[TBD] discrepancy regarding the tokenize method behavior - should the token correspond to the token in the vocabulary or to the initial text
## Environment info
```
- `transformers` version: 4.17.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version (GPU?): 1.10.0+cu111 (False)
- Tensorflow version (GPU?): 2.8.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
```

## Information

When adding a token to a tokenizer with a slow backend or to a tokenizer with a fast backend, if you use the `AddedToken` class with the `lstrip=True` argument, the output of the tokenize method is not the same.

This difference should be put into perspective by the fact that the encoding (the sequence of ids) is identical: the model will see the correct input.

## To reproduce

```python
from transformers import AutoTokenizer, AddedToken

def print_tokenizer_result(text, tokenizer):
    tokens = tokenizer.tokenize(text)
    print(f"tokenize method: {tokens}")

model_name = "patrickvonplaten/norwegian-roberta-base"

tokenizer_init = AutoTokenizer.from_pretrained(model_name)
tokenizer_init.save_pretrained("local_tokenizer")

model_name = "local_tokenizer"
tokenizer_s = AutoTokenizer.from_pretrained(model_name, use_fast=False)
tokenizer_f = AutoTokenizer.from_pretrained(model_name, use_fast=True)

new_token = "added_token_lstrip_false"
tokenizer_s.add_tokens(AddedToken(new_token, lstrip=True))
tokenizer_f.add_tokens(AddedToken(new_token, lstrip=True))

text = "Example with added_token_lstrip_false"
print("Output for the fast:")
print_tokenizer_result(text, tokenizer_f)
print("\nOutput for the slow:")
print_tokenizer_result(text, tokenizer_s)
```

Output:
```
Output for the fast:
tokenize method: ['Ex', 'amp', 'le', 'Ġwith', ' added_token_lstrip_false'] # Note the space at the beginning of ' added_token_lstrip_false'

Output for the slow:
tokenize method: ['Ex', 'amp', 'le', 'Ġwith', 'added_token_lstrip_false']
```
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