283 lines
11 KiB
C++
283 lines
11 KiB
C++
#include "ngram-cache.h"
|
|
#include "common.h"
|
|
#include "log.h"
|
|
|
|
#include <cstdint>
|
|
#include <fstream>
|
|
|
|
void llama_ngram_cache_update(llama_ngram_cache & ngram_cache, int ngram_min, int ngram_max,
|
|
std::vector<llama_token> & inp, int nnew, bool print_progress) {
|
|
const int64_t t_start_ms = ggml_time_ms();
|
|
const int64_t inp_size = inp.size();
|
|
|
|
const int64_t n_todo = inp_size * (ngram_max - ngram_min + 1);
|
|
int64_t n_done = 0;
|
|
|
|
for (int64_t ngram_size = ngram_min; ngram_size <= ngram_max; ++ngram_size) {
|
|
const int64_t i_start = std::max(inp_size - nnew, ngram_size);
|
|
for (int64_t i = i_start; i < inp_size; ++i) {
|
|
const int64_t ngram_start = i - ngram_size;
|
|
llama_ngram ngram(&inp[ngram_start], ngram_size);
|
|
const llama_token token = inp[i];
|
|
|
|
llama_ngram_cache::iterator part_it = ngram_cache.find(ngram);
|
|
if (part_it == ngram_cache.end()) {
|
|
llama_ngram_cache_part part;
|
|
part.emplace(token, 1);
|
|
ngram_cache.emplace(ngram, part);
|
|
} else {
|
|
llama_ngram_cache_part::iterator token_count_it = part_it->second.find(token);
|
|
if (token_count_it == part_it->second.end()) {
|
|
part_it->second.emplace(token, 1);
|
|
} else {
|
|
token_count_it->second++;
|
|
}
|
|
}
|
|
++n_done;
|
|
|
|
if (print_progress && n_done % 10000000 == 0) {
|
|
const int64_t t_now_ms = ggml_time_ms();
|
|
const int64_t eta_ms = (inp_size*(ngram_max-ngram_min+1) - n_done) * (t_now_ms - t_start_ms) / n_done;
|
|
const int64_t eta_min = eta_ms / (60*1000);
|
|
const int64_t eta_s = (eta_ms - 60*1000*eta_min) / 1000;
|
|
|
|
fprintf(stderr, "%s: %" PRId64 "/%" PRId64 " done, ETA: %02" PRId64 ":%02" PRId64 "\n", __func__, n_done, n_todo, eta_min, eta_s);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Helper function to get a token from the combined, speculative sequence of inp and draft.
|
|
static llama_token get_token(const std::vector<llama_token> & inp, const std::vector<llama_token> & draft, const size_t i) {
|
|
return i < inp.size() ? inp[i] : draft[1 + i - inp.size()];
|
|
}
|
|
|
|
// If sample size or percentage are below these thresholds the draft is aborted early:
|
|
constexpr int draft_min_sample_size_lax[LLAMA_NGRAM_MAX] = { 2, 2, 1, 1};
|
|
constexpr int draft_min_percent_lax[LLAMA_NGRAM_MAX] = {66, 50, 50, 50};
|
|
constexpr int draft_min_sample_size_strict[LLAMA_NGRAM_MAX] = { 4, 3, 2, 2};
|
|
constexpr int draft_min_percent_strict[LLAMA_NGRAM_MAX] = {75, 66, 66, 66};
|
|
|
|
// Helper function that tries to draft a token from only the static ngram cache:
|
|
static llama_token try_draft(llama_ngram_cache & nc_static, const llama_ngram ngram_static) {
|
|
llama_ngram_cache::iterator part_static_it = nc_static.find(ngram_static);
|
|
if (part_static_it == nc_static.end()) {
|
|
return -1;
|
|
}
|
|
const llama_ngram_cache_part part_static = part_static_it->second;
|
|
|
|
int max_count_static = 0;
|
|
int sum_count_static = 0;
|
|
llama_token max_token = -1;
|
|
|
|
for (std::pair<llama_token, int> token_count_static : part_static) {
|
|
const llama_token token = token_count_static.first;
|
|
const int32_t count_static = token_count_static.second;
|
|
|
|
if (count_static > max_count_static) {
|
|
max_token = token;
|
|
max_count_static = count_static;
|
|
}
|
|
sum_count_static += count_static;
|
|
}
|
|
|
|
if (sum_count_static < draft_min_sample_size_lax[LLAMA_NGRAM_STATIC-1]) {
|
|
return -1;
|
|
}
|
|
if (100*max_count_static < draft_min_percent_lax[LLAMA_NGRAM_STATIC-1]*sum_count_static) {
|
|
return -1;
|
|
}
|
|
return max_token;
|
|
}
|
|
|
|
// Try to draft a token from primary cache (context/dynamic), validate with static cache:
|
|
static llama_token try_draft(
|
|
llama_ngram_cache & nc_primary, const std::vector<llama_ngram> & ngrams_primary, llama_ngram_cache_part & part_static,
|
|
const int * min_sample_size, const int * min_percent) {
|
|
|
|
llama_token drafted_token = -1;
|
|
|
|
for (int i = ngrams_primary.size()-1; i >= 0 && drafted_token == -1; --i) {
|
|
const llama_ngram ngram_primary = ngrams_primary[i];
|
|
|
|
llama_ngram_cache::iterator part_primary_it = nc_primary.find(ngram_primary);
|
|
if (part_primary_it == nc_primary.end()) {
|
|
continue;
|
|
}
|
|
const llama_ngram_cache_part part_primary = part_primary_it->second;
|
|
|
|
int max_count_primary = 0;
|
|
int max_count_static = 0;
|
|
int sum_count_primary = 0;
|
|
llama_token max_token = -1;
|
|
|
|
for (std::pair<llama_token, int> token_count_primary : part_primary) {
|
|
const llama_token token = token_count_primary.first;
|
|
|
|
llama_ngram_cache_part::iterator token_count_static_it = part_static.find(token);
|
|
|
|
const int32_t count_primary = token_count_primary.second;
|
|
const int32_t count_static = token_count_static_it != part_static.end() ? 100*token_count_static_it->second : 1;
|
|
|
|
if (count_primary*count_static > max_count_primary*max_count_static) {
|
|
max_token = token;
|
|
max_count_primary = count_primary;
|
|
max_count_static = count_static;
|
|
}
|
|
sum_count_primary += count_primary;
|
|
}
|
|
|
|
if (sum_count_primary < min_sample_size[i]) {
|
|
continue;
|
|
}
|
|
if (100*max_count_primary < min_percent[i]*sum_count_primary) {
|
|
continue;;
|
|
}
|
|
drafted_token = max_token;
|
|
}
|
|
|
|
return drafted_token;
|
|
}
|
|
|
|
void llama_ngram_cache_draft(
|
|
std::vector<llama_token> & inp, std::vector<llama_token> & draft, int n_draft, int ngram_min, int ngram_max,
|
|
llama_ngram_cache & nc_context, llama_ngram_cache & nc_dynamic, llama_ngram_cache & nc_static
|
|
) {
|
|
GGML_ASSERT(draft.size() == 1);
|
|
const int inp_size = inp.size();
|
|
|
|
if (inp_size < LLAMA_NGRAM_STATIC) {
|
|
return;
|
|
}
|
|
|
|
while ((int) draft.size()-1 < n_draft) {
|
|
llama_token drafted_token = -1;
|
|
|
|
const int ngram_start_static = inp_size-LLAMA_NGRAM_STATIC + draft.size()-1;
|
|
llama_ngram ngram_static;
|
|
for (int j = ngram_start_static; j < ngram_start_static + LLAMA_NGRAM_STATIC; ++j) {
|
|
ngram_static.tokens[j-ngram_start_static] = get_token(inp, draft, j);
|
|
}
|
|
llama_ngram_cache::iterator part_static_it = nc_static.find(ngram_static);
|
|
llama_ngram_cache_part part_static;
|
|
if (part_static_it != nc_static.end()) {
|
|
part_static = part_static_it->second;
|
|
}
|
|
|
|
// cd = context + dynamic
|
|
std::vector<llama_ngram> ngrams_cd;
|
|
for (int ngram_size_cd = ngram_min; ngram_size_cd <= ngram_max; ++ngram_size_cd) {
|
|
const int ngram_start_cd = inp_size-ngram_size_cd + draft.size()-1;
|
|
llama_ngram ngram_cd;
|
|
for (int j = ngram_start_cd; j < ngram_start_cd + ngram_size_cd; ++j) {
|
|
ngram_cd.tokens[j-ngram_start_cd] = get_token(inp, draft, j);
|
|
}
|
|
ngrams_cd.push_back(ngram_cd);
|
|
}
|
|
if (drafted_token == -1) {
|
|
drafted_token = try_draft(nc_context, ngrams_cd, part_static, draft_min_sample_size_lax, draft_min_percent_lax);
|
|
}
|
|
if (drafted_token == -1) {
|
|
drafted_token = try_draft(nc_dynamic, ngrams_cd, part_static, draft_min_sample_size_strict, draft_min_percent_strict);
|
|
}
|
|
if (drafted_token == -1) {
|
|
drafted_token = try_draft(nc_static, ngram_static);
|
|
}
|
|
|
|
if (drafted_token == -1) {
|
|
break;
|
|
}
|
|
|
|
LOG(" - draft candidate: token=%d\n", drafted_token);
|
|
draft.push_back(drafted_token);
|
|
}
|
|
}
|
|
|
|
void llama_ngram_cache_save(llama_ngram_cache & ngram_cache, std::string & filename) {
|
|
std::ofstream file_out(filename, std::ios::binary);
|
|
for (std::pair<llama_ngram, llama_ngram_cache_part> item : ngram_cache) {
|
|
const llama_ngram ngram = item.first;
|
|
llama_ngram_cache_part token_counts = item.second;
|
|
GGML_ASSERT(!token_counts.empty());
|
|
const int32_t ntokens = token_counts.size();
|
|
GGML_ASSERT(ntokens > 0);
|
|
|
|
file_out.write(reinterpret_cast<const char *>(&ngram), sizeof(llama_ngram));
|
|
file_out.write(reinterpret_cast<const char *>(&ntokens), sizeof(int32_t));
|
|
for (std::pair<llama_token, int32_t> item2 : token_counts) {
|
|
const llama_token token = item2.first;
|
|
const int32_t count = item2.second;
|
|
GGML_ASSERT(count > 0);
|
|
|
|
file_out.write(reinterpret_cast<const char *>(&token), sizeof(llama_token));
|
|
file_out.write(reinterpret_cast<const char *>(&count), sizeof(int32_t));
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
llama_ngram_cache llama_ngram_cache_load(std::string & filename) {
|
|
std::ifstream hashmap_file(filename, std::ios::binary);
|
|
if (!hashmap_file) {
|
|
throw std::ifstream::failure("Unable to open file " + filename);
|
|
}
|
|
llama_ngram_cache ngram_cache;
|
|
|
|
llama_ngram ngram;
|
|
int32_t ntokens;
|
|
llama_token token;
|
|
int32_t count;
|
|
|
|
char * ngramc = reinterpret_cast<char*>(&ngram);
|
|
char * ntokensc = reinterpret_cast<char*>(&ntokens);
|
|
char * tokenc = reinterpret_cast<char*>(&token);
|
|
char * countc = reinterpret_cast<char*>(&count);
|
|
while(hashmap_file.read(ngramc, sizeof(llama_ngram))) {
|
|
GGML_ASSERT(!hashmap_file.eof());
|
|
GGML_ASSERT(hashmap_file.read(ntokensc, sizeof(int32_t)));
|
|
GGML_ASSERT(ntokens > 0);
|
|
llama_ngram_cache_part token_counts;
|
|
|
|
for (int i = 0; i < ntokens; ++i) {
|
|
GGML_ASSERT(!hashmap_file.eof());
|
|
GGML_ASSERT(hashmap_file.read(tokenc, sizeof(llama_token)));
|
|
GGML_ASSERT(!hashmap_file.eof());
|
|
GGML_ASSERT(hashmap_file.read(countc, sizeof(int32_t)));
|
|
GGML_ASSERT(count > 0);
|
|
token_counts.emplace(token, count);
|
|
}
|
|
|
|
ngram_cache.emplace(ngram, token_counts);
|
|
}
|
|
GGML_ASSERT(hashmap_file.eof());
|
|
|
|
return ngram_cache;
|
|
}
|
|
|
|
void llama_ngram_cache_merge(llama_ngram_cache & ngram_cache_target, llama_ngram_cache & ngram_cache_add) {
|
|
for (std::pair<llama_ngram, llama_ngram_cache_part> ngram_part : ngram_cache_add) {
|
|
const llama_ngram ngram = ngram_part.first;
|
|
llama_ngram_cache_part part = ngram_part.second;
|
|
|
|
llama_ngram_cache::iterator part_merged_it = ngram_cache_target.find(ngram);
|
|
if (part_merged_it == ngram_cache_target.end()) {
|
|
ngram_cache_target.emplace(ngram, part);
|
|
continue;
|
|
}
|
|
|
|
for (std::pair<llama_token, int32_t> token_count : part) {
|
|
const llama_token token = token_count.first;
|
|
const int32_t count = token_count.second;
|
|
GGML_ASSERT(count > 0);
|
|
|
|
llama_ngram_cache_part::iterator token_count_merged_it = part_merged_it->second.find(token);
|
|
if (token_count_merged_it == part_merged_it->second.end()) {
|
|
part_merged_it->second.emplace(token, count);
|
|
continue;
|
|
}
|
|
|
|
token_count_merged_it->second += count;
|
|
}
|
|
}
|
|
}
|