Continued to test and fix issues in sdkit, after the change to support DirectML. The change is fairly intrusive, since it removes direct references to torch.cuda with a layer of abstraction.
Fixed a few regressions, and it now passes all the regression tests for CPU and CUDA support (i.e. existing users). Will test for DirectML next, although it will fail (with out-of-memory) for anything but the simplest tests (since DirectML is quirky with memory allocation).
Spent a bit of time with Freebird - added the ability to scale the radius of curve points in Freebird (in EDIT mode), thanks to a user code contribution. And did some user support.
Also experimented with libtorch and wrote a simple C++ program that uses libtorch for computation. Managed to compile it for CPU and CUDA using the instructions on their website. But it feels fairly heavyweight compared to ggml, especially if compiling staticly (would take a LONG time). The experiment was driven by a desire to reduce the installation size of Easy Diffusion (from the current 6-8 GB behemoth), without necessarily discarding torch. Might experiment with compiling libtorch staticly sometime, just to see how long it takes, and whether the final binary size is small enough for my needs.