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| """Smoke tests verifying all new modules are importable from package level.""" | |
| from __future__ import annotations | |
| class TestTopLevelImports: | |
| """Verify obliteratus top-level exports.""" | |
| def test_set_seed(self): | |
| from obliteratus import set_seed | |
| assert callable(set_seed) | |
| def test_run_sweep(self): | |
| from obliteratus import run_sweep | |
| assert callable(run_sweep) | |
| def test_sweep_config(self): | |
| from obliteratus import SweepConfig | |
| cfg = SweepConfig( | |
| model_name="test", | |
| sweep_params={"n_directions": [1, 2]}, | |
| ) | |
| assert cfg.model_name == "test" | |
| def test_sweep_result(self): | |
| from obliteratus import SweepResult | |
| r = SweepResult( | |
| params={"n_directions": 1}, | |
| seed=42, | |
| quality_metrics={}, | |
| stage_durations={}, | |
| strong_layers=[], | |
| ) | |
| assert r.seed == 42 | |
| class TestEvaluationImports: | |
| """Verify evaluation subpackage exports.""" | |
| def test_refusal_rate_with_ci(self): | |
| from obliteratus.evaluation import refusal_rate_with_ci | |
| result = refusal_rate_with_ci(["Sure, here you go."], mode="combined") | |
| assert result["rate"] == 0.0 | |
| assert result["n_samples"] == 1 | |
| def test_random_direction_ablation(self): | |
| from obliteratus.evaluation import random_direction_ablation | |
| assert callable(random_direction_ablation) | |
| def test_direction_specificity_test(self): | |
| from obliteratus.evaluation import direction_specificity_test | |
| assert callable(direction_specificity_test) | |
| def test_run_benchmarks(self): | |
| from obliteratus.evaluation import run_benchmarks | |
| assert callable(run_benchmarks) | |
| def test_compare_models(self): | |
| from obliteratus.evaluation import compare_models | |
| assert callable(compare_models) | |
| class TestDirectImports: | |
| """Verify direct module imports still work.""" | |
| def test_reproducibility(self): | |
| from obliteratus.reproducibility import set_seed | |
| import torch | |
| set_seed(999, deterministic=False) | |
| a = torch.randn(10) | |
| set_seed(999, deterministic=False) | |
| b = torch.randn(10) | |
| assert torch.equal(a, b) | |
| def test_baselines(self): | |
| from obliteratus.evaluation.baselines import ( | |
| BaselineResult, | |
| ) | |
| assert BaselineResult is not None | |
| def test_lm_eval_integration(self): | |
| from obliteratus.evaluation.lm_eval_integration import ( | |
| run_benchmarks, | |
| ) | |
| assert callable(run_benchmarks) | |