mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-29 07:34:18 +01:00
llama : allow exporting a view of the KV cache (#4180)
* Allow exporting a view of the KV cache * Allow dumping the sequences per cell in common * Track max contiguous cells value and position as well * Fix max contiguous empty cells index calculation Make dump functions deal with lengths or sequences counts > 10 better * Fix off by one error in dump_kv_cache_view * Add doc comments for KV cache view functions Eliminate cell sequence struct; use llama_seq_id directly Minor cleanups
This commit is contained in:
parent
671f639c59
commit
5df7d06c42
@ -12,6 +12,7 @@
|
|||||||
#include <regex>
|
#include <regex>
|
||||||
#include <sstream>
|
#include <sstream>
|
||||||
#include <string>
|
#include <string>
|
||||||
|
#include <unordered_map>
|
||||||
#include <unordered_set>
|
#include <unordered_set>
|
||||||
#include <vector>
|
#include <vector>
|
||||||
#include <cinttypes>
|
#include <cinttypes>
|
||||||
@ -1386,3 +1387,77 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
|
|||||||
fprintf(stream, "typical_p: %f # default: 1.0\n", sparams.typical_p);
|
fprintf(stream, "typical_p: %f # default: 1.0\n", sparams.typical_p);
|
||||||
fprintf(stream, "verbose_prompt: %s # default: false\n", params.verbose_prompt ? "true" : "false");
|
fprintf(stream, "verbose_prompt: %s # default: false\n", params.verbose_prompt ? "true" : "false");
|
||||||
}
|
}
|
||||||
|
|
||||||
|
//
|
||||||
|
// KV cache utils
|
||||||
|
//
|
||||||
|
|
||||||
|
void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size) {
|
||||||
|
static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+";
|
||||||
|
|
||||||
|
printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d",
|
||||||
|
view.n_cells, view.n_max_seq, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
|
||||||
|
|
||||||
|
llama_kv_cache_view_cell * c_curr = view.cells;
|
||||||
|
llama_seq_id * cs_curr = view.cells_sequences;
|
||||||
|
|
||||||
|
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
|
||||||
|
if (i % row_size == 0) {
|
||||||
|
printf("\n%5d: ", i);
|
||||||
|
}
|
||||||
|
int seq_count = 0;
|
||||||
|
for (int j = 0; j < view.n_max_seq; j++) {
|
||||||
|
if (cs_curr[j] >= 0) { seq_count++; }
|
||||||
|
}
|
||||||
|
putchar(slot_chars[std::min(sizeof(slot_chars) - 2, size_t(seq_count))]);
|
||||||
|
}
|
||||||
|
|
||||||
|
printf("\n=== Done dumping\n");
|
||||||
|
}
|
||||||
|
|
||||||
|
void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size) {
|
||||||
|
static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
|
||||||
|
|
||||||
|
printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n",
|
||||||
|
view.n_cells, view.n_max_seq, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
|
||||||
|
|
||||||
|
std::unordered_map<llama_seq_id, size_t> seqs;
|
||||||
|
llama_kv_cache_view_cell * c_curr = view.cells;
|
||||||
|
llama_seq_id * cs_curr = view.cells_sequences;
|
||||||
|
|
||||||
|
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
|
||||||
|
for (int j = 0; j < view.n_max_seq; j++) {
|
||||||
|
if (cs_curr[j] < 0) { continue; }
|
||||||
|
if (seqs.find(cs_curr[j]) == seqs.end()) {
|
||||||
|
if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
|
||||||
|
seqs[cs_curr[j]] = seqs.size();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
|
||||||
|
}
|
||||||
|
|
||||||
|
printf("=== Sequence legend: ");
|
||||||
|
for (const auto & it : seqs) {
|
||||||
|
printf("%zu=%d, ", it.second, it.first);
|
||||||
|
}
|
||||||
|
printf("'+'=other sequence ids");
|
||||||
|
|
||||||
|
c_curr = view.cells;
|
||||||
|
cs_curr = view.cells_sequences;
|
||||||
|
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
|
||||||
|
if (i % row_size == 0) {
|
||||||
|
printf("\n%5d: ", i);
|
||||||
|
}
|
||||||
|
for (int j = 0; j < view.n_max_seq; j++) {
|
||||||
|
if (cs_curr[j] >= 0) {
|
||||||
|
const auto & it = seqs.find(cs_curr[j]);
|
||||||
|
putchar(it != seqs.end() ? int(slot_chars[it->second]) : '+');
|
||||||
|
} else {
|
||||||
|
putchar('.');
|
||||||
|
}
|
||||||
|
}
|
||||||
|
putchar(' ');
|
||||||
|
}
|
||||||
|
|
||||||
|
printf("\n=== Done dumping\n");
|
||||||
|
}
|
||||||
|
@ -218,3 +218,13 @@ std::string get_sortable_timestamp();
|
|||||||
void dump_non_result_info_yaml(
|
void dump_non_result_info_yaml(
|
||||||
FILE * stream, const gpt_params & params, const llama_context * lctx,
|
FILE * stream, const gpt_params & params, const llama_context * lctx,
|
||||||
const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
|
const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
|
||||||
|
|
||||||
|
//
|
||||||
|
// KV cache utils
|
||||||
|
//
|
||||||
|
|
||||||
|
// Dump the KV cache view with the number of sequences per cell.
|
||||||
|
void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size = 80);
|
||||||
|
|
||||||
|
// Dump the KV cache view showing individual sequences in each cell (long output).
|
||||||
|
void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
|
||||||
|
@ -172,6 +172,8 @@ int main(int argc, char ** argv) {
|
|||||||
int32_t n_total_gen = 0;
|
int32_t n_total_gen = 0;
|
||||||
int32_t n_cache_miss = 0;
|
int32_t n_cache_miss = 0;
|
||||||
|
|
||||||
|
struct llama_kv_cache_view kvc_view = llama_kv_cache_view_init(ctx, n_clients);
|
||||||
|
|
||||||
const auto t_main_start = ggml_time_us();
|
const auto t_main_start = ggml_time_us();
|
||||||
|
|
||||||
LOG_TEE("%s: Simulating parallel requests from clients:\n", __func__);
|
LOG_TEE("%s: Simulating parallel requests from clients:\n", __func__);
|
||||||
@ -201,6 +203,9 @@ int main(int argc, char ** argv) {
|
|||||||
LOG_TEE("Processing requests ...\n\n");
|
LOG_TEE("Processing requests ...\n\n");
|
||||||
|
|
||||||
while (true) {
|
while (true) {
|
||||||
|
llama_kv_cache_view_update(ctx, &kvc_view);
|
||||||
|
dump_kv_cache_view_seqs(kvc_view, 40);
|
||||||
|
|
||||||
llama_batch_clear(batch);
|
llama_batch_clear(batch);
|
||||||
|
|
||||||
// decode any currently ongoing sequences
|
// decode any currently ongoing sequences
|
||||||
|
89
llama.cpp
89
llama.cpp
@ -8805,6 +8805,95 @@ int llama_model_apply_lora_from_file(const struct llama_model * model, const cha
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_context * ctx, int32_t n_max_seq) {
|
||||||
|
struct llama_kv_cache_view result = {
|
||||||
|
/*.n_cells = */ 0,
|
||||||
|
/*.n_max_seq = */ n_max_seq,
|
||||||
|
/*.token_count = */ 0,
|
||||||
|
/*.used_cells = */ llama_get_kv_cache_used_cells(ctx),
|
||||||
|
/*.max_contiguous = */ 0,
|
||||||
|
/*.max_contiguous_idx = */ -1,
|
||||||
|
/*.cells = */ nullptr,
|
||||||
|
/*.cells_sequences = */ nullptr,
|
||||||
|
};
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
void llama_kv_cache_view_free(struct llama_kv_cache_view * view) {
|
||||||
|
if (view->cells != nullptr) {
|
||||||
|
free(view->cells);
|
||||||
|
view->cells = nullptr;
|
||||||
|
}
|
||||||
|
if (view->cells_sequences != nullptr) {
|
||||||
|
free(view->cells_sequences);
|
||||||
|
view->cells_sequences = nullptr;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
void llama_kv_cache_view_update(const struct llama_context * ctx, struct llama_kv_cache_view * view) {
|
||||||
|
if (uint32_t(view->n_cells) < ctx->kv_self.size || view->cells == nullptr) {
|
||||||
|
view->n_cells = int32_t(ctx->kv_self.size);
|
||||||
|
void * p = realloc(view->cells, sizeof(struct llama_kv_cache_view_cell) * view->n_cells);
|
||||||
|
GGML_ASSERT(p != nullptr && "Failed to alloc kv_cache_view cells");
|
||||||
|
view->cells = (struct llama_kv_cache_view_cell *)p;
|
||||||
|
p = realloc(view->cells_sequences, sizeof(llama_seq_id) * view->n_max_seq * view->n_cells);
|
||||||
|
GGML_ASSERT(p != nullptr && "Failed to alloc kv_cache_view cells sequences");
|
||||||
|
view->cells_sequences = (llama_seq_id *)p;
|
||||||
|
}
|
||||||
|
|
||||||
|
const std::vector<llama_kv_cell> & kv_cells = ctx->kv_self.cells;
|
||||||
|
llama_kv_cache_view_cell * c_curr = view->cells;
|
||||||
|
llama_seq_id * cs_curr = view->cells_sequences;
|
||||||
|
int32_t used_cells = 0;
|
||||||
|
int32_t token_count = 0;
|
||||||
|
int32_t curr_contig_idx = -1;
|
||||||
|
uint32_t max_contig = 0;
|
||||||
|
int32_t max_contig_idx = -1;
|
||||||
|
|
||||||
|
for (int32_t i = 0; i < int32_t(ctx->kv_self.size); i++, c_curr++, cs_curr += view->n_max_seq) {
|
||||||
|
const size_t curr_size = kv_cells[i].seq_id.size();
|
||||||
|
token_count += curr_size;
|
||||||
|
c_curr->pos = kv_cells[i].pos + kv_cells[i].delta;
|
||||||
|
|
||||||
|
if (curr_size > 0) {
|
||||||
|
if (curr_contig_idx >= 0 && uint32_t(i - curr_contig_idx) > max_contig) {
|
||||||
|
max_contig = i - curr_contig_idx;
|
||||||
|
max_contig_idx = curr_contig_idx;
|
||||||
|
}
|
||||||
|
curr_contig_idx = -1;
|
||||||
|
} else if (curr_contig_idx < 0) {
|
||||||
|
curr_contig_idx = i;
|
||||||
|
}
|
||||||
|
|
||||||
|
int seq_idx = 0;
|
||||||
|
for (const llama_seq_id it : kv_cells[i].seq_id) {
|
||||||
|
if (seq_idx >= view->n_max_seq) {
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
cs_curr[seq_idx] = it;
|
||||||
|
seq_idx++;
|
||||||
|
}
|
||||||
|
if (seq_idx != 0) {
|
||||||
|
used_cells++;
|
||||||
|
}
|
||||||
|
for (; seq_idx < view->n_max_seq; seq_idx++) {
|
||||||
|
cs_curr[seq_idx] = -1;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if (curr_contig_idx >= 0 && kv_cells.size() - curr_contig_idx > max_contig) {
|
||||||
|
max_contig_idx = curr_contig_idx;
|
||||||
|
max_contig = kv_cells.size() - curr_contig_idx;
|
||||||
|
}
|
||||||
|
view->max_contiguous = max_contig;
|
||||||
|
view->max_contiguous_idx = max_contig_idx;
|
||||||
|
view->token_count = token_count;
|
||||||
|
view->used_cells = used_cells;
|
||||||
|
if (uint32_t(used_cells) != ctx->kv_self.used) {
|
||||||
|
LLAMA_LOG_ERROR("%s: used cells mismatch. kv_cache says %d but we calculated %d\n",
|
||||||
|
__func__, ctx->kv_self.used, used_cells);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
int llama_get_kv_cache_token_count(const struct llama_context * ctx) {
|
int llama_get_kv_cache_token_count(const struct llama_context * ctx) {
|
||||||
int result = 0;
|
int result = 0;
|
||||||
|
|
||||||
|
48
llama.h
48
llama.h
@ -361,6 +361,54 @@ extern "C" {
|
|||||||
// KV cache
|
// KV cache
|
||||||
//
|
//
|
||||||
|
|
||||||
|
// Information associated with an individual cell in the KV cache view.
|
||||||
|
struct llama_kv_cache_view_cell {
|
||||||
|
// The position for this cell. Takes KV cache shifts into account.
|
||||||
|
// May be negative if the cell is not populated.
|
||||||
|
llama_pos pos;
|
||||||
|
};
|
||||||
|
|
||||||
|
// An updateable view of the KV cache.
|
||||||
|
struct llama_kv_cache_view {
|
||||||
|
// Number of KV cache cells. This will be the same as the context size.
|
||||||
|
int32_t n_cells;
|
||||||
|
|
||||||
|
// Maximum number of sequences that can exist in a cell. It's not an error
|
||||||
|
// if there are more sequences in a cell than this value, however they will
|
||||||
|
// not be visible in the view cells_sequences.
|
||||||
|
int32_t n_max_seq;
|
||||||
|
|
||||||
|
// Number of tokens in the cache. For example, if there are two populated
|
||||||
|
// cells, the first with 1 sequence id in it and the second with 2 sequence
|
||||||
|
// ids then you'll have 3 tokens.
|
||||||
|
int32_t token_count;
|
||||||
|
|
||||||
|
// Number of populated cache cells.
|
||||||
|
int32_t used_cells;
|
||||||
|
|
||||||
|
// Maximum contiguous empty slots in the cache.
|
||||||
|
int32_t max_contiguous;
|
||||||
|
|
||||||
|
// Index to the start of the max_contiguous slot range. Can be negative
|
||||||
|
// when cache is full.
|
||||||
|
int32_t max_contiguous_idx;
|
||||||
|
|
||||||
|
// Information for an individual cell.
|
||||||
|
struct llama_kv_cache_view_cell * cells;
|
||||||
|
|
||||||
|
// The sequences for each cell. There will be n_max_seq items per cell.
|
||||||
|
llama_seq_id * cells_sequences;
|
||||||
|
};
|
||||||
|
|
||||||
|
// Create an empty KV cache view.
|
||||||
|
LLAMA_API struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_context * ctx, int32_t n_max_seq);
|
||||||
|
|
||||||
|
// Free a KV cache view.
|
||||||
|
LLAMA_API void llama_kv_cache_view_free(struct llama_kv_cache_view * view);
|
||||||
|
|
||||||
|
// Update the KV cache view structure with the current state of the KV cache.
|
||||||
|
LLAMA_API void llama_kv_cache_view_update(const struct llama_context * ctx, struct llama_kv_cache_view * view);
|
||||||
|
|
||||||
// Returns the number of tokens in the KV cache (slow, use only for debug)
|
// Returns the number of tokens in the KV cache (slow, use only for debug)
|
||||||
// If a KV cell has multiple sequences assigned to it, it will be counted multiple times
|
// If a KV cell has multiple sequences assigned to it, it will be counted multiple times
|
||||||
LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
|
LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
|
||||||
|
Loading…
Reference in New Issue
Block a user