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