chore: allow protobuf 3.20.3 requirement
Allow latest bugfix release for protobuf (3.20.3)

# What does this PR do?
Change in requirements for python library so it allows the use of latest bugfix release for protobuf (3.20.3) instead of restricting it to the upper bound limit for this dependency to 3.20.2 (<=3.20.2).


The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_22759). All of your documentation changes will be reflected on that endpoint.<|||||>cc @ydshieh <|||||>Hi @jose-turintech Thank you for this PR ❤️ .

Unfortunately, as you can see in the CI results, the changes cause some errors

```python
FAILED tests/models/albert/test_tokenization_albert.py::AlbertTokenizationTest::test_pickle_subword_regularization_tokenizer
FAILED tests/models/bert_generation/test_tokenization_bert_generation.py::BertGenerationTokenizationTest::test_pickle_subword_regularization_tokenizer
```
(Fatal Python error: Segmentation fault)

So we are not able to merge this PR so far. There might be some way to fix these 2 issues, but I am not sure. Let me know if you want to dive into this.
<|||||>Hey @jose-turintech ,

Thanks for submitting this PR! The latest `tensorflow==2.12` release depends on `protobuf >= 3.20.3`, so this would unblock installing the latest `tensorflow` alongside `transformers`. 

After setting up this PR's environment, I just ran this locally and those tests seem to pass. Would it be possible to trigger a re-run @ydshieh? Alternatively, would it be possible to get extra logs on the CI failures? <|||||>> Hey @jose-turintech ,
> 
> Thanks for submitting this PR! The latest `tensorflow==2.12` release depends on `protobuf >= 3.20.3`, so this would unblock installing the latest `tensorflow` alongside `transformers`.
> 
> After setting up this PR's environment, I just ran this locally and those tests seem to pass. Would it be possible to trigger a re-run @ydshieh? Alternatively, would it be possible to get extra logs on the CI failures?

Hello @adriangonz, just updated my branch with latest changes on origin in order to test if the PR check would retrigger. It seems so; so i guess we'll see if the PR passes all check within some minutes.

Thanks for your comment.<|||||>As you can see in [the latest run](https://app.circleci.com/pipelines/github/huggingface/transformers/63908/workflows/bcaedcfc-54af-42e8-9e9c-a97d9612b185/jobs/789487), the 2 failed tests are still there.

The error (provided at the end below) is some processes crashed, and there is no more informative log being given by the `pytest`.

When I run the two failed tests individually on my local env., they pass.

However, since the latest release of `tensorflow-probaility` broke everything in the CI since we don't support `TensorFlow 2.12` yet and it needs that version, we will take a more deep look to see if we can unblock this situation.

```bash
=================================== FAILURES ===================================
______ tests/models/bert_generation/test_tokenization_bert_generation.py _______
[gw0] linux -- Python 3.8.12 /home/circleci/.pyenv/versions/3.8.12/bin/python
worker 'gw0' crashed while running 'tests/models/bert_generation/test_tokenization_bert_generation.py::BertGenerationTokenizationTest::test_pickle_subword_regularization_tokenizer'
_______________ tests/models/albert/test_tokenization_albert.py ________________
[gw6] linux -- Python 3.8.12 /home/circleci/.pyenv/versions/3.8.12/bin/python
worker 'gw6' crashed while running 'tests/models/albert/test_tokenization_albert.py::AlbertTokenizationTest::test_pickle_subword_regularization_tokenizer'
``` <|||||>@ydshieh i've merged origin into this branch once again to retrigger CI checks just to see if test passed after the downtime of some huggingface transformers yesterday. Tests pass now after your modifications :) .

Only difference with main is the tensorflow-probaility>0.20 restriction is not applied in this CI build.

Thanks for taking the time to take a look into the issue.<|||||>@jose-turintech I accidentally pushed the experimental changes to this PR branch, I am really sorry. The CI is green as I removed some 3rd packages (tensorflow for example), which it should be kept.

I am still looking how to resolve the issue. There is a big problem (at least the desired environment when running inside CircleCI runner). I will keep you update soon.<|||||>In the meantime, let us convert this PR into a draft mode, so it won't be merged by accident. Thank you for your comprehension.<|||||>## Issue

(for the hack to fix, see the next reply)

This PR want to use `protobuf==3.20.3` so we can use `tensorflow==2.12`. However, some tests like `test_pickle_subword_regularization_tokenizer` fails with this environment. The following describes the issue.

- First, setup the env. to have `tensorflow-cpu==2.12` with `potobuf==3.20.3`  but `without torch installed`. 
- Use a `sentencepiece` tokenizer with `enable_sampling=True`
- `run the code with pytest` --> crash (core dump)
    - (run with a script --> no crash)
    - (run the code with pytest where torch is also there --> no crash)

Here are 2 code snippets to reproduce (and not): run in python 3.8 will more likely to reproduce
 ______________________________________________________________________________

- create `tests/test_foo.py`  and run `python -m pytest -v tests/test_foo.py` --> crash

```
from transformers import AlbertTokenizer
def test_foo():

    fn = "tests/fixtures/spiece.model"
    text = "This is a test for subword regularization."

    # `encode` works with `False`
    sp_model_kwargs = {"enable_sampling": False}
    tokenizer = AlbertTokenizer(fn, sp_model_kwargs=sp_model_kwargs)

    # test 1 (usage in `transformers`)
    # _ = tokenizer.tokenize(text)

    # test 2 (direct use in sentencepiece)
    pieces = tokenizer.sp_model.encode(text, out_type=str)

    # `encode` fails with `True` if torch is not installed and tf==2.12
    sp_model_kwargs = {"enable_sampling": True}
    tokenizer = AlbertTokenizer(fn, sp_model_kwargs=sp_model_kwargs)

    # test 1 (usage in `transformers`)
    # _ = tokenizer.tokenize(text)

    # This gives `Segmentation fault (core dumped)` under the above mentioned conditions
    # test 2 (direct use in sentencepiece)
    pieces = tokenizer.sp_model.encode(text, out_type=str)
    print(pieces)
```

- create `foo.py`  and run `python foo.py` -> no crash

```
from transformers import AlbertTokenizer

fn = "tests/fixtures/spiece.model"
text = "This is a test for subword regularization."

# `encode` works with `False`
sp_model_kwargs = {"enable_sampling": False}
tokenizer = AlbertTokenizer(fn, sp_model_kwargs=sp_model_kwargs)

# test 1 (usage in `transformers`)
# _ = tokenizer.tokenize(text)

# test 2 (direct use in sentencepiece)
pieces = tokenizer.sp_model.encode(text, out_type=str)

# `encode` works with `True` if torch is not installed and tf==2.12
sp_model_kwargs = {"enable_sampling": True}
tokenizer = AlbertTokenizer(fn, sp_model_kwargs=sp_model_kwargs)

# test 1 (usage in `transformers`)
# _ = tokenizer.tokenize(text)

# This works
# test 2 (direct use in sentencepiece)
pieces = tokenizer.sp_model.encode(text, out_type=str)
print(pieces)
```<|||||>## (Hacky) Fix 
The relevant failing tests are:
- test_subword_regularization_tokenizer
- test_pickle_subword_regularization_tokenizer

As mentioned above, those failing tests only happen when running with pytest. Furthermore, those test don't actually need `protobuf` in order to run. However, in the TF CI job, `protobuf` is a dependency from TensorFlow.

It turns out that running those 2 problematic tests in a subprocess will avoid the crash. It's unclear what actually happens though.

This PR modify those 2 tests to be run in a subprocess, so we can have `protobuf==3.20.3` along with `tensroflow==2.12`.<|||||>The TF job is successful with the last fix, see this job run

https://app.circleci.com/pipelines/github/huggingface/transformers/64174/workflows/688a1174-8a6f-4599-9479-f51bbc2aacdb/jobs/793536/artifacts

The other jobs should be fine (we will see in 30 minutes) as they already pass before.<|||||>> Thank you again @jose-turintech for this PR, which allows to use TF 2.12!

Thank you very much for taking the time to fix the issues, you did all the work; really appreciate it.