This release adds support for Python 3.13. In order to do this we're requiring Pydantic >= 2.0 and updated compilation to use Cython 3.0. This required an updated to the blis packaged that's not binary compatible, but thinc itself should not have any binary backwards compatibility issues.

Previous releases have used releases of our blis package that vendor newer releases of the upstream blis library. Unfortunately these newer releases have had intermittent crashes on Windows that we haven't been able to track down.

I've therefore released a v1.2 of the blis package that goes back to the known-good v0.7 release of the vendored blis code, which we were using before. This release updates the verison-pin to use it.

It took a surprisingly long time to get v0.7 of blis to compile, due to conflicts on Windows. I regret the delay.

• Update blis pin to v1.1. This updates the vendored blis code to 1.1, which should fix crashes from the previously vendored v0.9 code on Windows.
• Widen numpy pin, allowing versions across v1 and v2. Previously I had thought that if I build against numpy v2, I couldn't also have v1 as a runtime dependency. This is actually incorrect, so we can widen the numpy pin
• Set flag on loading PyTorch models to improve safety of loading PyTorch models.

• Fix regression to torch training introduced in v8.3.1
• Restore MacOS ARM wheels, which were missing from previous builds
• Fix compatibility with thinc-apple-ops

torch.cuda.amp is deprecated (Pytorch 2.4). This PR updates shims pytorch.py to use torch.amp.autocast instead of torch.cuda.amp.autocast.

Thanks to @Atlogit for the patch.

Previously we used a complicated build process that used self-hosted runners to build wheels for platforms Github Actions did not support. Github Actions has been adding support for ARM recently, so we've simplified the CI process to rely only on it exclusively.

This release adds back support for MacOS ARM64 wheels that were missing from the previous release. Linux ARM wheels are still pending, as Linux ARM architectures are currently only supported for private repos. Cross-compilation with QEMU is possible in theory, but in practice the build timed out after several hours.

Numpy is a build dependency of Thinc, and numpy 2.0 is not binary compatible with numpy 1.0 (fair enough). This means we can't have a version that's compatible across numpy v1 and numpy v2.

This release updates v9 by pinning to numpy 2.0, and builds against it. No other changes are made, so that we have paired versions that only differ in their dependencies.

Numpy is a build dependency of Thinc, and numpy 2.0 is not binary compatible with numpy 1.0 (fair enough). This means we can't have a version that's compatible across numpy v1 and numpy v2.

This release updates the pins to numpy 2.0 and builds against it. No other changes are made, so that we have paired versions that only differ in their dependencies.

Numpy v2.0 isn't binary compatible with v1 (understandably). We build against numpy so we need to restrict the pin.

✨ New features and improvements

• Bump nbconvert pin
• Bump typing_extensions pin for Python 3.7
• Updates to the test suite

👥 Contributors

@honnibal, @ines, @svlandeg