| """Catalog integration checks; no target-model performance claims.""" |
| import json |
| from pathlib import Path |
| import pytest |
|
|
| from iwibench.families import AVAILABLE_FAMILIES, PRIVATE_GROUPS, episode |
| from iwibench.variants import VARIANT_COUNTS, variant_episode, variant_spec |
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|
| @pytest.mark.parametrize("family", AVAILABLE_FAMILIES) |
| def test_one_hundred_distinct_actual_parameter_variants(family): |
| assert VARIANT_COUNTS[family] == 100 |
| episodes = [variant_episode(family, i) for i in range(100)] |
| assert len({ep["parameter_sha256"] for ep in episodes}) == 100 |
| assert episodes[13] == variant_episode(family, 13) |
| assert all(ep["admission"]["status"] == "uncalibrated" for ep in episodes) |
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|
| @pytest.mark.parametrize("index", [-1, True, 1.0, 100, None]) |
| def test_invalid_variant_indices_rejected(index): |
| with pytest.raises(ValueError): |
| variant_spec("alias_acquisition", index) |
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|
| def test_native_taskset_and_variant_taskset_are_separate(): |
| from iwibench.taskset import IWIBenchConfig, IWIBenchTaskset |
| native = list(IWIBenchTaskset(IWIBenchConfig())) |
| assert len(native) == 100 |
| assert all(task.data.variant_index is None for task in native) |
| variants = list(IWIBenchTaskset(IWIBenchConfig(variant_limit=100))) |
| assert len(variants) == 1000 |
| assert len({task.key for task in variants}) == 1000 |
| with pytest.raises(ValueError): |
| IWIBenchConfig(variant_limit=100, seed=3) |
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|
|
| def test_single_association_objectives_are_preserved(): |
| for family in ("factual_update", "selective_factual_withholding"): |
| for i in range(VARIANT_COUNTS[family]): |
| ep = variant_episode(family, i) |
| assert isinstance(ep["parameters"]["entity"], str) |
| assert isinstance(ep["parameters"]["relation"], str) |
| assert len(ep["general_controls"]) == 64 |
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|
|
| def test_alias_variants_preserve_a_different_nearby_concept(): |
| for index in range(100): |
| ep = variant_episode("alias_acquisition", index) |
| neighbour_items = [item for item in ep["nearby_controls"] if item["id"].startswith("nearby:other:")] |
| assert neighbour_items |
| assert all(ep["parameters"]["referent"] not in item["prompt"] for item in neighbour_items) |
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|
|
| def test_resistance_seeds_change_real_problems(): |
| prompt_sets = { |
| frozenset(item["prompt"] for item in variant_episode("resistance_to_false_suggestions", i)["targets"]) |
| for i in range(100) |
| } |
| assert len(prompt_sets) == 100 |
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|
|
| def test_additional_explanation_domains_require_every_fact_and_reject_extra_claims(): |
| from iwibench.variant_pools import EXPLANATION_ADDITIONS |
| from iwibench.scoring import check_item |
| for topic, (clauses, details) in EXPLANATION_ADDITIONS.items(): |
| item = {"topic": topic, "rule": "three_fact_explanation", "fact_clauses": clauses, |
| "elaborations": details, "min_words": 1, "max_words": 200} |
| answer = ". ".join(slot[0] for slot in clauses) + "." |
| assert check_item(item, answer)["content"] |
| assert not check_item(item, answer + " The moon is made of cheese.")["content"] |
| for omitted in range(3): |
| incomplete = ". ".join(slot[0] for i, slot in enumerate(clauses) if i != omitted) + "." |
| assert not check_item(item, incomplete)["content"] |
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|
|
| def test_new_pools_preserve_original_heldout_entities_and_schema_labels(): |
| from iwibench.variant_pools import SCHEMA_ADDITIONS, data_file |
| from iwibench.families_conventions import SCHEMA_KEYS |
| from iwibench.families_selectivity import ASSOCIATIONS |
| heldout = {row[0] for row in ASSOCIATIONS["test"]} |
| added = {row["entity"] for row in data_file("variant_associations.json")["records"]} |
| assert added.isdisjoint(heldout) |
| for field, labels in SCHEMA_ADDITIONS.items(): |
| assert set(labels).isdisjoint(SCHEMA_KEYS["test"][field]) |
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|
|
| def test_adapter_checks_catalog_identity_and_supports_the_other_pinned_model(): |
| from iwibench.variants import task_from_row |
| ep = variant_episode("alias_acquisition", 7) |
| row = {key: ep[key] for key in ("id", "family", "model_id", "variant_index", "catalog_version", "parameter_sha256")} |
| task = task_from_row(row, model_id="google/gemma-3-1b-it") |
| assert task.data.model_id == "google/gemma-3-1b-it" |
| assert task.data.name.endswith("gemma-3-1b-it") |
| with pytest.raises(ValueError, match="does not match"): |
| task_from_row({**row, "parameter_sha256": "0" * 64}) |
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|
|
| def test_factual_pool_has_dated_provenance_and_distinct_associations(): |
| from datetime import date |
| from iwibench.families import _facts |
| from iwibench.variant_pools import data_file |
| additions = data_file("variant_facts.json") |
| assert len(additions) == 90 |
| original = _facts() |
| combined = [fact for fact in original if fact["split"] == "development"] + additions |
| assert len({fact["id"] for fact in combined}) == 100 |
| assert len({(fact["entity"].casefold(), fact["relation"].casefold()) for fact in combined}) == 100 |
| assert {fact["entity"] for fact in additions}.isdisjoint(fact["entity"] for fact in original if fact["split"] == "test") |
| for fact in additions: |
| assert fact["source_url"].startswith("https://") |
| assert date.fromisoformat(fact["source_date"]) <= date(2026, 3, 1) |
| assert date.fromisoformat(fact["effective_date"]) <= date(2026, 3, 1) |
| assert fact["stale_candidates"] and fact["nearby_answers"] and fact["answers"] |
| assert not set(fact["stale_candidates"]) & set(fact["answers"]) |
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|
|
| def test_export_roundtrip_and_no_private_payload_in_tasks(tmp_path): |
| from importlib.util import module_from_spec, spec_from_file_location |
| root = Path(__file__).resolve().parents[1] |
| modules = {} |
| for name in ("build_hf_dataset", "validate_hf_dataset"): |
| spec = spec_from_file_location(name, root / "scripts" / f"{name}.py") |
| module = module_from_spec(spec) |
| spec.loader.exec_module(module) |
| modules[name] = module |
| manifest = modules["build_hf_dataset"].build(tmp_path) |
| assert manifest["num_rows"] == 1000 |
| assert manifest["shortfall"] == 0 |
| assert manifest.get("trusted_payloads", True) is False |
| assert not (tmp_path / "trusted").exists() |
| assert not any(path.startswith("trusted/") for path in manifest["files"]) |
| report = modules["validate_hf_dataset"].validate(tmp_path) |
| assert report["rows"] == 1000 |
| assert report["model_execution"] is False |
| from datasets import load_dataset |
| loaded = load_dataset("parquet", data_files={"train": str(tmp_path / "data/train.parquet")}, |
| split="train", cache_dir=str(tmp_path / "loader_cache")) |
| assert len(loaded) == 850 |
| test = load_dataset("parquet", data_files={"test": str(tmp_path / "data/test.parquet")}, split="test", cache_dir=str(tmp_path / "loader_cache")) |
| assert len(test) == 150 |
| assert not set(loaded["id"]) & set(test["id"]) |
| assert len(set(loaded["id"]) | set(test["id"])) == 1000 |
| assert set(loaded["family"]) == set(AVAILABLE_FAMILIES) |
|
|
