llama-adapter.h

/**
 * llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
 *
 * MIT License
 *
 * Copyright (c) 2023-2024 The ggml authors
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */

#pragma once

#include "llama-impl.h"
#include "llama-hparams.h"

#include "ggml-cpp.h"

#include <unordered_map>
#include <vector>

//
// llama_adapter_cvec
//

// TODO: rename to llama_adapter_cvec
struct llama_control_vector {
    std::vector<ggml_context_ptr> ctxs;
    std::vector<ggml_backend_buffer_ptr> bufs;

    std::vector<struct ggml_tensor *> tensors; // per layer

    int32_t layer_start = -1;
    int32_t layer_end   = -1;

    struct ggml_tensor * tensor_for(int il) const;

    struct ggml_tensor * apply_to(struct ggml_context * ctx, struct ggml_tensor * cur, int  il) const;
};

int32_t llama_control_vector_apply(
        struct llama_control_vector & cvec,
        const llama_model & model,
        const float * data,
        size_t len,
        int32_t n_embd,
        int32_t il_start,
        int32_t il_end);

//
// llama_adapter_lora
//

// TODO: rename to llama_adapter_lora_weight
struct llama_lora_weight {
    struct ggml_tensor * a = nullptr;
    struct ggml_tensor * b = nullptr;

    llama_lora_weight() = default;
    llama_lora_weight(struct ggml_tensor * a, struct ggml_tensor * b) : a(a), b(b) {}
};

// TODO: rename to llama_adapter_lora
struct llama_lora_adapter {
    // map tensor name to lora_a_b
    std::unordered_map<std::string, struct llama_lora_weight> ab_map;

    std::vector<ggml_context_ptr> ctxs;
    std::vector<ggml_backend_buffer_ptr> bufs;

    float alpha;

    llama_lora_adapter() = default;
    ~llama_lora_adapter() = default;

    llama_lora_weight * get_weight(struct ggml_tensor * w);
};