#!/usr/bin/env python3
"""
Evolutionary JEPA Masking Search (Evo-JEPA)
============================================
Uses CMA-ES to evolve optimal masking parameters for I-JEPA self-supervised pretraining.
Fitness is evaluated via kNN accuracy on CIFAR-100 after short pretraining runs.

Paper motivation:
- I-JEPA (arxiv:2301.08243) showed masking params swing accuracy by 45+ points
- FER paper (arxiv:2505.11581) showed evolution produces better representations than SGD
- This combines both: evolving the masking strategy that guides SGD-based JEPA training
"""