avoiding conditional indexing in positionalencoding to avoid possibil…
Author: ppadjinTT
Pull request: yes
Labels: name: Audio


# What does this PR do?

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This PR avoids the use of conditional indexing in the SpeechT5 RelativePositionalEncoding forward pass. As explained in 
 https://github.com/huggingface/transformers/issues/42087 this type of advanced indexing can result in zero-shaped tensors which can be problematic for custom AI accelerators / torch backends.

This PR provides a simple and equivalent alternative. Instead of using:

```
        pos_seq[pos_seq < -self.max_length] = -self.max_length
        pos_seq[pos_seq >= self.max_length] = self.max_length - 1
```

These torch operations can be used:

```
        pos_seq = torch.where(pos_seq < -self.max_length, -self.max_length, pos_seq)
        pos_seq = torch.where(pos_seq >= self.max_length, self.max_length - 1, pos_seq)
```


Fixes https://github.com/huggingface/transformers/issues/42087


### Quick test of equivalence

This simple script can be used to verify that indeed these two expressions are same:

```
import torch

def method1(pos_seq, max_length):
    pos_seq = torch.where(pos_seq < -max_length, -max_length, pos_seq)
    pos_seq = torch.where(pos_seq >= max_length, max_length - 1, pos_seq)
    return pos_seq

def method2(pos_seq, max_length):
    pos_seq[pos_seq < -max_length] = -max_length
    pos_seq[pos_seq >= max_length] = max_length - 1
    return pos_seq

seq_len = 512
max_length = 160
device = 'cpu'
pos_seq = torch.arange(0, seq_len).to(device=device, dtype=torch.long)
pos_seq = pos_seq[:, None] - pos_seq[None, :]

print(torch.allclose(method1(pos_seq, max_length), method2(pos_seq, max_length)))
print(torch.max(torch.abs(method1(pos_seq, max_length) - method2(pos_seq, max_length))))
```
Output of the script above:
```
True
tensor(0)
```


## Who can review?
@eustlb @ebezzam 


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Comments:
@eustlb, can we get approval for other workflows as well? :)) 

Thanks @eustlb! Could you run the remaining tests? 

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: speecht5

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_42090). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.