[ENH] - Tensorflow with GPUs support

[GoldenCorgo]

What docker image(s) is this feature applicable to?

tensorflow-notebook

What changes are you proposing?

I propose to add GPUs support, because currently when I try to launch GPU calculations I get an error, I try to install inline Conda packages as described on tensor flow webpage, but it doesn't solve the problem.

How does this affect the user?

• Users will be able to use GPUs
• Users will waste less time on trying to configure GPUs to work with TF

Anything else?

No response

[mathbunnyru]

@GoldenCorgo is your issue the same as described here?

[mathbunnyru]

Closing as duplicate.

[benz0li]

@GoldenCorgo You may be interested in the CUDA-enabled JupyterLab Python docker stack, then:

[...]

Prerequisites

The same as the JupyterLab Python docker stack plus

• NVIDIA GPU
• NVIDIA Linux driver
• NVIDIA Container Toolkit

ℹ️ The host running the GPU accelerated images only requires the NVIDIA driver, the CUDA toolkit does not have to be installed.

[...]

Similar projects

• iot-salzburg/gpu-jupyter
• prp/jupyter-stack

What makes this project different:

1. Multi-arch: linux/amd64, linux/arm64/v8
2. Derived from nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
   • including development libraries and headers
3. TensortRT and TensorRT plugin libraries
   • including development libraries and headers
4. IDE: code-server next to JupyterLab
5. Just Python – no Conda / Mamba

See Notes for tweaks, settings, etc.