dtourolleandClaude Opus 5
ffdad9873d
Four test files and one node header carried no TRACES tag, so the requirements they verify read as implemented-but-unverified. Tagging a test is what distinguishes the two. test_calibration.cpp is AR-023; its three [report] cases verify GR-003 and are tagged separately, since the report is fitted from the same distributions but is its own requirement. test_similarity.cpp is the CI half of AR-026 — equivalence against hand-computed dot products, where throughput at scale is AR-027 and cannot run on this host. test_face_tracker.cpp is AR-007 and AR-008. Two headers described code that no longer exists. face_aligner_node.hpp still documented the RANSAC fit AR-005 replaced with an Umeyama least-squares fit over all five points — not merely out of date but the opposite of what the file does, and it reads as a rationale for discarding the landmarks AR-030 measures. test_face_tracker.cpp still described the park/revive branch AR-008 deleted, and the raw-cosine cut_revive_sim that guarded it, which AR-024 retired. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> TRACES: AR-005, AR-007, AR-008, AR-023, AR-026, AR-030 | GR-003 | SR-001, SR-002
98 lines
3.4 KiB
C++
98 lines
3.4 KiB
C++
// TRACES: AR-026 | SR-001
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//
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// Unit tests for the CPU reference similarity engine (backends/gemm_backend.cpp,
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// SAE_GEMM_CPU) and the l2_normalise helper. All pure, GPU-free, model-free.
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//
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// This is the CI half of AR-026: equivalence between the GEMM path and
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// hand-computed dot products on small input. Throughput at scale (AR-027) is T4
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// and cannot run here.
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#include <catch2/catch_test_macros.hpp>
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#include <catch2/matchers/catch_matchers_floating_point.hpp>
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#include "face_utils.hpp"
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#include "inference/similarity.hpp"
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#include <array>
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#include <cmath>
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#include <vector>
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using Catch::Matchers::WithinAbs;
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namespace {
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// A 512-d embedding that is 1.0 in one slot and 0 elsewhere (already unit-norm).
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std::array<float, 512> one_hot(int slot) {
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std::array<float, 512> e{};
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e[slot] = 1.0f;
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return e;
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}
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} // namespace
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TEST_CASE("l2_normalise produces a unit vector", "[similarity]") {
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std::array<float, 512> raw{};
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raw[0] = 3.0f;
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raw[1] = 4.0f; // norm 5
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Embedding n = l2_normalise(raw.data());
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CHECK_THAT(n[0], WithinAbs(0.6f, 1e-6f));
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CHECK_THAT(n[1], WithinAbs(0.8f, 1e-6f));
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float norm = 0.f;
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for (float v : n) norm += v * v;
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CHECK_THAT(std::sqrt(norm), WithinAbs(1.0f, 1e-6f));
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}
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TEST_CASE("l2_normalise guards against a zero vector", "[similarity]") {
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std::array<float, 512> zero{};
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Embedding n = l2_normalise(zero.data());
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for (float v : n) CHECK(v == 0.0f); // 0 / 1e-6 == 0, no NaN
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}
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TEST_CASE("CPU similarity engine matches hand-computed dot products", "[similarity]") {
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// Gallery of three orthonormal one-hot embeddings.
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std::vector<float> gallery;
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for (int slot : {0, 1, 2}) {
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auto e = one_hot(slot);
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gallery.insert(gallery.end(), e.begin(), e.end());
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}
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const int n_gallery = 3;
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const int max_faces = 2;
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auto engine = make_similarity_engine(gallery.data(), n_gallery, max_faces);
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REQUIRE(engine->max_faces() == max_faces);
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// Two query faces: face0 == gallery row 1, face1 is 45° between rows 0 and 2.
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std::vector<float> query(static_cast<size_t>(max_faces) * 512, 0.0f);
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query[1] = 1.0f; // face0: one-hot slot 1
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const float s = std::sqrt(0.5f);
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query[512 + 0] = s; // face1: (1/√2, 0, 1/√2, …)
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query[512 + 2] = s;
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const float* S = engine->compute(query.data(), 2);
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// Column-major: S[g + f*n_gallery].
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// face0 vs gallery {0,1,2} → {0, 1, 0}
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CHECK_THAT(S[0 + 0 * n_gallery], WithinAbs(0.0f, 1e-6f));
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CHECK_THAT(S[1 + 0 * n_gallery], WithinAbs(1.0f, 1e-6f));
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CHECK_THAT(S[2 + 0 * n_gallery], WithinAbs(0.0f, 1e-6f));
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// face1 vs gallery {0,1,2} → {1/√2, 0, 1/√2}
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CHECK_THAT(S[0 + 1 * n_gallery], WithinAbs(s, 1e-6f));
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CHECK_THAT(S[1 + 1 * n_gallery], WithinAbs(0.0f, 1e-6f));
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CHECK_THAT(S[2 + 1 * n_gallery], WithinAbs(s, 1e-6f));
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}
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TEST_CASE("CPU similarity engine rejects too many faces", "[similarity]") {
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auto e = one_hot(0);
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auto engine = make_similarity_engine(e.data(), /*n_gallery=*/1, /*max_faces=*/1);
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std::array<float, 512 * 2> q{};
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CHECK_THROWS(engine->compute(q.data(), 2));
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}
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TEST_CASE("CPU similarity engine handles zero query faces", "[similarity]") {
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auto e = one_hot(0);
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auto engine = make_similarity_engine(e.data(), 1, 4);
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// n_faces == 0 must not read the (null) query pointer.
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CHECK_NOTHROW(engine->compute(nullptr, 0));
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}
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