在Windows上使用Python3.8.5编译支持CUDA11和cuDNN8.0.2的TensorFlow2.3，并提供编译后的文件下载链接

基本参照我的这篇文章&＃xff1a;《Windows下编译带CUDA 10.2的TensorFlow 2.2&＃xff08;Python3.8.2&＃xff0c;附编译结果下载&＃xff09;》&＃xff0c;有些地方有所改动&＃xff0c;现列出来&＃xff1a;

D:\tensorflow-2.3.0>python ./configure.py

You have bazel 3.4.1 installed.

Please specify the location of python. [Default is C:\Python38\python.exe]:

Found possible Python library paths:

C:\Python38\lib\site-packages

Please input the desired Python library path to use. Default is [C:\Python38\lib\site-packages]

Do you wish to build TensorFlow with ROCm support? [y/N]:

No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y

CUDA support will be enabled for TensorFlow.

Found CUDA 11.0 in:

D:/CUDA11/lib/x64

D:/CUDA11/include

Found cuDNN 8 in:

D:/CUDA11/lib/x64

D:/CUDA11/include

Please specify a list of comma-separated CUDA compute capabilities you want to build with.

You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus. Each capability can be specified as "x.y" or "compute_xy" to include both virtual and binary GPU code, or as "sm_xy" to only include the binary code.

Please note that each additional compute capability significantly increases your build time and binary size, and that TensorFlow only supports compute capabilities >&＃61; 3.5 [Default is: 3.5,7.0]: 3.5,3.7,5.0,5.2,6.0,6.1,7.0,7.5,8.0

Please specify optimization flags to use during compilation when bazel option "--config&＃61;opt" is specified [Default is /arch:AVX]: /arch:AVX2

Would you like to override eigen strong inline for some C&＃43;&＃43; compilation to reduce the compilation time? [Y/n]:

Eigen strong inline overridden.

Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:

Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config&＃61;<>" to your build command. See .bazelrc for more details.

--config&＃61;mkl # Build with MKL support.

--config&＃61;monolithic # Config for mostly static monolithic build.

--config&＃61;ngraph # Build with Intel nGraph support.

--config&＃61;numa # Build with NUMA support.

--config&＃61;dynamic_kernels # (Experimental) Build kernels into separate shared objects.

--config&＃61;v2 # Build TensorFlow 2.x instead of 1.x.

Preconfigured Bazel build configs to DISABLE default on features:

--config&＃61;noaws # Disable AWS S3 filesystem support.

--config&＃61;nogcp # Disable GCP support.

--config&＃61;nohdfs # Disable HDFS support.

--config&＃61;nonccl # Disable NVIDIA NCCL support.

编译命令稍后补充&＃xff0c;先甩成品链接&＃xff1a;

pip安装包&＃xff1a;tensorflow-2.3.0-cp38-cp38-win_amd64.whl

pip安装包流量管家版&＃xff1a;tensorflow-2.3.0-cp38-cp38-win_amd64.rar

pip安装包&＃xff08;MKL&＃xff09;&＃xff1a;tensorflow-mkl-2.3.0-cp38-cp38-win_amd64.whl

pip安装包流量管家版&＃xff1a;&＃xff08;MKL&＃xff09;&＃xff1a;tensorflow-mkl-2.3.0-cp38-cp38-win_amd64.rar

pip安装包的流量管家版&＃xff0c;解压后再用ZIP打包&＃xff0c;改后缀为“whl”即可正常安装。

C库&＃xff1a;libtensorflow-2.3.0.rar

C库&＃xff08;MKL&＃xff09;&＃xff1a;libtensorflow-2.3.0-mkl.rar