[MNT] Swapped tensorflow and pytorch to install only CPU version

[chrisholder]

Reference Issues/PRs

#2415

What does this implement/fix? Explain your changes.

This PR adds a custom github action when installing all_extras on ubuntu. The custom action installs tensorflow-cpu and pytorch cpu instead of the "normal" version which comes with all the GPU code. By installing the CPU version it saves considerable install time but in addition saves a considerable amount of RAM usage during the test running (as the package sizes are dramatically smaller). This should help to prevent issues causing the CI to crash due to exceeding memory limits.

Does your contribution introduce a new dependency? If yes, which one?

Any other comments?

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[chrisholder]

Do not merge this yet need to get rid of the additional periodic test which I turned on just for this branch.

[MatthewMiddlehurst]

1. why only linux?
2. doesn't this still install tensorflow and torch through all_extras?
3. wouldnt we want to still install the gpu versions somewhere in the testing workflows?

[chrisholder]

1. why only linux?
2. doesn't this still install tensorflow and torch through all_extras?
3. wouldnt we want to still install the gpu versions somewhere in the testing workflows?

why only linux?
By default windows and macos doesn't install the gpu version so you only need to opt out on linux. There docs say:

Windows:
Caution: 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](https://tensorflow.org/install/pip#windows-%5Bwsl2%5D), or install tensorflow-cpu and, optionally, try the [TensorFlow-DirectML-Plugin](https://github.com/microsoft/tensorflow-directml-plugin#tensorflow-directml-plugin-)

Macos:
Currently there is no official GPU support for running TensorFlow on MacOS. The following instructions are for running on CPU.

The same is true for Torch macos doesn't support GPU, and windows you have to specify additional parameters to get the GPU version (which we don't currently do).

doesn't this still install tensorflow and torch through all_extras?
I believe if you install the dependency (i.e. tensorflow/torch) on a specific version and then run pip install .[all_extras] it won't reinstall them as they already are installed (and pip won't try change the version). While tensorflow-cpu has a different name it resolves to tensorflow so pip doesn't know the difference. I checked the logs here: https://github.com/aeon-toolkit/aeon/actions/runs/12073657794/job/33670204314?pr=2416#step:5:346 and it seems that it doesn't try reinstall the dependency.

wouldnt we want to still install the gpu versions somewhere in the testing workflows?
I don't think so? The code that we run in the CI will be the exact same. Tensorflow-cpu is literally just the same code but all the extra gpu "stuff" is excluded from the build (which we never ran for any OS in the CI). Unless we're able to run the CI with a GPU then I don't think there is a point.

[MatthewMiddlehurst]

ok, let me know when its ready

[chrisholder]

Ready for review @MatthewMiddlehurst

[MatthewMiddlehurst]

lgtm