From c9a0874f35a4c8e2681b0f4fc59c27f093a10e2f Mon Sep 17 00:00:00 2001
From: Ed Addario <eaddario@hotmail.com>
Date: Tue, 28 Oct 2025 18:29:59 +0000
Subject: [PATCH] Clamp CosSim to [-1, 1] to avoid float drift

---
 tools/imatrix/imatrix.cpp | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/tools/imatrix/imatrix.cpp b/tools/imatrix/imatrix.cpp
index 6935e44255..d047d0302e 100644
--- a/tools/imatrix/imatrix.cpp
+++ b/tools/imatrix/imatrix.cpp
@@ -258,12 +258,12 @@ static void compute_tensor_statistics(std::vector<tensor_statistics> & tstats) {
 
         if (std::smatch match; std::regex_search(ts.tensor, match, pattern)) {
             const int blk = std::stoi(match[1]);
-            if (blk <= 0) continue;
+            if (blk <= 0) { continue; }
             std::string tname(ts.tensor);
             tname.replace(match.position(1), match.length(1), std::to_string(blk-1));
             auto prev = std::find_if(tstats.begin(), tstats.end(),
                 [tname](const tensor_statistics & t) { return t.tensor == tname; });
-            if (prev == tstats.end()) continue;
+            if (prev == tstats.end()) { continue; }
             const auto curr_avg = compute_tensor_averages(ts.stats);
             const auto prev_avg = compute_tensor_averages(prev->stats);
             if (curr_avg.size() == prev_avg.size() && !curr_avg.empty()) {
@@ -275,7 +275,12 @@ static void compute_tensor_statistics(std::vector<tensor_statistics> & tstats) {
                     vec1  += curr_avg[i] * curr_avg[i];
                     vec2  += prev_avg[i] * prev_avg[i];
                 }
-                if (vec1 > 0 && vec2 > 0) ts.cossim = dot_prod / (std::sqrt(vec1) * std::sqrt(vec2));
+                if (vec1 > 0 && vec2 > 0) {
+                    float cs = dot_prod / (std::sqrt(vec1) * std::sqrt(vec2));
+                    cs = std::min(cs, 1.0f);
+                    cs = std::max(cs, -1.0f);
+                    ts.cossim = cs;
+                }
             }
         }
     }
@@ -283,19 +288,19 @@ static void compute_tensor_statistics(std::vector<tensor_statistics> & tstats) {
     // compute the L2 Norm (Euclidian Distance) between the same tensors in consecutive layers
     for (auto & ts : tstats) {
         ts.l2_norm = 0.0f;
-        if (ts.stats.activations.empty()) continue;
+        if (ts.stats.activations.empty()) { continue; }
 
         if (std::smatch match; std::regex_search(ts.tensor, match, pattern)) {
             const int blk = std::stoi(match[1]);
-            if (blk <= 0) continue;
+            if (blk <= 0) { continue; }
             std::string tname(ts.tensor);
             tname.replace(match.position(1), match.length(1), std::to_string(blk - 1));
             auto prev = std::find_if(tstats.begin(), tstats.end(),
                 [tname](const tensor_statistics & t) { return t.tensor == tname; });
-            if (prev == tstats.end()) continue;
+            if (prev == tstats.end()) { continue; }
             const auto cur_avg = compute_tensor_averages(ts.stats);
             const auto prev_avg = compute_tensor_averages(prev->stats);
-            if (cur_avg.empty() || prev_avg.empty() || cur_avg.size() != prev_avg.size()) continue;
+            if (cur_avg.empty() || prev_avg.empty() || cur_avg.size() != prev_avg.size()) { continue; }
 
             float dist = 0.0;
             for (size_t i = 0; i < cur_avg.size(); ++i) {