BertTokenizerFast ignores `pad_to_max_length`
# 🐛 Bug

Hi,

I noticed some strange behavior with the fast tokenizers in `v2.5.0`, which I think is a bug:
It seems `BertTokenizerFast` is ignoring the `pad_to_max_length` argument, as shown below:

```python
>>> from transformers import AutoTokenizer, BertTokenizer
>>> tok_auto = AutoTokenizer.from_pretrained('bert-base-uncased')
>>> tok_bert = BertTokenizer.from_pretrained('bert-base-uncased')
>>> a, b = 'Sentence 1', 'Sentence 2'
>>> 
>>> tok_bert.encode(a, b, max_length=10, pad_to_max_length=True)
[101, 6251, 1015, 102, 6251, 1016, 102, 0, 0, 0]  # <-- Expected behavior
>>> tok_auto.encode(a, b, max_length=10, pad_to_max_length=True)
[101, 6251, 1015, 102, 6251, 1016, 102] # <-- Actual behavior
```

Also, can some please explain the reason for the warning below that's raised when I set `pad_to_max_length=False` (which is only there in the fast tokenizer)?
```python
>>> tok_auto.encode(a, b, max_length=10, pad_to_max_length=False)
Disabled padding because no padding token set (pad_token: [PAD], pad_token_id: 0).
To remove this error, you can add a new pad token and then resize model embedding:
	tokenizer.pad_token = '<PAD>'
	model.resize_token_embeddings(len(tokenizer))
[101, 6251, 1015, 102, 6251, 1016, 102]
>>> tok_bert.encode(a, b, max_length=10, pad_to_max_length=False)
[101, 6251, 1015, 102, 6251, 1016, 102] # <-- No warning
```

Thanks!
Duplicate of #2947<|||||>Thanks @ranamihir @fte10kso, 

I'll have a look today. <|||||>Thanks @mfuntowicz!