I have a new computer running Windows 11, with CUDA 12.1 supporting an RTX 4080 GPU. I installed Tensorflow 2.13.0 and have Python 3.11.4. Tensorflow does not find the GPU. Is Tensorflow 2.13.0 compatible with CUDA 12.1?
P.S. tried installing the nightly, which also didn’t detect the GPU.
I had the same problem and it solved by following this Zainstaluj TensorFlow z pip
do the following steps:
- conda create --name tf python=3.9
- conda activate tf
- conda install -c conda-forge cudatoolkit=11.8.0
- pip install nvidia-cudnn-cu11==188.8.131.52
- pip install --upgrade pip
- pip install tensorflow==2.13.*
- test the GPU
Hi @Steve_F, As per the test build configuration Tensorflow 2.13 supports cuDNN: 8.6, CUDA:11.8 and again TensorFlow
2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow
2.11 , you will need to install TensorFlow in WSL2 for using the GPU. Thank You.
I’ve run aground in WSL2 installation – when attempting to install the cuDNN libraries with
sudo apt-get install libcudnn8
I get the following:
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
E: Unable to locate package libcudnn8
As a consequence, Tensorflow doesn’t find the GPU. I’ve researched this and haven’t found a solution that works.
Thanks – did not work for me.
Finally got it to work by installing the cuDNN library locally, following the Debian installation instructions found here.
Sorry for asking, but I couldn’t find where the doc mentioned that Tensorflow 2.10 was the last tf release that supported GPU on native Windows. Would you mind providing the link?
Hi @Chieh-Sheng_Chen, You can see it here. Thank You!
Thanks for replying.
I think I know why I couldn’t find related information before because my default language of the doc is zh-TW.
After I changed it to English, there is actually more information.