Harden CRUXEval output comparison

[Danielxu0208]

Summary

• build the CRUXEval output assertion from parsed expressions instead of interpolated source
• reuse OpenCompass's type-aware equality helper to reject forged __eq__ results
• execute dataset code before injecting the protected comparison helper
• add adversarial and compatibility regression coverage

Why

CRUXEval previously evaluated assert {expected} == {prediction}. A generated object with an always-true __eq__, or an expression that changed the outer boolean assertion, could be scored as correct without matching the expected output. This bypasses benchmark correctness rather than solving the task.

Validation

• rejected top-level and nested forged-equality objects
• rejected outer-assertion injection payloads
• retained valid nested builtin values, multiple predictions, and echo anti-cheat behavior
• python -m py_compile opencompass/datasets/cruxeval.py tests/datasets/test_cruxeval.py
• git diff --check