Method get_n_kv

subprojects/llama.cpp/src/llama-kv-cache.cpp:1000–1014

}

uint32_t llama_kv_cache::get_n_kv(const slot_info & sinfo) const {
    uint32_t result = 0;

    // pad the n_kv value so that the graph remains constant across batches and can be reused
    // note: this also helps some backends with performance (f.ex https://github.com/ggml-org/llama.cpp/pull/16812#issuecomment-3455112220)
    const uint32_t n_pad_cur = std::max(n_pad, 256u);

    for (uint32_t s = 0; s < sinfo.n_stream(); ++s) {
        const auto & cells = v_cells[sinfo.strm[s]];

        result = std::max(std::min(cells.size(), std::max(n_pad_cur, GGML_PAD(cells.used_max_p1(), n_pad_cur))), result);
    }

    return result;
}

ggml_tensor * llama_kv_cache::get_k(ggml_context * ctx, int32_t il, uint32_t n_kv, const slot_info & sinfo) const {
    const int32_t ikv = map_layer_ids.at(il);