Tokenizer could accept a string tensor
Currently, the [`batch_encode_plus`](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.batch_encode_plus) method from tokenizer, can return a Tensorflow tensor. 
It can be done assigning `tf` to the optional parameter `return_tensors`.

It would be great if this method also accepted a Tensorflow string tensor in parameter ` batch_text_or_text_pairs`.


For instance, if someone has the following `sample_string_tensor`:

```python
import tensorflow as tf

batch_size = 4
sample_string_tensor = tf.convert_to_tensor(
["sãmple utf-8 stríng - " + str(i) for i in range(n_strings)]
)

# <tf.Tensor: shape=(4,), dtype=string, numpy=
# array([b's\xc3\xa3mple utf-8 str\xc3\xadng - 0',
#        b's\xc3\xa3mple utf-8 str\xc3\xadng - 1',
#        b's\xc3\xa3mple utf-8 str\xc3\xadng - 2',
#        b's\xc3\xa3mple utf-8 str\xc3\xadng - 3'], dtype=object)>
```
the tokenization would be as simple as:
```python
tokenized_sample = tokenizer.batch_encode_plus(
    sample_string_tensor, 
    max_length=max_length, 
    pad_to_max_length=True, 
    return_tensors="tf"
)
```
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
