apptainer docker tensorflow container issue with 2.18 - skipping loading of GPU
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 35/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- docker, tensorflow
- Domain
- build-system, devops
Research direction
Start by reproducing the issue with the tensorflow/tensorflow:2.18-gpu and 2.17-gpu container images, comparing the available cuDNN libraries and GPU loading behavior. Trace the container build configuration to determine why the required library is unavailable; done means the 2.18 GPU container loads the GPU successfully without breaking the documented setup.
Written by the indexing model from the issue text.
Description
I'm using apptainer pull docker://tensorflow/tensorflow:latest-gpu, but tensorflow 2.18 is skipping loading of GPU, with this message:
W0000 00:00:1736383795.205652 747392 gpu_device.cc:2344] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at [https://www.tensorflow.org/install/gpu] for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
The tensor 2.17 container worked fine, but it appears that the 2.18 container wants to use libcudnn.9.0 but the container only provides libcudnn.8.0. The system libcudnn is not mapped to the container. The system has both 8 and 9 installed. This looks like a bug in the build of the container.
Note: Just using the system python and installing 2.18 (no containers), works fine as the system has both cudnn 8 and 9 installed.
- Dominant language
- Shell
- Stars
- 310
- Forks
- 141
- Avg merge
- 1h 28m
- Merged PRs (30d)
- 1
Getting set up
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First steps
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