llama : refactor src/llama.cpp (#10902)
* 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]
This commit is contained in:
Georgi Gerganov
GitHub
parent
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commit
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61 changed files with 12193 additions and 11649 deletions
218
src/llama-kv-cache.h
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218
src/llama-kv-cache.h
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#pragma once
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#include "llama.h"
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#include "ggml-cpp.h"
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#include <set>
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#include <vector>
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struct llama_kv_cell {
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llama_pos pos = -1;
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llama_pos delta = 0;
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int32_t src = -1; // used by recurrent state models to copy states
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int32_t tail = -1;
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std::set<llama_seq_id> seq_id;
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bool has_seq_id(const llama_seq_id & id) const {
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return seq_id.find(id) != seq_id.end();
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}
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bool is_empty() const {
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return seq_id.empty();
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}
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bool is_same_seq(const llama_kv_cell & other) const {
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return seq_id == other.seq_id;
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}
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};
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// ring-buffer of cached KV data
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struct llama_kv_cache {
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bool has_shift = false;
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bool do_defrag = false;
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bool recurrent = false; // with recurrent state models, a cell can hold the state for more than one past token
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bool v_trans = true; // the value tensor is transposed
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bool can_shift = false;
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// Note: The value of head isn't only used to optimize searching
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// for a free KV slot. llama_decode_internal also uses it, so it
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// cannot be freely changed after a slot has been allocated.
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uint32_t head = 0;
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uint32_t size = 0;
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uint32_t used = 0; // used cells (i.e. at least one seq_id)
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// computed before each graph build
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uint32_t n = 0;
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ggml_type type_k = GGML_TYPE_F16;
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ggml_type type_v = GGML_TYPE_F16;
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std::vector<llama_kv_cell> cells;
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std::vector<struct ggml_tensor *> k_l; // per layer
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std::vector<struct ggml_tensor *> v_l;
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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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size_t total_size() const {
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size_t size = 0;
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for (const auto & buf : bufs) {
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size += ggml_backend_buffer_get_size(buf.get());
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}
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return size;
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}
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// TODO: better data structures to reduce the cost of this operation
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llama_pos max_pos() const {
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llama_pos max_pos = -1;
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for (const auto & cell : cells) {
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max_pos = std::max(max_pos, cell.pos);
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}
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return max_pos;
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}
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};
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// a structure holds information about the slot found in llama_kv_cache_find_slot
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struct llama_kv_cache_slot_info {
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std::pair<uint32_t, uint32_t> boundaries; // slot boundaries [begin, end)
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bool found = false; // the slot was found
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explicit llama_kv_cache_slot_info(bool found_) : found{found_} {}
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llama_kv_cache_slot_info(uint32_t begin, uint32_t end) : boundaries{begin, end}, found{true} {}
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operator bool() const { return found; }
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};
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// TODO: maybe not needed
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uint32_t llama_kv_cache_get_padding(const struct llama_cparams & cparams);
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bool llama_kv_cache_init(
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struct llama_kv_cache & cache,
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const llama_model & model,
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const llama_cparams & cparams,
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ggml_type type_k,
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ggml_type type_v,
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uint32_t kv_size,
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bool offload);
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// find an empty slot of size "n_tokens" in the cache
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// updates the cache head
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// returns a structure holding information about the slot found
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// Note: On success, it's important that cache.head points
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// to the first cell of the slot.
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struct llama_kv_cache_slot_info llama_kv_cache_find_slot(
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struct llama_kv_cache & cache,
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const struct llama_ubatch & batch);
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// find how many cells are currently in use
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uint32_t llama_kv_cache_cell_max(const struct llama_kv_cache & cache);
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void llama_kv_cache_clear(struct llama_kv_cache & cache);
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bool llama_kv_cache_seq_rm(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id,
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llama_pos p0,
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llama_pos p1);
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void llama_kv_cache_seq_cp(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id_src,
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llama_seq_id seq_id_dst,
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llama_pos p0,
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llama_pos p1);
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void llama_kv_cache_seq_keep(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id);
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void llama_kv_cache_seq_add(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id,
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llama_pos p0,
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llama_pos p1,
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llama_pos delta);
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void llama_kv_cache_seq_div(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id,
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llama_pos p0,
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llama_pos p1,
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int d);
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llama_pos llama_kv_cache_seq_pos_max(
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struct llama_kv_cache & cache,
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llama_seq_id seq_id);
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void llama_kv_cache_defrag(struct llama_kv_cache & cache);
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int32_t llama_get_kv_cache_token_count(const struct llama_kv_cache & kv);
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int32_t llama_get_kv_cache_used_cells(const struct llama_kv_cache & kv);
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bool llama_kv_cache_can_shift(const struct llama_kv_cache & kv);
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//
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// kv cache view
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//
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struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_kv_cache & kv, int32_t n_seq_max);
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void llama_kv_cache_view_update(struct llama_kv_cache_view * view, const struct llama_kv_cache & kv);
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//
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// kv cache restore
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//
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// saves the kv_cache state for future recovery.
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// used to rollback llama_kv_cache_find_slot changes.
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struct llama_kv_slot_restorer {
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struct llama_kv_cache_state {
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uint32_t head = 0;
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uint32_t n = 0;
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} old_state;
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// for non-recurrent models only
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// list of slots to restore
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std::vector<std::pair<uint32_t, uint32_t>> slot_boundaries;
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bool do_restore = false;
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explicit llama_kv_slot_restorer(const struct llama_kv_cache & cache) {
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old_state.head = cache.head;
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old_state.n = cache.n;
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}
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// saves a slot information for future restoration
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void save(const struct llama_kv_cache_slot_info & slot) {
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if (slot) {
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do_restore = true;
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if (slot.boundaries.first != slot.boundaries.second) {
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slot_boundaries.push_back(slot.boundaries);
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}
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}
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}
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// must be explicitly called to restore the kv_cache state
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// and rollback changes from all llama_kv_cache_find_slot calls
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void restore(struct llama_kv_cache & cache) {
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if (do_restore) {
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cache.head = old_state.head;
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cache.n = old_state.n;
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if (cache.recurrent) { // recurrent models like Mamba or RWKV can't have a state partially erased
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llama_kv_cache_seq_rm(cache, -1, -1, -1);
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} else {
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for (auto & slot : slot_boundaries) {
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llama_kv_cache_seq_rm(cache, -1, slot.first, slot.second);
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}
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}
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}
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}
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};
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