CamembertTokenizer cannot be pickled
Author: GMarzinotto
Pull request: no

## 🐛 Bug

<!-- Important information -->

Model I am using (Bert, XLNet....):  Camembert

Language I am using the model on (English, Chinese....): French

The problem arise when using my own modified scripts: 
  I have a nn.Module and, within this module, I store the tokenizers
  I can normally save these tokenizers easily, but CamemberTokenizer
  gives me a  **TypeError: can't pickle SwigPyObject objects** 


The tasks I am working on consists in creating a model and saving it using torch.save()

## To Reproduce
```
import torch
from transformers import  CamembertTokenizer, BertTokenizer

class MyModelCamembert(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.cheese =  CamembertTokenizer.from_pretrained('camembert-base') 

    def forward(self, x):
        return 1


class MyModelBert(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.cheese = BertTokenizer.from_pretrained('bert-base')

    def forward(self, x):
        return 1
        

# with bert it works
no_cheese = MyModelBert()
torch.save(no_cheese, "~/bert.pkl")

# with camembert it doesn't
cheese = MyModelCamembert()
torch.save(cheese, "~/camembert.pkl")
```


Steps to reproduce the behavior:

1. Try to save a module containing a tokenizer using the torch.save()
2. Find out it works for Bert but not for Camembert

<!-- If you have a code sample, error messages, stack traces, please provide it here as well. -->
Stack Trace when saving CamembertTokenizer

Traceback (most recent call last):
  File "/home/swqh0332/Desktop/blablapy.py", line 28, in <module>
    torch.save(cheese, "/home/swqh0332/camembert.pkl")
  File "/home/swqh0332/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/serialization.py", line 260, in save
    return _with_file_like(f, "wb", lambda f: _save(obj, f, pickle_module, pickle_protocol))
  File "/home/swqh0332/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/serialization.py", line 185, in _with_file_like
    return body(f)
  File "/home/swqh0332/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/serialization.py", line 260, in <lambda>
    return _with_file_like(f, "wb", lambda f: _save(obj, f, pickle_module, pickle_protocol))
  File "/home/swqh0332/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/serialization.py", line 332, in _save
    pickler.dump(obj)
TypeError: can't pickle SwigPyObject objects



## Expected behavior

I would like to be able to pickle the CamembertTokenizer as I it is possible with the other models


## Environment

* OS: Ubuntu 18
* Python version: 3.6.9
* PyTorch version: 1.3.1
* PyTorch Transformers version (or branch): 2.2.2
* Using GPU ? No
* Distributed or parallel setup ? No




Comments:
Did you look into just calling `save_pretrained()` on your CamembertTokenizer (and not include it inside your `MyModelCamembert`)?

No I did not try that because my model class is quite a big class that extends `nn.Module` and not `PreTrainedModel`. 
I'm just surprised that saving the model it works for Bert but fails for Camembert

Indeed, there was the state management lacking in the CamemBERT tokenizer, so it couldn't be pickled. It should have been fixed with 908230d.

Great !  So I'll just wait for the next release, Thanks ! :))

You can also install from source using `pip install git+https://github.com/huggingface/transformers` if you want to work with it now