Update compile_paddle_lib_en.md (#9795)

* Update compile_paddle_lib_en.md Fix https://github.com/PaddlePaddle/Paddle/issues/8916 * Update compile_paddle_lib_en.md

Update compile_paddle_lib_en.md (#9795)
* Update compile_paddle_lib_en.md Fix https://github.com/PaddlePaddle/Paddle/issues/8916 * Update compile_paddle_lib_en.md
3ebc5e1b · cwgis · Abhinav Arora · e0babe7c · 3ebc5e1b
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 ## Install and Build

-TBD
+### Download & Install 
+
+  Download the latest C-API development package from CI system and install. You can find the required version in the table below:
+<table>
+<thead>
+<tr>
+<th>Version Tips</th>
+<th>C-API</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>cpu_avx_mkl</td>
+<td><a href="https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddle.tgz" rel="nofollow">paddle.tgz</a></td>
+</tr>
+<tr>
+<td>cpu_avx_openblas</td>
+<td>-</td>
+</tr>
+<tr>
+<td>cpu_noavx_openblas</td>
+<td><a href="https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddle.tgz" rel="nofollow">paddle.tgz</a></td>
+</tr>
+<tr>
+<td>cuda7.5_cudnn5_avx_mkl</td>
+<td><a href="https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/paddle.tgz" rel="nofollow">paddle.tgz</a></td>
+</tr>
+<tr>
+<td>cuda8.0_cudnn5_avx_mkl</td>
+<td><a href="https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddle.tgz" rel="nofollow">paddle.tgz</a></td>
+</tr>
+<tr>
+<td>cuda8.0_cudnn7_avx_mkl</td>
+<td><a href="https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddle.tgz" rel="nofollow">paddle.tgz</a></td>
+</tr></tbody></table>
+
+### From source
+
+  Users can also compile the C-API library from PaddlePaddle source code by compiling with the following compilation options:
+  
+<table>
+<thead>
+<tr>
+<th>Options</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>WITH_C_API</td>
+<td>ON</td>
+</tr>
+<tr>
+<td>WITH_PYTHON</td>
+<td>OFF（recommended）</td>
+</tr>
+<tr>
+<td>WITH_SWIG_PY</td>
+<td>OFF（recommended）</td>
+</tr>
+<tr>
+<td>WITH_GOLANG</td>
+<td>OFF（recommended）</td>
+</tr>
+<tr>
+<td>WITH_GPU</td>
+<td>ON/OFF</td>
+</tr>
+<tr>
+<td>WITH_MKL</td>
+<td>ON/OFF</td>
+</tr></tbody></table>
+
+It is best to set up with recommended values to avoid linking with unnecessary libraries. Set other compilation options as you need.
+
+Pull the latest following code snippet from github, and configure compilation options(replace PADDLE_ROOT with the installation path of the PaddlePaddle C-API inference library):
+
+```shell
+PADDLE_ROOT=/path/of/capi
+git clone https://github.com/PaddlePaddle/Paddle.git
+cd Paddle
+mkdir build
+cd build
+cmake -DCMAKE_INSTALL_PREFIX=$PADDLE_ROOT \
+      -DCMAKE_BUILD_TYPE=Release \
+      -DWITH_C_API=ON \
+      -DWITH_SWIG_PY=OFF \
+      -DWITH_GOLANG=OFF \
+      -DWITH_PYTHON=OFF \
+      -DWITH_MKL=OFF \
+      -DWITH_GPU=OFF  \
+      ..
+```
+
+After running the above code to generate Makefile , run: `make && make install`.  After successful compilation, the dependencies required by C-API(includes: (1)PaddlePaddle inference library and header files; (2) Third-party libraries and header files) will be stored in the `PADDLE_ROOT` directory.
+
+If the compilation is successful, see the following directory structure under `PADDLE_ROOT`(includes PaddlePaddle header files and libraries, and third-party libraries and header files(determined by the link methods if necessary)):
+
+```text
+├── include
+│   └── paddle
+│       ├── arguments.h
+│       ├── capi.h
+│       ├── capi_private.h
+│       ├── config.h
+│       ├── error.h
+│       ├── gradient_machine.h
+│       ├── main.h
+│       ├── matrix.h
+│       ├── paddle_capi.map
+│       └── vector.h
+├── lib
+│   ├── libpaddle_capi_engine.a
+│   ├── libpaddle_capi_layers.a
+│   ├── libpaddle_capi_shared.so
+│   └── libpaddle_capi_whole.a
+└── third_party
+    ├── gflags
+    │   ├── include
+    │   │   └── gflags
+    │   │       ├── gflags_completions.h
+    │   │       ├── gflags_declare.h
+    │   │       ...
+    │   └── lib
+    │       └── libgflags.a
+    ├── glog
+    │   ├── include
+    │   │   └── glog
+    │   │       ├── config.h
+    │   │       ...
+    │   └── lib
+    │       └── libglog.a
+    ├── openblas
+    │   ├── include
+    │   │   ├── cblas.h
+    │   │   ...
+    │   └── lib
+    │       ...
+    ├── protobuf
+    │   ├── include
+    │   │   └── google
+    │   │       └── protobuf
+    │   │           ...
+    │   └── lib
+    │       └── libprotobuf-lite.a
+    └── zlib
+        ├── include
+        │   ...
+        └── lib
+            ...
+
+```
+
+### Linking Description:
+
+There are three kinds of linking methods:
+
+1. Linking with dynamic library `libpaddle_capi_shared.so`（This way is much more convenient and easier, **Without special requirements, it is recommended**）, refer to the following：
+    1. Compiling with CPU version and using `OpenBLAS`; only need to link one library named `libpaddle_capi_shared.so` to develop prediction program through C-API.
+    1. Compiling with CPU version and using `MKL` lib, you need to link MKL library directly to develop prediction program through PaddlePaddle C-API, due to `MKL` has its own dynamic library.
+    1. Compiling with GPU version, CUDA library will be loaded dynamically on prediction program run-time, and also set CUDA library to  `LD_LIBRARY_PATH` environment variable.
+
+2. Linking with static library `libpaddle_capi_whole.a`，refer to the following：
+    1. Specify `-Wl,--whole-archive` linking options.
+    1. Explicitly link third-party libraries such as `gflags`、`glog`、`libz`、`protobuf` .etc, you can find them under `PADDLE_ROOT/third_party` directory.
+    1. Use OpenBLAS library if compiling C-API，must explicitly link `libopenblas.a`.
+    1. Use MKL when compiling C-API, must explicitly link MKL dynamic library.
+
+3. Linking with static library `libpaddle_capi_layers.a` and `libpaddle_capi_engine.a`，refer to the following：
+    1. This linking methods is mainly used for mobile prediction.
+    1. Split `libpaddle_capi_whole.a` into two static linking library at least to reduce the size of linking libraries.
+    1. Specify `-Wl,--whole-archive -lpaddle_capi_layers`  and  `-Wl,--no-whole-archive -lpaddle_capi_engine` for linking.
+    1. The third-party dependencies need explicitly link same as method 2 above.