Enable CUDA build for ARM64

[dictcp]

Enable CUDA build for ARM64

Since there are ARM64 platform like DGX spark, we need CUDA build for ARM64.
(give DGX spark case, given it requires CUDA capacity of 12.1, so latest CUDA is fine)

Checklist (especially for first-time contributors)

• I have performed a self-review of my code
• If it is a core feature, I have added thorough tests
• I will try not to use force-push to make the review process easier for reviewers
• I have updated the documentation for significant changes

[Copilot]

Pull Request Overview

This PR adds support for CUDA-enabled Docker images on ARM64 (aarch64) architecture to support platforms like NVIDIA DGX Spark. It introduces two new workflow jobs for building TensorFlow and PyTorch notebooks with CUDA support on aarch64 and adds these jobs to the dependency chain in the tag-push workflow.

• Adds aarch64-tensorflow-cuda job using CUDA variant
• Adds aarch64-pytorch-cuda12 job using CUDA 12 variant
• Updates tag-push workflow dependencies to include the new aarch64 CUDA jobs

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[Copilot]

Pull Request Overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated no new comments.

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[mathbunnyru]

You either have to make it work for pytorch-cuda11, or do not download it here, otherwise it will fail

[dictcp]

added pytorch-cuda11 to keep thing easier to read. (and ppl using GH100 can use this image 😀)

[mathbunnyru]

@dictcp it seems we can't build it, so you need to revert last commit and make an exception here

[Copilot]

Pull Request Overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

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[benz0li]

@mathbunnyru I think you need to change the first item in the checklist from

I have performed a self-review of my code

to

I, or Copilot on my behalf, have performed a review of the code