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llama.cpp/tools/tts/tts.cpp
T
2026-08-01 16:35:17 +02:00

175 lines
5.9 KiB
C++

#include "arg.h"
#include "common.h"
#include "sampling.h"
#include "log.h"
#include "llama.h"
#include "mtmd.h"
#include "mtmd-helper.h"
#include <cstdio>
#include <cstring>
#include <string>
/**
* Please note that this is NOT a production-ready binary.
* It is a playground for trying TTS support in llama.cpp.
* For contributors: please keep this code simple and easy to understand. Do not add unnecessary complexity. The goal is to have a simple CLI for testing TTS support.
*/
struct tts_timings {
int64_t t_start_us = ggml_time_us();
int64_t t_last_us = t_start_us;
void report(int n_frames) {
const int64_t t_now_us = ggml_time_us();
if (t_now_us - t_last_us < 2000000) {
return;
}
t_last_us = t_now_us;
const double t_elapsed_s = (t_now_us - t_start_us) / 1e6;
const double fps = t_elapsed_s > 0 ? n_frames / t_elapsed_s : 0.0;
LOG_INF("frames generated: %d, speed: %.2f frames/s\n", n_frames, fps);
}
};
static void print_usage(int, char ** argv) {
LOG("\nexample usage:\n");
LOG("\n %s -m backbone.gguf -mm mmproj.gguf -p \"text to speak\" -o output.wav", argv[0]);
LOG("\n %s -hf user/model -p \"text to speak\" -o output.wav\n", argv[0]);
LOG("\nnote: --tts-lang and --tts-speaker-file may not be supported in all models");
LOG("\n use -n to limit the output length");
LOG("\n see tts/README.md for per-model usage notes");
LOG("\n\n");
}
int main(int argc, char ** argv) {
common_params params;
common_init();
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_TTS, print_usage)) {
return 1;
}
mtmd_helper_log_set(common_log_default_callback, nullptr);
if (params.prompt.empty()) {
LOG_ERR("no prompt provided, use -p \"text\"\n");
return 1;
}
if (params.mmproj.path.empty()) {
LOG_ERR("no mmproj provided, use --mmproj\n");
return 1;
}
// always enable embd, so that we can pass hidden states to the audio generation helper
params.embedding = true;
llama_backend_init();
llama_numa_init(params.numa);
auto llama_init = common_init_from_params(params);
llama_model * model = llama_init->model();
llama_context * lctx = llama_init->context();
common_sampler * smpl = llama_init->sampler(0);
if (!model || !lctx) {
LOG_ERR("failed to init model/context\n");
return 1;
}
mtmd_context_params mtmd_params = mtmd_context_params_default();
mtmd_params.use_gpu = params.mmproj_use_gpu;
mtmd::context_ptr mctx(mtmd_init_from_file(params.mmproj.path.c_str(), model, mtmd_params));
if (!mctx) {
LOG_ERR("failed to load mmproj %s\n", params.mmproj.path.c_str());
return 1;
}
if (mtmd_gen_audio_get_info(mctx.get()).type == MTMD_GEN_AUDIO_TYPE_NONE) {
LOG_ERR("mmproj does not support audio generation\n");
return 1;
}
mtmd::bitmap_ptr speaker_bitmap;
if (!params.tts_speaker_file.empty()) {
auto wrapper = mtmd_helper_bitmap_init_from_file(mctx.get(), params.tts_speaker_file.c_str(), false);
if (!wrapper.bitmap) {
LOG_ERR("failed to load speaker file %s\n", params.tts_speaker_file.c_str());
return 1;
}
speaker_bitmap.reset(wrapper.bitmap);
}
mtmd_helper::gen_audio gen(lctx, mctx.get());
mtmd_helper_gen_audio_inp inp{};
inp.prompt = params.prompt.c_str();
inp.prompt_len = params.prompt.size();
inp.speaker_ref = speaker_bitmap.get();
inp.lang = params.tts_lang.c_str();
inp.top_k = params.sampling.top_k;
inp.top_p = params.sampling.top_p;
inp.out_type = MTMD_HELPER_GEN_AUDIO_OUTTYPE_WAV;
const int64_t t_prompt_start_us = ggml_time_us();
if (gen.set_input(&inp) != 0) {
LOG_ERR("set_input failed\n");
return 1;
}
LOG_INF("prompt eval took %.2f seconds\n", (ggml_time_us() - t_prompt_start_us) / 1e6);
// codec_0 (backbone) EOS token: ordinary LLM sampling concern, kept out of the
// model-agnostic audio-generation helper
const llama_vocab * vocab = llama_model_get_vocab(model);
llama_token codec_eos_tok = LLAMA_TOKEN_NULL;
for (llama_token t = 0; t < llama_vocab_n_tokens(vocab); t++) {
if (!strcmp(llama_vocab_get_text(vocab, t), "<|codec_eos_token|>")) { codec_eos_tok = t; break; }
}
if (codec_eos_tok == LLAMA_TOKEN_NULL) {
LOG_ERR("missing codec eos token in vocab\n");
return 1;
}
auto sample_codec0 = [&]() -> llama_token {
llama_token t = common_sampler_sample(smpl, lctx, -1);
common_sampler_accept(smpl, t, true);
return t;
};
const int max_new = params.n_predict > 0 ? params.n_predict : 512;
int n_frames = 0;
llama_token sampled = sample_codec0();
const float * h_state = llama_get_embeddings_ith(lctx, -1);
tts_timings timings;
for (; n_frames < max_new && sampled != codec_eos_tok; n_frames++) {
const float * h_next = nullptr;
if (gen.step(sampled, h_state, &h_next) != 0) {
LOG_ERR("step failed at frame %d\n", n_frames);
return 1;
}
h_state = h_next;
sampled = sample_codec0();
timings.report(n_frames + 1);
}
int32_t sample_rate = 0;
const char * data = nullptr;
size_t data_len = 0;
if (gen.get_output(&sample_rate, &data, &data_len) != 0) {
LOG_ERR("get_output failed\n");
return 1;
}
LOG_INF("generated %d frames, %zu bytes of WAV audio (%d Hz)\n", n_frames, data_len, sample_rate);
FILE * f = fopen(params.out_file.c_str(), "wb");
if (!f) {
LOG_ERR("failed to open %s\n", params.out_file.c_str());
return 1;
}
fwrite(data, 1, data_len, f);
fclose(f);
LOG_INF("wrote %s\n", params.out_file.c_str());
llama_backend_free();
return 0;
}