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<a name="third_party"></a>
# Appendix


## Compile Dependency Table

<p align="center">
<table>
    <thead>
    <tr>
        <th> Dependency package name </th>
        <th> Version </th>
        <th> Description </th>
        <th> Installation command </th>
    </tr>
    </thead>
    <tbody>
    <tr>
        <td> CMake </td>
        <td> 3.4 </td>
        <td>  </td>
        <td>  </td>
    </tr>
    <tr>
        <td> GCC </td>
        <td> 4.8 / 5.4 </td>
        <td>  recommends using devtools2 for CentOS </td>
        <td>  </td>
29 30 31 32 33 34
    </tr>
    <tr>
		<td> Clang (MacOS Only) </td>
		<td> 9.0 and above </td>
		<td> Usually use the clang version of MacOS 10.11 and above </td>
		<td>  </td>
35 36
    </tr>
        <tr>
37 38 39 40
        <td> Python(64 bit) </td>
        <td> 2.7.x. or 3.5+.x </td>
        <td> depends on libpython2.7.so or libpython3.5+.so </td>
        <td> <code> apt install python-dev </code> or <code> yum install python-devel </code> if installing python3, please go to <a href="https://www.python.org">Python official website </a></td>
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    </tr>
    <tr>
        <td> SWIG </td>
        <td> at least 2.0 </td>
        <td>  </td>
        <td> <code>apt install swig </code> or <code> yum install swig </code> </td>
    </tr>
    <tr>
        <td> wget </td>
        <td> any </td>
        <td>  </td>
        <td> <code> apt install wget </code>  or <code> yum install wget </code> </td>
    </tr>
    <tr>
        <td> openblas </td>
        <td> any </td>
57
        <td> optional </td>
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        <td>  </td>
    </tr>
    <tr>
        <td> pip </td>
        <td> at least 9.0.1 </td>
        <td>  </td>
        <td> <code> apt install python-pip </code> or <code> yum install Python-pip </code> </td>
    </tr>
    <tr>
        <td> numpy </td>
        <td> >=1.12.0 </td>
        <td>  </td>
70
        <td> <code> pip install numpy </code> </td>
71 72 73
    </tr>
    <tr>
        <td> protobuf </td>
74
        <td> >=3.1.0 </td>
75
        <td>  </td>
76
        <td> <code> pip install protobuf </code> </td>
77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
    </tr>
    <tr>
        <td> wheel </td>
        <td> any </td>
        <td>  </td>
        <td> <code> pip install wheel </code> </td>
    </tr>
    <tr>
        <td> patchELF </td>
        <td> any </td>
        <td>  </td>
        <td> <code> apt install patchelf </code> or read github <a href="https://gist.github.com/ruario/80fefd174b3395d34c14">patchELF official documentation</a></td>
    </tr>
    <tr>
        <td> go </td>
        <td> >=1.8 </td>
        <td> optional </td>
        <td>  </td>
    </tr>
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    <tr>
		<td> setuptools </td>
		<td> >= 28.0.0 </td>
		<td> </td>
		<td>  </td>
    </tr>
    <tr>
		<td> unrar </td>
		<td>  </td>
		<td> </td>
		<td> brew install unrar (For MacOS), apt-get install unrar (For Ubuntu) </td>
	</tr>
108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177
    </tbody>
</table>
</p>


<a name="Compile"></a>
</br></br>
## **Compile Option Table**

<p align="center">
<table>
    <thead>
    <tr>
        <th> Option </th>
        <th> Description  </th>
        <th> Default </th>
    </tr>
    </thead>
    <tbody>
    <tr>
        <td> WITH_GPU </td>
        <td> Whether to support GPU </td>
        <td> ON </td>
    </tr>
    <tr>
        <td> WITH_DSO </td>
        <td> whether to load CUDA dynamic libraries dynamically at runtime, instead of statically loading CUDA dynamic libraries. </td>
        <td> ON </td>
    </tr>
    <tr>
        <td> WITH_AVX </td>
        <td> whether to compile PaddlePaddle binaries file containing the AVX instruction set </td>
        <td> ON </td>
    </tr>
    <tr>
        <td> WITH_PYTHON </td>
        <td> Whether the PYTHON interpreter is embedded </td>
        <td> ON </td>
    </tr>
    <tr>
        <td> WITH_TESTING </td>
        <td>  Whether to turn on unit test </td>
        <td> OFF </td>
    </tr>
    <tr>
        <td> WITH_MKL </td>
        <td> Whether to use the MKL math library, if not,using OpenBLAS </td>
        <td> ON </td>
    </tr>
    <tr>
        <td> WITH_SYSTEM_BLAS </td>
        <td> Whether to use the system's BLAS </td>
        <td> OFF </td>
    </tr>
    <tr>
        <td> WITH_DISTRIBUTE </td>
        <td> Whether to Compile with distributed version </td>
        <td> OFF </td>
    </tr>
    <tr>
        <td> WITH_BRPC_RDMA </td>
        <td> Whether to use BRPC RDMA as RPC protocol </td>
        <td> OFF </td>
    </tr>
        <tr>
        <td> ON_INFER </td>
        <td> Whether to turn on prediction optimization </td>
        <td> OFF </td>
    </tr>
    <tr>
178 179 180 181
        <tr>
        <td> CUDA_ARCH_NAME </td>
        <td> Compile only for current CUDA schema or not</td>
        <td> All:Compile all supported CUDA architectures  optional: Auto automatically recognizes the schema compilation of the current environment</td>
182
    </tr>
183 184 185 186 187 188 189
    <tr>
        <tr>
        <td> TENSORRT_ROOT </td>
        <td> Specify TensorRT path </td>
        <td> The default value under windows is '/', The default value under windows is '/usr/' </td>
    </tr>

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**BLAS**

PaddlePaddle supports two BLAS libraries, [MKL](https://software.intel.com/en-us/mkl) and [OpenBlAS](http://www.openblas.net/). MKL is used by default. If you use MKL and the machine contains the AVX2 instruction set, you will also download the MKL-DNN math library, for details please refer to [here](https://github.com/PaddlePaddle/Paddle/tree/release/0.11.0/doc/design/mkldnn#cmake).

If you close MKL, OpenBLAS will be used as the BLAS library.

**CUDA/cuDNN**

PaddlePaddle automatically finds the CUDA and cuDNN libraries installed in the system for compilation and execution at compile time/runtime. Use the parameter `-DCUDA_ARCH_NAME=Auto` to specify to enable automatic detection of the SM architecture and speed up compilation.

PaddlePaddle can be compiled and run using any version after cuDNN v5.1, but try to keep the same version of cuDNN in the compiling and running processes. We recommend using the latest version of cuDNN.

**Configure Compile Options**

PaddePaddle implements references to various BLAS/CUDA/cuDNN libraries by specifying paths at compile time. When cmake compiles, it first searches the system paths ( `/usr/liby` and `/usr/local/lib` ) for these libraries, and also reads the relevant path variables for searching. Can be set by using the `-D` command, for example:

> `Cmake .. -DWITH_GPU=ON -DWITH_TESTING=OFF -DCUDNN_ROOT=/opt/cudnnv5`

**Note**: The settings introduced here for these compilation options are only valid for the first cmake. If you want to reset it later, it is recommended to clean up the entire build directory ( rm -rf ) and then specify it.


<a name="whls"></a>
</br></br>
## **Installation Package List**


<p align="center">
<table>
    <thead>
    <tr>
        <th> Version Number </th>
        <th> Release Discription </th>
    </tr>
    </thead>
    <tbody>
    <tr>
228
        <td> paddlepaddle==[version code] such as paddlepaddle==1.7.2 </td>
229 230 231
        <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>
232
        <td> paddlepaddle-gpu==[version code], such as paddlepaddle-gpu==1.7.2 </td>
233
        <td> The default installation supports the PaddlePaddle installation package corresponding to [version number] of CUDA 10.0 and cuDNN 7 </td>
234 235
    </tr>
    <tr>
236
        <td> paddlepaddle-gpu==[version code].postXX, such as paddlepaddle-gpu==1.7.2.post97 </td>
237
        <td> Installation package supporting the corresponding PaddlePaddle version of CUDA 9.0 and cuDNN 7 </td>
238 239 240 241 242 243
    </tr>
   </tbody>
</table>
</p>

You can find various distributions of PaddlePaddle-gpu in [the Release History](https://pypi.org/project/paddlepaddle-gpu/#history).
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> '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.
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249
<a name="ciwhls-release"></a>
250
</br></br>
251 252 253

## **Multi-version whl package list - Release**

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<p align="center">
<table>
    <thead>
    <tr>
259 260 261 262 263 264
        <th> Release Instruction </th>
        <th> cp27-cp27mu </th>
        <th> cp27-cp27m </th>
        <th> cp35-cp35m </th>
        <th> cp36-cp36m </th>
        <th> cp37-cp37m </th>
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    </tr>
    </thead>
    <tbody>
    <tr>
269
		<td> cpu-mkl </td>
270 271 272 273 274 275 276 277 278 279
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mkl/paddlepaddle-1.7.2-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mkl/paddlepaddle-1.7.2-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mkl/paddlepaddle-1.7.2-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mkl/paddlepaddle-1.7.2-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mkl/paddlepaddle-1.7.2-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
280 281 282
	</tr>
	<tr>
		<td> cpu-openblas </td>
283 284 285 286 287 288 289 290 291
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-openblas/paddlepaddle-1.7.2-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-openblas/paddlepaddle-1.7.2-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-openblas/paddlepaddle-1.7.2-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-openblas/paddlepaddle-1.7.2-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-openblas/paddlepaddle-1.7.2-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
292 293
	</tr>
	<tr>
294 295 296 297 298 299
		<td> cuda9-cudnn7-openblas </td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
300 301 302
	</tr>
	<tr>
		<td> cuda9-cudnn7-mkl </td>
303 304 305 306 307
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post97-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post97-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post97-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post97-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post97-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
308 309 310
	</tr>
	<tr>
		<td> cuda10_cudnn7-mkl </td>
311 312 313 314 315 316 317
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post107-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post107-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post107-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post107-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-1.7.2.post107-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
318 319 320 321
	</tr>
	<tr>
		<td> win_cpu_mkl </td>
		<td> - </td>
322 323 324 325 326 327 328 329
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle-1.7.2-cp27-cp27m-win_amd64.whl">
		paddlepaddle-1.7.2-cp27-cp27m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle-1.7.2-cp35-cp35m-win_amd64.whl">
		paddlepaddle-1.7.2-cp35-cp35m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle-1.7.2-cp36-cp36m-win_amd64.whl">
		paddlepaddle-1.7.2-cp36-cp36m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle-1.7.2-cp37-cp37m-win_amd64.whl">
		paddlepaddle-1.7.2-cp37-cp37m-win_amd64.whl</a></td>
330 331 332 333
	</tr>
	<tr>
		<td> win_cuda9_cudnn7_mkl </td>
		<td> - </td>
334 335 336 337 338 339 340 341
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post97-cp27-cp27m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp27-cp27m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post97-cp35-cp35m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp35-cp35m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post97-cp36-cp36m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp36-cp36m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post97-cp37-cp37m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp37-cp37m-win_amd64.whl</a></td>
342 343 344 345
	</tr>  
	<tr>
		<td> win_cuda10_cudnn7_mkl </td>
		<td> - </td>
346 347 348 349 350 351 352 353
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post107-cp27-cp27m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp27-cp27m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post107-cp35-cp35m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp35-cp35m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post107-cp36-cp36m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp36-cp36m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-mkl/paddlepaddle_gpu-1.7.2.post107-cp37-cp37m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp37-cp37m-win_amd64.whl</a></td>
354 355 356 357
	</tr>
	<tr>
		<td> win_cpu_openblas </td>
		<td> - </td>
358 359 360 361 362 363 364 365
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle-1.7.2-cp27-cp27m-win_amd64.whl">
		paddlepaddle-1.7.2-cp27-cp27m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle-1.7.2-cp35-cp35m-win_amd64.whl">
		paddlepaddle-1.7.2-cp35-cp35m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle-1.7.2-cp36-cp36m-win_amd64.whl">
		paddlepaddle-1.7.2-cp36-cp36m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle-1.7.2-cp37-cp37m-win_amd64.whl">
		paddlepaddle-1.7.2-cp37-cp37m-win_amd64.whl</a></td>
366 367 368 369
	</tr>  
	<tr>
		<td> win_cuda9_cudnn7_openblas </td>
		<td> - </td>
370 371 372 373 374 375 376 377
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle_gpu-1.7.2.post97-cp27-cp27m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp27-cp27m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle_gpu-1.7.2.post97-cp35-cp35m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp35-cp35m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle_gpu-1.7.2.post97-cp36-cp36m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp36-cp36m-win_amd64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2/win-open/paddlepaddle_gpu-1.7.2.post97-cp37-cp37m-win_amd64.whl">
		paddlepaddle_gpu-1.7.2-cp37-cp37m-win_amd64.whl</a></td>
378 379 380 381
	</tr>  
	<tr>
		<td> mac_cpu </td>
		<td> - </td>
382 383 384 385 386 387 388 389
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mac/paddlepaddle-1.7.2-cp27-cp27m-macosx_10_6_intel.whl">
		paddlepaddle-1.7.2-cp27-cp27m-macosx_10_6_intel.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mac/paddlepaddle-1.7.2-cp35-cp35m-macosx_10_6_intel.whl">
		paddlepaddle-1.7.2-cp35-cp35m-macosx_10_6_intel.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mac/paddlepaddle-1.7.2-cp36-cp36m-macosx_10_6_intel.whl">
		paddlepaddle-1.7.2-cp36-cp36m-macosx_10_6_intel.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-cpu-mac/paddlepaddle-1.7.2-cp37-cp37m-macosx_10_6_intel.whl">
		paddlepaddle-1.7.2-cp37-cp37m-macosx_10_6_intel.whl</a></td>
390
	</tr>
391 392 393 394 395
   </tbody>
</table>
</p>


396
### Table instruction
397

398
- Vertical axis
399

400
cpu-mkl: Support CPU training and prediction, use Intel MKL math library
401

402 403 404
cpu-openblas: Support CPU training and prediction, use openblas math library

cuda9-cudnn7-openblas: Support GPU training and prediction, use openblas math library
405

406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440
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


- Transverse axis

Generally, it is similar to "cp27-cp27mu", in which:

27:python tag, refers to python2. Similarly, there are "35", "36", "37", etc

mu:refers to unicode version python, if it is m, refers to non Unicode version Python

- Installation package naming rules

Each installation package has a unique name. They are named according to the official rules of Python. The form is as follows:

{distribution}-{version}(-{build tag})?-{python tag}-{abi tag}-{platform tag}.whl

The build tag can be missing, and other parts cannot be missing

distribution: wheel name

version: Version, for example 0.14.0 (must be in numeric format)

python tag: similar to 'py27', 'py2', 'py3', used to indicate the corresponding Python version

abi tag: similar to 'cp33m', 'abi3', 'none'

platform tag: similar to 'linux_x86_64', 'any'


<a name="ciwhls"></a>
</br></br>
## **Multi-version whl package list - dev**
441 442
<p align="center">
<table>
443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480
	<thead>
	<tr>
		<th> version number </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/0.0.0-cpu-mkl/paddlepaddle-0.0.0-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-mkl/paddlepaddle-0.0.0-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-mkl/paddlepaddle-0.0.0-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-mkl/paddlepaddle-0.0.0-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-mkl/paddlepaddle-0.0.0-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cpu-openblas </td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-openblas/paddlepaddle-0.0.0-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-openblas/paddlepaddle-0.0.0-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-openblas/paddlepaddle-0.0.0-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-openblas/paddlepaddle-0.0.0-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-cpu-openblas/paddlepaddle-0.0.0-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda9-cudnn7-openblas </td>
481 482 483 484 485
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-0.0.0-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-0.0.0-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-0.0.0-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-0.0.0-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-openblas/paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504
	</tr>
	<tr>
		<td> cuda9-cudnn7-mkl </td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda10-cudnn7-mkl </td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
505 506 507 508 509
   </tbody>
</table>
</p>


510
<a name="ciwhls-gcc8.2-develop"></a>
511
</br></br>
512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541
## **Multi-version whl package list(gcc8.2)-develop**
<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/0.0.0-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle_gpu-0.0.0-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle_gpu-0.0.0-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle_gpu-0.0.0-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-0.0.0-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
   </tbody>
</table>
</p>
542 543


544 545 546
<a name="ciwhls-gcc8.2-release"></a>
</br></br>
## **Multi-version whl package list(gcc8.2)-release**
547 548
<p align="center">
<table>
549 550 551 552 553 554 555 556 557 558 559 560 561
	<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>
562 563 564 565 566 567 568 569 570 571
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="https://paddle-wheel.bj.bcebos.com/1.7.2-gpu-cuda10.1-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.7.2-cp37-cp37m-linux_x86_64.whl</a></td>
572
	</tr>
573 574 575 576
   </tbody>
</table>
</p>

577
<!--TODO this part should be in a new webpage-->
578 579 580

</br></br>

581

582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643
## Execute the PaddlePaddle training program in Docker


Suppose you have written a PaddlePaddle program in the current directory (such as /home/work): `train.py` ( refer to [PaddlePaddleBook](https://github.com/PaddlePaddle/book/blob/develop/01.fit_a_line/README.cn.md) to write), you can start the training with the following command:


    cd /home/work
    docker run -it -v $PWD:/work hub.baidubce.com/paddlepaddle/paddle /work/train.py


In the above commands, the `-it` parameter indicates that the container has been run interactively; `-v $PWD:/work` specifies that the current path (the absolute path where the PWD variable in Linux will expand to the current path) is mounted to the `:/work` directory inside the container: `Hub.baidubce.com/paddlepaddle/paddle` specifies the container to be used; finally `/work/train.py` is the command executed inside the container, ie. the training program.

Of course, you can also enter into the Docker container and execute or debug your code interactively:


    docker run -it -v $PWD:/work hub.baidubce.com/paddlepaddle/paddle /bin/bash
    cd /work
    python train.py


**Note: 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` **(which installs vim for you) in the container.**

</br></br>

## Start PaddlePaddle Book tutorial with Docker


Use Docker to quickly launch a local Jupyter Notebook containing the PaddlePaddle official Book tutorial, which can be viewed on the web. PaddlePaddle Book is an interactive Jupyter Notebook for users and developers. If you want to learn more about deep learning, PaddlePaddle Book is definitely your best choice. You can read tutorials or create and share interactive documents with code, formulas, charts, and text.

We provide a Docker image that can run the PaddlePaddle Book directly, running directly:

`docker run -p 8888:8888 hub.baidubce.com/paddlepaddle/book`

Domestic users can use the following image source to speed up access:

`docker run -p 8888:8888 hub.baidubce.com/paddlepaddle/book`

Then enter the following URL in your browser:

`http://localhost:8888/`

It's that simple and bon voyage! For further questions, please refer to the [FAQ](#FAQ).


</br></br>
## Perform GPU training using Docker


In order to ensure that the GPU driver works properly in the image, we recommend using [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) to run the image. Don't forget to install the latest GPU drivers on your physical machine in advance.

`Nvidia-docker run -it -v $PWD:/work hub.baidubce.com/paddlepaddle/paddle:latest-gpu /bin/bash`

**Note: If you don't have nvidia-docker installed, you can try the following to mount the CUDA library and Linux devices into the Docker container:**


    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 hub.baidubce.com/paddlepaddle/paddle:latest-gpu