Fixed save_imatrix to match old behaviour for MoE (#7099)

* Fixed save_imatrix to match old behaviour for MoE

This fix is simple and clear, but unnecessarily doubles the memory overhead..

* Fixed missing idx variable

* Unconditionally increment ncall

Co-authored-by: slaren <slarengh@gmail.com>

* Fixed 2 bugs in save_imatrix()

- Fixed segfault bug because the counts vector needed to be created.
- Fixed pre-existing bug didn't actually add to the counts for "--combine" option.

* ncall needs summing too

* Trailing whitespace

---------

Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
jukofyork 2024-05-08 01:24:16 +01:00 committed by GitHub
parent af0a5b6163
commit 48b2f9c1fc
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@ -19,6 +19,7 @@
struct Stats { struct Stats {
std::vector<float> values; std::vector<float> values;
std::vector<int> counts;
int ncall = 0; int ncall = 0;
}; };
@ -121,12 +122,10 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void *
auto & e = m_stats[wname]; auto & e = m_stats[wname];
++e.ncall; ++e.ncall;
// NOTE: since we select top-k experts, the number of calls for the expert tensors will be k times larger
// using the following line, we can correct for that if needed by replacing the line above with:
//if (idx == t->src[0]->ne[0] - 1) ++e.ncall;
if (e.values.empty()) { if (e.values.empty()) {
e.values.resize(src1->ne[0]*n_as, 0); e.values.resize(src1->ne[0]*n_as, 0);
e.counts.resize(src1->ne[0]*n_as, 0);
} }
else if (e.values.size() != (size_t)src1->ne[0]*n_as) { else if (e.values.size() != (size_t)src1->ne[0]*n_as) {
fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]*n_as); fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]*n_as);
@ -153,6 +152,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void *
for (int j = 0; j < (int)src1->ne[0]; ++j) { for (int j = 0; j < (int)src1->ne[0]; ++j) {
e.values[e_start + j] += x[j]*x[j]; e.values[e_start + j] += x[j]*x[j];
e.counts[e_start + j]++;
} }
} }
} }
@ -170,6 +170,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void *
auto& e = m_stats[wname]; auto& e = m_stats[wname];
if (e.values.empty()) { if (e.values.empty()) {
e.values.resize(src1->ne[0], 0); e.values.resize(src1->ne[0], 0);
e.counts.resize(src1->ne[0], 0);
} }
else if (e.values.size() != (size_t)src1->ne[0]) { else if (e.values.size() != (size_t)src1->ne[0]) {
fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]); fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]);
@ -183,6 +184,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void *
const float * x = data + row * src1->ne[0]; const float * x = data + row * src1->ne[0];
for (int j = 0; j < (int)src1->ne[0]; ++j) { for (int j = 0; j < (int)src1->ne[0]; ++j) {
e.values[j] += x[j]*x[j]; e.values[j] += x[j]*x[j];
e.counts[j]++;
} }
} }
if (e.ncall > m_last_call) { if (e.ncall > m_last_call) {
@ -222,7 +224,13 @@ void IMatrixCollector::save_imatrix(const char * fname, const char * dataset) co
out.write((const char *) &p.second.ncall, sizeof(p.second.ncall)); out.write((const char *) &p.second.ncall, sizeof(p.second.ncall));
int nval = p.second.values.size(); int nval = p.second.values.size();
out.write((const char *) &nval, sizeof(nval)); out.write((const char *) &nval, sizeof(nval));
if (nval > 0) out.write((const char *) p.second.values.data(), nval * sizeof(float)); if (nval > 0) {
std::vector<float> tmp(nval);
for (int i = 0; i < nval; i++) {
tmp[i] = (p.second.values[i] / static_cast<float>(p.second.counts[i])) * static_cast<float>(p.second.ncall);
}
out.write((const char*)tmp.data(), nval*sizeof(float));
}
} }
// Write the number of call the matrix was computed with // Write the number of call the matrix was computed with
@ -270,14 +278,28 @@ bool IMatrixCollector::load_imatrix(const char * imatrix_file, std::unordered_ma
imatrix_data = {}; imatrix_data = {};
return false; return false;
} }
e.values.resize(nval);
in.read((char*)e.values.data(), nval*sizeof(float)); // When re-called from load_imatrix() with add set, this will already be created.
if (e.values.empty()) {
e.values.resize(nval, 0);
e.counts.resize(nval, 0);
}
std::vector<float> tmp(nval);
in.read((char*)tmp.data(), nval*sizeof(float));
if (in.fail()) { if (in.fail()) {
printf("%s: failed reading data for entry %d\n",__func__,i); printf("%s: failed reading data for entry %d\n",__func__,i);
imatrix_data = {}; imatrix_data = {};
return false; return false;
} }
e.ncall = ncall;
// Recreate the state as expected by save_imatrix(), and corerct for weighted sum.
for (int i = 0; i < nval; i++) {
e.values[i] += tmp[i];
e.counts[i] += ncall;
}
e.ncall += ncall;
} }
return true; return true;
} }