· Both Linux and Windows are supported. Linux is recommended for performance and compatibility reasons. · 64-bit Python 3.6 installation. We recommend Anaconda3 with numpy 1.14.3 or newer. · TensorFlow 1.14 or 1.15 with GPU support. The code does not support TensorFlow 2.0. · On Windows, you need to use TensorFlow 1.14 — TensorFlow 1.15 will not work. · One or more high-end NVIDIA GPUs, NVIDIA drivers, CUDA 10.0 toolkit
and cuDNN 7.5. To reproduce the results reported in the paper, you need
an NVIDIA GPU with at least 16 GB of DRAM. · Docker users: use the provided Dockerfile to build an image with the required library dependencies. - On Windows, the compilation requires Microsoft Visual Studio to be in PATH. We recommend installing Visual Studio Community Edition and adding into PATH using "C:Program Files (x86)Microsoft Visual Studio2019CommunityVCAuxiliaryBuildvcvars64.bat". 我的测试环境配置为:Win10,1050Ti,CUDA 10.0,CuDNN 7.6.5,tensorflow-gpu 1.14.0,VS2017可完美运行。
Windows下常见问题 :Could not find MSVC/GCC/CLANG installation on this computer如何解决?