#include "common.h"
#include "llama.h"
+#include "grammar-parser.h"
#include <cmath>
#include <cstdio>
// 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);
++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;
}
// 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;
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);
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);
}
}
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());
}
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");