| """End-to-end integration tests for PPO training and MinimaxLoop.""" | |
| from aegis.configs.dataclasses import AEGISConfig, ModelConfig, EvidenceConfig, TrainingConfig | |
| from aegis.data.loaders import GSM8KLoader | |
| from aegis.models.adversary import Adversary | |
| from aegis.models.judge import Judge | |
| from aegis.training.minimax_loop import MinimaxLoop | |
| def test_minimax_loop_mock(): | |
| cfg = AEGISConfig() | |
| cfg.judge = ModelConfig(is_mock=True) | |
| cfg.adversary = ModelConfig(is_mock=True) | |
| cfg.evidence = EvidenceConfig(is_mock=True) | |
| cfg.training = TrainingConfig( | |
| total_iterations=2, | |
| judge_update_steps=1, | |
| adversary_update_steps=1, | |
| batch_size=2, | |
| horizon=2, | |
| log_interval=1, | |
| eval_interval=2, | |
| save_interval=2, | |
| ) | |
| cfg.experiment.output_dir = "outputs/test_run" | |
| loader = GSM8KLoader(split="train", max_samples=4) | |
| loop = MinimaxLoop( | |
| config=cfg, | |
| train_loader=loader, | |
| eval_loader=loader, | |
| ) | |
| metrics = loop.run() | |
| assert isinstance(metrics, dict) | |
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