Support identity normalizer in SentencePiece model
# What does this PR do?

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SentencePiece can train a model with a specified normalizer (for example `normalization_rule_name="nfkc"`).
https://github.com/google/sentencepiece/blob/master/doc/normalization.md

However, no normalization is done with `normalization_rule_name="identity"`, and `proto.normalizer_spec.precompiled_charsmap` in the SentencePiece model is empty.
Loading this model with `AlbertTokenizerFast.from_pretrained` occurres the following error:

```
>>> tokenizer = AlbertTokenizerFast.from_pretrained('.')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 1804, in from_pretrained
    return cls._from_pretrained(
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 1959, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/models/albert/tokenization_albert_fast.py", line 148, in __init__
    super().__init__(
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/tokenization_utils_fast.py", line 114, in __init__
    fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/convert_slow_tokenizer.py", line 1162, in convert_slow_tokenizer
    return converter_class(transformer_tokenizer).converted()
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/convert_slow_tokenizer.py", line 503, in converted
    tokenizer.normalizer = self.normalizer(self.proto)
  File "/Users/nminami/.pyenv/versions/3.10.4/lib/python3.10/site-packages/transformers/convert_slow_tokenizer.py", line 535, in normalizer
    list_normalizers.append(normalizers.Precompiled(precompiled_charsmap))
Exception: Error while attempting to build Precompiled normalizer: Cannot parse precompiled_charsmap
```

This error is caused by passing empty bytes to `normalizers.Precompiled`. So, this PR prevents the problem to check `proto.normalizer_spec.name` before passing empty bytes.

## How to reproduce this problem

```
OS/Arch: macOS/Apple Silicon
Python 3.10.4 (main, Jun 26 2022, 22:29:49) [Clang 13.0.0 (clang-1300.0.27.3)] on darwin

protobuf==3.19.0
sentencepiece==0.1.97
transformers==4.28.1
```

Save SentencePiece model using [python/test/botchan.txt](https://github.com/google/sentencepiece/blob/master/python/test/botchan.txt).
```python
import sentencepiece as spm
spm.SentencePieceTrainer.train(input='python/test/botchan.txt', model_prefix='spiece', vocab_size=1000, normalization_rule_name='identity')
```

Read SentencePiece model using `AlbertTokenizerFast.from_pretrained`.
```python
from transformers import AlbertTokenizerFast
tokenizer = AlbertTokenizerFast.from_pretrained('.')
```

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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      Pull Request section?
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      to it if that's the case.
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      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
  - I think this is a bug fix. So, no documentation updates required.
- [ ] Did you write any new necessary tests?


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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: HF Trainer: @stas00, Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

 -->

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_22809). All of your documentation changes will be reflected on that endpoint.<|||||>cc @ArthurZucker <|||||>> cc @Narsil if I am missing something (maybe the normalizers in rust should support identity type)

`normalizer: None` should do nothing.

Most likely a case not handled by our current code, we probably need to check that the spec is set to indentity, and not even attempt to create the `precompiled_charsmap` (since it's invalid and we already have a mecanism for identity)<|||||>@ArthurZucker Thank you for reviewing!
I fixed all issues related to empty `precompiled_charsmap` referring to following code.
https://github.com/huggingface/transformers/blob/dc67da01829090ec92dfc24653242cf3f56d1a01/src/transformers/convert_slow_tokenizer.py#L625-L628<|||||>The current modification LGTM. I'm not sure why the test fail, maybe rebase ?<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>Closing in favor of #24618