T5Tokenizer shouldn't add pad token as prefix to labels

## Information
`prepare_seq2seq_batch` method in `T5Tokenizer` now prefixes `pad` token to the `labels`. [here](https://github.com/huggingface/transformers/blob/master/src/transformers/tokenization_t5.py#L362)
But in finetune.py [here](https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune.py#L149) we are calling `_shift_right` for T5 , which again adds another `pad` token at the beginning, so now `decoder_input_ids` contain two `pad` tokens. 
## To reproduce

```python
from transformers import T5Tokenizer, T5Model
model = T5Model.from_pretrained("t5-small")
tok = T5Tokenizer.from_pretrained("t5-small")
enc = tok.prepare_seq2seq_batch("src text", "target text", return_tensors="pt")
print(enc["labels"])
# tensor([[   0, 2387, 1499,    1]])
decoder_input_ids = model._shift_right(enc["labels"]) # call _shift_right
print(decoder_input_ids)
#tensor([[   0,    0, 2387, 1499]])
```
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## Expected behavior
There should be no special prefix token for T5 `labels`

@sshleifer 
