Tables_en.md 30.0 KB
Newer Older
1
***
2 3
<a name="third_party"></a>
# Appendix
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211


## 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>
	</tr>
		<tr>
		<td> Python </td>
		<td> 2.7.x. </td>
		<td> depends on libpython2.7.so </td>
		<td> <code> apt install python-dev </code> or <code> yum install python-devel </code></td>
	</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>
		<td>  </td>
		<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>
		<td> <code> pip install numpy==1.14.0 </code> </td>
	</tr>
	<tr>
		<td> protobuf </td>
		<td> 3.1.0 </td>
		<td>  </td>
		<td> <code> pip install protobuf==3.1.0 </code> </td>
	</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>
	</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_C_API </td>
		<td> Whether to compile CAPI </td>
		<td>  OFF </td>
	</tr>
		<tr>
		<td> WITH_DOUBLE </td>
		<td> Whether to use double precision floating point numeber </td>
		<td> OFF </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_STYLE_CHECK </td>
		<td> Whether to perform code style checking at compile time </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_DOC </td>
		<td> Whether to compile Chinese and English documents </td>
		<td> OFF </td>
	</tr>
	<tr>
		<td> WITH_SWIG_PY </td>
		<td> Whether to compile PYTHON's SWIG interface, which can be used for predicting and customizing training </td>
		<td> Auto </td>
	<tr>
		<td> WITH_GOLANG </td>
		<td> Whether to compile the fault-tolerant parameter server of the go language </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_MKL </td>
		<td> Whether to uses the MKL math library, if not, using OpenBLAS </td>
		<td> ON </td>
	</tr>
	<tr>
		<td> WITH_RDMA </td>
		<td> Whether to compile the relevant parts that supports RDMA </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>
		<td> DWITH_ANAKIN </td>
		<td> Whether to Compile ANAKIN </td>
		<td> OFF </td>
	</tr>
   </tbody>
</table>
</p>


**BLAS**

C
Cheerego 已提交
212
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).
213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231

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.


***
232
<a name="whls"></a>
233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326
</br></br>
## **Installation Package List**


<p align="center">
<table>
	<thead>
	<tr>
		<th> Version Number </th>
		<th> Release Discription </th>
	</tr>
	</thead>
	<tbody>
	<tr>
		<td> paddlepaddle==[version code] such as paddlepaddle==1.0.1 (download version 1.0.1 which only supports CPU PaddlePaddle)</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==1.0.1 </td>
		<td>  Using version 1.0.1 compiled with CUDA 9.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==1.0.1.post87 </td>
		<td> Using version 1.0.1 compiled with CUDA 8.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==1.0.1.post85 </td>
		<td> Using version 1.0.1 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==1.0.0 </td>
		<td> Using version 1.0.0 compiled with CUDA 9.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==1.0.0.post87 </td>
		<td> Using version 1.0.0 compiled with CUDA 8.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==1.0.0.post85 </td>
		<td> Using version 1.0.0 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.15.0 </td>
		<td> Using version 0.15.0 compiled with CUDA 9.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.15.0.post87 </td>
		<td> Using version 0.15.0 compiled with CUDA 8.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.15.0.post85 </td>
		<td> Using version 0.15.0 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.14.0 </td>
		<td> Using version 0.15.0 compiled with CUDA 9.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.14.0.post87 </td>
		<td> Using version 0.15.0 compiled with CUDA 8.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.14.0.post85 </td>
		<td> Using version 0.15.0 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.13.0 </td>
		<td> Using version 0.13.0 compiled with CUDA 9.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.12.0 </td>
		<td> Using version 0.12.0 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.11.0.post87 </td>
		<td> Using version 0.11.0 compiled with CUDA 8.0 and cuDNN 7 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.11.0.post85 </td>
		<td> Using version 0.11.0 compiled with CUDA 8.0 and cuDNN 5 </td>
	</tr>
	<tr>
		<td> paddlepaddle-gpu==0.11.0 </td>
		<td> Using version 0.11.0 compiled with CUDA 7.5 and cuDNN 5 </td>
	</tr>
   </tbody>
</table>
</p>



You can find various distributions of PaddlePaddle-gpu in [the Release History](https://pypi.org/project/paddlepaddle-gpu/#history).

***
327
<a name="dockers"></a>
328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364
</br></br>
## Installation Mirrors and Introduction

<p align="center">
<table>
	<thead>
	<tr>
		<th> Version Number </th>
		<th> Release Description </th>
	</tr>
	</thead>
	<tbody>
	<tr>
		<td> hub.baidubce.com/paddlepaddle/paddle:latest </td>
		<td> The latest pre-installed image of the PaddlePaddle CPU version </td>
	</tr>
	<tr>
		<td> hub.baidubce.com/paddlepaddle/paddle:latest-dev </td>
		<td> The latest PaddlePaddle development environment </td>
	</tr>
		<tr>
		<td> hub.baidubce.com/paddlepaddle/paddle:[Version] </td>
		<td>  Replace version with a specific version, preinstalled PaddlePaddle image in historical version </td>
	</tr>
	<tr>
		<td> hub.baidubce.com/paddlepaddle/paddle:latest-gpu </td>
		<td> The latest pre-installed image of the PaddlePaddle GPU version </td>
	</tr>
   </tbody>
</table>
</p>



You can find the docker image for each release of PaddlePaddle in the [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/).

***
365
<a name="ciwhls-release"></a>
366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384
</br></br>

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

<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-noavx-mkl </td>
385 386 387 388 389 390 391 392 393 394
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-noavx-mkl/paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-noavx-mkl/paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-noavx-mkl/paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-noavx-mkl/paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-noavx-mkl/paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
395 396 397
	</tr>
	<tr>
		<td> cpu_avx_mkl </td>
398 399 400 401 402 403 404 405 406 407
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-mkl/paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-mkl/paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-mkl/paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-mkl/paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-mkl/paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
408 409 410
	</tr>
	<tr>
		<td> cpu_avx_openblas </td>
411 412 413 414 415 416 417 418 419
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-openblas/paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-openblas/paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-openblas/paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-openblas/paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-cpu-avx-openblas/paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
420 421 422
	</tr>
	<tr>
		<td> cuda8.0_cudnn5_avx_mkl </td>
423 424 425 426 427 428 429
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-1.2.1.post85-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-1.2.1.post85-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-1.2.1.post85-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-1.2.1.post85-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-1.2.1.post85-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
430 431 432
	</tr>
	<tr>
		<td> cuda8.0_cudnn7_noavx_mkl </td>
433 434 435 436 437 438 439
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-1.2.1-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-1.2.1-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-1.2.1-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-1.2.1-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-1.2.1-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
440 441 442
	</tr>
	<tr>
		<td> cuda8.0_cudnn7_avx_mkl </td>
443 444 445 446 447 448 449
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post87-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1.post87-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post87-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1.post87-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post87-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1.post87-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post87-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1.post87-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post87-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1.post87-cp37-cp37m-linux_x86_64.whl</a></td>
450 451 452
	</tr>
	<tr>
		<td> cuda9.0_cudnn7_avx_mkl </td>
453 454 455 456 457 458 459
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post97-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post97-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post97-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-1.2.1-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post97-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/1.2.1-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-1.2.1.post97-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-1.2.1-cp37-cp37m-linux_x86_64.whl</a></td>
460 461 462 463 464 465
	</tr>
   </tbody>
</table>
</p>


466
<a name="ciwhls"></a>
467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567
</br></br>

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


<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-noavx-mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-noavx-mkl/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-noavx-mkl/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-noavx-mkl/paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-noavx-mkl/paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-noavx-mkl/paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cpu_avx_mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-mkl/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-mkl/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-mkl/paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-mkl/paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-mkl/paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cpu_avx_openblas </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-openblas/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl">
		paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-openblas/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl"> paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-openblas/paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl">
		paddlepaddle-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-openblas/paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-cpu-avx-openblas/paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda8.0_cudnn5_avx_mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn5-avx-mkl/paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda8.0_cudnn7_noavx_mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl">
		paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-noavx-mkl/paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl">
		paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda8.0_cudnn7_avx_mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda8-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
	<tr>
		<td> cuda9.0_cudnn7_avx_mkl </td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl</a></td>
		<td><a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp35-cp35m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
		<td> <a href="http://paddlepaddle.org/download?url=http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda9-cudnn7-avx-mkl/paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
	</tr>
   </tbody>
</table>
</p>


</br></br>

## Execute the PaddlePaddle training program in Docker

***

C
Cheerego 已提交
568
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:
569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631


    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



**About AVX:**

C
Cheerego 已提交
632
AVX is a set of CPU instructions that speeds up the calculation of PaddlePaddle. The latest PaddlePaddle Docker image is enabled by default for AVX compilation, so if your computer does not support AVX, you need to compile PaddlePaddle to no-avx version separately.
633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666

The following instructions can check if the Linux computer supports AVX:

`if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi`

If the output is No, you need to choose a mirror that uses no-AVX.