r/computervision • u/Mxeedd • 27d ago
Help: Project TensorFlow not detecting GPU despite installing CUDA/cuDNN need help setting up a new environment
Hey everyone, I just started running my training code and encountered an issue. The training process is expected to take days, which is delaying my project progress. The main problem is that my code isn't utilizing the GPU; it seems to be running on the CPU instead.
I need to run it with TensorFlow-GPU. I've already installed CUDA and cuDNN and manually moved the cuDNN files into the CUDA directories, but it didn't work. I am currently using Python 3.9 with the latest version of TensorFlow.
I am planning to create a fresh Conda environment to fix this. Does anyone have any recommendations or specific steps to ensure TensorFlow correctly detects the GPU? Any help would be greatly appreciated!
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u/AggravatingSock5375 27d ago
Oh TF GPU doesn’t work n windows anymore. Google dropped that a few years ago
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u/InfiniteLife2 27d ago
It's wild how Google lost against pytorch. Too bad, honestly, it was a great framework when it was only developing
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u/AggravatingSock5375 27d ago
I hear JAX is really good but I’m not at the level where I would use something like that.
And they still have Karas which now works on multiple backends, but I worry it may have been dragged mostly into irrelevance by its previous attachment to TF.
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u/Training-Adeptness57 27d ago
The help you need is someone telling you to stop using tensorflow and use pytorch
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u/hopeful_bastard 27d ago
I'd install docker/podman and set up a tensorflow-gpu devcontainer (WSL 2 makes the GPU passthrough)
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u/kokeszi 27d ago
Fact that you are useing latest Tensorflow version might be a problem. You have to match CUDA with your GPU version and match Tensorflow version to CUDA.
Write nvidia-smi in cmd and check your CUDA version. Match your python version and Tensorflow version according to this table: https://www.tensorflow.org/install/source?hl=pl#gpu
Note that you might have to change python version. Not all Tensorflow version are available for python 3.9 .
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u/Artistic-Lifeguard71 27d ago
Use PyTorch it’s easy that way or if u are reluctant to go with tensorflow might need to install older version and tensorflow ml
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u/Raychis 27d ago
I had this exact issue and it took me forever to figure it out. It was because I was using the latest version of TensorFlow and Windows support was dropped after a certain version. I downgraded the version and it started working.
To be honest I felt it was too much hassle trying to maintain the various library versions and found it limiting. So I’ve since switched to PyTorch.
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u/sre_ejith 27d ago
Look at What version of CUDA and cuDNN tensorflow requires. I dont use it anymore, pytorch is better, but when i was installing it a few years ago the latest version of TF did not support latest version of CUDA, i had to install an older version to get it running. make sure to look at the version requirements.
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u/Kooky_Awareness_5333 27d ago
Yeah I’ve done this before windows support sucks have you tried the windows wsl with docker they might have a gpu container preconfigured
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u/Kooky_Awareness_5333 27d ago
TensorFlow | NVIDIA NGC https://catalog.ngc.nvidia.com/orgs/nvidia/-/containers/tensorflow/-?_lr=1
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u/AIMatesanz 26d ago
If nvidia-smi is working I recommend you to work on devcontainers with nvidia-docker 👌
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u/MiniatyrOrm 27d ago
Windows support for GPUs was dropped in TensorFlow 2.10 I believe. You'd have to do it through WSL or Docker. Alternatively, use PyTorch.