译者：冯宝宝
从源码中构建
包含可选组件
Windows PyTorch有两个受支持的组件：MKL和MAGMA。 以下是使用它们构建的步骤。
REM Make sure you have 7z and curl installed.
REM Download MKL files
curl https://s3.amazonaws.com/ossci-windows/mkl_2018.2.185.7z -k -O
7z x -aoa mkl_2018.2.185.7z -omkl
REM Download MAGMA files
REM cuda90/cuda92/cuda100 is also available in the following line.
set CUDA_PREFIX=cuda80
curl -k https://s3.amazonaws.com/ossci-windows/magma_2.4.0_%CUDA_PREFIX%_release.7z -o magma.7z
7z x -aoa magma.7z -omagma
REM Setting essential environment variables
set "CMAKE_INCLUDE_PATH=%cd%\\mkl\\include"
set "LIB=%cd%\\mkl\\lib;%LIB%"
set "MAGMA_HOME=%cd%\\magma"
为Windows构建加速CUDA
Visual Studio当前不支持并行自定义任务。 作为替代方案，我们可以使用Ninja来并行化CUDA构建任务。 只需键入几行代码即可使用它。
REM Let's install ninja first.
pip install ninja
REM Set it as the cmake generator
set CMAKE_GENERATOR=Ninja