inconsistent tokenize output
# 🐛 Bug

## Information

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

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

The problem arises when using: BertTokenizer

I am using the BertModel. When predicting the result, it got inconsistent output (the output differs from time to time). It turns out that the tokenizer gets different output when the input string is "\n" or "\n\n". 

for example: 
<pre><code> 
from transformers.tokenization_bert import BertTokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-chinese')
tokens = tokenizer.tokenize("\n\n")
output: ['[SEP]'] or ['[PAD]'] or ['[CLS]']
</code></pre>


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