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imatrix : warn when writing partial data, to help guess dataset coverage

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Also make the legacy format store partial data
by using neutral values for missing data.
This matches what is done at read-time for the new format,
and so should get the same quality in case the old format is still used.
This commit is contained in:
Francis Couture-Harpin
2025-07-12 14:09:28 -04:00
parent 42423ec4d3
commit 50f53b3e40
1 changed files with 31 additions and 6 deletions
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37
tools/imatrix/imatrix.cpp
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@@ -254,7 +254,7 @@ void IMatrixCollector::save_imatrix_legacy(int32_t ncall) const {
fname += std::to_string(ncall);
}
// avoid writing imatrix entries that do not have full data
// warn when writing imatrix entries that do not have full data
// this can happen with MoE models where some of the experts end up not being exercised by the provided training data
int n_entries = 0;
@@ -286,8 +286,7 @@ void IMatrixCollector::save_imatrix_legacy(int32_t ncall) const {
}
if (n_zeros > 0) {
LOG_WRN("%s: entry '%40s' has partial data (%.2f%%) - skipping\n", __func__, kv.first.c_str(), 100.0f * (n_all - n_zeros) / n_all);
continue;
LOG_WRN("%s: entry '%40s' has partial data (%.2f%%)\n", __func__, kv.first.c_str(), 100.0f * (n_all - n_zeros) / n_all);
}
n_entries++;
@@ -310,7 +309,8 @@ void IMatrixCollector::save_imatrix_legacy(int32_t ncall) const {
const int32_t len = name.size();
out.write((const char *) &len, sizeof(len));
out.write(name.c_str(), len);
const int32_t ncall = *std::max_element(stat.counts.begin(), stat.counts.end()) / chunk_size;
// ceiling division to avoid accidental zeros
const int32_t ncall = (*std::max_element(stat.counts.begin(), stat.counts.end()) + (chunk_size - 1)) / chunk_size;
out.write((const char *) &ncall, sizeof(ncall));
const int32_t nval = stat.values.size();
const int32_t nmat = stat.counts.size();
@@ -318,8 +318,14 @@ void IMatrixCollector::save_imatrix_legacy(int32_t ncall) const {
if (nval > 0 && nmat > 0) {
std::vector<float> tmp(nval);
for (int32_t i = 0; i < nval; i++) {
const float counts = static_cast<float>(stat.counts[i / (nval / nmat)]);
tmp[i] = (stat.values[i] / counts) * static_cast<float>(ncall);
float count = static_cast<float>(stat.counts[i / (nval / nmat)]);
float value = stat.values[i];
if (count == 0.0f) {
// store 1 for partial data
value = 1.0f;
count = 1.0f;
}
tmp[i] = (value / count) * static_cast<float>(ncall);
}
out.write((const char *) tmp.data(), nval * sizeof(float));
}
@@ -367,7 +373,26 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const {
std::vector<std::string> to_store;
size_t data_size = 0;
bool is_first = true; // for printing
for (const auto & kv : m_stats) {
const int n_all = kv.second.counts.size();
int n_zeros = 0;
for (const auto c : kv.second.counts) {
if (c == 0) {
n_zeros++;
}
}
if (n_zeros != 0 && is_first) {
LOG_INF("\n");
is_first = false;
}
if (n_zeros > 0) {
LOG_WRN("%s: entry '%40s' has partial data (%.2f%%)\n", __func__, kv.first.c_str(), 100.0f * (n_all - n_zeros) / n_all);
}
to_store.push_back(kv.first);
data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.values.size(), GGML_MEM_ALIGN);
data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.counts.size(), GGML_MEM_ALIGN);