File size: 6,896 Bytes
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import sys
from pathlib import Path
import pytest
REPO_ROOT = Path(__file__).resolve().parents[1]
if str(REPO_ROOT) not in sys.path:
sys.path.insert(0, str(REPO_ROOT))
from scripts.make_eval_split import (
build_split,
dataset_binding,
has_hallucinated,
row_split_group,
validate_split_summary,
)
def make_rows(n_pos: int, n_neg: int) -> list[dict]:
rows = [
{"id": f"positive-{index}", "prompt": f"positive {index}", "labels": [0, 1, 0]}
for index in range(n_pos)
]
rows += [
{"id": f"negative-{index}", "prompt": f"negative {index}", "labels": [0, 0]}
for index in range(n_neg)
]
return rows
def test_has_hallucinated():
assert has_hallucinated([0, 2, 1]) is True
assert has_hallucinated(["G", "H", "U"]) is True
assert has_hallucinated([0, 2, 0]) is False
assert has_hallucinated(None) is False
def test_build_split_is_deterministic_and_partitions():
rows = make_rows(40, 60)
a = build_split(rows, test_fraction=0.15, seed=42)
b = build_split(rows, test_fraction=0.15, seed=42)
assert a == b # deterministic given the seed
train = a["split"]["train_indices"]
test = a["split"]["eval_indices"]
# disjoint and covering
assert set(train).isdisjoint(test)
assert sorted(train + test) == list(range(len(rows)))
assert len(test) == round(40 * 0.15) + round(60 * 0.15) # per-stratum rounding
assert a["dataset_binding"] == dataset_binding(rows)
assert a["test_fraction"] == 0.15
assert validate_split_summary(a, rows) == a["split"]
def test_build_split_stratifies_positive_rate():
rows = make_rows(50, 50)
split = build_split(rows, test_fraction=0.2, seed=7)
test = split["split"]["eval_indices"]
positives = sum(1 for i in test if has_hallucinated(rows[i]["labels"]))
# ~half the held-out examples should carry a hallucinated token
assert positives == pytest.approx(len(test) / 2, abs=1)
def test_build_split_can_emit_train_validation_test_partitions():
rows = make_rows(50, 50)
result = build_split(
rows,
test_fraction=0.10,
validation_fraction=0.15,
train_fraction=0.75,
seed=11,
)
train = result["split"]["train_indices"]
validation = result["split"]["validation_indices"]
test = result["split"]["eval_indices"]
assert set(train).isdisjoint(validation)
assert set(train).isdisjoint(test)
assert set(validation).isdisjoint(test)
assert sorted(train + validation + test) == list(range(len(rows)))
assert len(train) == 75
assert len(validation) == 15
assert len(test) == 10
assert result["scheme"] == "grouped_stratified_train_validation_test"
for partition in (train, validation, test):
positives = sum(1 for i in partition if has_hallucinated(rows[i]["labels"]))
assert positives == pytest.approx(len(partition) / 2, abs=1)
def test_build_split_keeps_duplicate_prompts_in_one_partition():
rows = [
{
"id": f"row-{index}",
"prompt": f"question {index}",
"labels": [0, index % 2],
"metadata": {"source": "source_a" if index % 2 else "source_b"},
}
for index in range(40)
]
rows.append(
{
"id": "row-duplicate-question-3",
"prompt": " QUESTION 3 ",
"labels": [0, 1],
"metadata": {"source": "source_a"},
}
)
result = build_split(
rows,
test_fraction=0.10,
validation_fraction=0.15,
train_fraction=0.75,
seed=9,
)
partitions = {
index: name
for name, indices in (
("train", result["split"]["train_indices"]),
("validation", result["split"]["validation_indices"]),
("test", result["split"]["eval_indices"]),
)
for index in indices
}
assert partitions[3] == partitions[40]
assert result["n_groups"] == 40
assert result["grouped_by"] == "v5_1.split_group or normalized prompt"
def test_build_split_rejects_bad_fraction():
with pytest.raises(ValueError):
build_split(make_rows(5, 5), test_fraction=0.0, seed=1)
def test_duplicate_prompts_never_cross_train_test():
rows = make_rows(8, 8)
rows[0]["prompt"] = "Duplicate question?"
rows[1]["prompt"] = " DUPLICATE question? "
for index, row in enumerate(rows[2:], 2):
row["prompt"] = f"unique-{index}"
split = build_split(rows, test_fraction=0.25, seed=7)
train = set(split["split"]["train_indices"])
test = set(split["split"]["eval_indices"])
assert ({0, 1} <= train) or ({0, 1} <= test)
assert split["groups"] == 15
def test_explicit_v5_1_group_takes_precedence():
first = {
"prompt": "one",
"metadata": {"extra": {"v5_1": {"split_group": "shared"}}},
}
second = {
"prompt": "two",
"metadata": {"extra": {"v5_1": {"split_group": "shared"}}},
}
assert row_split_group(first, 0) == row_split_group(second, 1)
def test_dataset_binding_rejects_missing_and_duplicate_ids():
with pytest.raises(ValueError, match="non-empty string id"):
dataset_binding([{"prompt": "missing"}])
with pytest.raises(ValueError, match="duplicate row id"):
dataset_binding([{"id": "same"}, {"id": "same"}])
def test_dataset_binding_changes_for_edit_or_reorder():
rows = make_rows(2, 2)
original = dataset_binding(rows)
edited = [dict(row) for row in rows]
edited[1]["labels"] = [1]
assert dataset_binding(edited)["ordered_rows_sha256"] != original["ordered_rows_sha256"]
assert dataset_binding(list(reversed(rows)))["ordered_ids_sha256"] != original[
"ordered_ids_sha256"
]
def test_validator_rejects_group_safe_but_non_deterministic_partition():
rows = make_rows(40, 60)
summary = build_split(rows, test_fraction=0.15, seed=42)
broken = copy.deepcopy(summary)
train = broken["split"]["train_indices"]
test = broken["split"]["eval_indices"]
train[0], test[0] = test[0], train[0]
with pytest.raises(ValueError, match="do not match the deterministic"):
validate_split_summary(broken, rows)
def test_validator_rejects_empty_partition_before_recomputation():
rows = make_rows(5, 5)
summary = build_split(rows, test_fraction=0.2, seed=42)
broken = copy.deepcopy(summary)
broken["split"]["train_indices"] = list(range(len(rows)))
broken["split"]["eval_indices"] = []
with pytest.raises(ValueError, match="must both be non-empty"):
validate_split_summary(broken, rows)
def test_validator_accepts_legacy_fraction_encoded_in_scheme():
rows = make_rows(10, 10)
summary = build_split(rows, test_fraction=0.2, seed=42)
summary.pop("test_fraction")
assert validate_split_summary(summary, rows) == summary["split"]
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