Keyword errors on tokenizer.encode_plus
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): BertTokenizer

Language I am using the model on (English, Chinese ...): English (`bert-base-uncased`)

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)

## To reproduce

Steps to reproduce the behavior:

Code:
```
tokenizer = BERTTokenizer.from_pretrained('bert-base-uncased')`
result = tokenizer.encode_plus("This is an example sentence", add_special_tokens=True, 
max_length=64, pad_to_max_length=True, return_attention_masks=True, return_tensors='pt'
```

Result:
```
Traceback (most recent call last): 
File "<stdin>", line 1, in <module>
File ".../python3.8/site-packages/transformers/tokenization_utils.py", line 786, in encode_plus
        first_ids = get_input_ids(text)
File ".../python3.8/site-packages/transformers/tokenization_utils.py", line 778, in get_input_ids
        return self.convert_tokens_to_ids(self.tokenize(text, **kwargs))
File ".../python3.8/site-packages/transformers/tokenization_utils.py", line 649, in tokenize                                     
        tokenized_text = split_on_tokens(added_tokens, text)
File ".../python3.8/site-packages/transformers/tokenization_utils.py", line 644, in split_on_tokens             
        return sum((self._tokenize(token, **kwargs) if token not \ 
File ".../python3.8/site-packages/transformers/tokenization_utils.py", line 644, in <genexpr>                  
        return sum((self._tokenize(token, **kwargs) if token not \ 
TypeError: _tokenize() got an unexpected keyword argument 'pad_to_max_length'   
```

A similar issue occurs if I remove the `pad_to_max_length` keyword; then `return_attention_masks` is the unexpected keyword.

## Expected behavior

Expected: the function returns without error a dict with the attention masks, padded sequence, and some other info, as specified by the documentation.

## Environment info

- `transformers` version: 2.1.1
- Platform: WSL 2, Ubuntu 18.04.4 LTS
- Python version: 3.8
- PyTorch version (GPU?): 1.4.0
- Tensorflow version (GPU?): N/A
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no

@tchainzzz  Can you tell how you resolved the particular issue?
