Fix trimming logic

Author: EAddario

src/llama-quant.cpp

@@ -849,8 +849,12 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
     };
 
     auto delete_bpw_state = [&] {
-        LLAMA_LOG_INFO("%s: deleting %s\n", func, checkpoint_file.c_str());
-        std::remove(checkpoint_file.c_str());
+        std::ifstream ifs(checkpoint_file);
+        if (ifs.good()) {
+            LLAMA_LOG_INFO("%s: deleting %s\n", func, checkpoint_file.c_str());
+            std::remove(checkpoint_file.c_str());
+        }
+
     };
 
     auto check_signal_handler = [&](const std::vector<tensor_info> & all_vec) {
@@ -988,14 +992,16 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
         }
 
         // Compute error per slice with trimmed aggregation
-        auto trimmed_sum = [](std::vector<double> & v) -> double {
+        auto trimmed_mean = [](std::vector<double> & v) -> double {
             const int64_t n = (int64_t)v.size();
             if (n == 0) { return 0.0; }
-            if (n < 50) { return std::accumulate(v.begin(), v.end(), 0.0); } // use all samples for small datasets
-
-            int64_t k = (int64_t) std::floor(0.025 * (double)n); // trim 2.5% from each tail of the distribution
+            double sum = std::accumulate(v.begin(), v.end(), 0.0);
+            if (n < 50) { return sum / (double)n; } // too few elements to trim
+            int64_t k = (int64_t) std::floor(0.025 * (double)n); // trim 5% (2.5% each side)
             std::sort(v.begin(), v.end());
-            return std::accumulate(v.begin() + k, v.begin() + (n - k), 0.0);
+            const auto num = (double)(n - 2 * k);
+            sum = std::accumulate(v.begin() + k, v.begin() + (n - k), 0.0);
+            return sum / std::max(1.0, num);
         };
 
         size_t off = 0;
@@ -1028,7 +1034,7 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
                 }
 
                 const double denom_x = row_sq_norm[ridx];
-                const double m_norm  = w_mse / (denom_x + epsilon);
+                const double m_norm = w_mse / (denom_x + epsilon);
                 row_mse_norm.push_back(std::isfinite(m_norm) ? m_norm : infinity);
 
                 if (a) {
@@ -1044,9 +1050,8 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
                 off += (size_t)n_per_row;
             }
 
-            const double scale_rows = (double)nrows / std::max(1.0, (double)rs);
-            const double slice_mse = trimmed_sum(row_mse_norm) * scale_rows;
-            const double slice_proj = a ? trimmed_sum(row_proj_norm) * scale_rows : 0.0;
+            const double slice_mse = trimmed_mean(row_mse_norm) * (double)nrows;
+            const double slice_proj = a ? trimmed_mean(row_proj_norm) * (double)nrows : 0.0;
 
             total_mse += slice_mse;
             total_proj += slice_proj;