Question about the output linear weight  
I notice that the output linear weight for BertForMaskedLM is the same as input embedding. I don't read anywhere in the original paper that the output projection is tied with word embedding? Can you please explain the design choice here? 

To reproduce:
```
m = transformers.BertForMaskedLM.from_pretrained('bert-base-uncased')
m.get_input_embeddings().weight - m.get_output_embeddings().weight
```

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