"""单元测试: 用理论文档中的典型边界 case 固化分支判定与仲裁逻辑. 覆盖: - v0.98 §十 典型边界 case (MergeBatch/IterBatch 分界) - v1.1 §4.5 统一分界条件 (K 截断 + b_core 阈值) - MergeBatch 五条进入条件逐条触发 - 时延模型自洽性 (MergeBatch 胜时确实更优) 运行: python -m unittest discover -s tests -v """ import unittest from bmm_theory.models import BmmCase from bmm_theory.router import BranchRouter, BRANCH_TO_MATMUL, BRANCH_SPECIAL from bmm_theory.branches.merge_batch import MergeBatchBranch from bmm_theory.branches.iter_batch import IterBatchBranch def mkcase(b, m, n, k, **kw): return BmmCase(case_id=f"B{b}_M{m}_N{n}_K{k}", batch_a=b, batch_b=b, m=m, n=n, k=k, **kw) class TestBranchEntry(unittest.TestCase): """v0.98 §十 典型边界 case 的分支归属.""" def setUp(self): self.router = BranchRouter() def test_mergebatch_boundary_case(self): # 文档: B=128 M=N=64 K=512 -> MergeBatch 五条全过 r = self.router.route(mkcase(128, 64, 64, 512)) self.assertEqual(r["candidates"].get("MergeBatch"), True) def test_iterbatch_when_datamount_insufficient(self): # 文档: 同上但 K=256 -> 条件 3 不满足 -> IterBatch r = self.router.route(mkcase(128, 64, 64, 256)) self.assertEqual(r["branch"], "IterBatch") mb = MergeBatchBranch().analyze(mkcase(128, 64, 64, 256)) self.assertFalse(mb.capable) def test_iterbatch_when_l0c_too_small(self): # 文档: B=512 M=N=128 K=128 -> 条件 2 不满足 (MN=16384>8192) -> IterBatch mb = MergeBatchBranch().analyze(mkcase(512, 128, 128, 128)) self.assertFalse(mb.capable) r = self.router.route(mkcase(512, 128, 128, 128)) self.assertEqual(r["branch"], "IterBatch") def test_iterbatch_form_d(self): # 文档: B=64 M=N=64 K=8192 -> IterBatch 形态 d r = self.router.route(mkcase(64, 64, 64, 8192)) self.assertEqual(r["branch"], "IterBatch") self.assertIn("d_", r["plan"].l1_form) def test_to_matmul(self): r = self.router.route(BmmCase(case_id="t", batch_a=1, batch_b=1, m=2048, n=2048, k=2048)) self.assertEqual(r["branch"], BRANCH_TO_MATMUL) def test_special_k1(self): r = self.router.route(mkcase(128, 256, 256, 1)) self.assertEqual(r["branch"], BRANCH_SPECIAL) class TestArbitration(unittest.TestCase): """v1.1 §4.5: MergeBatch 仅 K 截断且 b_core 足够大时胜.""" def setUp(self): self.mb = MergeBatchBranch() def test_l1_bound_mergebatch_loses(self): # L1 绑定 (k_L1 < K): MergeBatch 恒劣 win, detail = self.mb.beats_iterbatch(mkcase(256, 128, 128, 4096)) self.assertFalse(win) self.assertIn("L1绑定", detail) def test_large_batch_mergebatch_wins(self): # 大 B + 小 MN + K 截断: MergeBatch 应胜 (v1.1 §4.5) case = mkcase(2048, 32, 32, 256) self.assertTrue(MergeBatchBranch().analyze(case).capable) win, detail = self.mb.beats_iterbatch(case) self.assertTrue(win, detail) class TestTimingSanity(unittest.TestCase): """时延模型自洽性.""" def test_mergebatch_dma_cmd_saved(self): # K 截断时 MergeBatch 的 DMA 命令数 = IterBatch 的 1/b0 # B=2048 M=N=32 K=256 是 K 截断 case (b0=4, k_l1=256=K) case = mkcase(2048, 32, 32, 256) mb = MergeBatchBranch().analyze(case) ib = IterBatchBranch().analyze(case) self.assertTrue(mb.capable) self.assertTrue(ib.capable) self.assertGreaterEqual(mb.plan.k_l1, case.k) # 确认 K 截断前提 ratio = mb.timing.dma_cmd_count / ib.timing.dma_cmd_count self.assertAlmostEqual(ratio, 1.0 / mb.plan.merge_b0, places=1) def test_bottleneck_memory_bound_for_small_mn(self): # MergeBatch case 必为访存 Bound (进入条件 5) case = mkcase(128, 64, 64, 512) mb = MergeBatchBranch().analyze(case) self.assertIn(mb.timing.bottleneck, ("MTE2_GM", "MTE2_L2")) def test_fixpipe_dtype_conversion(self): # C 指定 fp16 输出时, 写出量按 2B 而非 L0C 的 4B case = mkcase(128, 64, 64, 512, dtype_c="fp16") ib = IterBatchBranch().analyze(case) expect = ib.plan.b_core * 64 * 64 * 2 self.assertAlmostEqual(ib.timing.fixpipe_bytes, expect) if __name__ == "__main__": unittest.main()