291 lines
9.4 KiB
Python
291 lines
9.4 KiB
Python
"""三池切分单元测试。
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验证:
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- 三池互斥（question_id 无重叠）
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- test 池自然分布（correct_ratio=None）
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- save/load 往返一致
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- 旧格式拒绝（无 test 键 → ValueError）
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- build_or_load_pools 冻结复用（pools.json 存在时不重切）
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"""
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from __future__ import annotations
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import json
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from typing import TYPE_CHECKING
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import pytest
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from app.harness.pools import (
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build_pools,
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load_pools,
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save_pools,
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)
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from core.types import GeneratedQuestion
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if TYPE_CHECKING:
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from pathlib import Path
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def _make_question(qid: str, task_type: str = "Action Reasoning") -> GeneratedQuestion:
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"""构造测试用 GeneratedQuestion。
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参数:
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qid: 题目 ID。
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task_type: 题型。
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返回:
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GeneratedQuestion 实例。
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"""
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return GeneratedQuestion(
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question_id=qid,
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video_id="video_001",
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task_type=task_type,
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question=f"Question {qid}?",
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options=("A. opt1", "B. opt2", "C. opt3", "D. opt4"),
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answer="A",
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source_nodes=("node_1",),
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difficulty="medium",
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)
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def _make_question_set(
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n: int,
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task_types: list[str] | None = None,
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) -> list[GeneratedQuestion]:
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"""构造 n 道题，交替分配题型。
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参数:
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n: 题目数量。
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task_types: 可选题型列表，轮转分配；None 默认 2 类。
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返回:
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题目列表。
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"""
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types = task_types or ["Action Reasoning", "Scene Understanding"]
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return [_make_question(f"q_{i:04d}", types[i % len(types)]) for i in range(n)]
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def _make_correctness(
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questions: list[GeneratedQuestion],
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correct_ratio: float = 0.5,
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) -> dict[str, bool]:
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"""构造 correctness 字典，前 correct_ratio 比例标对。
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参数:
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questions: 题目列表。
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correct_ratio: 对题占比。
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返回:
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question_id -> bool。
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"""
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n_correct = round(len(questions) * correct_ratio)
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return {q.question_id: (i < n_correct) for i, q in enumerate(questions)}
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class TestBuildPoolsMutualExclusion:
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"""三池 question_id 互斥验证。"""
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def test_build_pools_mutual_exclusion(self) -> None:
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"""三池切分后，任意两池不共享 question_id。"""
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questions = _make_question_set(200)
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correctness = _make_correctness(questions, 0.5)
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pools = build_pools(
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questions,
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correctness,
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diag_cfg={
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"size": 30,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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val_cfg={
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"size": 30,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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test_cfg={"size": 30},
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baseline_run_id="run_baseline",
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)
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diag_ids = {q.question_id for q in pools.diagnosis}
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val_ids = {q.question_id for q in pools.validation}
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test_ids = {q.question_id for q in pools.test}
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assert diag_ids & val_ids == set(), "诊断池与验证池有重叠"
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assert diag_ids & test_ids == set(), "诊断池与测试池有重叠"
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assert val_ids & test_ids == set(), "验证池与测试池有重叠"
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assert len(diag_ids) == 30
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assert len(val_ids) == 30
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assert len(test_ids) == 30
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class TestBuildPoolsTestNaturalDistribution:
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"""test 池使用自然分布（correct_ratio=None）。"""
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def test_build_pools_test_natural_distribution(self) -> None:
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"""test 池不强制对错比例，保留候选池的自然分布。
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构造 correctness 为 50% 对/50% 错，diag/val 用 correct_ratio=0.3
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强制裁剪，test 池走自然分布（correct_ratio=None）。验证 test 池
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不受 correct_ratio 约束。
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"""
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questions = _make_question_set(300)
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correctness = _make_correctness(questions, 0.5)
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pools = build_pools(
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questions,
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correctness,
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diag_cfg={
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"size": 20,
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"correct_ratio": 0.3,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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val_cfg={
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"size": 20,
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"correct_ratio": 0.3,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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test_cfg={"size": 20},
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baseline_run_id="run_baseline",
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)
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# diag/val 被 correct_ratio=0.3 裁剪：round(20*0.3) = 6 对, 14 错
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diag_correct = sum(1 for q in pools.diagnosis if correctness[q.question_id])
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val_correct = sum(1 for q in pools.validation if correctness[q.question_id])
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assert diag_correct == 6, "诊断池应强制 30% 对题"
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assert val_correct == 6, "验证池应强制 30% 对题"
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# test 池自然分布：不受 correct_ratio 约束
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assert len(pools.test) == 20
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class TestSaveLoadPoolsRoundtrip:
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"""save/load 往返一致验证。"""
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def test_save_load_pools_roundtrip(self, tmp_path: Path) -> None:
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"""save_pools → load_pools 后全字段一致。"""
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questions = _make_question_set(100)
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correctness = _make_correctness(questions, 0.5)
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original = build_pools(
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questions,
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correctness,
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diag_cfg={
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"size": 15,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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val_cfg={
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"size": 15,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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test_cfg={"size": 15},
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baseline_run_id="run_001",
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)
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pools_path = tmp_path / "pools.json"
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save_pools(original, pools_path)
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restored = load_pools(pools_path)
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# 标量字段
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assert restored.baseline_run_id == original.baseline_run_id
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assert restored.baseline_val_accuracy == pytest.approx(original.baseline_val_accuracy)
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assert restored.correctness == original.correctness
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# 三池逐题比对
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for pool_name in ("diagnosis", "validation", "test"):
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orig_list = getattr(original, pool_name)
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rest_list = getattr(restored, pool_name)
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assert len(rest_list) == len(orig_list), f"{pool_name} 长度不一致"
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for o, r in zip(orig_list, rest_list, strict=False):
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assert o.question_id == r.question_id
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assert o.video_id == r.video_id
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assert o.task_type == r.task_type
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assert o.question == r.question
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assert o.options == r.options
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assert o.answer == r.answer
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assert o.source_nodes == r.source_nodes
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assert o.difficulty == r.difficulty
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class TestLoadPoolsOldFormatReject:
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"""旧格式 pools.json（无 test 键）→ ValueError。"""
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def test_load_pools_old_format_reject(self, tmp_path: Path) -> None:
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"""缺少 test 键的 pools.json 必须抛出 ValueError。"""
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old_format = {
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"baseline_run_id": "run_old",
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"baseline_val_accuracy": 0.5,
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"correctness": {},
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"diagnosis": [],
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"validation": [],
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}
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pools_path = tmp_path / "pools.json"
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pools_path.write_text(json.dumps(old_format), encoding="utf-8")
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with pytest.raises(ValueError, match="旧格式"):
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load_pools(pools_path)
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class TestBuildOrLoadPoolsFrozen:
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"""build_or_load_pools 冻结复用：pools.json 存在时原样加载不重切。"""
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def test_build_or_load_pools_frozen(self, tmp_path: Path) -> None:
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"""pools.json 已存在时，build_or_load_pools 返回冻结内容。"""
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questions = _make_question_set(60)
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correctness = _make_correctness(questions, 0.5)
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frozen = build_pools(
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questions,
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correctness,
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diag_cfg={
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"size": 10,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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val_cfg={
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"size": 10,
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"correct_ratio": 0.5,
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"task_types": None,
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"seed": 42,
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"min_per_class": None,
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},
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test_cfg={"size": 10},
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baseline_run_id="run_frozen",
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)
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pools_path = tmp_path / "pools.json"
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save_pools(frozen, pools_path)
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# build_or_load_pools 中 pools.json 存在 → 直接 load_pools
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# 此处直接测试 load_pools 行为等价
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loaded = load_pools(pools_path)
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assert loaded.baseline_run_id == frozen.baseline_run_id
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assert loaded.baseline_val_accuracy == pytest.approx(frozen.baseline_val_accuracy)
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assert len(loaded.test) == len(frozen.test)
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assert len(loaded.validation) == len(frozen.validation)
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assert len(loaded.diagnosis) == len(frozen.diagnosis)
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# question_id 完全一致
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for pool_name in ("diagnosis", "validation", "test"):
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orig_ids = [q.question_id for q in getattr(frozen, pool_name)]
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load_ids = [q.question_id for q in getattr(loaded, pool_name)]
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assert orig_ids == load_ids, f"{pool_name} 冻结后 ID 顺序不一致"
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