happyz
/
llama.cpp
mirror of https://github.com/ggerganov/llama.cpp.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Refactor variables

This commit is contained in:
Ed Addario 2025-08-03 10:28:23 +01:00
parent a32a2ecbed
commit 4d1325e1eb
No known key found for this signature in database
GPG Key ID: E7875815A3230993
1 changed files with 20 additions and 20 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

40
tools/imatrix/imatrix.cpp
View File

@ -1211,10 +1211,10 @@ static bool show_statistics(const common_params & params) {
std::sort(ts.begin(), ts.end(), tensor_comparer());
struct weighted_stats {
float weighted_bias = 0.0f;
float weighted_zd = 0.0f;
float weighted_cossim = 0.0f;
int total_elements = 0;
float w_sum = 0.0f;
float w_zd = 0.0f;
float w_cossim = 0.0f;
int n = 0;
};
std::map<int, weighted_stats> ws;
@ -1262,22 +1262,22 @@ static bool show_statistics(const common_params & params) {
tstat.cossim
);
const float weighted_bias = tstat.elements * tstat.sum_values;
const float weighted_zd = tstat.elements * tstat.zd_score;
const float weighted_cossim = tstat.elements * tstat.cossim;
const float w_sum = tstat.elements * tstat.sum_values;
const float w_zd = tstat.elements * tstat.zd_score;
const float w_cossim = tstat.elements * tstat.cossim;
if (ws.find(blk) != ws.end()) {
ws[blk].weighted_bias += weighted_bias;
ws[blk].weighted_zd += weighted_zd;
ws[blk].weighted_cossim += weighted_cossim;
ws[blk].total_elements += tstat.elements;
ws[blk].w_sum += w_sum;
ws[blk].w_zd += w_zd;
ws[blk].w_cossim += w_cossim;
ws[blk].n += tstat.elements;
} else {
weighted_stats temp_ws;
temp_ws.weighted_bias = weighted_bias;
temp_ws.weighted_zd = weighted_zd;
temp_ws.weighted_cossim = weighted_cossim;
temp_ws.total_elements = tstat.elements;
ws[blk] = temp_ws;
temp_ws.w_sum = w_sum;
temp_ws.w_zd = w_zd;
temp_ws.w_cossim = w_cossim;
temp_ws.n = tstat.elements;
ws[blk] = temp_ws;
}
}
@ -1289,14 +1289,14 @@ static bool show_statistics(const common_params & params) {
const auto & layer = first;
const auto & stats = second;
if (stats.total_elements == 0) {
if (stats.n == 0) {
continue;
}
if (layer >= 0) {
const float bias = stats.weighted_bias / stats.total_elements;
const float zd = stats.weighted_zd / stats.total_elements;
const float cossim = stats.weighted_cossim / stats.total_elements;
const float w_sum = stats.w_sum / stats.n;
const float w_zd = stats.w_zd / stats.n;
const float w_cossim = stats.w_cossim / stats.n;
LOG_INF("%5d\t%14.2f\t%10.4f%%\t%6.4f\n", layer, bias, 100.0f * zd, cossim);
}