[RAG] RagTokenizer failing in decoding RAG Generator output
## Environment info
- `transformers` version: 3.3.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0+cu101 (False)
- Tensorflow version (GPU?): 2.3.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help
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## Information

Model I am using (Bert, XLNet ...): RAG

The problem arises when using:
* [X] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [X] an official GLUE/SQUaD task: `dummy_dataset`
* [ ] my own task or dataset: (give details below)

## To reproduce
Steps to reproduce the behavior:

1. Run example code snippet from https://huggingface.co/transformers/master/model_doc/rag.html on `dummy_dataset`
2. Generate string from model output (Tried both `rag-sequence-nq` and `rag-token-nq`

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```
!pip install git+https://github.com/huggingface/transformers.git
!pip install datasets
!pip install faiss-cpu

from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration, RagSequenceForGeneration
import torch
import faiss

tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-nq")
model = RagSequenceForGeneration.from_pretrained("facebook/rag-token-nq", use_dummy_dataset=True)
retriever = RagRetriever.from_pretrained("facebook/rag-token-nq", index_name="exact", use_dummy_dataset=True)

input_dict = tokenizer.prepare_seq2seq_batch("How many people live in Paris?", "In Paris, there are 10 million people.", return_tensors="pt")
input_ids = input_dict["input_ids"]

model = RagTokenForGeneration.from_pretrained("facebook/rag-token-nq", retriever=retriever)
outputs = model(input_ids=input_ids, labels=input_dict["labels"])

generated_string = tokenizer.batch_decode(outputs, skip_special_tokens=True)
print(generated_string)
```
Error returned is on executing `tokenizer.batch_decode(outputs, skip_special_tokens=True)` -
```
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils.py in convert_ids_to_tokens(self, ids, skip_special_tokens)
    721         tokens = []
    722         for index in ids:
--> 723             index = int(index)
    724             if skip_special_tokens and index in self.all_special_ids:
    725                 continue

ValueError: invalid literal for int() with base 10: 'l'
```
## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
Tokenizer should decode to string. Not sure but closely related to https://github.com/huggingface/transformers/pull/4836
Sorry it was my mistake, I need to get generated ids calling `model.generate` instead of `model`.

Adding fix here if anyone search for the same issue -

```
generated_ids = model.generate(input_ids=input_ids, labels=input_dict["labels"])

generated_string = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
print(generated_string)
``` 
