This instruction will show you how to compile PaddlePaddle on a *64-bit desktop or laptop* and Windows 10. The Windows systems we support must meet the following requirements:
This instruction will show you how to compile PaddlePaddle on a *64-bit desktop or laptop* and Windows 10. The Windows systems we support must meet the following requirements:
* Windows 10 Family Edition / Professional Edition / Enterprise Edition
* Windows 10 Professional Edition / Enterprise Edition
* Visual Studio 2015 Update3
* Visual Studio 2015 Update3
## Determine which version to compile
***Only PaddlePaddle for CPU is supported.**
## Choose a compilation method
## Choose a compilation method
We provide one compilation method under the Windows system:
We provide one compilation method under the Windows system:
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Since the situation on host machine is more complicated, we only support specific systems.
Since the situation on host machine is more complicated, we only support specific systems.
Please note: The current version does not support NCCL, distributed, AVX, warpctc and MKL related functions.
Please note: The current version does not support NCCL and distributed related functions.
### ***Local compilation***
### ***Local compilation***
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1. Check that your computer and operating system meet our supported compilation standards
1. Check that your computer and operating system meet our supported compilation standards
* Windows 10 Family Edition / Professional Edition / Enterprise Edition
* Windows 10 Professional Edition / Enterprise Edition
* Visual Studio 2015 Update3
* Visual Studio 2015 Update3
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4. Switch to a more stable release branch for compilation :
4. Switch to a more stable release branch for compilation :
- `git checkout release/1.2`
- `git checkout release/1.5`
5. Create a directory called build and enter it:
5. Create a directory called build and enter it:
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-DPYTHON_LIBRARY = $ {PYTHON_LIBRARY}
-DPYTHON_LIBRARY = $ {PYTHON_LIBRARY}
-DPYTHON_EXECUTABLE = $ {PYTHON_EXECUTABLE} -DWITH_FLUID_ONLY = ON -DWITH_GPU = OFF -DWITH_TESTING =OFF -DCMAKE_BUILD_TYPE=Release`
-DPYTHON_EXECUTABLE = $ {PYTHON_EXECUTABLE} -DWITH_FLUID_ONLY = ON -DWITH_GPU = OFF -DWITH_TESTING =OFF -DCMAKE_BUILD_TYPE=Release`
> If you encounter `Could NOT find PROTOBUF (missing: PROTOBUF_LIBRARY PROTOBUF_INCLUDE_DIR)`, you can re-execute the cmake command.
7. Some third-party dependencies (openblas, snappystream) currently require users to provide pre-compiled versions, or download pre-compiled files from `https://github.com/wopeizl/Paddle_deps` and place the entire `third_party` folder in the `build` directory.
7. Some third-party dependencies (openblas, snappystream) currently require users to provide pre-compiled versions, or download pre-compiled files from `https://github.com/wopeizl/Paddle_deps` and place the entire `third_party` folder in the `build` directory.
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Please use the following command to uninstall PaddlePaddle:
Please use the following command to uninstall PaddlePaddle:
****CPU version of PaddlePaddle*** : `pip uninstall paddlepaddle` or `pip3 uninstall paddlepaddle`
****CPU version of PaddlePaddle*** : `pip uninstall paddlepaddle` or `pip3 uninstall paddlepaddle`
****GPU version of PaddlePaddle*** : `pip uninstall paddlepaddle-gpu` or `pip3 uninstall paddlepaddle-gpu`
* If your computer doesn’t have NVIDIA® GPU, please install the CPU version of PaddlePaddle
* If your computer doesn’t have NVIDIA® GPU, please install the CPU version of PaddlePaddle
* If your computer has NVIDIA® GPU, and it satisfies the following requirements, we recommend you to install the GPU version of PaddlePaddle
* If your computer has NVIDIA® GPU, and it satisfies the following requirements, we recommend you to install the GPU version of PaddlePaddle
**CUDA Toolkit 8.0 with cuDNN v7*
**CUDA Toolkit 8.0/9.2 with cuDNN v7.3+*
**GPU's computing capability exceeds 1.0*
**GPU's computing capability exceeds 1.0*
Please refer to the NVIDIA official documents for the installation process and the configuration methods of [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) and [cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/).
Please refer to the NVIDIA official documents for the installation process and the configuration methods of [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) and [cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/).