This prevents surprises when passing two scalars, which are interpreted differently in the numpy API

These nodes must always be rebuilt in non-strict mode

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.12.3 to 2.13.1.
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.12.3...v2.13.1)

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

Otherwise, it will show up everytime a Composite has been cached by th C backend

This allows the outputs to be views of the inputs. The Python and Numba implementation do that, but the C still performs a copy

Following the update of index.rst, a corresponding update of index.ipynb is necessary.

The `pydot_ng` recommendation should definitely be dropped since that project is officially archived in favor of pydot: https://github.com/pydot/pydot-ng

* Use better ASCII symbols
* Show continuation hint for already seen nodes
* Don't repeat entries for multiple output inner graphs

* Add failed assertion message in CI

* Pin numpy upper bound in numba install

numba-scipy downgrades the installed scipy to 1.7.3 in Python 3.8, but not numpy, even though scipy 1.7 requires numpy<1.23. When installing PyTensor next, pip installs a lower version of numpy via the PyPI.

* Run numba and jax tests in separate jobs

---------
Co-authored-by: Ben Mares <services-git-throwaway1@tensorial.com>

Supposed to be removed in 6d431aa6

Moving caused a circular dependency with tensor.blas. It seems most
linalg rewrites are in the stablize set, so should run before the blas
specializers anyway, so these checks were removed.

This also deleted the unused `spectral_radius_bound` and dummy
`Minimal(Op)`.

Having Ops and rewrites in the same files was causing circular imports.