Felipe97/llama-cpp-compiled

1#pragma once2 3#include "llama.h"4 5#include "ggml-cpp.h"6 7#include <string>8#include <unordered_map>9#include <vector>10 11// TODO: pimpl12 13//14// llama_adapter_cvec15//16 17struct llama_adapter_cvec {18    ggml_tensor * tensor_for(int il) const;19 20    ggml_tensor * apply_to(ggml_context * ctx, ggml_tensor * cur, int  il) const;21 22    bool apply(23            const llama_model & model,24            const float * data,25            size_t len,26            int32_t n_embd,27            int32_t il_start,28            int32_t il_end);29 30private:31    bool init(const llama_model & model);32 33    int32_t layer_start = -1;34    int32_t layer_end   = -1;35 36    std::vector<ggml_context_ptr> ctxs;37    std::vector<ggml_backend_buffer_ptr> bufs;38 39    std::vector<ggml_tensor *> tensors; // per layer40};41 42using llama_adapter_cvec_ptr = std::shared_ptr<llama_adapter_cvec>;43 44//45// llama_adapter_lora46//47 48struct llama_adapter_lora_weight {49    ggml_tensor * a = nullptr;50    ggml_tensor * b = nullptr;51 52    // get actual scale based on rank and alpha53    float get_scale(float alpha, float adapter_scale) const {54        const float rank  = (float) b->ne[0];55        const float scale = alpha ? adapter_scale * alpha / rank : adapter_scale;56        return scale;57    }58 59    llama_adapter_lora_weight() = default;60    llama_adapter_lora_weight(ggml_tensor * a, ggml_tensor * b) : a(a), b(b) {}61};62 63struct llama_adapter_lora {64    llama_model * model = nullptr;65 66    // map tensor name to lora_a_b67    std::unordered_map<std::string, llama_adapter_lora_weight> ab_map;68 69    std::vector<ggml_context_ptr> ctxs;70    std::vector<ggml_backend_buffer_ptr> bufs;71 72    float alpha;73 74    // gguf metadata75    std::unordered_map<std::string, std::string> gguf_kv;76 77    // activated lora (aLoRA)78    std::vector<llama_token> alora_invocation_tokens;79 80    explicit llama_adapter_lora(llama_model * model) : model(model) {}81    ~llama_adapter_lora() = default;82 83    llama_adapter_lora_weight * get_weight(ggml_tensor * w);84 85    uint32_t get_n_nodes() const {86        return ab_map.size() * 6u; // a, b, scale, add, 2 x mul_mat87    }88};89 90using llama_adapter_loras = std::unordered_map<llama_adapter_lora *, float>;91using llama_adapter_loras_ptr = std::unique_ptr<llama_adapter_loras>;92