Fix failure with narrowing of ssize_t to int in macos

[ricardoV94]

Everything is npy_intp now which is the type of numpy array shape and strides anyway.

CI started failing recently in the macos test, because there the old ssize_t was a long, and we were trying to initialize an int array out of it.

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📚 Documentation preview 📚: https://pytensor--1602.org.readthedocs.build/en/1602/

[Copilot]

Pull Request Overview

This PR fixes a compilation failure on macOS by standardizing variable types from platform-specific types to npy_intp. The issue occurred because ssize_t is a long on macOS, which couldn't be safely narrowed to int array initializers.

• Replaces all ssize_t and int declarations with npy_intp for consistency with NumPy array shape/stride types
• Updates loop iterator variables to use npy_intp instead of int
• Increments C code cache version numbers to reflect the type changes

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.

File	Description
pytensor/tensor/elemwise_cgen.py	Changes stride, jump, and iterator variable declarations from ssize_t/int to npy_intp
pytensor/tensor/elemwise.py	Updates C code cache version numbers to reflect the type changes

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 81.71%. Comparing base (7092f55) to head (87cb6d4).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1602   +/-   ##
=======================================
  Coverage   81.71%   81.71%           
=======================================
  Files         230      230           
  Lines       52924    52925    +1     
  Branches     9402     9402           
=======================================
+ Hits        43248    43249    +1     
  Misses       7244     7244           
  Partials     2432     2432           

Files with missing lines	Coverage Δ
pytensor/tensor/elemwise.py	90.01% <100.00%> (ø)
pytensor/tensor/elemwise_cgen.py	96.82% <100.00%> (ø)

... and 2 files with indirect coverage changes

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[jessegrabowski]

lgtm