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Hello angerson,
i already added it to the meeting notes, but can this please be discussed:
opened 09:15AM - 07 Mar 23 UTC
stat:awaiting tensorflower
type:build/install
subtype:windows
TF 2.11
<details><summary>Click to expand!</summary>
### Issue Type
Others
#… ## Have you reproduced the bug with TF nightly?
Yes
### Source
binary
### Tensorflow Version
2.11
### Custom Code
Yes
### OS Platform and Distribution
Windows 10
### Mobile device
_No response_
### Python version
3.9
### Bazel version
_No response_
### GCC/Compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current Behaviour?
I am very disappointed and sad that native Windows CUDA support was simply dropped.
The replacement with WSL2 is not sufficient for processes and systems that are not able to use WSL2 because, for example, if they are also Windows-native applications and the port is too expensive. So we can only use version 2.10 (of both the Python and C APIs) and are stuck with it, which is a shame because it prevents us from benefiting from and participating in new developments. We also see a performance loss of about 5% in WSL2, which leads to higher power consumption and thus has a direct impact on our climate, which can make a big difference in our already very compute-intensive business. In addition, the Windows Direct-ML-Plugin interface is not sufficient, since the performance does not yet reach CUDA and optimizations like XLA and others are not supported. Also, you lose all your highly optimized and expensively developed TF CUDA Custom Ops.
It is also clear that the native CUDA feature on Windows is much needed, see here in the following issues other people are looking for exactly the native CUDA feature on Windows:
- #https://github.com/tensorflow/tensorflow/issues/58629
- #https://github.com/tensorflow/tensorflow/issues/58933
- #https://github.com/tensorflow/tensorflow/issues/59905
- #https://github.com/tensorflow/tensorflow/issues/59119
- #https://github.com/tensorflow/tensorflow/issues/59016
- #https://github.com/tensorflow/tensorflow/issues/58985
- #https://github.com/tensorflow/tensorflow/issues/58729
**All this leads to the simple exclusion and virtual discrimination of a large part of the Tensorflow community that uses CUDA Windows natively.**
Why has support been dropped? You could at least keep support for CUDA Windows Native in custom builds.
I hope and ask that you bring back Windows native CUDA support and let people decide for themselves if they want to use native CUDA or WSL2.
Thank you for the development of Tensorflow! My favourite DL framework! :)
### Standalone code to reproduce the issue
```shell
import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))
```
### Relevant log output
_No response_</details>
It would be very nice if this feature could be enabled again. There are people that depend on it.
Thank you for your work.