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llama.cpp
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Define one variable per line and refactor names

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Ed Addario 2025-08-17 08:16:41 +01:00
parent 12607d3203
commit a96013f720
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1 changed files with 30 additions and 28 deletions
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50
tools/imatrix/imatrix.cpp
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@ -341,14 +341,16 @@ static void compute_layer_statistics(const std::vector<tensor_statistics> & tsta
const auto & curr = kv.second.curr_avg; const auto & curr = kv.second.curr_avg;
const auto & prev = kv.second.prev_avg; const auto & prev = kv.second.prev_avg;
if (curr.size() != prev.size() || curr.empty()) continue; if (curr.size() != prev.size() || curr.empty()) continue;
float dot_prod = 0.0, lyr1 = 0.0, lyr2 = 0.0; float dot_prod = 0.0;
float layer1 = 0.0;
float layer2 = 0.0;
for (size_t i = 0; i < curr.size(); ++i) { for (size_t i = 0; i < curr.size(); ++i) {
dot_prod += curr[i] * prev[i]; dot_prod += curr[i] * prev[i];
lyr1 += curr[i] * curr[i]; layer1 += curr[i] * curr[i];
lyr2 += prev[i] * prev[i]; layer2 += prev[i] * prev[i];
} }
float cossim = 0.0f; float cossim = 0.0f;
if (lyr1 > 0.0 && lyr2 > 0.0) cossim = dot_prod / (std::sqrt(lyr1) * std::sqrt(lyr2)); if (layer1 > 0.0 && layer2 > 0.0) cossim = dot_prod / (std::sqrt(layer1) * std::sqrt(layer2));
layer_cossim[kv.first] = cossim; layer_cossim[kv.first] = cossim;
} }
@ -1297,8 +1299,8 @@ static bool show_statistics(const common_params & params) {
std::sort(ts.begin(), ts.end(), tensor_comparer(legacy_mode)); std::sort(ts.begin(), ts.end(), tensor_comparer(legacy_mode));
struct layer_stats { struct layer_stats {
float lyr_sum = 0.0f; float layer_sum = 0.0f;
float lyr_zd = 0.0f; float layer_zd = 0.0f;
int n = 0; int n = 0;
}; };
std::map<int, layer_stats> ls; std::map<int, layer_stats> ls;
@ -1348,21 +1350,21 @@ static bool show_statistics(const common_params & params) {
const float zd = tstat.elements * tstat.zd_score; const float zd = tstat.elements * tstat.zd_score;
if (ls.find(blk) != ls.end()) { if (ls.find(blk) != ls.end()) {
ls[blk].lyr_sum += tstat.sum_values; ls[blk].layer_sum += tstat.sum_values;
ls[blk].lyr_zd += zd; ls[blk].layer_zd += zd;
ls[blk].n += tstat.elements; ls[blk].n += tstat.elements;
} else { } else {
layer_stats temp_ls; layer_stats temp_ls;
temp_ls.lyr_sum = tstat.sum_values; temp_ls.layer_sum = tstat.sum_values;
temp_ls.lyr_zd = zd; temp_ls.layer_zd = zd;
temp_ls.n = tstat.elements; temp_ls.n = tstat.elements;
ls[blk] = temp_ls; ls[blk] = temp_ls;
} }
} }
std::map<int, float> lyr_cossim; std::map<int, float> layer_cossim;
std::map<int, float> lyr_l2_norm; std::map<int, float> layer_l2_norm;
compute_layer_statistics(ts, lyr_cossim, lyr_l2_norm, g_collector.get_mstats()); compute_layer_statistics(ts, layer_cossim, layer_l2_norm, g_collector.get_mstats());
const auto layers = std::count_if(ls.begin(), ls.end(), [](const auto & kv) { return kv.first >= 0; }); const auto layers = std::count_if(ls.begin(), ls.end(), [](const auto & kv) { return kv.first >= 0; });
LOG_INF("\nComputing layer statistics (%ld layers)\n", layers); LOG_INF("\nComputing layer statistics (%ld layers)\n", layers);
@ -1379,23 +1381,23 @@ static bool show_statistics(const common_params & params) {
} }
for (const auto & [layer, stats] : ls) { for (const auto & [layer, stats] : ls) {
if (layer < 0 || stats.n == 0) continue; if (layer < 0 || stats.n == 0) continue;
const auto lcs = lyr_cossim.find(layer); const auto lcs = layer_cossim.find(layer);
const float lyr_cs = lcs != lyr_cossim.end() ? lcs->second : 0.0f; const float layer_cs = lcs != layer_cossim.end() ? lcs->second : 0.0f;
const auto ll2n = lyr_l2_norm.find(layer); const auto ll2n = layer_l2_norm.find(layer);
const float lyr_l2n = ll2n != lyr_l2_norm.end() ? ll2n->second : 0.0f; const float layer_l2n = ll2n != layer_l2_norm.end() ? ll2n->second : 0.0f;
if (legacy_mode) { if (legacy_mode) {
LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\n", LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\n",
layer, layer,
stats.lyr_sum, stats.layer_sum,
100.0f * stats.lyr_zd / stats.n, 100.0f * stats.layer_zd / stats.n,
lyr_cs); layer_cs);
} else { } else {
LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\t%8.4f\n", LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\t%8.4f\n",
layer, layer,
lyr_l2n, layer_l2n,
100.0f * stats.lyr_zd / stats.n, 100.0f * stats.layer_zd / stats.n,
lyr_cs, layer_cs,
100.0f * std::exp(-0.01f * lyr_l2n) * std::pow(fabs(lyr_cs), 10.0f)); 100.0f * std::exp(-0.01f * layer_l2n) * std::pow(fabs(layer_cs), 10.0f));
} }
} }
LOG_INF("\n"); LOG_INF("\n");