Add 3D attention_mask input support
Author: SmileTM
Pull request: yes

Add 3D attention_mask input support. (The PyTorch version support, but TF cant.)
Sometimes we need to input custom 3D attention_mask.

```python
import tensorflow as tf
from transformers import TFBertModel
plm_name = "bert-base-chinese"
plm = TFBertModel.from_pretrained(plm_name, return_dict=False)
i = tf.ones((1, 512), dtype=tf.int32)
m = tf.ones((1, 512, 512), dtype=tf.int32)
a, b = plm((i, m, i))
print(a)
print(b)
```


# What does this PR do?

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Fixes # (issue) Add 3D attention_mask input support. 


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Comments:
This code will be copied to RemBERT and RoBERTa as well, because those inherit the same `call()` method. I think we can accept the PR with just a BERT test, though I'm not sure - @sgugger WDYT?

I think it's important to also have parity for the rest of the TF models - can all models accept the 3D attention mask? How hard is it to propagate this to all models? I don't think it's best if BERT can accept differing inputs than other TF models. 

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.