mikhail/llama.cpp-mtp-turboquant
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common : refactor common_sampler + grammar logic changes (#17937)

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* common : refactor common_sampler + grammar logic changes

* tests : increase max_tokens to get needed response

* batched : fix uninitialized samplers
This commit is contained in:
Georgi Gerganov
2025-12-14 10:11:13 +02:00
committed by GitHub
parent 3238b1400c
commit 254098a279
27 changed files with 372 additions and 293 deletions
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examples/training/finetune.cpp
+9 -8
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@@ -39,9 +39,10 @@ int main(int argc, char ** argv) {
llama_backend_init();
llama_numa_init(params.numa);
// load the model and apply lora adapter, if any
common_init_result llama_init = common_init_from_params(params);
llama_model_ptr & model = llama_init.model;
llama_context_ptr & ctx = llama_init.context;
auto llama_init = common_init_from_params(params);
auto * model = llama_init->model();
auto * ctx = llama_init->context();
if (model == NULL) {
LOG_ERR("%s: unable to load model\n", __func__);
@@ -54,8 +55,8 @@ int main(int argc, char ** argv) {
LOG_INF("%s\n", common_params_get_system_info(params).c_str());
}
std::vector<llama_token> tokens = common_tokenize(ctx.get(), params.prompt, true);
ggml_opt_dataset_t dataset = common_opt_dataset_init(ctx.get(), tokens, llama_n_ctx(ctx.get()) / 2);
std::vector<llama_token> tokens = common_tokenize(ctx, params.prompt, true);
ggml_opt_dataset_t dataset = common_opt_dataset_init(ctx, tokens, llama_n_ctx(ctx) / 2);
struct lr_opt & lr = params.lr;
LOG_INF("-optimizer %s -lr0 %.2g -wd %.2g -lr-min %.2g -min-epochs %.2g -epochs %d -period %.2g -val %.2g\n",
@@ -70,7 +71,7 @@ int main(int argc, char ** argv) {
/*get_opt_pars_ud =*/&params.lr,
/*optimizer_type =*/params.optimizer,
};
llama_opt_init(ctx.get(), model.get(), lopt_params);
llama_opt_init(ctx, model, lopt_params);
const int64_t idata_split = ggml_opt_dataset_ndata(dataset) * (1.0f - params.val_split);
@@ -78,7 +79,7 @@ int main(int argc, char ** argv) {
ggml_opt_result_t result_eval = ggml_opt_result_init();
for (lr.epoch = 0; lr.epoch < lr.epochs; ++lr.epoch) {
llama_opt_epoch(ctx.get(), dataset, result_train, result_eval, idata_split,
llama_opt_epoch(ctx, dataset, result_train, result_eval, idata_split,
ggml_opt_epoch_callback_progress_bar, ggml_opt_epoch_callback_progress_bar);
fprintf(stderr, "\n");
@@ -88,7 +89,7 @@ int main(int argc, char ** argv) {
ggml_opt_result_free(result_train);
ggml_opt_result_free(result_eval);
llama_model_save_to_file(model.get(), params.out_file.c_str());
llama_model_save_to_file(model, params.out_file.c_str());
llama_backend_free();