Transformer-XL: wrong encoding in the vocab
Seems that something odd happened during vocab serialization as many symbols with non-latin symbols are broken.
E.g.:
```
In [1]: import pytorch_pretrained_bert

In [2]: tokenizer = pytorch_pretrained_bert.TransfoXLTokenizer.from_pretrained('transfo-xl-wt103')

In [4]: print(tokenizer.idx2sym[224178])
'EnquÃªtes
```

The correct token should be "'Enquêtes". And there are around 10k tokens like this.

Could it be 'encoding="latin1"' here?
https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/pytorch_pretrained_bert/convert_transfo_xl_checkpoint_to_pytorch.py#L54
Yeah, the re-encoding seems to fix the bug:
```
In [6]: "'EnquÃªtes".encode('latin1').decode('utf8')
Out[6]: "'Enquêtes"
```<|||||>which version of python are you using?<|||||>It's python3.6. Does the snippet above gives different result on other version?

JFYI: I'm using the script below to create a fixed vocab and save in the current folder.
```(python)
import collections
import urllib.request

from pytorch_pretrained_bert import tokenization_transfo_xl
import torch


def fix(x):
    return x.encode('latin1').decode('utf8')


def main():
    basedir = '.'
    good_vocab_path = basedir + '/' + tokenization_transfo_xl.VOCAB_NAME
    vocab_url = tokenization_transfo_xl.PRETRAINED_VOCAB_ARCHIVE_MAP['transfo-xl-wt103']
    urllib.request.urlretrieve(vocab_url, basedir + '/vocab.buggy.bin')
    vocab = torch.load(basedir + '/vocab.buggy.bin')

    vocab['counter'] = collections.Counter({fix(k): v for k, v in vocab['counter'].items()})
    vocab['sym2idx'] = {fix(k): v for k, v in vocab['sym2idx'].items()}
    vocab['idx2sym'] = [fix(k) for k in vocab['idx2sym']]
    torch.save(vocab, good_vocab_path)


if __name__ == "__main__":
    main()
```<|||||>Maybe indeed. Do you want to submit a PR to fix this?<|||||>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.
