support for python 3.11, support for tf 2.13, is this project abandoned?

[peku33]

I came up with link to this repository on official TF website. It encourages to use this plugin for GPU learning for TF versions > 2.10.

I've checked the requirements, my windows version and my python version are listed as supported, however there is a "1" annotation in README.md here which isn't explained anywhere else.

When trying to install this plugin with pip, I get:

ERROR: Could not find a version that satisfies the requirement tensorflow-directml-plugin (from versions: none)
ERROR: No matching distribution found for tensorflow-directml-plugin

For me it seems like support for 3.11 was not published on pypi or never created.

Also there are new versions of TF released (2.13), some questions have been asked here about support, but no official awnsers were given.

Is this repository actively maintained, or something else should be used instead?

Maybe mentioning the only contributor, @maggie1059 would help a bit?

[countradooku]

@maggie1059

[PatriceVignola]

@radudiaconu0 I apologize for the delay. This project hasn't been abandoned per say, but unfortunately we had to pause development of this plugin until further notice. For the time being, all latest DirectML features and performance improvements are going into onnxruntime for inference scenarios. We'll update this issue if/when things change.

[leo-smi]

up

[JackTrapper]

@radudiaconu0 all latest DirectML features and performance improvements are going into onnxruntime for inference scenarios.

It's important to note that ONNX isn't a machine learning framework. You aren't supposed to ONNX code to perform machine learning.

ONNX's goal is to let you:

• take code written for Tensorflow, Numpy, or HuggingFace
• convert it to ONNX format
• and then run it inside this runtime

You still do all your research, programming, development in Tensorflow. (Which no longer supports GPUs/CUDA under Windows)

And Microsoft's DirectML plug-in for Tensorflow is now abandoned.

So you really can't do research, programming, or development under Windows anymore.

I don't know why Microsoft is so desperate to dump support for Windows developers.

[leo-smi]

@radudiaconu0 all latest DirectML features and performance improvements are going into onnxruntime for inference scenarios.

It's important to note that ONNX isn't a machine learning framework. You aren't supposed to ONNX code to perform machine learning.

ONNX's goal is to let you:

• take code written for Tensorflow, Numpy, or HuggingFace
• convert it to ONNX format
• and then run it inside this runtime

You still do all your research, programming, development in Tensorflow. (Which no longer supports GPUs/CUDA under Windows)

And Microsoft's DirectML plug-in for Tensorflow is now abandoned.

So you really can't do research, programming, or development under Windows anymore.

I don't know why Microsoft is so desperate to dump support for Windows developers.

TIME TO MOVE TO LINUX ONCE FOR ALL

[JackTrapper]

Time to move to Linux once for all.

The problem with moving to Linux is that it's not Windows.

• In addition to Linus Torvolds explaining why Linux on the desktop sucks
• you can't really develop and test Windows applications on Linux
• and your Windows users cannot run Linux applications on Windows natively

[xalteropsx]

plz add 3.11

[yanite]

plz add 3.11

[JackTrapper]

From Microsoft:

Enable GPU acceleration for TensorFlow 2 with tensorflow-directml-plugin

🛈 Important

This project is now discontinued, and isn't actively being worked on.

🛈 Note

You can install tensorflow-directml-plugin by using Python x86-64 3.10. But tensorflow-directml-plugin isn't supported for version 3.11 and later.

I guess it makes sense: you don't want developers running AI in-box—competing with the ML-as-a-Service.

It's just...not what any of us would have wanted.