As stated in the installation guide,
The current TensorFlow version, 2.10, is the last TensorFlow release that will support GPU on native-Windows.
Just wondering what the thinking behind this step is? And I presume it isn’t that binaries won’t be made it simply won’t work? Where as Pytorch supports Windows and JAX you can build it yourself from source.
TensorFlow with GPU access is supported for WSL2 on Windows 10 19044 or higher. This corresponds to Windows 10 version 21H2, the November 2021 update. For instructions please refer Install WSL2 and NVIDIA’s setup docs for CUDA in WSL.
Note: We might consider making the WSL2 path the primary way for ML practitioners to run TensorFlow on Windows/GPU
Thank you.
I understand that TF2 is still going to be available via windows based linux kernel, which means setting up whole new python environments in WSL2 etc.
I am asking why native support is being dropped? And is it just pre-built binaries or is complete support being dropped i.e. JAX can be built to run natively on Windows.
I suppose that over time, complete support will be dropped.
Beginning with Tensorflow 2.11, support for GPU on native windows has changed. You can install tensorflow-cpu within windows machines or try the TensorFlow-DirectML-Plugin. Going forward, Tensorflow support will be developed and maintained by Tensorflow Official build collaborators (Intel, AWS, ARM, linaro etc.). For more details please refer to the link. Thank you!
Just to verify, then, if you downloaded the Tensorflow 2.11 source and built it yourself on native Windows, it would still not be able to support GPU, correct?