Add Torch grid interpolation using grid_sample with autograd support

[gustavu92]

Add Torch support for grid-based phase interpolation

This PR adds full Torch backend support for grid-based phase profiles using torch.nn.functional.grid_sample.

Key updates:

• Implement backend-agnostic GridInterpolator
• Add Torch support with autograd for accurate gradients
• Ensure gradients are computed in physical coordinates
• Keep NumPy backend using RectBivariateSpline
• Unify tests for NumPy and Torch backends
• Restore consistent serialization for grid and height profiles

Closes #492.

[codecov]

Codecov Report

❌ Patch coverage is 65.00000% with 35 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
optiland/phase/interpolators.py	50.70%	35 Missing ⚠️

❌ Your patch status has failed because the patch coverage (65.00%) is below the target coverage (75.00%). You can increase the patch coverage or adjust the target coverage.

@@            Coverage Diff             @@
##           master     #493      +/-   ##
==========================================
- Coverage   93.19%   93.05%   -0.15%     
==========================================
  Files         310      311       +1     
  Lines       18381    18437      +56     
==========================================
+ Hits        17130    17156      +26     
- Misses       1251     1281      +30     

Files with missing lines	Coverage Δ
optiland/phase/grid.py	100.00% <100.00%> (+7.89%)	⬆️
optiland/phase/height_profile.py	97.61% <100.00%> (+3.74%)	⬆️
optiland/phase/interpolators.py	50.70% <50.70%> (ø)

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[HarrisonKramer]

Hi @gustavu92,

Thanks for adding this! It was on the todo list for a long time and I am very glad it's now implemented. Merging now!

Regards,
Kramer