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
--- /dev/null
+#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;
+}
--- /dev/null
+#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);
#include "arg.h"
#include "common.h"
+#include "imatrix-loader.h"
#include "log.h"
#include "llama.h"
#include "gguf.h"
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;
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:
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);
+bool IMatrixCollector::load_imatrix(const char * file_name) {
+ common_imatrix loaded;
+ if (!common_imatrix_load(file_name, loaded)) {
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;
- }
+ const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel;
+ const bool is_legacy = loaded.is_legacy;
- // 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;
- }
- }
+ for (auto & [name, entry] : loaded.entries) {
+ auto & e = m_stats[name];
- {
- // 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;
- }
+ 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);
}
- }
- 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());
+ 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;
}
- }
- }
-
- 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);
- 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;
- }
-
- auto & e = m_stats[name];
-
- int64_t nval = ggml_nelements(in_sum2);
- 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;
- }
+ // 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());
+ 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;
- }
+ if (e.counts.empty()) {
+ e.counts.resize(ncounts, 0);
+ } else if (e.counts.size() == 1 && ncounts > 1) {
+ 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());
+ 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 < ncounts; j++) {
- e.counts[j] += std::lround(((const float *) counts->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];
+ }
}
}
- // 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) {
}
}
}
- 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;
}
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;
#include "build-info.h"
#include "common.h"
+#include "imatrix-loader.h"
#include "gguf.h"
#include <vector>
#include <string>
#include <unordered_map>
-#include <map>
#include <fstream>
#include <filesystem>
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)) {
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; }
+ for (const auto & [name, entry] : loaded.entries) {
+ auto & e = imatrix_data[name];
+ 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] = entry.sums[j*ne0 + i] / count;
+ }
+ } else {
+ for (int64_t i = 0; i < ne0; ++i) {
+ e[j*ne0 + i] = 1;
+ }
+ }
+ }
- 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;
+ 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 {
- // 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];
-
- 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];
- if (count > 0.0f) {
- for (int64_t i = 0; i < ne0; ++i) {
- e[j*ne0 + i] = ((const float *) sums->data)[j*ne0 + i] / count;
+ // 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 {
- // Partial imatrix data, this tensor never got any input during calibration
- for (int64_t i = 0; i < ne0; ++i) {
- e[j*ne0 + i] = 1;
+ for (size_t i = 0; i < entry.sums.size(); ++i) {
+ e[i] = entry.sums[i];
}
}
- if (count > max_count) {
- max_count = count;
+
+ if (getenv("LLAMA_TRACE")) {
+ printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n",
+ __func__, int(e.size()), int(ncall), name.c_str());
}
}
- 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());
- }
}
- 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));
- }
- 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());
+ 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("]\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);
- gguf_free(ctx_gguf);
- ggml_free(ctx);
+ 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);
- return m_last_chunk;
+ return loaded.chunk_count;
}
static int prepare_imatrix(const std::string & imatrix_file,
overview / pkg / ggml / sources / llama.cpp / commitdiff