shapiq Benchmark

[IsaH57]

Motivation and Context

This PR consolidates and validates a full shapiq_benchmark layer, ensuring all benchmark types (Interventional, Pathdependent, Local XAI, Image, and TabPFN) share a consistent interface for exact value computation and game access. It also strengthens the string-based dataset/model loading flow and the known-parameter lookup path, so benchmarks can be reproduced reliably across datasets and model families while still supporting custom inputs.

What’s included

• Benchmark protocol and ground-truth computer abstractions
• Dataset/model loading and validation, including string-based loaders and known-parameter lookups
• Benchmark implementations:
  -- Interventional tree explanations in InterventionalBench()
  -- Pathdependent tree explanations in PathdependentBench()
  -- Local XAI explanations in LocalXAIBench()
  -- Image explanations in ImageBench()
  -- TabPFN explanations in TabPFNBench()
• Metrics for approximation quality and ranking comparison
• Configs holding optimized parameters for 6 model - dataset combinations

Public API Changes

• No Public API changes
• Yes, Public API changes (Details below)

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How Has This Been Tested?

• Manual test runs for all benchmarks
• Each test covers both string-based loading and custom model/data paths where applicable

Checklist

• The changes have been tested locally.
• Documentation has been updated (if the public API or usage changes).
• An entry has been added to CHANGELOG.md (if relevant for users).
• The code follows the project's style guidelines.
• I have considered the impact of these changes on the public API.

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.

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