I work on xFormers and we definitely appreciate the candid feedback:
- We partnered with our PyTorch colleagues and some of the PyTorch 2.0 kernels for efficient attention actually originated from xFormers, so glad to read that having this now built-in into PyTorch is something users are really eager to use.
- While xFormers was originally targeting a pure researcher audience, we were aware of the installation problems: we started end of last year gradually making it easier to setup and use the library (both internally and externally). We have recently introduced non-dev conda packages, pip wheels and are also trying to release more often,
- We very much welcome hearing about any issue with the library and would certainly love discussing more the specifics of your experience (or others' who read this) if you have time (maybe via our GitHub to start with). Thanks again for the feedback here!
- We partnered with our PyTorch colleagues and some of the PyTorch 2.0 kernels for efficient attention actually originated from xFormers, so glad to read that having this now built-in into PyTorch is something users are really eager to use.
- While xFormers was originally targeting a pure researcher audience, we were aware of the installation problems: we started end of last year gradually making it easier to setup and use the library (both internally and externally). We have recently introduced non-dev conda packages, pip wheels and are also trying to release more often,
- We very much welcome hearing about any issue with the library and would certainly love discussing more the specifics of your experience (or others' who read this) if you have time (maybe via our GitHub to start with). Thanks again for the feedback here!