Rework LongFormer to make it compatible with ONNX
- [x] Remove implicit `bool` -> `int` conversion while padding attention_mask with `False` value.
- [x] Remove call to `einsum` where `matmul` + `transpose` can be used (makes optimizations easier for ONNX)
- [ ] Diagonal matrix computation try to avoid ScatterND with negative steps / index
- [ ] Use `torch.div(a, b, rounding_mode='trunc')` instead of `floor_divide` 
- [ ] Check [function](https://github.com/huggingface/transformers/blob/master/src/transformers/models/longformer/modeling_longformer.py#L783) reporting `torch.Tensor` return type which doesn't return anything
I'm fine with this rework as long as all the slow tests are passing :-) <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>Hey github actions, I need to find some time to continue my work here ! :D 