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update windows build guide (#47840)

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Summary:
Fixes https://github.com/pytorch/pytorch/issues/47483

Pull Request resolved: https://github.com/pytorch/pytorch/pull/47840

Reviewed By: malfet

Differential Revision: D24951466

Pulled By: walterddr

fbshipit-source-id: 7530ec5a3aff7095978c330d9b78e58b10349373
This commit is contained in:
Yi Zhang 2020-11-16 08:08:43 -08:00 committed by Facebook GitHub Bot
parent 147a48fb27
commit f9552e6da4
1 changed files with 28 additions and 20 deletions
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README.md
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@ -158,6 +158,7 @@ If you want to compile with CUDA support, install
- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 9.2 or above
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v7 or above
- [Compiler](https://gist.github.com/ax3l/9489132) compatible with CUDA
Note: You could refer to the [cuDNN Support Matrix](https://docs.nvidia.com/deeplearning/cudnn/pdf/cuDNN-Support-Matrix.pdf) for cuDNN versions with the various supported CUDA, CUDA driver and NVIDIA hardwares
If you want to disable CUDA support, export environment variable `USE_CUDA=0`.
Other potentially useful environment variables may be found in `setup.py`.
@ -233,44 +234,51 @@ Each CUDA version only supports one particular XCode version. The following comb
On Windows
At least Visual Studio 2017 version 15.6 with the toolset 14.13 and [NVTX](https://docs.nvidia.com/gameworks/content/gameworkslibrary/nvtx/nvidia_tools_extension_library_nvtx.htm) are needed.
Build with CPU
If the version of Visual Studio 2017 is higher than 15.6, installing of "VC++ 2017 version 15.6 v14.13 toolset" is strongly recommended.
<br/> If the version of Visual Studio 2017 is lesser than 15.6, please update Visual Studio 2017 to the latest version along with installing "VC++ 2017 version 15.6 v14.13 toolset".
<br/> There is no guarantee of the correct building with VC++ 2017 toolsets, others than version 15.6 v14.13.
<br/> "VC++ 2017 version 15.6 v14.13 toolset" might be installed onto already installed Visual Studio 2017 by running its installation once again and checking the corresponding checkbox under "Individual components"/"Compilers, build tools, and runtimes".
It's fairly easy to build with CPU. Visual Studio 2019 version 16.7.6 (MSVC toolchain version 14.27) or higher is recommended.
Build with CUDA
[NVTX](https://docs.nvidia.com/gameworks/content/gameworkslibrary/nvtx/nvidia_tools_extension_library_nvtx.htm) is needed to build Pytorch with CUDA.
NVTX is a part of CUDA distributive, where it is called "Nsight Compute". To install it onto already installed CUDA run CUDA installation once again and check the corresponding checkbox.
Be sure that CUDA with Nsight Compute is installed after Visual Studio 2017.
Make sure that CUDA with Nsight Compute is installed after Visual Studio.
Currently, VS 2017, VS 2019, and Ninja are supported as the generator of CMake. If `ninja.exe` is detected in `PATH`, then Ninja will be used as the default generator, otherwise, it will use VS 2017.
<br/> If Ninja is selected as the generator, the latest MSVC which is newer than VS 2015 (14.0) will get selected as the underlying toolchain. If you use CMake <= 3.14.2 and has VS 2019 installed, then even if you specify VS 2017 as the generator, VS 2019 will get selected as the generator.
Currently, VS 2017 / 2019, and Ninja are supported as the generator of CMake. If `ninja.exe` is detected in `PATH`, then Ninja will be used as the default generator, otherwise, it will use VS 2017 / 2019.
<br/> If Ninja is selected as the generator, the latest MSVC will get selected as the underlying toolchain.
CUDA and MSVC have strong version dependencies, so even if you use VS 2017 / 2019, you will get build errors like `nvcc fatal : Host compiler targets unsupported OS`. For this kind of problem, please install the corresponding VS toolchain in the table below, and then you can either specify the toolset during activation (recommended) or set `CUDAHOSTCXX` to override the Cuda host compiler (not recommended if there are big version differences).
CUDA, MSVC, and PyTorch versions are interdependent; please install matching versions from this table:
| CUDA version | Newest supported VS version | PyTorch version |
| ------------ | ------------------------------------------------------- | --------------- |
| 9.2 | Visual Studio 2017 Update 5 (15.5) (`_MSC_VER` <= 1912) | 0.4.1 ~ 1.5.1 |
| 10.1 | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930) | 1.3.0 ~ 1.7.0 |
| 10.2 | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930) | 1.5.0 ~ 1.7.0 |
| 11.0 | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930) | 1.7.0 |
Note: There's a [compilation issue](https://github.com/oneapi-src/oneDNN/issues/812) in serveral Visual Studio 2019 versions since 16.7.1, so please make sure your Visual Studio 2019 version is not in 16.7.1 ~ 16.7.5
Additional libraries such as
[Magma](https://developer.nvidia.com/magma), [oneDNN, a.k.a MKLDNN or DNNL](https://github.com/oneapi-src/oneDNN), and [Sccache](https://github.com/mozilla/sccache) are often needed. Please refer to the [installation-helper](https://github.com/pytorch/pytorch/tree/master/.jenkins/pytorch/win-test-helpers/installation-helpers) to install them.
You can refer to the [build_pytorch.bat](https://github.com/pytorch/pytorch/blob/master/.jenkins/pytorch/win-test-helpers/build_pytorch.bat) script for some other environment variables configurations
| CUDA version | Newest supported VS version |
| ------------ | ------------------------------------------------------- |
| 9.2 | Visual Studio 2017 Update 5 (15.5) (`_MSC_VER` <= 1912) |
| 10.0 | Visual Studio 2017 (15.X) (`_MSC_VER` < 1920) |
| 10.1 | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930) |
```cmd
cmd
:: [Optional] If you want to build with VS 2019 generator, please change the value in the next line to `Visual Studio 16 2019`.
:: [Optional] If you want to build with the VS 2017 generator for old CUDA and PyTorch, please change the value in the next line to `Visual Studio 15 2017`.
:: Note: This value is useless if Ninja is detected. However, you can force that by using `set USE_NINJA=OFF`.
set CMAKE_GENERATOR=Visual Studio 15 2017
set CMAKE_GENERATOR=Visual Studio 16 2019
:: Read the content in the previous section carefully before you proceed.
:: [Optional] If you want to override the underlying toolset used by Ninja and Visual Studio with CUDA, please run the following script block.
:: "Visual Studio 2017 Developer Command Prompt" will be run automatically.
:: "Visual Studio 2019 Developer Command Prompt" will be run automatically.
:: Make sure you have CMake >= 3.12 before you do this when you use the Visual Studio generator.
set CMAKE_GENERATOR_TOOLSET_VERSION=14.11
set CMAKE_GENERATOR_TOOLSET_VERSION=14.27
set DISTUTILS_USE_SDK=1
for /f "usebackq tokens=*" %i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe" -version [15^,16^) -products * -latest -property installationPath`) do call "%i\VC\Auxiliary\Build\vcvarsall.bat" x64 -vcvars_ver=%CMAKE_GENERATOR_TOOLSET_VERSION%
:: [Optional] If you want to override the Cuda host compiler
set CUDAHOSTCXX=C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\VC\Tools\MSVC\14.11.25503\bin\HostX64\x64\cl.exe
:: [Optional] If you want to override the CUDA host compiler
set CUDAHOSTCXX=C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.27.29110\bin\HostX64\x64\cl.exe
python setup.py install