**
(1). 首先需要安装 `nvidia-docker <https://github.com/NVIDIA/nvidia-docker>`_
注意：
* 处理器需要支持 MKL
* 您的计算机需要具有支持 CUDA 驱动的 NVIDIA 显卡
* 需要安装 `cuDNN <https://docs.nvidia.com/deeplearning/sdk/cudnn-install/>`_ ，版本要求 7.3+(For CUDA9/10), 7.1+(For CUDA 8)
* 如果您需要 GPU 多卡模式，需要安装 `NCCL 2 <https://developer.nvidia.com/nccl/>`_
* 仅 Ubuntu/CentOS 支持 NCCL 2 技术
* 需要安装 `CUDA <https://docs.nvidia.com/cuda/cuda-installation-guide-windows/>`_ ，根据您系统不同，对 CUDA 版本要求不同：
* Ubuntu/CentOS 7 ，如果您是使用 nvidia-docker 安装，支持 CUDA 8.0/9.0/9.1/9.2/10.0
* Windows/MacOS/CentOS 6 不支持 nvidia-docker 方式安装
(2). 拉取支持 CUDA 10.0 , cuDNN 7.3+ 预安装 PaddlePaddle 的镜像：
::
nvidia-docker pull hub.baidubce.com/paddlepaddle/paddle:1.8.1-gpu-cuda10.0-cudnn7
(3). 用镜像构建并进入Docker容器：
::
nvidia-docker run --name paddle -it -v dir1:dir2 hub.baidubce.com/paddlepaddle/paddle:1.8.1-gpu-cuda10.0-cudnn7 /bin/bash
> --name [Name of container] 设定Docker的名称；
> -it 参数说明容器已和本机交互式运行；
> -v 参数用于宿主机与容器里文件共享；其中dir1为宿主机目录，dir2为挂载到容器内部的目录，用户可以通过设定dir1和dir2自定义自己的挂载目录；例如：$PWD:/paddle 指定将宿主机的当前路径（Linux中PWD变量会展开为当前路径的绝对路径）挂载到容器内部的 /paddle 目录；
> hub.baidubce.com/paddlepaddle/paddle:1.8.1-gpu-cuda10.0-cudnn7 是需要使用的image名称；/bin/bash是在Docker中要执行的命令
或如果您需要支持 **CUDA 9** 的版本，将上述命令的 **cuda10.0** 替换成 **cuda9.0** 即可
3. 如果您的机器不在中国大陆地区，可以直接从DockerHub拉取镜像：
::
docker run --name paddle -it -v dir1:dir2 paddlepaddle/paddle:1.8.1 /bin/bash
> --name [Name of container] 设定Docker的名称；
> -it 参数说明容器已和本机交互式运行；
> -v 参数用于宿主机与容器里文件共享；其中dir1为宿主机目录，dir2为挂载到容器内部的目录，用户可以通过设定dir1和dir2自定义自己的挂载目录；例如：$PWD:/paddle 指定将宿主机的当前路径（Linux中PWD变量会展开为当前路径的绝对路径）挂载到容器内部的 /paddle 目录；
> paddlepaddle/paddle:1.8.1 是需要使用的image名称；/bin/bash是在Docker中要执行的命令
4. 验证安装
使用 python 或 python3 进入python解释器，输入import paddle.fluid ，再输入 paddle.fluid.install_check.run_check()。
如果出现 Your Paddle Fluid is installed succesfully!，说明您已成功安装。
5. 更多帮助信息请参考：
`使用Docker安装 <install_Docker.html>`_
第四种安装方式：使用源代码编译安装
第二种安装方式：使用源代码编译安装
====================================
- 如果您只是使用 PaddlePaddle ，建议从 **pip** 和 **conda** 、 **docker** 三种安装方式中选取一种进行安装即可。
- 如果您只是使用 PaddlePaddle ，建议使用 **pip** 安装即可。
- 如果您有开发PaddlePaddle的需求，请参考：`从源码编译 <compile/fromsource.html>`_
.. toctree::
......@@ -526,8 +236,6 @@
install_CentOS.md
install_MacOS.md
install_Windows.md
install_Conda.md
install_Docker.md
compile/fromsource.rst
Tables.md
doc/fluid/install/index_en.rst
浏览文件 @ 377f7dd7
......@@ -182,20 +182,14 @@ This section describes how to use pip to install.
If you are using Python 2, command to install CPU version is:
::
python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple
or
python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple
If you are using Python 3, command to install CPU version is:
::
python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple
or
python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple
If you are using Python 3, please change **python** in the above command to **python3** and install.
(2). **GPU version** : If you only want to install GPU version, please refer to command below
......@@ -204,32 +198,14 @@ This section describes how to use pip to install.
* You need to confirm that your GPU meets the requirements listed above
If you are using Python2, please attention that PaddlePaddle installed through command below supports CUDA10.0 under Windows、Ubuntu、CentOS by default:
::
python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
or
python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple
If you are using Python 2, CUDA 9, cuDNN 7.3+, command to install GPU version:
If you are using Python2, please attention that PaddlePaddle installed through command below only supports CUDA10.0 under Windows、Ubuntu、CentOS:
::
python -m pip install paddlepaddle-gpu==1.8.1.post97 -i https://mirror.baidu.com/pypi/simple
python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple
or
python -m pip install paddlepaddle-gpu==1.8.1.post97 -i https://pypi.tuna.tsinghua.edu.cn/simple
If you are using Python 2, CUDA 10.0, cuDNN 7.3+, command to install GPU version:
::
python -m pip install paddlepaddle-gpu==1.8.1.post107 -i https://mirror.baidu.com/pypi/simple
or
python -m pip install paddlepaddle-gpu==1.8.1.post107 -i https://pypi.tuna.tsinghua.edu.cn/simple
python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple
If you are using Python 3, please change **python** in the above command to **python3** and install.
......@@ -251,280 +227,10 @@ This section describes how to use pip to install.
`install under Windows <install_Windows_en.html>`_
The second way to install: use Conda to install
================================
You can choose any of the four ways to install: "use pip to install", "use Conda to install", "use Docker to install", "compiling from the source code"
This section describes how to use Conda to install.
1. You need to confirm that your operating system meets the requirements listed above
2. You need to confirm that your processor meets the requirements listed above
3. Confirm that the Python where you need to install PaddlePaddle is your expected location, because your computer may have multiple Python
3. For domestic users unable to connect to the official source of anaconda, you can add Tsinghua source for installation according to the following command.
::
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/Paddle/
conda config --set show_channel_urls yes
4. If you need to create a new Conda virtual environment specifically for Paddle to use (the environment name after --name, you can choose by yourself):
If you are using Python2 under Window
::
conda create --name paddle python=2.7
activate paddle
If you are using Python2 under MacOS/Linux
::
conda create --name paddle python=2.7
conda activate paddle
If you are using Python3 under Window, note: python3 version can be 3.5.1+/3.6/3.7
::
conda create --name paddle python=3.7
activate paddle
If you are using Python3 under MacOS/Linux, note: python3 version can be 3.5.1+/3.6/3.7
::
conda create --name paddle python=3.7
conda activate paddle
5. Confirm that the Python where you need to install PaddlePaddle is your expected location, because your computer may have multiple Python, enter Anaconda's command-line terminal, enter the following instructions to confirm the Python location
If you use Python 2, use the following command to output Python path. Depending on your environment, you may need to replace Python in all command lines in the description with specific Python path
In the Windows environment, the command to output Python path is:
::
where python
In the MacOS/Linux environment, the command to output Python path is:
::
which python
If you use Python 3, use the following command to output Python path. Depending on your environment, you may need to replace Python3 in all command lines in the description with Python or specific Python path
In the Windows environment, the command to output Python path is:
::
where python3
In the MacOS/Linux environment, the command to output Python path is:
::
which python3
6. Check the version of Python
If you are using Python 2, use the following command to confirm it is 2.7.15+
::
python --version
If you are using Python 3, use the following command to confirm it is 3.5.1+/3.6/3.7
::
python3 --version
7. Check the version of pip and confirm it is 9.0.1+
If you are using Python 2
::
python -m ensurepip
python -m pip --version
If you are using Python 3
::
python3 -m ensurepip
python3 -m pip --version
8. Confirm Python and pip is 64 bit, and the processor architecture is x86_64(or called x64,Intel 64,AMD64) architecture. Currently, PaddlePaddle doesn't support arm64 architecture. The first line below outputs "64bit", and the second line outputs "x86_64", "x64" or "AMD64":
If you are using Python 2
::
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
If you are using Python 3
::
python3 -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
9. If you want to use Conda to install PaddlePaddle, you can directly use commands below:
(1). **CPU version** :If you just want to install the CPU version, please refer to the following command installation
::
conda install paddlepaddle
(2). **GPU version** :If you just want to install the GPU version, please refer to the following command installation
Note:
* You need to confirm that your GPU meets the requirements listed above
If you are using CUDA 8，cuDNN 7.1+, the command to install GPU version:
::
conda install paddlepaddle-gpu cudatoolkit=8.0
If you are using CUDA 9，cuDNN 7.3+, the command to install GPU version:
::
conda install paddlepaddle-gpu cudatoolkit=9.0
If you are using CUDA 10.0，cuDNN 7.3+, the command to install GPU version:：
::
conda install paddlepaddle-gpu cudatoolkit=10.0
10. Verify installation
After the installation is complete, you can use `python` or `python3` to enter the Python interpreter and then use `import paddle.fluid as fluid` and then `fluid.install_check.run_check()` to verify that the installation was successful.
If `Your Paddle Fluid is installed succesfully!` appears, it means the installation was successful.
11. For more information to help, please refer to:
`install under conda <install_Conda_en.html>`_
The third way to install: use Docker to install
================================
You can choose any of the four ways to install: "use pip to install", "use Conda to install", "use Docker to install", "compiling from the source code"
This section describes how to use Docker to install.
If you want to use `docker <https://www.docker.com>`_ to install PaddlePaddle, you can use command below:
1. **CPU version**
(1). At first you need to install `docker <https://www.docker.com>`_
Note:
* CentOS 6 not support docker installation
* processor need supporting MKL
(2). Pull the image of the preinstalled PaddlePaddle:
::
docker pull hub.baidubce.com/paddlepaddle/paddle:1.8.1
(3). Use the image to build and enter the Docker container:
::
docker run --name paddle -it -v dir1:dir2 hub.baidubce.com/paddlepaddle/paddle:1.8.1 /bin/bash
> --name [Name of container] set the name of Docker;
> -it The parameter indicates that the container has been operated interactively with the local machine;
> -v Parameter is used to share files between the host and the container. dir1 is the host directory and dir2 is the directory mounted inside the container. Users can customize their own mounting directory by setting dir1 and dir2.For example, $PWD:/paddle specifies to mount the current path of the host (PWD variable in Linux will expand to the absolute path of the current path) to the /paddle directory inside the container;
> hub.baidubce.com/paddlepaddle/paddle:1.8.1 is the image name you need to use；/bin/bash is the command to be executed in Docker
2. **GPU version**
(1). At first you need to install `nvidia-docker <https://github.com/NVIDIA/nvidia-docker>`_
Note:
* processor need supporting MKL
* Your computer needs to have NVIDIA graphics card supporting CUDA driver
* You need to install `cuDNN <https://docs.nvidia.com/deeplearning/sdk/cudnn-install/>`_ ，version requires 7.3+(For CUDA9/10), 7.1+(For CUDA 8)
* If you need GPU multi-card mode, you need to install `NCCL 2 <https://developer.nvidia.com/nccl/>`_
* Only Ubuntu/CentOS support NCCL 2 technology
* You need to install `CUDA <https://docs.nvidia.com/cuda/cuda-installation-guide-windows/>`_ , depending on your system, there are different requirements for CUDA version:
* Ubuntu/CentOS 7 ，if you use nvidia-docker to install, CUDA 8.0/9.0/9.1/9.2/10.0 is supported
* Windows/MacOS/CentOS 6 not support nvidia-docker to install
(2). Pull the image that supports CUDA 10.0, cuDNN 7.3 + pre installed PaddlePaddle:
::
nvidia-docker pull hub.baidubce.com/paddlepaddle/paddle:1.8.1-gpu-cuda10.0-cudnn7
(3). Use the image to build and enter the docker container:
::
nvidia-docker run --name paddle -it -v dir1:dir2 hub.baidubce.com/paddlepaddle/paddle:1.8.1-gpu-cuda10.0-cudnn7 /bin/bash
> --name [Name of container] set name of Docker;
> -it The parameter indicates that the container has been operated interactively with the local machine;
> -v Parameter is used to share files between the host and the container. dir1 is the host directory and dir2 is the directory mounted inside the container. Users can customize their own mounting directory by setting dir1 and dir2.For example, $PWD:/paddle specifies to mount the current path of the host (PWD variable in Linux will expand to the absolute path of the current path) to the /paddle directory inside the container;
> hub.baidubce.com/paddlepaddle/paddle:1.8.1 is the image name you need to use；/bin/bash is the command to be executed in Docker
Or if you need the version supporting **CUDA 9**, replace **cuda10.0** of the above command with **cuda9.0**
3. If your machine is not in China's mainland , you can pull the image directly from DockerHub:
::
docker run --name paddle -it -v dir1:dir2 paddlepaddle/paddle:1.8.1 /bin/bash
> --name [Name of container] set name of Docker;
> -it The parameter indicates that the container has been operated interactively with the local machine;
> -v Parameter is used to share files between the host and the container. dir1 is the host directory and dir2 is the directory mounted inside the container. Users can customize their own mounting directory by setting dir1 and dir2.For example, $PWD:/paddle specifies to mount the current path of the host (PWD variable in Linux will expand to the absolute path of the current path) to the /paddle directory inside the container;
> paddlepaddle/paddle:1.8.1 is the image name you need to use；/bin/bash is the command to be executed in docker
4. Verify installation
After the installation is complete, you can use `python` or `python3` to enter the Python interpreter and then use `import paddle.fluid as fluid` and then `fluid.install_check.run_check()` to verify that the installation was successful.
If `Your Paddle Fluid is installed succesfully!` appears, it means the installation was successful.
5. For more help, refer to:
`use Docker to install <install_Docker_en.html>`_
The fourth way to install: compile and install with source code
The second way to install: compile and install with source code
====================================
- If you use PaddlePaddle only, we suggest you to choose one of the three installation methods **pip**, **conda**, **docker** to install.
- If you use PaddlePaddle only, we suggest you installation methods **pip** to install.
- If you need to develop PaddlePaddle, please refer to `compile from source code <compile/fromsource.html>`_
.. toctree::
......@@ -534,7 +240,5 @@ The fourth way to install: compile and install with source code
install_CentOS_en.md
install_MacOS_en.md
install_Windows_en.md
install_Conda_en.md
install_Docker_en.md
compile/fromsource_en.rst
Tables_en.md
doc/fluid/install/install_CentOS.md
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......@@ -81,11 +81,9 @@
## 安装方式
CentOS系统下有5种安装方式：
CentOS系统下有3种安装方式：
* pip安装（推荐）
* [conda安装](./install_Conda.html)
* [Docker安装](./install_Docker.html)
* [源码编译安装](./compile/compile_CentOS.html#ct_source)
* [Docker源码编译安装](./compile/compile_CentOS.html#ct_docker)
......@@ -94,11 +92,11 @@ CentOS系统下有5种安装方式：
## 安装步骤
* CPU版PaddlePaddle：
* 对于Python 2： `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 2： `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU版PaddlePaddle：
* 对于Python 2： `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 2： `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
您可[验证是否安装成功](#check)，如有问题请查看[FAQ](./FAQ.html)
......@@ -107,7 +105,7 @@ CentOS系统下有5种安装方式：
* 如果是python2.7, 建议使用`python`命令; 如果是python3.x, 则建议使用`python3`命令
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0 cuDNN v7的PaddlePaddle，如您对CUDA或cuDNN版本有不同要求，可用`python -m pip install paddlepaddle-gpu==[版本号] -i https://pypi.tuna.tsinghua.edu.cn/simple`或 `python3 -m pip install paddlepaddle-gpu==[版本号] -i https://pypi.tuna.tsinghua.edu.cn/simple`命令来安装，版本号请见[这里](https://pypi.org/project/paddlepaddle-gpu#history), 关于paddlepaddle与CUDA, cuDNN版本的对应关系请见[安装包列表](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0 cuDNN v7的PaddlePaddle。
* 默认下载最新稳定版的安装包，如需获取开发版安装包，请参考[这里](./Tables.html#ciwhls)
......
doc/fluid/install/install_CentOS_en.md
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......@@ -81,11 +81,9 @@
## Installation method
There are five installation methods under CentOS system:
There are three installation methods under CentOS system:
* pip installation（recommend）
* [Conda Installation](./install_Conda_en.html)
* [Docker Installation](./install_Docker_en.html)
* [Compile From Source Code](./compile/compile_CentOS_en.html#ct_source)
* [Compile From Docker Source Code](./compile/compile_CentOS_en.html#ct_docker)
......@@ -94,11 +92,11 @@ Here is pip installation
## Installation steps
* CPU version of PaddlePaddle：
* For Python 2: `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 2: `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU version of PaddlePaddle：
* For Python 2： `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 2： `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
You can[Verify installation succeeded or not](#check)，if you have any questions, you can refer to [FAQ](./FAQ.html)
......@@ -108,7 +106,7 @@ Note:
* If it is python2.7, it is recommended to use the `python` command; if it is python3.x, it is recommended to use the 'python3' command
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install the PaddlePaddle that supports CUDA 10.0 cuDNN v7. If you have different requirements for CUDA or cuDNN version, you can use `python -m pip install paddlepaddle-gpu==[Version number] -i https://pypi.tuna.tsinghua.edu.cn/simple` or `python3 -m pip install paddlepaddle-gpu==[version] -i https://pypi.tuna.tsinghua.edu.cn/simple` command to install. For version number, you can see[here](https://pypi.org/project/paddlepaddle-gpu#history), for the correspondence between paddlepaddle and CUDA, cuDNN version, please see [installation package list](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install the PaddlePaddle that supports CUDA 10.0 cuDNN v7.
* Download the latest stable installation package by default. For development installation package, please refer to [here](./Tables.html#ciwhls)
......
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# **使用Conda安装**
[Anaconda](https://www.anaconda.com/)是一个免费开源的Python和R语言的发行版本，用于计算科学，Anaconda致力于简化包管理和部署。Anaconda的包使用软件包管理系统Conda进行管理。Conda是一个开源包管理系统和环境管理系统，可在Windows、macOS和Linux上运行。
## 环境准备
在进行PaddlePaddle安装之前请确保您的Anaconda软件环境已经正确安装。软件下载和安装参见Anaconda官网(https://www.anaconda.com/)。在您已经正确安装Anaconda的情况下请按照下列步骤安装PaddlePaddle。
## 安装步骤
1. 创建虚拟环境
首先根据具体的Python版本创建Anaconda虚拟环境，PaddlePaddle的Anaconda安装支持以下四种Python安装环境。
如果您想使用的python版本为2.7:
conda create -n paddle_env python=2.7
如果您想使用的python版本为3.5:
conda create -n paddle_env python=3.5
如果您想使用的python版本为3.6:
conda create -n paddle_env python=3.6
如果您想使用的python版本为3.7:
conda create -n paddle_env python=3.7
activate paddle_env (for Windows) 或 conda activate paddle_env (for MacOS/Linux) 命令进入Anaconda虚拟环境。
2. 确认您的conda虚拟环境和需要安装PaddlePaddle的Python是您预期的位置，因为您计算机可能有多个Python。进入Anaconda的命令行终端，输入以下指令确认Python位置。
在 Windows 环境下，输出 Python 路径的命令为
where python
在 MacOS/Linux 环境下，输出 Python 路径的命令为
如果您使用 Python 2: which python
如果您使用 Python 3: which python3
根据您的环境，您可能需要将说明中所有命令行中的 python3 替换为 python 或者替换为具体的 Python 路径
3. 检查Python的版本
在 Windows 环境下，使用以下命令确认版本(Python2 应对应 2.7.15+，Python3 应对应 3.5.1+/3.6/3.7)
python --version
在 MacOS/Linux 环境下
如果您是使用 Python 2，使用以下命令确认是 2.7.15+:
python --version
如果您是使用 Python 3，使用以下命令确认是 3.5.1+/3.6/3.7:
python3 --version
4. 确认Python和pip是64bit，并且处理器架构是x86_64（或称作x64、Intel 64、AMD64）架构，目前PaddlePaddle不支持arm64架构。下面的第一行输出的是"64bit"，第二行输出的是"x86_64（或x64、AMD64）"即可：
在 Windows 环境下
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
在 MacOS/Linux 环境下
如果您使用Python2:
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
如果您使用Python3:
python3 -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
5. 安装PaddlePaddle
(1). **CPU版本**：如果您只是想安装CPU版本请参考如下命令安装
conda install paddlepaddle
(2). **GPU版本**：如果您想使用GPU版本请参考如下命令安装
如果您是使用 CUDA 9，cuDNN 7.3+，安装GPU版本的命令为:
conda install paddlepaddle-gpu cudatoolkit=9.0
如果您是使用 CUDA 10.0，cuDNN 7.3+，安装GPU版本的命令为:
conda install paddlepaddle-gpu cudatoolkit=10.0
6. 安装环境验证
使用python进入python解释器，输入import paddle.fluid，再输入 paddle.fluid.install_check.run_check()。如果出现“Your Paddle Fluid is installed succesfully!”，说明您已成功安装。
## 注意
对于国内用户无法连接到Anaconda官方源的可以按照以下命令添加清华源进行安装。
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/Paddle/
conda config --set show_channel_urls yes
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***
# **Conda Installation**
Anaconda is a free and open source distribution of Python and R for computational science. Anaconda is dedicated to simplifying package management and deployment. Anaconda's packages are managed using the package management system Conda. Conda is an open source package management system and environment management system that runs on Windows, macOS, and Linux.
## Environmental preparation
Before performing PaddlePaddle installation, please make sure that your Anaconda software environment is properly installed. For software download and installation, see Anaconda's official website (https://www.anaconda.com/). If you have installed Anaconda correctly, follow these steps to install PaddlePaddle.
## Installation steps
1.Create virtual environment
First create the Anaconda virtual environment according to the specific Python version. The Anaconda installation of PaddlePaddle supports the following four Python installation environments.
If you want to use python version 2.7: `conda create -n paddle_env python=2.7`
If you want to use python version 3.5: `conda create -n paddle_env python=3.5`
If you want to use python version 3.6: `conda create -n paddle_env python=3.6`
If you want to use python version 3.7: `conda create -n paddle_env python=3.7`
Activate paddle_env (for Windows) or conda activate paddle_env (for MacOS / Linux) command to enter the Anaconda virtual environment.
2.Confirm that your conda virtual environment and the Python loaction which is preapared to install PaddlePaddle are where you expected them for your computer may have multiple Pythons environments. Enter Anaconda's command line terminal and enter the following command to confirm the Python location.
If you are using Python 2, use the following command to get the Python path. Depending on your environment, you may need to replace python in all command lines in the instructions with specific Python path.
In a Windows environment, the command to get the Python path is: where python
In a MacOS/Linux environment, the command to get the Python path is: which python
If you are using Python 3, use the following command to get the Python path. Depending on your environment, you may need to replace python in all command lines in the instructions with specific Python path.
In a Windows environment, the command to get the Python path is: where python3
In a MacOS/Linux environment, the command to get the Python path is: which python3
3.Check the version of Python
If you are using Python 2, use the following command to confirm it's version is 2.7.15+
python --version
If you are using Python 3, use the following command to confirm it's version is 3.5.1+/3.6/3.7
python3 --version
Confirm that Python and pip are 64bit, and the processor architecture is x86_64 (or x64, Intel 64, AMD64) architecture. Currently PaddlePaddle does not support arm64 architecture. The first line below print "64bit", the second line prints "x86_64 (or x64, AMD64)."
If you are using Python2:
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
If you are using Python3:
python3 -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
5.Install PaddlePaddle
> (1) CPU version: If you just want to install the CPU version, please refer to the following command to install:
conda install paddlepaddle
> (2) GPU version: If you want to use the GPU version, please refer to the following command to install:
If you are using CUDA 9, cuDNN 7.3+, the command to install the GPU version is:
conda install paddlepaddle-gpu cudatoolkit=9.0
If you are using CUDA 10.0, cuDNN 7.3+, the command to install the GPU version is:
conda install paddlepaddle-gpu cudatoolkit=10.0
6.Installation environment verification
Use python to enter the python interpreter, enter import paddle.fluid, and then enter paddle.fluid.install_check.run_check (). If "Your Paddle Fluid is installed succesfully!" Appears, you have successfully installed.
## Notice
For domestic users who cannot connect to the Anaconda official source, you can add Tsinghua source to install it according to the following command.
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/Paddle/
conda config --set show_channel_urls yes
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# **使用Docker安装**
[Docker](https://docs.docker.com/install/)是一个开源的应用容器引擎。使用Docker，既可以将PaddlePaddle的安装&使用与系统环境隔离，也可以与主机共享GPU、网络等资源
## 环境准备
- 目前支持的系统类型，请见[安装说明](./index_cn.html)，请注意目前暂不支持在CentOS 6使用Docker
- 在本地主机上[安装Docker](https://hub.docker.com/search/?type=edition&offering=community)
- 如需在Linux开启GPU支持，请[安装nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
## 安装步骤
1. 拉取PaddlePaddle镜像
* CPU版的PaddlePaddle： `docker pull hub.baidubce.com/paddlepaddle/paddle:[版本号]`
* GPU版的PaddlePaddle： `docker pull hub.baidubce.com/paddlepaddle/paddle:[版本号]-gpu-cuda9.0-cudnn7`
如果您的机器不在中国大陆地区，可以直接从DockerHub拉取镜像：
* CPU版的PaddlePaddle： `docker pull paddlepaddle/paddle:[版本号]`
* GPU版的PaddlePaddle： `docker pull paddlepaddle/paddle:[版本号]-gpu-cuda9.0-cudnn7`
在`:`后请您填写PaddlePaddle版本号，例如当前版本，更多请见[镜像简介](#dockers)，上例中，`cuda9.0-cudnn7` 也仅作示意用，您可以访问[DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/)获取与您机器适配的镜像。
2. 构建、进入Docker容器
* 使用CPU版本的PaddlePaddle：
`docker run --name [Name of container] -it -v $PWD:/paddle <imagename> /bin/bash`
> --name [Name of container] 设定Docker的名称；
> -it 参数说明容器已和本机交互式运行；
> -v $PWD:/paddle 指定将当前路径（Linux中PWD变量会展开为当前路径的绝对路径）挂载到容器内部的 /paddle 目录；
> `<imagename>` 指定需要使用的image名称，您可以通过`docker images`命令查看；/bin/bash是在Docker中要执行的命令
* 使用GPU版本的PaddlePaddle：
`nvidia-docker run --name [Name of container] -it -v $PWD:/paddle <imagename> /bin/bash`
> --name [Name of container] 设定Docker的名称；
> -it 参数说明容器已和本机交互式运行；
> -v $PWD:/paddle 指定将当前路径（Linux中PWD变量会展开为当前路径的绝对路径）挂载到容器内部的 /paddle 目录；
> `<imagename>` 指定需要使用的image名称，您可以通过`docker images`命令查看；/bin/bash是在Docker中要执行的命令
至此，您已经成功使用Docker安装PaddlePaddle，更多Docker使用请参见[Docker官方文档](https://docs.docker.com)
<a name="dockers"></a>
</br></br>
### **镜像简介**
<p align="center">
<table>
<thead>
<tr>
<th> 镜像源 </th>
<th> 镜像说明 </th>
</tr>
</thead>
<tbody>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:[Version] </td>
<td> 安装了指定版本PaddlePaddle </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest </td>
<td> 安装了开发版PaddlePaddle。注意：此版本可能包含尚未发布的特性和不稳定的功能，因此不推荐常规用户或在生产环境中使用。 </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest-gpu </td>
<td> 安装了开发版PaddlePaddle（支持GPU）。注意：此版本可能包含尚未发布的特性和不稳定的功能，因此不推荐常规用户或在生产环境中使用。 </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest-dev </td>
<td> 安装了PaddlePaddle最新的开发环境 </td>
</tr>
</tbody>
</table>
</p>
您可以在 [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/) 中找到PaddlePaddle的各个发行的版本的docker镜像。
### 注意事项
* 镜像中Python版本为2.7
* PaddlePaddle Docker镜像为了减小体积，默认没有安装`vim`，您可以在容器中执行 `apt-get install -y vim` 安装后，在容器中编辑代码
### 补充说明
* 当您需要第二次进入Docker容器中，使用如下命令：
```
#启动之前创建的容器
docker start [Name of container]
#进入启动的容器
docker attach [Name of container]
```
* 如您是Docker新手，您可以参考互联网上的资料学习，例如[Docker教程](http://www.runoob.com/docker/docker-hello-world.html)
## 如何卸载
请您进入Docker容器后，执行如下命令
* **CPU版本的PaddlePaddle**: `pip uninstall paddlepaddle`
* **GPU版本的PaddlePaddle**: `pip uninstall paddlepaddle-gpu`
或通过`docker rm [Name of container]`来直接删除Docker容器
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# **Docker Installation**
[Docker](https://docs.docker.com/install/) is an open source application container engine. Using docker, you can not only isolate the installation and use of paddlepaddle from the system environment, but also share GPU, network and other resources with the host
## Environment preparation
- Currently supported system types, please see [Installation instruction](./index_cn.html), please note that Docker is not currently supported in CentOS 6
- On the local host [Install Docker](https://hub.docker.com/search/?type=edition&offering=community)
- To enable GPU support on Linux, please [Install nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
## Installation steps
1. Pull PaddlePaddle image
* CPU version of PaddlePaddle： `docker pull hub.baidubce.com/paddlepaddle/paddle:[version number]`
* GPU version of PaddlePaddle： `docker pull hub.baidubce.com/paddlepaddle/paddle:[version number]-gpu-cuda9.0-cudnn7`
If your machine is not in mainland China, you can pull the image directly from DockerHub:
* CPU version of PaddlePaddle： `docker pull paddlepaddle/paddle:[version number]`
* GPU version of PaddlePaddle： `docker pull paddlepaddle/paddle:[version number]-gpu-cuda9.0-cudnn7`
After `:', please fill in the PaddlePaddle version number, such as the current version. For more details, please refer to [image profile](#dockers), in the above example, `cuda9.0-cudnn7` is only for illustration. you can see [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/) to get the image that matches your machine.
2. Build and enter Docker container
* Use CPU version of PaddlePaddle：
`docker run --name [Name of container] -it -v $PWD:/paddle <imagename> /bin/bash`
> --name [Name of container] set name of Docker;
> -it The parameter indicates that the container has been operated interactively with the local machine;
> -v $PWD:/paddle specifies to mount the current path of the host (PWD variable in Linux will expand to the absolute path of the current path) to the /paddle directory inside the container;
> `<imagename>` Specify the name of the image to be used. You can view it through the 'docker images' command. /bin/Bash is the command to be executed in Docker
* Use GPU version of PaddlePaddle：
`nvidia-docker run --name [Name of container] -it -v $PWD:/paddle <imagename> /bin/bash`
> --name [Name of container] set name of Docker;
> -it The parameter indicates that the container has been operated interactively with the local machine;
> -v $PWD:/paddle specifies to mount the current path of the host (PWD variable in Linux will expand to the absolute path of the current path) to the /paddle directory inside the container;
> `<imagename>` Specify the name of the image to be used. You can view it through the 'docker images' command. /bin/Bash is the command to be executed in Docker
Now you have successfully used Docker to install PaddlePaddle. For more information about using Docker, see[Docker official documents](https://docs.docker.com)
<a name="dockers"></a>
</br></br>
### **Introduction to mirror images**
<p align="center">
<table>
<thead>
<tr>
<th> Mirror source </th>
<th> Mirror description </th>
</tr>
</thead>
<tbody>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:[Version] </td>
<td> Install pecified version of PaddlePaddle </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest </td>
<td> Install development version of PaddlePaddle。Note: This release may contain features and unstable features that have not yet been released, so it is not recommended for regular users or production environments. </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest-gpu </td>
<td> Install development of PaddlePaddle(support GPU). Note: This release may contain features and unstable features that have not yet been released, so it is not recommended for regular users or production environments. </td>
</tr>
<tr>
<td> hub.baidubce.com/paddlepaddle/paddle:latest-dev </td>
<td> Install the latest development environment of PaddlePaddle </td>
</tr>
</tbody>
</table>
</p>
You can find the docker mirroring of the published versions of PaddlePaddle in [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/).
### Note
* Python version in the image is 2.7
* In order to reduce the size, `vim` is not installed in PaddlePaddle Docker image by default. You can edit the code in the container after executing `apt-get install -y vim` in the container.
### 补充说明
* When you need to enter the docker container for the second time, use the following command:
```
#Container created before startup
docker start [Name of container]
#Enter the starting container
docker attach [Name of container]
```
* If you are a newcomer to Docker, you can refer to the materials on the Internet for learning, such as [Docker tutorial](http://www.runoob.com/docker/docker-hello-world.html)
## How to uninstall
After entering the Docker container, execute the following command:
* **CPU version of PaddlePaddle**: `pip uninstall paddlepaddle`
* **GPU version of PaddlePaddle**: `pip uninstall paddlepaddle-gpu`
Or delete the docker container directly through `docker rm [Name of container]`
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......@@ -60,11 +60,9 @@
## 安装方式
MacOS系统下有5种安装方式：
MacOS系统下有3种安装方式：
* pip安装（推荐）
* [conda安装](./install_Conda.html)
* [Docker安装](./install_Docker.html)
* [源码编译安装](./compile/compile_MacOS.html#mac_source)
* [Docker源码编译安装](./compile/compile_MacOS.html#mac_docker)
......@@ -74,8 +72,8 @@ MacOS系统下有5种安装方式：
## 安装步骤
* CPU版PaddlePaddle：
* 对于Python 2： `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 2： `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
您可[验证是否安装成功](#check)，如有问题请查看[FAQ](./FAQ.html)
......
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......@@ -61,11 +61,9 @@
## Choose an installation method
Under the MacOS system we offer 5 installation methods:
Under the MacOS system we offer 3 installation methods:
* Pip installation (recommend)
* [Conda installation](./install_Conda.html)
* [Docker installation](./install_Docker.html)
* [Source code compilation and installation](./compile/compile_MacOS.html#mac_source)
* [Docker source code compilation and installation](./compile/compile_MacOS.html#mac_docker)
......@@ -75,8 +73,8 @@ We will introduce pip installation here.
## Installation steps
* CPU version of PaddlePaddle：
* For Python 2: `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3: `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 2: `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3: `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
You can[Verify installation succeeded or not](#check), if you have any questions, please check[FAQ](./FAQ.html)
......
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......@@ -82,11 +82,9 @@
## 安装方式
Ubuntu系统下有5种安装方式：
Ubuntu系统下有3种安装方式：
* pip安装（推荐）
* [conda安装](./install_Conda.html)
* [Docker安装](./install_Docker.html)
* [源码编译安装](./compile/compile_Ubuntu.html#ubt_source)
* [Docker源码编译安装](./compile/compile_Ubuntu.html#ubt_docker)
......@@ -95,12 +93,12 @@ Ubuntu系统下有5种安装方式：
## 安装步骤
* CPU版PaddlePaddle：
* 对于Python 2： `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 2： `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU版PaddlePaddle：
* 对于Python 2： `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 2： `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* 对于Python 3： `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
您可[验证是否安装成功](#check)，如有问题请查看[FAQ](./FAQ.html)
......@@ -108,7 +106,7 @@ Ubuntu系统下有5种安装方式：
* 如果是python2.7, 建议使用`python`命令; 如果是python3.x, 则建议使用`python3`命令
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0 cuDNN v7的PaddlePaddle，如您对CUDA或cuDNN版本有不同要求，可用`python -m pip install paddlepaddle-gpu==[版本号] -i https://pypi.tuna.tsinghua.edu.cn/simple`或 `python3 -m pip install paddlepaddle-gpu==[版本号] -i https://pypi.tuna.tsinghua.edu.cn/simple`命令来安装，版本号请见[这里](https://pypi.org/project/paddlepaddle-gpu#history)，关于paddlepaddle与CUDA, cuDNN版本的对应关系请见[安装包列表](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0 cuDNN v7的PaddlePaddle。
* 默认下载最新稳定版的安装包，如需获取开发版安装包，请参考[这里](./Tables.html#ciwhls)
......
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......@@ -82,11 +82,9 @@
## Choose an installation method
Under the Ubuntu system, we offer 5 installation methods:
Under the Ubuntu system, we offer 3 installation methods:
* Pip installation (recommended)
* [Conda安装](./install_Conda.html)
* [Docker installation](./install_Docker.html)
* [Source code compilation and installation](./compile/compile_Ubuntu.html#ubt_source)
* [Docker source code compilation and installation](./compile/compile_Ubuntu.html#ubt_docker)
......@@ -95,12 +93,12 @@ We will introduce pip installation here.
## Installation steps
* CPU version of PaddlePaddle：
* For Python 2： `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 2： `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU version PaddlePaddle：
* For Python 2： `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 2： `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* For Python 3： `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` or `python3 -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
You can [verify whether the installation is successful](#check), if you have any questions please see [FAQ](./FAQ.html)
......@@ -108,7 +106,7 @@ Note:
* For python2.7, we recommend to use `python` command; For python3.x, we recommend to use `python3` command.
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install PaddlePaddle supporting CUDA 10.0 cuDNN v7, if you have different requirement to the version of CUDA or cuDNN, you can use `python -m pip install paddlepaddle-gpu==[version number] -i https://pypi.tuna.tsinghua.edu.cn/simple` or `python3 -m pip install paddlepaddle-gpu==[version number] -i https://pypi.tuna.tsinghua.edu.cn/simple` command to install, for version number please see[version number](https://pypi.org/project/paddlepaddle-gpu#history), for correspondence between paddlepaddle and CUDA and cuDNN version, please see [Installation package list](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install PaddlePaddle supporting CUDA 10.0 cuDNN v7.
* Download the latest stable installation package by default. For development installation package, please refer to[here](./Tables.html#ciwhls)
......
doc/fluid/install/install_Windows.md
浏览文件 @ 377f7dd7
......@@ -58,10 +58,9 @@
## 安装方式
Windows系统下有3种安装方式：
Windows系统下有2种安装方式：
* pip安装（推荐）
* [conda安装](./install_Conda.html)
* [源码编译安装](./compile/compile_Windows.html#win_source)
这里为您介绍pip安装方式
......@@ -69,16 +68,16 @@ Windows系统下有3种安装方式：
## 安装步骤
* CPU版PaddlePaddle：
* `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple`（推荐使用百度源） 或 `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple`（推荐使用百度源） 或 `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU版PaddlePaddle：
* `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple` 或 `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
您可[验证是否安装成功](#check)，如有问题请查看[FAQ](./FAQ.html)
注：
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0(配合cuDNN v7.3+)的PaddlePaddle，如您对CUDA或cuDNN版本有不同要求，可用`python -m pip install paddlepaddle-gpu==[版本号] -i https://pypi.tuna.tsinghua.edu.cn/simple`命令来安装，版本号请见[这里](https://pypi.org/project/paddlepaddle-gpu#history), 关于paddlepaddle与CUDA, cuDNN版本的对应关系请见[安装包列表](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` 此命令将安装支持CUDA 10.0(配合cuDNN v7.3+)的PaddlePaddle。
<a name="check"></a>
......
doc/fluid/install/install_Windows_en.md
浏览文件 @ 377f7dd7
......@@ -59,10 +59,9 @@ Please refer to the NVIDIA official documents for the installation process and t
## Installation Method
There are 3 ways to install PaddlePaddle on Windows:
There are 2 ways to install PaddlePaddle on Windows:
* pip installation (recommended)
* [Docker installation](./install_Docker.html)
* [source code compilation and installation](./compile/compile_Windows.html/#win_source)
We would like to introduce the pip installation here.
......@@ -70,16 +69,16 @@ We would like to introduce the pip installation here.
## Installation steps
* CPU version of PaddlePaddle:
* `python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple`(Baidu source is recommended) or `python -m pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple`
* `python -m pip install paddlepaddle==2.0.0a0 -i https://mirror.baidu.com/pypi/simple`(Baidu source is recommended) or `python -m pip install paddlepaddle==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
* GPU version of PaddlePaddle:
* `python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple`(Baidu source is recommended) or `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple`
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://mirror.baidu.com/pypi/simple`(Baidu source is recommended) or `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple`
There is a checking function below for [verifyig whether the installation is successful](#check). If you have any further questions, please check the [FAQ](./FAQ.html).
Notice:
* `python -m pip install paddlepaddle-gpu -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install PaddlePaddle that supports CUDA 10.0(with cuDNN v7.3+). If you have different requirements for the version of CUDA or cuDNN, you can use command `python -m pip install paddlepaddle-gpu==[version number] -i https://pypi.tuna.tsinghua.edu.cn/simple` to install, and you can see the version [here](https://pypi.org/project/paddlepaddle-gpu#history). For the corresponding relations between PaddlePaddle and CUDA, cuDNN version, please see the [installer package list](./Tables.html#whls)
* `python -m pip install paddlepaddle-gpu==2.0.0a0 -i https://pypi.tuna.tsinghua.edu.cn/simple` This command will install PaddlePaddle that supports CUDA 10.0(with cuDNN v7.3+).
<a name="check"></a>
## Installation Verification
After completing the installation process, you can use `python` to enter python interface and input `import paddle.fluid as fluid` and then `fluid.install_check.run_check()` to check whether the installation is successful.
......@@ -90,4 +89,4 @@ If you see `Your Paddle Fluid is installed succesfully!`, your installation is v
* ***CPU version of PaddlePaddle***: `python -m pip uninstall paddlepaddle`
* ***GPU version of PaddlePaddle***: `python -m pip uninstall paddlepaddle-gpu`
\ No newline at end of file
* ***GPU version of PaddlePaddle***: `python -m pip uninstall paddlepaddle-gpu`
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