Make the TF dummies even smaller
cc @ydshieh - this will probably break some things, but if I can make it work it should reduce the memory usage during building a lot
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_24071). All of your documentation changes will be reflected on that endpoint.<|||||>Adding @frostming's fix for Keras 2.13 to this PR as well<|||||>Tests are passing now, pinging @ydshieh and @amyeroberts for quick review! Unfortunately it's quite hard for me to test if this PR will fix the entire memory issue in the overnight CI, but we'll try this fix and if the memory issues remain then I'll try some other things too.<|||||>I can trigger a run.<|||||>It's more like when several processes are run in parallel: on circleci, 8 pytest processes.<|||||>I also have the same question on why the memory usage increases that much. Previously, we don't really use batch size 1 in dummy if I remember correctly.<|||||>A run is triggered [here](https://app.circleci.com/pipelines/github/huggingface/transformers/65919/workflows/b0c80ba6-3278-47a0-87d9-228c402b35e9/jobs/819654).

If you need more changes and more runs to check, you can update the branch 

https://github.com/huggingface/transformers/tree/run_even_lower_tf_dummy_memory

on top of this PR branch.<|||||>@amyeroberts I don't have a very good intuition for this, actually. I think it's some combination of:

- The test runners were already at 90%+ memory usage before all of these PRs and tests are run in parallel as @ydshieh said, which means small perturbations could push them over the limit.
- The update changed the shapes of dummies a bit - they should be smaller on average, especially after this PR, but maybe they ended up a little larger for some high-memory models and that caused the issues.

It's also possible that the update sped up building by removing unnecessary build ops left over from TF 1 and not unneccessarily passing dummies when models were already built. Speeding up builds might cause tests to be in the actual model calls more of the time, and if peak model usage occurs during the actual model calls and we have lots of tests running in parallel then more tests being in the calls simultaneously might result in higher peak memory usage for the test server.

This is all purely speculative on my part, though - I can't reproduce the problem locally and the nature of the parallel tests makes it hard to point to a single culprit for an OOM error!<|||||>@ydshieh the new run seems to be passing - there's an unrelated issue with one of the vit-mae tests that I can't reproduce locally and that doesn't seem related, but I think this PR resolves most of the problems!<|||||>@Rocketknight1 Unfortunately, it doesn't pass. We have to go to the `Resource` tab, and see the memory usage.

<img width="1017" alt="Screenshot 2023-06-07 145417" src="https://github.com/huggingface/transformers/assets/2521628/59ad6a00-f07e-44e8-8fce-dd4164b7e3f6">

And if you click [Download the full output as a file](https://circleci.com/api/v1.1/project/github/huggingface/transformers/819654/output/111/0?file=true&allocation-id=64806dd5d4d5c9764f27e205-0-build%2F60721B2E), you will see `worker gw7 crashed and worker restarting disabled`.

😢 😭 
<|||||>Well, to be more sure, I can revert the PR #23234 on **another branch**, so would be `main` without that PR, and run the test. The goal is to make sure no other PRs contribute to the OOM issue.

Do you want me to do this?<|||||>No, I'm pretty confident that the change to the dummies is the cause!<|||||>@ydshieh Can we reduce the number of parallel workers by 1 for these tests? I think the speed boost from these PRs (plus some other ones I have planned) should compensate for any slowdown we experience, and it would be good to be able to make small changes without breaking fragile parallel tests like these<|||||>Let me open a PR for that :-)<|||||>(rebasing onto @ydshieh's PR to test everything in combination)