Enable type annotation rules in the Ruff linter.

[oscarkey]

Enable the ANN rules, but exclude some overly strict ones, in line with our other repositories.

I added type annotations where they were missing. I also:

• ignore ANN for src/tabpfn/architectures/base/preprocessing.py, due to a lot of errors
• delete a class and a method that were not used in any PriorLabs repository
• add noqa in some cases where the type was not obvious, to avoid getting it wrong

[gemini-code-assist]

Summary of Changes

Hello @oscarkey, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request aims to enhance code quality and maintainability by enabling and enforcing type annotation rules (ANN) within the Ruff linter configuration. It systematically adds missing type annotations across the codebase, while also making pragmatic exceptions for overly strict rules and specific files to balance strictness with development efficiency. Additionally, it cleans up unused code.

Highlights

• Linter Configuration Update: Activated Ruff's "ANN" rules for type annotation enforcement in "pyproject.toml".
• Targeted Rule Exemptions: Configured Ruff to ignore specific "ANN" rules (e.g., "ANN002" for "*args", "ANN003" for "**kwargs", "ANN204" for "init", "ANN401" for "Any") to avoid overly strict checks.
• File-Specific Exclusions: Excluded "src/tabpfn/architectures/base/preprocessing.py" from all "ANN" checks due to a high volume of existing errors.
• Extensive Type Annotation Additions: Applied numerous type annotations to function parameters and return types across various Python files (e.g., examples, src/tabpfn/architectures, src/tabpfn/classifier.py, src/tabpfn/inference.py, src/tabpfn/preprocessing.py, src/tabpfn/utils.py, tests/).
• Code Cleanup: Removed the "StyleEncoder" class and "get_linear_encoder_generator" function from "src/tabpfn/architectures/base/encoders.py" as they were identified as unused.
• "noqa" Annotations: Added "noqa" comments in cases where type inference was not straightforward, ensuring linter compliance without sacrificing clarity.

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[gemini-code-assist]

Code Review

This pull request enables Ruff's ANN rules to enforce type annotations, a great step towards improving code quality and maintainability. The changes primarily involve adding missing type hints across various files, along with necessary configuration adjustments in pyproject.toml to manage the new rules. The removal of unused code is also a welcome cleanup.

I've found one issue regarding an incorrect return type hint (NoReturn instead of None) in a base class method in src/tabpfn/inference.py. This violates type compatibility with subclass implementations and should be corrected. My detailed feedback is in the comment below.

[priorphil]

Thanks for adding these!