feat: add MMBench static evaluation mode (no OpenAI API needed)

[Luodian]

Summary

Add a static evaluation variant for MMBench EN Dev that uses regex-based MCQ answer extraction instead of GPT API calls, enabling fully offline evaluation without API costs.

Changes

• New mmbench_en_dev_static task config
• New mmbench_aggregate_dev_results_static function in en_utils.py
• Extended eval_sub_data and eval_result in mmbench_evals.py to support static eval method
• New shared _task_utils/mcq_extract.py utility for robust answer extraction across 10+ answer formats

Usage

# Static eval (no API key needed)
lmms-eval --tasks mmbench_en_dev_static --model <model> ...

# Original GPT-based eval still works
lmms-eval --tasks mmbench_en_dev --model <model> ...

Note

mcq_extract.py is also included in #1272 (physics benchmarks PR). Both PRs can merge independently — the file is identical.

Test plan

• Run mmbench_en_dev_static and compare accuracy with GPT-based eval
• Verify original mmbench_en_dev task still works unchanged
• Test MCQ extraction with various answer formats (A, (B), C., "the answer is D")