Function handcrafted_check_tensor_data

smallthinker/tests/test-gguf.cpp:623–660

}

static bool handcrafted_check_tensor_data(const gguf_context * gguf_ctx, const unsigned int seed, FILE * file) {
    if (!gguf_ctx) {
        return false;
    }

    std::mt19937 rng(seed);

    std::vector<tensor_config_t> tensor_configs = get_tensor_configs(rng);

    bool ok = true;

    for (int i = 0; i < int(tensor_configs.size()); ++i) {
        const ggml_type                          type  = tensor_configs[i].first;
        const std::array<int64_t, GGML_MAX_DIMS> shape = tensor_configs[i].second;

        int64_t ne = shape[0];
        for (size_t j = 1; j < GGML_MAX_DIMS; ++j) {
            ne *= shape[j];
        }
        const size_t size = ggml_row_size(type, ne);

        const std::string name = "my_tensor_" + std::to_string(i);
        const size_t offset = gguf_get_tensor_offset(gguf_ctx, gguf_find_tensor(gguf_ctx, name.c_str()));

        std::vector<uint8_t> data(size);
        GGML_ASSERT(fseek(file, gguf_get_data_offset(gguf_ctx) + offset, SEEK_SET) == 0);
        GGML_ASSERT(fread(data.data(), 1, data.size(), file) == data.size());

        for (size_t j = 0; j < size; ++j) {
            const uint8_t expected_byte = (j + offset) % 256;
            if (data[j] != expected_byte) {
                ok = false;
            }
        }
    }

    return ok;
}

static std::pair<int, int> test_handcrafted_file(const unsigned int seed) {
    int npass = 0;