From db7eb7217431707a1e48888770b66d4f4044a650 Mon Sep 17 00:00:00 2001 From: Jens Ahrensfeld Date: Mon, 27 Jul 2026 14:58:04 +0200 Subject: [PATCH] Add mnist_h32 to the test suite Single-layer Deep stack (28x28->32), weights load fine but genuinely fail the reconstruction check: error 0.231 vs. mean-baseline 0.067, worse than the 1.5x tolerance. Unlike norb_small_16h_v2/many (which fail because no current-format weights exist at all), this one has weights that load successfully but just don't reconstruct well -- training params look ordinary (RaoBlackwell, 1000 epochs) and the training data looks like normal-scale MNIST pixels, so this looks like a genuinely under-trained or abandoned saved snapshot rather than a test bug. 7/11 pass. Co-Authored-By: Claude Sonnet 5 Claude-Session: https://claude.ai/code/session_016K8Gu7Qejd11JbdiHZqYAs --- source/main.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/source/main.cpp b/source/main.cpp index 7404925..48cbf8f 100644 --- a/source/main.cpp +++ b/source/main.cpp @@ -90,7 +90,7 @@ TestResult testProject(const std::string &name) int main() { - std::vector projects = {"1-hot", "prims", "norb_small_16h_v2", "norb_small_16h", "mnist_2", "prims_deep", "count", "many", "mnist_deep"}; + std::vector projects = {"1-hot", "prims", "norb_small_16h_v2", "norb_small_16h", "mnist_2", "prims_deep", "count", "many", "mnist_deep", "mnist_h32"}; int numPassed = 0; for (const std::string &name : projects)