Fix C-cache bug related to input order of nominal variables

[ricardoV94]

Closes #1670

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📚 Documentation preview 📚: https://pytensor--1673.org.readthedocs.build/en/1673/

[ricardoV94]

PS I don't love the shared baseclass of Constant and NominalVariables as "atomics". They are more like root variables (always required) than constants. The only difference between nominal and generic root variables is that they evaluate equal based on the "position / type" instead of id.

from pytensor.graph.basic import NominalVariable
from pytensor.tensor.type import TensorType

ScalarType = TensorType(dtype="float64", shape=())

n1 = NominalVariable(0, ScalarType)
n2 = NominalVariable(0, ScalarType)
n3 = NominalVariable(1, ScalarType)

t1 = ScalarType()
t2 = ScalarType()

assert n1 == n2 != n3 and t1 != t2

That's however tangential to the bug here. It could be emulated just with regular variables and constants, as in the first test

[codecov]

Codecov Report

❌ Patch coverage is 75.00000% with 1 line in your changes missing coverage. Please review.
✅ Project coverage is 81.63%. Comparing base (27c21cd) to head (3b3c110).

Files with missing lines	Patch %	Lines
pytensor/link/c/basic.py	75.00%	0 Missing and 1 partial ⚠️

❌ Your patch check has failed because the patch coverage (75.00%) is below the target coverage (100.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1673   +/-   ##
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  Coverage   81.63%   81.63%           
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  Files         242      242           
  Lines       53569    53569           
  Branches     9451     9451           
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  Hits        43732    43732           
- Misses       7360     7362    +2     
+ Partials     2477     2475    -2     

Files with missing lines	Coverage Δ
pytensor/link/c/basic.py	87.44% <75.00%> (-0.31%)	⬇️

... and 1 file with indirect coverage changes

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[Copilot]

Pull Request Overview

This PR fixes a C-cache bug related to the input order of nominal variables in PyTensor's C linker. The issue occurred when compiling variants of the same graph with different orders of atomic inputs, which led to incorrect cache key generation and potential runtime errors.

Key changes:

• Modified the in_sig function in CLinker.cmodule_key_ to properly handle nominal variables that appear in the inputs list
• Added comprehensive test cases covering both constant and nominal variable scenarios with different input orderings

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
pytensor/link/c/basic.py	Fixed cache key generation logic to correctly identify and handle nominal/constant variables in input lists
tests/link/c/test_basic.py	Added regression tests for input order variations and C/CVM linker compatibility with nominal variables