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speculative : reuse grammar parser + better logs and comments

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Georgi Gerganov 2023-09-04 15:18:38 +03:00
parent 6c150d763e
commit e7dc5b08ac
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1 changed files with 41 additions and 43 deletions
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examples/speculative/speculative.cpp
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@ -114,35 +114,21 @@ int main(int argc, char ** argv) {
struct llama_grammar * grammar_dft = NULL;
struct llama_grammar * grammar_tgt = NULL;
grammar_parser::parse_state parsed_grammar_dft;
grammar_parser::parse_state parsed_grammar_tgt;
grammar_parser::parse_state parsed_grammar;
std::vector<llama_grammar *> grammar_mem(n_draft, NULL);
// if requested - load the grammar, error checking is omitted for brevity
if (!params.grammar.empty()) {
// dft
{
parsed_grammar_dft = grammar_parser::parse(params.grammar.c_str());
// will be empty (default) if there are parse errors
if (parsed_grammar_dft.rules.empty()) {
return 1;
}
std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar_dft.c_rules());
grammar_dft = llama_grammar_init(grammar_rules.data(), grammar_rules.size(), parsed_grammar_dft.symbol_ids.at("root"));
parsed_grammar = grammar_parser::parse(params.grammar.c_str());
// will be empty (default) if there are parse errors
if (parsed_grammar.rules.empty()) {
return 1;
}
// tgt
{
parsed_grammar_tgt = grammar_parser::parse(params.grammar.c_str());
// will be empty (default) if there are parse errors
if (parsed_grammar_tgt.rules.empty()) {
return 1;
}
std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar_tgt.c_rules());
grammar_tgt = llama_grammar_init(grammar_rules.data(), grammar_rules.size(), parsed_grammar_tgt.symbol_ids.at("root"));
}
std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar.c_rules());
grammar_dft = llama_grammar_init(grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
grammar_tgt = llama_grammar_init(grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
}
const auto t_dec_start = ggml_time_us();
@ -150,11 +136,12 @@ int main(int argc, char ** argv) {
while (true) {
LOG("drafted: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx_dft, drafted));
// sample from the drafted tokens if any
int i_dft = 0;
while (true) {
// sample from the target model
const llama_token id = llama_sample_token(ctx_tgt, NULL, grammar_tgt, params, last_tokens, candidates, i_dft);
// remember which tokens were sampled - used for repetition penalties during sampling
last_tokens.erase(last_tokens.begin());
last_tokens.push_back(id);
@ -170,8 +157,9 @@ int main(int argc, char ** argv) {
++n_predict;
// check if the draft matches the target
if (i_dft < (int) drafted.size() && id == drafted[i_dft]) {
LOG("drafted token %d accepted\n", id);
LOG("the sampled target token matches the %dth drafted token (%d, '%s') - accepted\n", i_dft, id, token_str.c_str());
++n_accept;
++n_past_tgt;
++n_past_dft;
@ -180,25 +168,20 @@ int main(int argc, char ** argv) {
continue;
}
// the drafted token was rejected or we are out of drafted tokens
if (i_dft < (int) drafted.size()) {
LOG("drafted token %d rejected\n", id);
LOG("the %dth drafted token (%d, '%s') does not match the sampled target token (%d, '%s') - rejected\n",
i_dft, drafted[i_dft], llama_token_to_piece(ctx_dft, drafted[i_dft]).c_str(), id, token_str.c_str());
if (grammar_mem[i_dft]) {
grammar_dft = llama_grammar_copy(grammar_mem[i_dft]);
LOG("restored grammar %d\n", i_dft);
LOG("restored draft grammar state %d\n", i_dft);
}
} else {
LOG("out of drafted tokens\n");
}
for (auto & g : grammar_mem) {
if (g) {
llama_grammar_free(g);
g = NULL;
}
}
LOG("i_dft = %d, drafted.size() = %d\n", i_dft, (int) drafted.size());
// the drafted token was rejected or we are out of drafted tokens
llama_eval(ctx_dft, &id, 1, n_past_dft, params.n_threads);
++n_past_dft;
@ -212,11 +195,20 @@ int main(int argc, char ** argv) {
break;
}
for (int i = 0; i < (int) grammar_mem.size(); ++i) {
auto & g = grammar_mem[i];
if (g) {
LOG("freeing grammar state %d\n", i);
llama_grammar_free(g);
g = NULL;
}
}
if (n_predict > params.n_predict || has_eos) {
break;
}
// sample n_draft tokens from the draft model picking the best token
// sample n_draft tokens from the draft model using greedy decoding
int n_past_cur = n_past_dft;
for (int i = 0; i < n_draft; ++i) {
// remember the grammar state
@ -244,11 +236,13 @@ int main(int argc, char ** argv) {
LOG(" - draft candidate %3d: %6d (%8.3f) '%s'\n", i, cur_p.data[i].id, cur_p.data[i].p, llama_token_to_piece(ctx_dft, cur_p.data[i].id).c_str());
}
// too low probability, stop drafting
// TODO: better logic?
if (cur_p.data[0].p < 2*cur_p.data[1].p) {
LOG("stopping drafting, probability too low: %8.f < 2*%8.f\n", cur_p.data[0].p, cur_p.data[1].p);
break;
}
// drafted token
const llama_token id = cur_p.data[0].id;
if (grammar_dft != NULL) {
@ -258,17 +252,21 @@ int main(int argc, char ** argv) {
drafted.push_back(id);
++n_drafted;
if (i < n_draft - 1) {
// evaluate the drafted token on the draft model
llama_eval(ctx_dft, &drafted.back(), 1, n_past_cur, params.n_threads);
++n_past_cur;
// no need to evaluate the last drafted token, since we won't use the result
if (i == n_draft - 1) {
break;
}
// evaluate the drafted token on the draft model
llama_eval(ctx_dft, &drafted.back(), 1, n_past_cur, params.n_threads);
++n_past_cur;
}
// evaluate the target model on the drafted tokens
llama_eval(ctx_tgt, drafted.data(), drafted.size(), n_past_tgt, params.n_threads);
++n_past_tgt;
// the first token is always proposed by the traget model before the speculation loop
drafted.erase(drafted.begin());
}