#include "arg.h"
#include "common.h"
#include "debug.h"
#include "log.h"
#include "llama.h"
#include <clocale>
#include <string>
#include <vector>
static bool run(llama_context * ctx, const common_params & params) {
const llama_model * model = llama_get_model(ctx);
const llama_vocab * vocab = llama_model_get_vocab(model);
const bool add_bos = llama_vocab_get_add_bos(vocab);
std::vector<llama_token> tokens = common_tokenize(ctx, params.prompt, add_bos, true);
if (tokens.empty()) {
LOG_ERR("%s : there are not input tokens to process - (try to provide a prompt with '-p')\n", __func__);
return false;
}
LOG_INF("number of input tokens = %zu\n", tokens.size());
for (size_t i = 0; i < tokens.size(); ++i) {
LOG_INF(" %d\n", tokens[i]);
}
if (llama_decode(ctx, llama_batch_get_one(tokens.data(), tokens.size()))) {
LOG_ERR("%s : failed to eval\n", __func__);
return false;
}
return true;
}
int main(int argc, char ** argv) {
std::setlocale(LC_NUMERIC, "C");
common_debug_cb_user_data cb_data;
common_params params;
common_init();
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
return 1;
}
llama_backend_init();
llama_numa_init(params.numa);
// pass the callback to the backend scheduler
// it will be executed for each node during the graph computation
params.cb_eval = common_debug_cb_eval;
params.cb_eval_user_data = &cb_data;
params.warmup = false;
// init
auto llama_init = common_init_from_params(params);
auto * model = llama_init->model();
auto * ctx = llama_init->context();
if (model == nullptr || ctx == nullptr) {
LOG_ERR("%s : failed to init\n", __func__);
return 1;
}
// print system information
{
LOG_INF("\n");
LOG_INF("%s\n", common_params_get_system_info(params).c_str());
LOG_INF("\n");
}
bool OK = run(ctx, params);
if (!OK) {
return 1;
}
LOG("\n");
llama_perf_context_print(ctx);
llama_backend_free();
return 0;
}