Fast Tokenizers do not work when `return_offsets_mapping=True, return_tensors="pt"`
Author: GuillemGSubies
Pull request: no

# 🐛 Bug

## Information

When I try the following code:

```python
from transformers import BertTokenizerFast
fast = BertTokenizerFast.from_pretrained("bert-base-cased")
fast.encode_plus("Hello I am tokenizing", return_offsets_mapping=True)
```

It works as intended.

However, if I try:

```python
from transformers import BertTokenizerFast
fast = BertTokenizerFast.from_pretrained("bert-base-cased")
fast.encode_plus("Hello I am tokenizing", return_offsets_mapping=True, return_tensors="pt")
```

It throws the following error:

```
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-2-c6ee501a801c> in <module>
      1 from transformers import BertTokenizer, BertTokenizerFast
      2 fast = BertTokenizerFast.from_pretrained("bert-base-cased")
----> 3 fast.encode_plus("Hello I am tokenizing", return_offsets_mapping=True, return_tensors="pt")

~/.conda/envs/bertology/lib/python3.7/site-packages/transformers/tokenization_utils.py in encode_plus(self, text, text_pair, add_special_tokens, max_length, pad_to_max_length, stride, truncation_strategy, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, **kwargs)
   1972             return_offsets_mapping=return_offsets_mapping,
   1973             pad_to_max_length=pad_to_max_length,
-> 1974             **kwargs,
   1975         )
   1976 

~/.conda/envs/bertology/lib/python3.7/site-packages/transformers/tokenization_utils.py in batch_encode_plus(self, batch_text_or_text_pairs, add_special_tokens, max_length, stride, truncation_strategy, pad_to_max_length, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, **kwargs)
   1926                 stack = tf.stack(stack, axis=0)
   1927             elif return_tensors == "pt":
-> 1928                 stack = torch.stack(stack, dim=0)
   1929             elif not return_tensors and len(stack) == 1:
   1930                 stack = stack[0]

TypeError: expected Tensor as element 0 in argument 0, but got list
```

## Environment info
 
- `transformers` version: 2.8.0
- Platform: Linux-4.4.0-174-generic-x86_64-with-debian-stretch-sid
- Python version: 3.7.6
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): not installed (NA)


Comments:
@GuillemGSubies I think this works with the lastest `master` version of Transformers and using `tokenizers` in version *0.7.0*:

```python
from transformers import BertTokenizerFast
fast = BertTokenizerFast.from_pretrained("bert-base-cased")
fast.encode_plus("Hello I am tokenizing", return_offsets_mapping=True, return_tensors="pt")
```

Outputs:

```bash
{'input_ids': tensor([[  101,  8667,   146,  1821, 22559,  4404,   102]]), 'token_type_ids': tensor([[0, 0, 0, 0, 0, 0, 0]]), 'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1]]), 'offset_mapping': tensor([[[ 0,  0],
         [ 0,  5],
         [ 6,  7],
         [ 8, 10],
         [11, 16],
         [16, 21],
         [ 0,  0]]])}
```

Oh, I should have tried in master before opening the issue. I will wait for the next release then, thanks you.