Fix invalid parameter default

[kadubhumika]

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Summary

Fixed the invalid-parameter-default type-checking errors.

• Updated data_type to use npt.DTypeLike in computer_vision/haralick_descriptors.py.
• Updated alpha to allow None in machine_learning/loss_functions.py.
• Removed the invalid-parameter-default ignore rule from pyproject.toml.

The invalid-parameter-default diagnostics are now clean.

[kadubhumika]

@cclauss @priya-sundaram-dev I’ve fixed the invalid-parameter-default issues and removed the rule from the ignore list. All checks are passing. Could you please review when you get a chance? Thank you!

[priya-sundaram-dev]

Thanks @kadubhumika — nice work, and the code fixes look correct to me:

• computer_vision/haralick_descriptors.py: data_type: npt.DTypeLike = np.uint8 is the right annotation (np.uint8 is a dtype-like class, not a np.dtype instance), so the default no longer violates the rule. 👍
• machine_learning/loss_functions.py: alpha: np.ndarray | None = None is exactly the intended fix. 👍

One thing to fix in pyproject.toml before this merges. The diff there is:

-rules.invalid-parameter-default = "ignore"
+rules.invalid-assignment = "ignore"

Removing invalid-parameter-default is correct — that's the rule you cleared. But this also re-adds invalid-assignment = "ignore", which isn't on master anymore (it was already cleaned up and removed in an earlier PR). Re-suppressing it silently disables a rule that's currently green.

Could you just delete the invalid-parameter-default line rather than renaming it, so invalid-assignment stays enabled? i.e. the block should read:

rules.invalid-argument-type = "ignore"
rules.invalid-return-type = "ignore"

with no invalid-assignment line between them. Checks stay green either way (an added ignore won't fail CI), which is exactly why it's worth catching by eye. Everything else is good to go once that's tidied. 🙌

[cclauss]

This line needs to be removed.

• Fix ty invalid assignment #15221
• Fix ty invalid assignment #15222

Always start new pull requests from an up-to-date master branch.

[priya-sundaram-dev]

Thanks @kadubhumika — this is exactly right now. The invalid-parameter-default line is cleanly removed from the ignore list (no other rule silently re-suppressed), and the two fixes are correct:

• haralick_descriptors.py: data_type: npt.DTypeLike = np.uint8 — np.uint8 is a dtype-like class rather than a np.dtype instance, so npt.DTypeLike is the accurate annotation. 👍
• loss_functions.py: alpha: np.ndarray | None = None — None default now matches the type.

ty passes with the rule fully enforced, and ruff/pre-commit are green. Nicely done. LGTM 🎉

[cclauss]

Sweet!!