Coerce dtype __props__ to string due to invalid hash of np.dtype() objects

[ricardoV94]

There were some odd errors cropping up in pymc-marketing and a private project.

The issue happened when you created an Arange with float64 and another with np.dtype("float64") (or any combo of dtype and string), which evaluate to the same thing, but hash differently (see below why). The PyTensor C-cache has a sanity-check mechanism to make sure the eq and hash of our Ops is correctly implemented, as the validity of the cache depends on this.

PyTensor uses the properties of Op to define equality and hash automatically, and for Arange that is it's dtype argument. Surprisingly though, np.dtype("float64") == "float64" and hash(np.dtype("float64")) != hash("float64"), which seems to be a fundamental bug in Numpy: numpy/numpy#17864

This only became a problem once we added a C-implementation to Arange in #1392 as this is where the automatic checks for hash/eq are performed.

I tried to look for other Ops parametrized by dtype of some form or another, and make sure those are always converted to the equivalent strings.

CC @lucianopaz and @juanitorduz

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📚 Documentation preview 📚: https://pytensor--1436.org.readthedocs.build/en/1436/

[codecov]

Codecov Report

❌ Patch coverage is 80.00000% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.12%. Comparing base (92eef5e) to head (fd371c3).
⚠️ Report is 131 commits behind head on main.

Files with missing lines	Patch %	Lines
pytensor/tensor/random/op.py	0.00%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1436   +/-   ##
=======================================
  Coverage   82.12%   82.12%           
=======================================
  Files         211      211           
  Lines       49751    49757    +6     
  Branches     8817     8819    +2     
=======================================
+ Hits        40857    40862    +5     
- Misses       6714     6715    +1     
  Partials     2180     2180           

Files with missing lines	Coverage Δ
pytensor/sparse/sandbox/sp2.py	82.79% <100.00%> (ø)
pytensor/tensor/basic.py	91.69% <100.00%> (+0.01%)	⬆️
pytensor/tensor/elemwise.py	90.01% <100.00%> (ø)
pytensor/tensor/io.py	77.41% <100.00%> (ø)
pytensor/tensor/random/op.py	92.51% <0.00%> (-1.01%)	⬇️

... and 2 files with indirect coverage changes

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