Add Euclidean–Cosine Score (ECS)
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@ -18,6 +18,7 @@
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#include <regex>
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#include <thread>
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#include <unordered_map>
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#include <valarray>
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#include <vector>
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#if defined(_MSC_VER)
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@ -1301,7 +1302,7 @@ static bool show_statistics(const common_params & params) {
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std::map<int, layer_stats> ls;
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LOG_INF("\nComputing tensor statistics for %s (%d tensors)\n", params.in_files[0].c_str(), static_cast<int>(ts.size()));
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LOG_INF("\n%6s\t%18s\t%13s\t%8s\t%8s\t%7s\t%15s\t%13s\t%12s\t%s\t%5s\t%10s\n",
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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",
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"Layer",
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"Tensor",
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legacy_mode ? "Σ(Act²)" : "L₂ Norm",
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@ -1310,8 +1311,8 @@ static bool show_statistics(const common_params & params) {
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"μ",
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"σ",
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"N",
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"Entropy",
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"E (norm)",
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"H Norm",
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legacy_mode ? "H" : "ECS",
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"ZD",
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"CosSim");
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LOG_INF(
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@ -1328,17 +1329,17 @@ static bool show_statistics(const common_params & params) {
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blk = -1; // not a block layer
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}
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LOG_INF("%5s\t%-20s\t%11.2f\t%10.4f\t%10.4f\t%8.2f\t%8.2f\t%7d\t%12.4f\t%7.2f%%\t%6.2f%%\t%10.4f\n",
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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",
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layer.c_str(),
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name.c_str(),
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legacy_mode == 1 ? tstat.sum_values : tstat.l2_norm,
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legacy_mode ? tstat.sum_values : tstat.l2_norm,
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tstat.min_values,
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tstat.max_values,
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tstat.mean_values,
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tstat.std_deviation,
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tstat.elements,
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tstat.entropy,
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100.0f * (tstat.entropy / std::log2(tstat.elements)),
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legacy_mode ? tstat.entropy : 100.0f * std::exp(-0.01f * tstat.l2_norm) * std::pow(fabs(tstat.cossim), 10.0f),
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100.0f * tstat.zd_score,
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tstat.cossim);
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@ -1363,25 +1364,37 @@ static bool show_statistics(const common_params & params) {
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const auto layers = std::count_if(ls.begin(), ls.end(), [](const auto & kv) { return kv.first >= 0; });
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LOG_INF("\nComputing layer statistics (%ld layers)\n", layers);
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LOG_INF("\n%6s\t%13s\t%5s\t%10s\n",
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LOG_INF("\n%6s\t%13s\t%6s\t%11s\t%6s\n",
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"Layer",
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legacy_mode ? "Σ(Act²)" : "L₂ Norm",
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"ZD",
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"CosSim");
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"CosSim",
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legacy_mode ? "" : "ECS");
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if (legacy_mode) {
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LOG_INF("============================================\n");
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} else {
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LOG_INF("=========================================================\n");
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}
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for (const auto & [layer, stats] : ls) {
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if (layer < 0 || stats.n == 0) continue;
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const float lyr_sum = stats.lyr_sum;
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const float lyr_zd = stats.lyr_zd / stats.n;
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const auto lcs = lyr_cossim.find(layer);
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const float lyr_cs = (lcs != lyr_cossim.end()) ? lcs->second : 0.0f;
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const float lyr_cs = lcs != lyr_cossim.end() ? lcs->second : 0.0f;
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const auto ll2n = lyr_l2_norm.find(layer);
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const float l2_norm = (ll2n != lyr_l2_norm.end()) ? ll2n->second : 0.0f;
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LOG_INF("%5d\t%11.2f\t%6.2f%%\t%10.4f\n",
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const float lyr_l2n = ll2n != lyr_l2_norm.end() ? ll2n->second : 0.0f;
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if (legacy_mode) {
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LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\n",
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layer,
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legacy_mode ? lyr_sum : l2_norm,
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100.0f * lyr_zd,
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stats.lyr_sum,
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100.0f * stats.lyr_zd / stats.n,
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lyr_cs);
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} else {
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LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\t%8.4f\n",
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layer,
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lyr_l2n,
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100.0f * stats.lyr_zd / stats.n,
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lyr_cs,
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100.0f * std::exp(-0.01f * lyr_l2n) * std::pow(fabs(lyr_cs), 10.0f));
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}
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}
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LOG_INF("\n");
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