Numba doesn't support dot with non-floating point arguments.

* Add pytensor function corresponding to

* Add pytensor function corresponding to

* Cast numpy to node output dtype, rather than depending on config.floatX

Change output type hint back to

* Cast numpy to node output dtype, rather than depending on config.floatX  Change output type hint back to

* Use  rather than  for output equality tests

Also fixes wrong gradient for negative offsets

This would trigger it for every Composite/ScalarLoop present in the C-cache

Bumps [pypa/gh-action-pypi-publish](https://github.com/pypa/gh-action-pypi-publish) from 1.8.8 to 1.8.10.
- [Release notes](https://github.com/pypa/gh-action-pypi-publish/releases)
- [Commits](https://github.com/pypa/gh-action-pypi-publish/compare/v1.8.8...v1.8.10)

---
updated-dependencies:
- dependency-name: pypa/gh-action-pypi-publish
  dependency-type: direct:production
  update-type: version-update:semver-patch
...
Signed-off-by: dependabot[bot] <support@github.com>

This can avoid some infinite rewrite loops where a SpecifyShape is lifted, removed and then reintroduced at the bottom by the MergeOptimizer