iomgaa
2429dad393
build_batches 改以 QuestionUnit 为原子调度单元：孪生对 2 题整锁进同一 batch、 按单元级正确性（双向 AND）落 correct/error 桶，不再因 P 对 Q 错被劈或被 FFD 拆箱。 - 非 AR（single）用 random.Random(seed) 复现旧逐题算法确切 draw 序列，AR（pair） 用 _rng_ns(seed,"AR") SHA-256 派生独立流；二者 draw 流互不干扰，故 AR 折叠不改变 非 AR 抽样/洗牌序列——纯非 AR 输入 build_batches 结果与引入 QuestionUnit 前逐字节一致。 - FFD 容量按 unit.size（pair 占 2），round-robin 遇碎片新开 bin 兜底而非报错。 - _select_mixed_by_task_type 分流各跑一次后合并，大类洗牌按 kind 拆分各用对应 rng。 新增黄金测试 test_batching_pair_lock.py 覆盖三条铁律（同 batch / 单元分桶 / 非 AR byte-identical + draw 流独立）；既有 batching 测试全绿。
293 lines
11 KiB
Python
293 lines
11 KiB
Python
"""app/harness/batching.py 的单元测试。
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覆盖 FFD + round-robin mini-batch 构建的核心场景：
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确定性、小类不拆、大类 round-robin、正确率混合、空错题、参数校验、
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correctness False vs None 精确匹配。
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"""
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from __future__ import annotations
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import random
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import pytest
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from app.harness.batching import (
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_select_mixed_by_task_type,
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_validate_params,
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build_batches,
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)
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from app.harness.question_units import build_units
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from core.types import GeneratedQuestion
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# ---------------------------------------------------------------------------
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# 辅助构造
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# ---------------------------------------------------------------------------
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def _make_q(
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qid: str,
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task_type: str = "default",
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video_id: str = "v1",
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) -> GeneratedQuestion:
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"""构造最小 GeneratedQuestion 用于测试。"""
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return GeneratedQuestion(
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question_id=qid,
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video_id=video_id,
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task_type=task_type,
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question=f"question_{qid}",
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options=("A. a", "B. b", "C. c", "D. d"),
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answer="A",
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source_nodes=("n1",),
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difficulty="medium",
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)
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# ---------------------------------------------------------------------------
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# test_build_batches_deterministic
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# ---------------------------------------------------------------------------
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class TestBuildBatchesDeterministic:
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"""相同输入 + 相同 seed 产出完全一致的切分。"""
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def test_same_seed_same_result(self) -> None:
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items = [_make_q(f"q{i}", task_type=f"type_{i % 3}") for i in range(20)]
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correctness = {f"q{i}": False for i in range(20)}
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r1 = build_batches(items, correctness, batch_size=5, min_class_per_batch=2, seed=42)
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r2 = build_batches(items, correctness, batch_size=5, min_class_per_batch=2, seed=42)
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assert r1 == r2
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def test_different_seed_may_differ(self) -> None:
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"""不同 seed 结果应不同（极大概率，用大量样本保证）。"""
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items = [_make_q(f"q{i}", task_type=f"type_{i % 5}") for i in range(50)]
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correctness = {f"q{i}": False for i in range(50)}
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r1 = build_batches(items, correctness, batch_size=10, min_class_per_batch=3, seed=1)
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r2 = build_batches(items, correctness, batch_size=10, min_class_per_batch=3, seed=99)
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# 至少 batch 内容不同（不比较结构，只比较 selected_count 一致性）
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assert r1[1] == r2[1] # 总题数一致
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# 但 batch 内部排列几乎必然不同
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flat1 = [q.question_id for b in r1[0] for q in b]
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flat2 = [q.question_id for b in r2[0] for q in b]
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assert flat1 != flat2
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# ---------------------------------------------------------------------------
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# test_small_class_not_split
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# ---------------------------------------------------------------------------
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class TestSmallClassNotSplit:
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"""小类（≤ min_class_per_batch）整组不拆，锁在同一 batch。"""
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def test_small_group_stays_together(self) -> None:
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# 2 道题属于 small_type（≤ min_class=3），应在同一 batch
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items = [
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_make_q("s1", task_type="small_type"),
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_make_q("s2", task_type="small_type"),
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# 大类 8 道题
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*[_make_q(f"big{i}", task_type="big_type") for i in range(8)],
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]
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correctness = {q.question_id: False for q in items}
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batches, count = build_batches(
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items, correctness, batch_size=5, min_class_per_batch=3, seed=0
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)
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assert count == 10
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# 找到包含 small_type 的 batch
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small_batch = [b for b in batches if any(q.task_type == "small_type" for q in b)]
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assert len(small_batch) == 1 # 整组在同一个 batch
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small_ids = {q.question_id for q in small_batch[0] if q.task_type == "small_type"}
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assert small_ids == {"s1", "s2"}
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# ---------------------------------------------------------------------------
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# test_large_class_round_robin
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# ---------------------------------------------------------------------------
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class TestLargeClassRoundRobin:
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"""大类样本 round-robin 散布到多个 batch，不集中于单一 batch。"""
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def test_large_group_distributed(self) -> None:
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# 12 道大类题，batch_size=4，min_class=2 → 大类 > 2 → round-robin
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items = [_make_q(f"q{i}", task_type="large_type") for i in range(12)]
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correctness = {q.question_id: False for q in items}
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batches, count = build_batches(
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items, correctness, batch_size=4, min_class_per_batch=2, seed=7
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)
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assert count == 12
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assert len(batches) >= 3 # ceil(12/4) = 3
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# 每个 batch 不超过 batch_size
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for b in batches:
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assert len(b) <= 4
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# ---------------------------------------------------------------------------
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# test_correct_ratio_mixing
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# ---------------------------------------------------------------------------
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class TestCorrectRatioMixing:
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"""correct_ratio > 0 时混入正确题。"""
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def test_mixed_includes_correct(self) -> None:
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items = [
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_make_q("e1", task_type="t1"),
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_make_q("e2", task_type="t1"),
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_make_q("c1", task_type="t1"),
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_make_q("c2", task_type="t1"),
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_make_q("c3", task_type="t1"),
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]
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correctness = {"e1": False, "e2": False, "c1": True, "c2": True, "c3": True}
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batches, count = build_batches(
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items,
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correctness,
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batch_size=10,
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min_class_per_batch=2,
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seed=0,
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correct_ratio=0.5,
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)
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# correct_ratio=0.5 → 错:正 = 1:1 → 2 错 + 2 正 = 4 题
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assert count == 4
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all_ids = {q.question_id for b in batches for q in b}
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assert {"e1", "e2"}.issubset(all_ids) # 错题全部
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correct_in = all_ids - {"e1", "e2"}
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assert len(correct_in) == 2 # 采样 2 个正确题
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assert correct_in.issubset({"c1", "c2", "c3"})
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def test_ratio_zero_pure_errors(self) -> None:
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items = [
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_make_q("e1", task_type="t1"),
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_make_q("c1", task_type="t1"),
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]
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correctness = {"e1": False, "c1": True}
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batches, count = build_batches(
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items,
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correctness,
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batch_size=10,
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min_class_per_batch=2,
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seed=0,
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correct_ratio=0.0,
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)
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assert count == 1
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assert batches[0][0].question_id == "e1"
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# ---------------------------------------------------------------------------
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# test_no_wrong_answers_empty
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# ---------------------------------------------------------------------------
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class TestNoWrongAnswersEmpty:
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"""无错题时返回空列表。"""
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def test_all_correct_returns_empty(self) -> None:
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items = [_make_q(f"q{i}") for i in range(5)]
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correctness = {f"q{i}": True for i in range(5)}
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batches, count = build_batches(
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items,
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correctness,
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batch_size=3,
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min_class_per_batch=1,
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seed=0,
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)
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assert batches == []
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assert count == 0
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def test_empty_items_returns_empty(self) -> None:
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batches, count = build_batches(
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[],
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{},
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batch_size=3,
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min_class_per_batch=1,
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seed=0,
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)
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assert batches == []
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assert count == 0
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# ---------------------------------------------------------------------------
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# test_validate_params_strict
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# ---------------------------------------------------------------------------
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class TestValidateParamsStrict:
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"""参数校验：batch_size < 1、min_class < 1、min_class >= batch_size 都报错。"""
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def test_batch_size_zero(self) -> None:
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with pytest.raises(ValueError, match="batch_size 必须 >= 1"):
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_validate_params(0, 1)
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def test_batch_size_negative(self) -> None:
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with pytest.raises(ValueError, match="batch_size 必须 >= 1"):
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_validate_params(-1, 1)
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def test_min_class_zero(self) -> None:
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with pytest.raises(ValueError, match="min_class_per_batch 必须 >= 1"):
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_validate_params(5, 0)
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def test_min_class_equals_batch_size(self) -> None:
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with pytest.raises(ValueError, match="min_class_per_batch 必须严格 < batch_size"):
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_validate_params(5, 5)
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def test_min_class_exceeds_batch_size(self) -> None:
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with pytest.raises(ValueError, match="min_class_per_batch 必须严格 < batch_size"):
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_validate_params(3, 5)
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def test_valid_params_no_error(self) -> None:
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_validate_params(5, 3) # 不抛异常
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# ---------------------------------------------------------------------------
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# test_correctness_false_vs_none
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# ---------------------------------------------------------------------------
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class TestCorrectnessFalseVsNone:
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"""correctness.get(qid) is False 精确匹配：None（未知题）不算错题。"""
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def test_none_excluded_from_errors(self) -> None:
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items = [
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_make_q("wrong", task_type="t1"),
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_make_q("right", task_type="t1"),
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_make_q("unknown", task_type="t1"),
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]
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# wrong=False（错题），right=True（正确题），unknown 不在 correctness（None）
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correctness: dict[str, bool] = {"wrong": False, "right": True}
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batches, count = build_batches(
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items,
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correctness,
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batch_size=10,
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min_class_per_batch=2,
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seed=0,
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correct_ratio=0.0,
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)
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# 仅 wrong 进入 batch，unknown 不算错题
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assert count == 1
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assert batches[0][0].question_id == "wrong"
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def test_explicit_false_only(self) -> None:
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"""直接测试 _select_mixed_by_task_type 内部逻辑（single 单元粒度）。"""
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items = [
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_make_q("f1", task_type="t1"),
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_make_q("n1", task_type="t1"), # None（未知）
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_make_q("t1", task_type="t1"), # True（正确）
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]
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correctness: dict[str, bool] = {"f1": False, "t1": True}
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rng = random.Random(0)
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result = _select_mixed_by_task_type(build_units(items), correctness, 0.0, rng)
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assert "t1" in result
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assert len(result["t1"]) == 1
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assert result["t1"][0].unit_id == "f1"
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def test_none_not_treated_as_correct(self) -> None:
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"""None（未知）不进正确组，不被 correct_ratio 采样（single 单元粒度）。"""
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items = [
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_make_q("err", task_type="t1"),
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_make_q("unk", task_type="t1"),
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]
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correctness: dict[str, bool] = {"err": False}
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rng = random.Random(0)
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result = _select_mixed_by_task_type(build_units(items), correctness, 0.5, rng)
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# 只有 err 一题错题，unk 不在 correctness 中 → get 返回 None → 不进 correct 组
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assert len(result["t1"]) == 1 # 只有错题，无正确题可混入
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