char-fork/llama.cpp

git clone https://git.t4t.associates/char-fork/llama.cpp

Xuan-Son Nguyenfix: check gguf array type before reading (#27075)27df9199d2026-08-15

#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_kv_type(ctx_gguf, datasets_key) == GGUF_TYPE_ARRAY &&
        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;
        }

        if (in_sum2->type != GGML_TYPE_F32 || counts->type != GGML_TYPE_F32) {
            LOG_ERR("%s: sums and counts for %s must be F32\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;
}