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Move duplicated imatrix code into single common imatrix-loader.cpp (#22445)

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* Deduplicate imatrix loading code

* Add back LLAMA_TRACE, early exit on quantize missing metadata
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Bartowski 2026-06-04 11:45:40 -04:00 committed by GitHub
parent 21444c822e
commit e7bcf1c3a8
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GPG Key ID: B5690EEEBB952194
5 changed files with 303 additions and 359 deletions
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2
common/CMakeLists.txt
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@ -78,6 +78,8 @@ add_library(${TARGET}
hf-cache.cpp
hf-cache.h
http.h
imatrix-loader.cpp
imatrix-loader.h
json-partial.cpp
json-partial.h
json-schema-to-grammar.cpp

165
common/imatrix-loader.cpp Normal file
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@ -0,0 +1,165 @@
#include "imatrix-loader.h"
#include "common.h"
#include "log.h"
#include "gguf.h"
#include <cmath>
#include <cstring>
#include <fstream>
static bool common_imatrix_load_legacy(const std::string & fname, common_imatrix & imatrix) {
std::ifstream in(fname, std::ios::binary);
if (!in) {
LOG_ERR("%s: failed to open %s\n", __func__, fname.c_str());
return false;
}
int n_entries;
in.read((char *) &n_entries, sizeof(n_entries));
if (in.fail() || n_entries < 1) {
LOG_ERR("%s: no data in file %s\n", __func__, fname.c_str());
return false;
}
for (int i = 0; i < n_entries; ++i) {
int32_t len = 0;
in.read((char *) &len, sizeof(len));
std::vector<char> name_as_vec(len + 1);
in.read((char *) name_as_vec.data(), len);
if (in.fail()) {
LOG_ERR("%s: failed reading name for entry %d from %s\n", __func__, i + 1, fname.c_str());
return false;
}
name_as_vec[len] = 0;
std::string name{ name_as_vec.data() };
int32_t ncall = 0;
in.read((char *) &ncall, sizeof(ncall));
int32_t nval = 0;
in.read((char *) &nval, sizeof(nval));
if (in.fail() || nval < 1) {
LOG_ERR("%s: failed reading number of values for entry %d\n", __func__, i);
return false;
}
auto & e = imatrix.entries[std::move(name)];
e.sums.resize(nval);
in.read((char *) e.sums.data(), nval * sizeof(float));
if (in.fail()) {
LOG_ERR("%s: failed reading data for entry %d\n", __func__, i);
return false;
}
e.counts.resize(1);
e.counts[0] = ncall;
}
// the trailing data (chunk count + dataset name) is optional
if (in.peek() != EOF) {
int32_t n_calls = 0;
in.read((char *) &n_calls, sizeof(n_calls));
imatrix.chunk_count = n_calls;
if (!in.fail()) {
int32_t len = 0;
in.read((char *) &len, sizeof(len));
if (!in.fail() && len > 0) {
std::vector<char> dataset(len + 1, 0);
in.read(dataset.data(), len);
if (!in.fail()) {
imatrix.datasets.push_back(dataset.data());
}
}
}
}
imatrix.chunk_size = 0;
imatrix.is_legacy = true;
return true;
}
bool common_imatrix_load(const std::string & fname, common_imatrix & imatrix) {
struct ggml_context * ctx = nullptr;
struct gguf_init_params meta_gguf_params = {
/* .no_alloc = */ false,
/* .ctx = */ &ctx,
};
struct gguf_context * ctx_gguf = gguf_init_from_file(fname.c_str(), meta_gguf_params);
if (!ctx_gguf) {
return common_imatrix_load_legacy(fname, imatrix);
}
const int32_t n_entries = gguf_get_n_tensors(ctx_gguf);
if (n_entries < 1) {
LOG_ERR("%s: no data in file %s\n", __func__, fname.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
return false;
}
const int64_t datasets_key = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASETS);
const int64_t chunk_count_key = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT);
const int64_t chunk_size_key = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE);
if (datasets_key != -1 && gguf_get_arr_type(ctx_gguf, datasets_key) == GGUF_TYPE_STRING) {
const int64_t n = gguf_get_arr_n(ctx_gguf, datasets_key);
imatrix.datasets.reserve(imatrix.datasets.size() + n);
for (int64_t i = 0; i < n; ++i) {
imatrix.datasets.push_back(gguf_get_arr_str(ctx_gguf, datasets_key, i));
}
}
imatrix.has_metadata = (datasets_key != -1 && chunk_count_key != -1 && chunk_size_key != -1);
imatrix.chunk_count = (chunk_count_key != -1) ? gguf_get_val_u32(ctx_gguf, chunk_count_key) : 0;
imatrix.chunk_size = (chunk_size_key != -1) ? gguf_get_val_u32(ctx_gguf, chunk_size_key) : 0;
const std::string in_sum2_suffix{ ".in_sum2" };
const std::string counts_suffix{ ".counts" };
std::map<std::string, std::pair<struct ggml_tensor *, struct ggml_tensor *>> sums_counts_for;
for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) {
std::string name = cur->name;
if (name.empty()) { continue; }
if (string_remove_suffix(name, in_sum2_suffix)) {
sums_counts_for[std::move(name)].first = cur;
} else if (string_remove_suffix(name, counts_suffix)) {
sums_counts_for[std::move(name)].second = cur;
}
}
for (const auto & sc : sums_counts_for) {
const std::string & name = sc.first;
const struct ggml_tensor * in_sum2 = sc.second.first;
const struct ggml_tensor * counts = sc.second.second;
if (!in_sum2 || !counts) {
LOG_ERR("%s: mismatched sums and counts for %s\n", __func__, name.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
return false;
}
auto & e = imatrix.entries[name];
const int64_t nval = ggml_nelements(in_sum2);
const int64_t ncounts = ggml_nelements(counts);
e.sums.resize(nval);
for (int64_t j = 0; j < nval; ++j) {
e.sums[j] = ((const float *) in_sum2->data)[j];
}
e.counts.resize(ncounts);
for (int64_t j = 0; j < ncounts; ++j) {
e.counts[j] = std::lround(((const float *) counts->data)[j]);
}
}
gguf_free(ctx_gguf);
ggml_free(ctx);
return true;
}

26
common/imatrix-loader.h Normal file
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@ -0,0 +1,26 @@
#pragma once
#include <cstdint>
#include <map>
#include <string>
#include <vector>
inline constexpr const char * LLM_KV_IMATRIX_DATASETS = "imatrix.datasets";
inline constexpr const char * LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count";
inline constexpr const char * LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size";
struct common_imatrix_entry {
std::vector<float> sums;
std::vector<int64_t> counts;
};
struct common_imatrix {
std::map<std::string, common_imatrix_entry> entries;
std::vector<std::string> datasets;
int32_t chunk_count = 0;
int32_t chunk_size = 0;
bool is_legacy = false;
bool has_metadata = false;
};
bool common_imatrix_load(const std::string & fname, common_imatrix & imatrix);

214
tools/imatrix/imatrix.cpp
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@ -1,5 +1,6 @@
#include "arg.h"
#include "common.h"
#include "imatrix-loader.h"
#include "log.h"
#include "llama.h"
#include "gguf.h"
@ -34,10 +35,6 @@ static void print_usage(int, char ** argv) {
LOG("\n");
}
static const char * const LLM_KV_IMATRIX_DATASETS = "imatrix.datasets";
static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count";
static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size";
struct Stats {
std::vector<float> values;
std::vector<int64_t> counts;
@ -65,7 +62,6 @@ public:
bool collect_imatrix(struct ggml_tensor * t, bool ask, void * user_data);
void save_imatrix_legacy(int32_t ncall = -1) const;
void save_imatrix(int32_t n_chunk = -1) const;
bool load_imatrix_legacy(const char * fname);
bool load_imatrix(const char * file_name);
const std::unordered_map<std::string, Stats> & get_mstats() const { return m_stats; }
private:
@ -624,204 +620,63 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const {
ggml_free(ctx);
}
bool IMatrixCollector::load_imatrix_legacy(const char * fname) {
std::ifstream in(fname, std::ios::binary);
if (!in) {
LOG_ERR("%s: failed to open %s\n", __func__, fname);
return false;
}
int n_entries;
in.read((char *) &n_entries, sizeof(n_entries));
if (in.fail() || n_entries < 1) {
LOG_ERR("%s: no data in file %s\n", __func__, fname);
return false;
}
// Guess the chunk size because it's not stored in the file
const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel;
for (int i = 0; i < n_entries; ++i) {
int32_t len = 0;
in.read((char *) &len, sizeof(len));
std::vector<char> name_as_vec(len + 1);
in.read((char *) name_as_vec.data(), len);
if (in.fail()) {
LOG_ERR("%s: failed reading name for entry %d from %s\n", __func__, i + 1, fname);
return false;
}
name_as_vec[len] = 0;
std::string name{ name_as_vec.data() };
auto & e = m_stats[std::move(name)];
int32_t ncall = 0;
in.read((char *) &ncall, sizeof(ncall));
int32_t nval = 0;
in.read((char *) &nval, sizeof(nval));
if (in.fail() || nval < 1) {
LOG_ERR("%s: failed reading number of values for entry %d\n", __func__, i);
m_stats = {};
return false;
}
if (e.values.empty()) {
e.values.resize(nval, 0.0f);
e.counts.resize(1, 0);
}
std::vector<float> tmp(nval);
in.read((char *) tmp.data(), nval * sizeof(float));
if (in.fail()) {
LOG_ERR("%s: failed reading data for entry %d\n", __func__, i);
m_stats = {};
return false;
}
// Recreate the state as expected by save_imatrix(), and correct for weighted sum.
for (int i = 0; i < nval; i++) {
e.values[i] += tmp[i] * chunk_size;
}
// The legacy format doesn't distinguish the counts for different experts
for (size_t j = 0; j < e.counts.size(); ++j) {
e.counts[j] += ncall * chunk_size;
}
}
{
// TODO: extract into its own method; this is also used by the GGUF-based format
// Calculate the last chunk count
int64_t max_count = 0;
for (const auto & stats : m_stats) {
for (int64_t count : stats.second.counts) {
if (count > max_count) {
max_count = count;
}
}
}
m_last_chunk = max_count / (chunk_size);
}
{
// Read the number of calls the matrix was computed with
int32_t n_calls;
in.read((char *) &n_calls, sizeof(n_calls));
// ignore it because it's not important
}
// Read the dataset path to include it when writing to GGUF
if (!in.fail()){
int32_t len = 0;
in.read((char *) &len, sizeof(len));
if (!in.fail()) {
std::vector<char> dataset;
dataset.resize(len + 1, 0);
in.read(dataset.data(), len);
if (!in.fail()) {
m_datasets.push_back(dataset.data());
}
}
}
return true;
}
// Using GGUF as the file format, for greater extensibility
bool IMatrixCollector::load_imatrix(const char * file_name) {
struct ggml_context * ctx = nullptr;
struct gguf_init_params meta_gguf_params = {
/* .no_alloc = */ false, // the data is needed
/* .ctx = */ &ctx,
};
struct gguf_context * ctx_gguf = gguf_init_from_file(file_name, meta_gguf_params);
if (!ctx_gguf) {
return this->load_imatrix_legacy(file_name);
}
const int32_t n_entries = gguf_get_n_tensors(ctx_gguf);
if (n_entries < 1) {
LOG_ERR("%s: no data in file %s\n", __func__, file_name);
gguf_free(ctx_gguf);
ggml_free(ctx);
common_imatrix loaded;
if (!common_imatrix_load(file_name, loaded)) {
return false;
}
const int64_t datasets_key = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASETS);
if (datasets_key != -1 && gguf_get_arr_type(ctx_gguf, datasets_key) == GGUF_TYPE_STRING) {
const int64_t n = gguf_get_arr_n(ctx_gguf, datasets_key);
m_datasets.reserve(m_datasets.size() + n);
for (int64_t i = 0; i < n; ++i) {
m_datasets.push_back(gguf_get_arr_str(ctx_gguf, datasets_key, i));
}
}
const std::string in_sum2_suffix{ ".in_sum2" };
const std::string counts_suffix{ ".counts" };
// Could re-use m_stats instead, but this allows
// checking for completeness of *each* loaded imatrix file
// and also makes it easier to re-use a similar implementation in quantize.cpp
// Using an ordered map to get a deterministic iteration order.
std::map<std::string, std::pair<struct ggml_tensor *, struct ggml_tensor *>> sums_counts_for;
for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) {
std::string name = cur->name;
if (name.empty()) { continue; }
if (string_remove_suffix(name, in_sum2_suffix)) {
// in_sum2
sums_counts_for[std::move(name)].first = cur;
} else if (string_remove_suffix(name, counts_suffix)) {
// counts
sums_counts_for[std::move(name)].second = cur;
} else {
// ignore other tensors
}
}
for (const auto & sc : sums_counts_for) {
const std::string & name = sc.first;
const struct ggml_tensor * in_sum2 = sc.second.first;
const struct ggml_tensor * counts = sc.second.second;
if (!in_sum2 || !counts) {
LOG_ERR("%s: mismatched sums and counts for %s\n", __func__, name.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
return false;
}
const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel;
const bool is_legacy = loaded.is_legacy;
for (auto & [name, entry] : loaded.entries) {
auto & e = m_stats[name];
int64_t nval = ggml_nelements(in_sum2);
if (is_legacy) {
// Legacy format: sums contain (raw_sum/raw_count)*ncall, counts contain {ncall}
// Reconstruct raw form by multiplying by chunk_size
if (e.values.empty()) {
e.values.resize(entry.sums.size(), 0.0f);
e.counts.resize(1, 0);
}
for (size_t j = 0; j < entry.sums.size(); ++j) {
e.values[j] += entry.sums[j] * chunk_size;
}
for (size_t j = 0; j < e.counts.size(); ++j) {
e.counts[j] += entry.counts[0] * chunk_size;
}
} else {
// GGUF format: raw sums and counts, accumulate directly
const int64_t nval = entry.sums.size();
const int64_t ncounts = entry.counts.size();
if (e.values.empty()) {
e.values.resize(nval, 0.0f);
} else if ((size_t) nval != e.values.size()) {
LOG_ERR("%s: mismatched sums size for %s: %zu != %zu\n", __func__, name.c_str(), (size_t) nval, e.values.size());
gguf_free(ctx_gguf);
ggml_free(ctx);
return false;
}
int64_t ncounts = ggml_nelements(counts);
if (e.counts.empty()) {
e.counts.resize(ncounts, 0);
} else if (e.counts.size() == 1 && ncounts > 1) {
// broadcast, when loading an old imatrix
e.counts.resize(ncounts, e.counts[0]);
} else if ((size_t) ncounts != e.counts.size()) {
LOG_ERR("%s: mismatched counts size for %s: %zu != %zu\n", __func__, name.c_str(), (size_t) ncounts, e.counts.size());
gguf_free(ctx_gguf);
ggml_free(ctx);
return false;
}
// Recreate the state as expected by save_imatrix()
for (int64_t j = 0; j < nval; j++) {
e.values[j] += ((const float *) in_sum2->data)[j];
for (int64_t j = 0; j < nval; ++j) {
e.values[j] += entry.sums[j];
}
for (int64_t j = 0; j < ncounts; ++j) {
e.counts[j] += entry.counts[j];
}
for (int64_t j = 0; j < ncounts; j++) {
e.counts[j] += std::lround(((const float *) counts->data)[j]);
}
}
// TODO: extract into its own method; this is also used by the legacy format
m_datasets.insert(m_datasets.end(), loaded.datasets.begin(), loaded.datasets.end());
// Calculate the last chunk count
int64_t max_count = 0;
for (const auto & stats : m_stats) {
@ -831,10 +686,8 @@ bool IMatrixCollector::load_imatrix(const char * file_name) {
}
}
}
m_last_chunk = max_count / (m_params.n_ctx / m_params.n_parallel);
m_last_chunk = max_count / chunk_size;
gguf_free(ctx_gguf);
ggml_free(ctx);
return true;
}
@ -1218,6 +1071,9 @@ int main(int argc, char ** argv) {
return 1;
}
// set_params before show_statistics so load_imatrix has valid n_ctx/n_parallel
g_collector.set_params(params);
if (params.show_statistics) {
if (!show_statistics(params)) {
return 1;

197
tools/quantize/quantize.cpp
View File

@ -2,6 +2,7 @@
#include "build-info.h"
#include "common.h"
#include "imatrix-loader.h"
#include "gguf.h"
@ -14,7 +15,6 @@
#include <vector>
#include <string>
#include <unordered_map>
#include <map>
#include <fstream>
#include <filesystem>
@ -78,11 +78,6 @@ static const char * const LLM_KV_QUANTIZE_IMATRIX_DATASET = "quantize.imatrix
static const char * const LLM_KV_QUANTIZE_IMATRIX_N_ENTRIES = "quantize.imatrix.entries_count";
static const char * const LLM_KV_QUANTIZE_IMATRIX_N_CHUNKS = "quantize.imatrix.chunks_count";
// TODO: share with imatrix.cpp
static const char * const LLM_KV_IMATRIX_DATASETS = "imatrix.datasets";
static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count";
static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size";
static bool striequals(const char * a, const char * b) {
while (*a && *b) {
if (std::tolower(*a) != std::tolower(*b)) {
@ -181,184 +176,84 @@ static void usage(const char * executable) {
exit(1);
}
static int load_legacy_imatrix(const std::string & imatrix_file, std::vector<std::string> & imatrix_datasets, std::unordered_map<std::string, std::vector<float>> & imatrix_data) {
std::ifstream in(imatrix_file.c_str(), std::ios::binary);
if (!in) {
printf("%s: failed to open %s\n",__func__, imatrix_file.c_str());
exit(1);
}
int n_entries;
in.read((char *)&n_entries, sizeof(n_entries));
if (in.fail() || n_entries < 1) {
printf("%s: no data in file %s\n", __func__, imatrix_file.c_str());
exit(1);
}
for (int i = 0; i < n_entries; ++i) {
int len; in.read((char *)&len, sizeof(len));
std::vector<char> name_as_vec(len+1);
in.read((char *)name_as_vec.data(), len);
if (in.fail()) {
printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str());
exit(1);
}
name_as_vec[len] = 0;
std::string name{name_as_vec.data()};
auto & e = imatrix_data[name];
int ncall;
in.read((char *)&ncall, sizeof(ncall));
int nval;
in.read((char *)&nval, sizeof(nval));
if (in.fail() || nval < 1) {
printf("%s: failed reading number of values for entry %d\n", __func__, i);
imatrix_data = {};
exit(1);
}
e.resize(nval);
in.read((char *)e.data(), nval*sizeof(float));
if (in.fail()) {
printf("%s: failed reading data for entry %d\n", __func__, i);
imatrix_data = {};
exit(1);
}
if (ncall > 0) {
for (auto & v : e) {
v /= ncall;
}
}
if (getenv("LLAMA_TRACE")) {
printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), ncall, name.c_str());
}
}
// latest legacy imatrix version contains the dataset filename at the end of the file
int m_last_call = 0;
if (in.peek() != EOF) {
in.read((char *)&m_last_call, sizeof(m_last_call));
int dataset_len;
in.read((char *)&dataset_len, sizeof(dataset_len));
std::vector<char> dataset_as_vec(dataset_len);
in.read(dataset_as_vec.data(), dataset_len);
imatrix_datasets.resize(1);
imatrix_datasets[0].assign(dataset_as_vec.begin(), dataset_as_vec.end());
printf("%s: imatrix dataset='%s'\n", __func__, imatrix_datasets[0].c_str());
}
printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_call);
return m_last_call;
}
static int load_imatrix(const std::string & imatrix_file, std::vector<std::string> & imatrix_datasets, std::unordered_map<std::string, std::vector<float>> & imatrix_data) {
struct ggml_context * ctx = nullptr;
struct gguf_init_params meta_gguf_params = {
/* .no_alloc = */ false, // the data is needed
/* .ctx = */ &ctx,
};
struct gguf_context * ctx_gguf = gguf_init_from_file(imatrix_file.c_str(), meta_gguf_params);
if (!ctx_gguf) {
fprintf(stderr, "%s: imatrix file '%s' is using old format\n", __func__, imatrix_file.c_str());
return load_legacy_imatrix(imatrix_file, imatrix_datasets, imatrix_data);
}
const int32_t n_entries = gguf_get_n_tensors(ctx_gguf);
if (n_entries < 1) {
fprintf(stderr, "%s: no data in file %s\n", __func__, imatrix_file.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
common_imatrix loaded;
if (!common_imatrix_load(imatrix_file, loaded)) {
fprintf(stderr, "%s: failed to load imatrix from '%s'\n", __func__, imatrix_file.c_str());
exit(1);
}
const int dataset_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASETS);
const int chunk_count_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT);
const int chunk_size_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE);
if (dataset_idx < 0 || chunk_count_idx < 0 || chunk_size_idx < 0) {
if (!loaded.is_legacy && !loaded.has_metadata) {
fprintf(stderr, "%s: missing imatrix metadata in file %s\n", __func__, imatrix_file.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
exit(1);
}
const uint32_t chunk_size = gguf_get_val_u32(ctx_gguf, chunk_size_idx);
const std::string sums_suffix{ ".in_sum2" };
const std::string counts_suffix{ ".counts" };
// Using an ordered map to get a deterministic iteration order.
std::map<std::string, std::pair<struct ggml_tensor *, struct ggml_tensor *>> sums_counts_for;
for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) {
std::string name = cur->name;
if (name.empty()) { continue; }
if (string_remove_suffix(name, sums_suffix)) {
// in_sum2
sums_counts_for[std::move(name)].first = cur;
} else if (string_remove_suffix(name, counts_suffix)) {
// counts
sums_counts_for[std::move(name)].second = cur;
} else {
// ignore other tensors
}
}
for (const auto & sc : sums_counts_for) {
const std::string & name = sc.first;
const struct ggml_tensor * sums = sc.second.first;
const struct ggml_tensor * counts = sc.second.second;
if (!sums || !counts) {
fprintf(stderr, "%s: mismatched sums and counts for %s\n", __func__, name.c_str());
gguf_free(ctx_gguf);
ggml_free(ctx);
exit(1);
}
const int64_t ne0 = sums->ne[0];
const int64_t ne1 = sums->ne[1];
for (const auto & [name, entry] : loaded.entries) {
auto & e = imatrix_data[name];
e.resize(ggml_nelements(sums));
float max_count = 0.0f;
for (int64_t j = 0; j < ne1; ++j) {
const float count = ((const float *) counts->data)[j];
e.resize(entry.sums.size());
if (!loaded.is_legacy) {
// GGUF format: normalize by per-expert counts
const int64_t ncounts = entry.counts.size();
const int64_t ne0 = (int64_t) entry.sums.size() / ncounts;
for (int64_t j = 0; j < ncounts; ++j) {
const float count = (float) entry.counts[j];
if (count > 0.0f) {
for (int64_t i = 0; i < ne0; ++i) {
e[j*ne0 + i] = ((const float *) sums->data)[j*ne0 + i] / count;
e[j*ne0 + i] = entry.sums[j*ne0 + i] / count;
}
} else {
// Partial imatrix data, this tensor never got any input during calibration
for (int64_t i = 0; i < ne0; ++i) {
e[j*ne0 + i] = 1;
}
}
}
if (getenv("LLAMA_TRACE")) {
float max_count = 0.0f;
for (int64_t j = 0; j < ncounts; ++j) {
const float count = (float) entry.counts[j];
if (count > max_count) {
max_count = count;
}
}
printf("%s: loaded data (size = %6d, n_tokens = %6d, n_chunks = %6d) for '%s'\n",
__func__, int(e.size()), int(max_count), int(max_count / loaded.chunk_size), name.c_str());
}
} else {
// Legacy format: sums contain (raw/count)*ncall, divide by ncall
const int64_t ncall = entry.counts.empty() ? 0 : entry.counts[0];
if (ncall > 0) {
for (size_t i = 0; i < entry.sums.size(); ++i) {
e[i] = entry.sums[i] / ncall;
}
} else {
for (size_t i = 0; i < entry.sums.size(); ++i) {
e[i] = entry.sums[i];
}
}
if (getenv("LLAMA_TRACE")) {
printf("%s: loaded data (size = %6d, n_tokens = %6d, n_chunks = %6d) for '%s'\n", __func__, int(e.size()), int(max_count), int(max_count / chunk_size), name.c_str());
printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n",
__func__, int(e.size()), int(ncall), name.c_str());
}
}
}
int m_last_chunk = gguf_get_val_u32(ctx_gguf, chunk_count_idx);
imatrix_datasets = std::move(loaded.datasets);
int64_t n_datasets = gguf_get_arr_n(ctx_gguf, dataset_idx);
imatrix_datasets.reserve(n_datasets);
for (int64_t i = 0; i < n_datasets; ++i) {
imatrix_datasets.push_back(gguf_get_arr_str(ctx_gguf, dataset_idx, i));
}
if (!imatrix_datasets.empty()) {
printf("%s: imatrix datasets=['%s'", __func__, imatrix_datasets[0].c_str());
for (size_t i = 1; i < imatrix_datasets.size(); ++i) {
printf(", '%s'", imatrix_datasets[i].c_str());
}
printf("]\n");
}
printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_chunk);
printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), loaded.chunk_count);
gguf_free(ctx_gguf);
ggml_free(ctx);
return m_last_chunk;
return loaded.chunk_count;
}
static int prepare_imatrix(const std::string & imatrix_file,