Question: Why no GPU support on Windows Native?
@aaronsuydam The introduction of Windows Subsystem for Linux 2 (WSL 2) provided a more efficient and consistent platform for GPU acceleration on Windows, leveraging established Linux builds. This delivers full access to GPU-enabled builds and superior performance.
Thank you! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. @sushreebarsa Hey! Sorry for the late response here. I am trying to develop a Windows app that leverages some functionality that has been implemented using tensor flow. Will the lack of GPU support impact that? As in, can a windows app that has some backend functionality that uses TF gpu stuff work on a system without wsl installed? I don't want users to have to install wsl to get that benefit, maybe i can find a workaround if that's the case? This is also just me being curious, I'm a college student, so this is really just a hobby for me. No stress either way. @aaronsuydam If you don't want to use WSL2 then there are a few alternatives. If your app's functionality can be achieved with TensorFlow 2.10 or older, you can utilize the native GPU support offered by those versions. However, this might limit access to newer features and optimizations. 
Microsoft released the DirectML Plugin for TensorFlow, enabling limited GPU acceleration via Microsoft's DirectML hardware acceleration library. 
Thank you! @sushreebarsa thanks for the quick reply. I looked into the DirectML plugin, and it looks like they paused development in favor of stuff with the ONNX Runtime.

From their repo: "⚠️ Development of TensorFlow-DirectML-Plugin has been paused until further notice. To take advantage of the latest DirectML features and performance improvements for inference scenarios, we recommend taking a look at [ONNX Runtime](https://github.com/microsoft/onnxruntime). ⚠️"

Are there plans to support feature integration with this new direction they are taking? @aaronsuydam You are right! Microsoft paused development of the TensorFlow-DirectML-Plugin in October 2023 in favor of focusing on ONNX Runtime for inference scenarios with DirectML. Currently, there's no concrete information about potential feature integration between these two directions. Please stay informed about future developments. 
Thank you! Will do! Thank you for the information! Are you satisfied with the resolution of your issue?
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### Issue type

Support

### Have you reproduced the bug with TensorFlow Nightly?

No

### Source

source

### TensorFlow version

tf 2.15

### Custom code

No

### OS platform and distribution

Windows 11

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

GTX 1660Ti

### Current behavior?

Hey there! This is just me trying to ask a question, I did some googling to try and figure it out, but I was just wondering why support for CUDA acceleration was dropped for TF > 2.10 on windows native installations? I'd be curious just learning what would be needed to manually work around that (I'm a CpE major, would be a fun activity i think)? I may be way out of my league, but I am curious!

### Standalone code to reproduce the issue

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### Relevant log output

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