GPT2TokenizerFast does not preserve special tokens' ids after a save and load.
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): GPT2 Fast Tokenizer

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

This problem only happens with `GPT2TokenizerFast` and not `GPT2Tokenizer`

## To reproduce

Steps to reproduce the behavior:

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```python
from transformers import GPT2TokenizerFast

tokenizer = GPT2TokenizerFast.from_pretrained('gpt2')
print('special tokens: ', tokenizer.additional_special_tokens, tokenizer.additional_special_tokens_ids)
tokenizer.add_special_tokens({'additional_special_tokens': ['<special_token>'], 'pad_token': '<pad>'})
print('special tokens: ', tokenizer.additional_special_tokens, tokenizer.additional_special_tokens_ids)
print(tokenizer.pad_token, tokenizer.convert_tokens_to_ids(tokenizer.pad_token))
tokenizer.save_pretrained('./save_dir/')

tokenizer = GPT2TokenizerFast.from_pretrained('./save_dir/')
print('special tokens: ', tokenizer.additional_special_tokens, tokenizer.additional_special_tokens_ids)
print(tokenizer.pad_token, tokenizer.convert_tokens_to_ids(tokenizer.pad_token))
```

It outputs

```
special tokens:  [] []
special tokens:  ['<special_token>'] [50257]
<pad> 50258
special tokens:  ['<special_token>'] [50258]
<pad> 50257
```

## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

```
special tokens:  [] []
special tokens:  ['<special_token>'] [50257]
<pad> 50258
special tokens:  ['<special_token>'] [50257]
<pad> 50258
```

## Environment info
<!-- You can run the command `python transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 2.5.1
- Platform: Linux-5.4.19-100.fc30.x86_64-x86_64-with-fedora-30-Thirty
- Python version: 3.7.6
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): 2.1.0 (True)
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: False

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
