mirror of
https://github.com/ggerganov/llama.cpp.git
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f66f582927
* llama : scatter llama.cpp into multiple modules (wip) * llama : control-vector -> adapter * llama : arch * llama : mmap ggml-ci * ci : remove BUILD_SHARED_LIBS=OFF ggml-ci * llama : arch (cont) ggml-ci * llama : chat ggml-ci * llama : model ggml-ci * llama : hparams ggml-ci * llama : adapter ggml-ci * examples : fix ggml-ci * rebase ggml-ci * minor * llama : kv cache ggml-ci * llama : impl ggml-ci * llama : batch ggml-ci * cont ggml-ci * llama : context ggml-ci * minor * llama : context (cont) ggml-ci * llama : model loader ggml-ci * common : update lora ggml-ci * llama : quant ggml-ci * llama : quant (cont) ggml-ci * minor [no ci]
67 lines
1.5 KiB
C++
67 lines
1.5 KiB
C++
#pragma once
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#include "llama-impl.h"
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#include "llama-hparams.h"
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#include "ggml-cpp.h"
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#include <unordered_map>
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#include <vector>
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//
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// llama_adapter_cvec
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//
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// TODO: rename to llama_adapter_cvec
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struct llama_control_vector {
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std::vector<ggml_context_ptr> ctxs;
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std::vector<ggml_backend_buffer_ptr> bufs;
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std::vector<struct ggml_tensor *> tensors; // per layer
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int32_t layer_start = -1;
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int32_t layer_end = -1;
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struct ggml_tensor * tensor_for(int il) const;
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struct ggml_tensor * apply_to(struct ggml_context * ctx, struct ggml_tensor * cur, int il) const;
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};
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int32_t llama_control_vector_apply(
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struct llama_control_vector & cvec,
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const llama_model & model,
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const float * data,
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size_t len,
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int32_t n_embd,
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int32_t il_start,
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int32_t il_end);
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//
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// llama_adapter_lora
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//
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// TODO: rename to llama_adapter_lora_weight
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struct llama_lora_weight {
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struct ggml_tensor * a = nullptr;
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struct ggml_tensor * b = nullptr;
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llama_lora_weight() = default;
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llama_lora_weight(struct ggml_tensor * a, struct ggml_tensor * b) : a(a), b(b) {}
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};
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// TODO: rename to llama_adapter_lora
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struct llama_lora_adapter {
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// map tensor name to lora_a_b
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std::unordered_map<std::string, struct llama_lora_weight> ab_map;
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std::vector<ggml_context_ptr> ctxs;
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std::vector<ggml_backend_buffer_ptr> bufs;
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float alpha;
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llama_lora_adapter() = default;
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~llama_lora_adapter() = default;
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llama_lora_weight * get_weight(struct ggml_tensor * w);
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};
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