Pass the original mask tensor when using ds-inference at BLOOM architecture
Author: RezaYazdaniAminabadi
Pull request: yes

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This resolves DeepSpeed-Inference integration for the BLOOM model. There is no need to convert `attention_mask` to `casual_mask` when using DeepSpeed to run inference. There is [this PR ](https://github.com/microsoft/DeepSpeed/pull/2217)on the DeepSpeed side that will add `ds_inference` attribute to the transformer network, and the mask remains intact in that case. Note that this PR will not change the flow on the modeling side and will only use a different mask when one calls `deepspeed.init_inference` on the created model.
cc: @stas00 


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Comments:
I confirm that this solves the problem of DS-Inference, which broke after this commit: https://github.com/huggingface/transformers/commit/b69a62d579ded31d490e0c9a01bf9ecb81cb9b65

cc: @thomasw21, @younesbelkada 

and also @LysandreJik - I hope it's OK if we sneak in a bit of `ds-inference` code into the BLOOM modeling code.

Unless of course you can think of how to make this configurable. perhaps a flag in the config file? that way other frameworks could choose that as well.

Thanks.

_The documentation is not available anymore as the PR was closed or merged._

Hum I'm not too familiar with how DS works in this case, but would something like `self._prepare_attn_mask = lambda attention_mask, *args, **kwargs: attention_mask` work? This would live inside DS instead of the modeling?

That's probably a sufficient hack. 

Reza, will this work for your needs?

@stas00 Will try, if it works, I am happy to use this instead. 
Thanks @thomasw21 

Okay, I have made this change on the DeepSpeed side [(here)](https://github.com/microsoft/DeepSpeed/pull/2217/commits/82a37d6d4393d9ed76a80dcb392c51e48188fd14#diff-fdbdbba9c01d8349399cfadeba4cce1c5a34fc15c38ec44a335e1340c11b13a4R177) as suggested. So, I am gonna close this PR as it not needed anymore.
Thanks,
Reza