speculative : add grammar support (#2991)

* speculative : add grammar support

* grammars : add json_arr.gbnf

* grammar : add comments to new grammar file

* grammar : remove one nested level

* common : warm-up with 2 tokens - seems to work better

* speculative : print draft token pieces

* speculative : reuse grammar parser + better logs and comments

* speculative : avoid grammar_mem

* make : fix speculative build
This commit is contained in:
Georgi Gerganov 2023-09-05 08:46:17 +03:00 committed by GitHub
parent 2ba85c8609
commit 921772104b
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6 changed files with 126 additions and 13 deletions

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@ -495,7 +495,7 @@ baby-llama: examples/baby-llama/baby-llama.cpp ggml.o llama.o common.o $(OBJS)
beam-search: examples/beam-search/beam-search.cpp build-info.h ggml.o llama.o common.o $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
speculative: examples/speculative/speculative.cpp build-info.h ggml.o llama.o common.o $(OBJS)
speculative: examples/speculative/speculative.cpp build-info.h ggml.o llama.o common.o grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
ifdef LLAMA_METAL

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@ -772,7 +772,7 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
{
LOG("warming up the model with an empty run\n");
const std::vector<llama_token> tmp = { llama_token_bos(lctx), };
const std::vector<llama_token> tmp = { llama_token_bos(lctx), llama_token_eos(lctx), };
llama_eval(lctx, tmp.data(), tmp.size(), 0, params.n_threads);
llama_reset_timings(lctx);
}

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@ -6,6 +6,7 @@
#include "common.h"
#include "llama.h"
#include "grammar-parser.h"
#include <cmath>
#include <cstdio>
@ -109,16 +110,35 @@ int main(int argc, char ** argv) {
// used to determine end of generation
bool has_eos = false;
// grammar stuff
struct llama_grammar * grammar_dft = NULL;
struct llama_grammar * grammar_tgt = NULL;
grammar_parser::parse_state parsed_grammar;
// if requested - load the grammar, error checking is omitted for brevity
if (!params.grammar.empty()) {
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;
}
std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar.c_rules());
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();
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) {
const llama_token id = llama_sample_token(ctx_tgt, NULL, NULL, params, last_tokens, candidates, i_dft);
// 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);
@ -134,8 +154,9 @@ 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;
@ -145,6 +166,14 @@ int main(int argc, char ** argv) {
}
// the drafted token was rejected or we are out of drafted tokens
if (i_dft < (int) drafted.size()) {
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());
} else {
LOG("out of drafted tokens\n");
}
llama_eval(ctx_dft, &id, 1, n_past_dft, params.n_threads);
++n_past_dft;
@ -158,7 +187,16 @@ int main(int argc, char ** argv) {
break;
}
// sample n_draft tokens from the draft model picking the best token
if (grammar_tgt) {
if (grammar_dft) {
llama_grammar_free(grammar_dft);
}
grammar_dft = llama_grammar_copy(grammar_tgt);
LOG("copied target grammar to draft grammar\n");
}
// 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) {
float * logits = llama_get_logits(ctx_dft);
@ -170,25 +208,40 @@ int main(int argc, char ** argv) {
llama_token_data_array cur_p = { candidates.data(), candidates.size(), false };
if (grammar_dft != NULL) {
llama_sample_grammar(ctx_dft, &cur_p, grammar_dft);
}
// computes softmax and sorts the candidates
llama_sample_softmax(ctx_dft, &cur_p);
for (int i = 0; i < 3; ++i) {
LOG(" - draft candidate %d: %d (%.3f)\n", i, cur_p.data[i].id, cur_p.data[i].p);
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: %.3f < 2*%.3f\n", cur_p.data[0].p, cur_p.data[1].p);
break;
}
drafted.push_back(cur_p.data[0].id);
// drafted token
const llama_token id = cur_p.data[0].id;
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;
if (grammar_dft != NULL) {
llama_grammar_accept_token(ctx_dft, grammar_dft, id);
}
}
@ -196,6 +249,7 @@ int main(int argc, char ** argv) {
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());
}
@ -226,6 +280,10 @@ int main(int argc, char ** argv) {
llama_free(ctx_dft);
llama_free_model(model_dft);
if (grammar_dft != NULL) {
llama_grammar_free(grammar_dft);
llama_grammar_free(grammar_tgt);
}
llama_backend_free();
fprintf(stderr, "\n\n");

34
grammars/json_arr.gbnf Normal file
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@ -0,0 +1,34 @@
# This is the same as json.gbnf but we restrict whitespaces at the end of the root array
# Useful for generating JSON arrays
root ::= arr
value ::= object | array | string | number | ("true" | "false" | "null") ws
arr ::=
"[\n" ws (
value
(",\n" ws value)*
)? "]"
object ::=
"{" ws (
string ":" ws value
("," ws string ":" ws value)*
)? "}" ws
array ::=
"[" ws (
value
("," ws value)*
)? "]" ws
string ::=
"\"" (
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
# Optional space: by convention, applied in this grammar after literal chars when allowed
ws ::= ([ \t\n] ws)?

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@ -3850,6 +3850,25 @@ void llama_grammar_free(struct llama_grammar * grammar) {
delete grammar;
}
struct llama_grammar * llama_grammar_copy(const struct llama_grammar * grammar) {
llama_grammar * result = new llama_grammar{ grammar->rules, grammar->stacks, grammar->partial_utf8 };
// redirect elements in stacks to point to new rules
for (size_t is = 0; is < result->stacks.size(); is++) {
for (size_t ie = 0; ie < result->stacks[is].size(); ie++) {
for (size_t ir0 = 0; ir0 < grammar->rules.size(); ir0++) {
for (size_t ir1 = 0; ir1 < grammar->rules[ir0].size(); ir1++) {
if (grammar->stacks[is][ie] == &grammar->rules[ir0][ir1]) {
result->stacks[is][ie] = &result->rules[ir0][ir1];
}
}
}
}
}
return result;
}
//
// sampling
//

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@ -410,6 +410,8 @@ extern "C" {
LLAMA_API void llama_grammar_free(struct llama_grammar * grammar);
LLAMA_API struct llama_grammar * llama_grammar_copy(const struct llama_grammar * grammar);
//
// Sampling functions
//