Fixed datatype related issues in `DataCollatorForLanguageModeling`
Author: capemox
Pull request: yes

# What does this PR do?
Fixes two issues regarding the test `tests/trainer/test_data_collator.py::TFDataCollatorIntegrationTest::test_all_mask_replacement`:

1. I got the error `RuntimeError: "bernoulli_tensor_cpu_p_" not implemented for 'Long'`. This is because the `mask_replacement_prob=1` and `torch.bernoulli` doesn't accept this type (which would be a `torch.long` dtype instead). I fixed this by manually casting the probability arguments in the `__post_init__` function of `DataCollatorForLanguageModeling`.
2. I also got the error 
```tensorflow.python.framework.errors_impl.InvalidArgumentError: cannot compute Equal as input #1(zero-based) was expected to be a int64 tensor but is a int32 tensor [Op:Equal]```
due to the line 
```tf.reduce_all((batch["input_ids"] == inputs) | (batch["input_ids"] == tokenizer.mask_token_id))```
in `test_data_collator.py`. This occurs because the type of the `inputs` variable is `tf.int32`. Solved this by manually casting it to `tf.int64` in the test, as the expected return type of `batch["input_ids"]` is `tf.int64`.

These changes were done on Python `3.12.8`. The dependencies installed were as `pip install -e ".[dev]"` along with:
- torch==2.6.0
- tensorflow==2.18.0
- tf-keras==2.18.0

Motivation: I wanted to make some contributions to `DataCollatorForLanguageModeling`, unfortunately though the tests were failing on the existing code itself. I thought I'll fix these bugs before moving forward with that.
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Fixes # (issue)


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## Who can review?

@Rocketknight1 should be able to review this!

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Comments:
Hi 👋, thank you for opening this pull request! The pull request is converted to draft by default. When it is ready for review, please click the `Ready for review` button (at the bottom of the PR page).

Hey @Rocketknight1! I saw the force push on the branch, but not really sure what to make of it. Hope the PR works as expected, and that there aren't any issues

Hi @capemox, the force push is caused by me rebasing with the "Update branch" tool in the Github interface, don't worry about it! I often do this with PRs before merging to fix any CI issues. You can `git pull` or `git reset` locally to catch up to it. 

Thanks a lot for the clarification @Rocketknight1! Feels great being able to contribute!

Not wanting to be too selfish, but could you also take a look at this PR:
https://github.com/huggingface/transformers/pull/36497