@@ -150,7 +150,7 @@ static std::vector<float> compute_tensor_averages(const Stats & tstats) {
150150 } else {
151151 // Mean
152152 for (size_t m = 0 ; m < n_mat; ++m) {
153- const float c = (float )tstats.counts [m];
153+ const auto c = (float )tstats.counts [m];
154154 const size_t off = m * row;
155155 if (c <= 0 .0f ) {
156156 vec.insert (vec.end (), row, 0 .0f ); // zero-fill rows for experts with zero count to preserve shape
@@ -215,7 +215,7 @@ static bool compute_vector_statistics(std::vector<tensor_statistics> & tstats, c
215215 double sqr_sum = 0.0 ;
216216 for (const float v : activations) { sqr_sum += (double )v * (double )v; }
217217 double variance = sqr_sum / (double )activations.size () - (double )mean * (double )mean;
218- if ( variance < 0.0 ) { variance = 0.0 ; }
218+ variance = std::max ( variance, 0.0 );
219219 const float std_deviation = std::sqrt ((float )variance);
220220
221221 float entropy = 0 .0f ;
@@ -1327,7 +1327,7 @@ static bool show_statistics(const common_params & params) {
13271327 LOG_INF (" \n %6s\t %18s\t %13s\t %8s\t %8s\t %7s\t %15s\t %13s\t %11s\t %8s\t %5s\t %10s\n " ,
13281328 " Layer" ,
13291329 " Tensor" ,
1330- legacy_mode ? " Σ( Act²) " : " L₂ Norm" ,
1330+ legacy_mode ? " Σ E[ Act²] " : " L₂ Norm" ,
13311331 " Min" ,
13321332 " Max" ,
13331333 " μ" ,
@@ -1356,7 +1356,7 @@ static bool show_statistics(const common_params & params) {
13561356 const float h_norm = tstat.elements > 1 ? 100 .0f * (tstat.entropy / std::log2 ((float ) tstat.elements )) : 0 .0f ;
13571357 const float ecs = 100 .0f * std::exp (-0 .01f * tstat.l2_norm ) * std::pow (std::fabs (tstat.cossim ), 10 .0f );
13581358
1359- LOG_INF (" %5s\t %-20s\t %11.2f \t %10.4f\t %10.4f\t %8.2f \t %8.2f \t %7d\t %10.2f%%\t %10.4f\t %6.2f%%\t %10.4f\n " ,
1359+ LOG_INF (" %5s\t %-20s\t %11.4f \t %10.4f\t %10.4f\t %8.4f \t %8.4f \t %7d\t %10.2f%%\t %10.4f\t %6.2f%%\t %10.4f\n " ,
13601360 layer.c_str (),
13611361 name.c_str (),
13621362 legacy_mode ? tstat.sum_values : tstat.l2_norm ,
@@ -1392,7 +1392,7 @@ static bool show_statistics(const common_params & params) {
13921392 LOG_INF (" \n Computing layer statistics (%zu layers)\n " , layers);
13931393 LOG_INF (" \n %6s\t %13s\t %6s\t %11s\t %6s\n " ,
13941394 " Layer" ,
1395- legacy_mode ? " Σ( Act²) " : " L₂ Norm" ,
1395+ legacy_mode ? " Σ E[ Act²] " : " L₂ Norm" ,
13961396 " ZD" ,
13971397 " CosSim" ,
13981398 legacy_mode ? " " : " ECS" );
@@ -1402,19 +1402,19 @@ static bool show_statistics(const common_params & params) {
14021402 LOG_INF (" =========================================================\n " );
14031403 }
14041404 for (const auto & [layer, stats] : ls) {
1405- if (layer < 0 || stats.n == 0 ) continue ;
1405+ if (layer < 0 || stats.n == 0 ) { continue ; }
14061406 const auto lcs = layer_cossim.find (layer);
14071407 const float layer_cs = lcs != layer_cossim.end () ? lcs->second : 0 .0f ;
14081408 const auto ll2n = layer_l2_norm.find (layer);
14091409 const float layer_l2n = ll2n != layer_l2_norm.end () ? ll2n->second : 0 .0f ;
14101410 if (legacy_mode) {
1411- LOG_INF (" %5d\t %11.2f \t %6.2f%%\t %11.4f\n " ,
1411+ LOG_INF (" %5d\t %11.4f \t %6.2f%%\t %11.4f\n " ,
14121412 layer,
14131413 stats.layer_sum ,
14141414 100 .0f * stats.layer_zd / stats.n ,
14151415 layer_cs);
14161416 } else {
1417- LOG_INF (" %5d\t %11.2f \t %6.2f%%\t %11.4f\t %8.4f\n " ,
1417+ LOG_INF (" %5d\t %11.4f \t %6.2f%%\t %11.4f\t %8.4f\n " ,
14181418 layer,
14191419 layer_l2n,
14201420 100 .0f * stats.layer_zd / stats.n ,
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