The check was failing incorrectly for cases that are supported such as constant Boolean arrays.
Besides that, user may dispatch without necessarily jitting the graph. There is no reason to fail eagerly.

Co-authored-by: HarshvirSandhu <harshvir2173@gmail.com>

Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

Co-authored-by: Ricardo Vieira <28983449+ricardoV94@users.noreply.github.com>

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.9 → v0.4.10](https://github.com/astral-sh/ruff-pre-commit/compare/v0.4.9...v0.4.10)

Importantly, it now provides broadcastability information which is needed elsewhere

This prevents undoing the rewrite that introduces AdvancedSubtensor1

Use ScalarTypes in MakeSlice for compatibility with Numba

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.18.1 to 2.19.1.
- [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/v2.18.1...v2.19.1)

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

Bumps [pypa/gh-action-pypi-publish](https://github.com/pypa/gh-action-pypi-publish) from 1.8.14 to 1.9.0.
- [Release notes](https://github.com/pypa/gh-action-pypi-publish/releases)
- [Commits](https://github.com/pypa/gh-action-pypi-publish/compare/v1.8.14...v1.9.0)

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

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.8 → v0.4.9](https://github.com/astral-sh/ruff-pre-commit/compare/v0.4.8...v0.4.9)

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.7 → v0.4.8](https://github.com/astral-sh/ruff-pre-commit/compare/v0.4.7...v0.4.8)

* Break MaxandArgmax to TensorMax and Argmax seperately
* XFAIL pytensor tests for uint64 data type
* Deprecate and raise AttributeError for MaxAndArgmax

* Switched from miniconda to micromamba for mypy workflow

* setup-micromamba for test.yml

* Specified environment-name for test.yml

* Changed mamba to micromamba for test.yml

Even though llvmlite is a dependency of numba, we explicitly import it,
so for us it should count as a direct dependency.