Bertabs example: index_select(): Expected dtype int64 for index
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.3.1
- Platform: Ubuntu 18.04
- Python version: 3.8.0
- PyTorch version (GPU?): torch==1.7.0
- Tensorflow version (GPU?):
- Using GPU in script?:yes
- Using distributed or parallel set-up in script?: no

### Who can help
@patil-suraj

## Information

Following the example in the seq2seq/bertabs readme.md.
I am getting this error:
```
File "/code/tools/transformers/examples/seq2seq/bertabs/modeling_bertabs.py", line 919, in _fast_translate_batch
    alive_seq = torch.cat([alive_seq.index_select(0, select_indices), topk_ids.view(-1, 1)], -1)
RuntimeError: index_select(): Expected dtype int64 for index
```
In a debugger, I see that the 'select_indices' parameter is a tensor of floats.

I don't understand the beam mechanism, so I don't know where to start troubleshooting this.

Any help would be great!

-Tim
Hello! The `bert_abs` example is not maintained anymore, and should be moved to `examples/contrib/legacy`.

The recommended way of training sequence-to-sequence models is described in the `examples/seq2seq/README.md` file. What are you trying to do with `bertabs`, so that we may help you find what you need?<|||||>Hi!
Thanks for your response.
I'm just starting to experiment with abstractive text summarization.
Is this something I should look for in the Hugging Face tools and samples?
Thanks again,
Tim<|||||>I believe abstractive text summarization is implemented in the `seq2seq` examples, as the XSUM models were trained to do abstractive text summarization.

Have you taken a look at the summarization examples in https://github.com/huggingface/transformers/tree/master/examples/seq2seq?

@patil-suraj may also be of help.<|||||>Thanks again!
I’ll take a look at the seq2seq examples.  
-Tim<|||||>This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.

If you think this still needs to be addressed please comment on this thread.