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Concedo 2025-01-16 21:41:18 +08:00
commit 2a00ee8fa8
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examples/tts/tts.cpp
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@ -414,38 +414,15 @@ static void prompt_add(llama_tokens & prompt, const llama_tokens & tokens) {
prompt.insert(prompt.end(), tokens.begin(), tokens.end());
}
static void prompt_add(llama_tokens & prompt, const llama_model * model, const std::string & txt, bool add_special, bool parse_special) {
auto tmp = common_tokenize(model, txt, add_special, parse_special);
static void prompt_add(llama_tokens & prompt, const llama_vocab * vocab, const std::string & txt, bool add_special, bool parse_special) {
auto tmp = common_tokenize(vocab, txt, add_special, parse_special);
prompt_add(prompt, tmp);
}
static void prompt_init(llama_tokens & prompt, const llama_model * model) {
static void prompt_init(llama_tokens & prompt, const llama_vocab * vocab) {
prompt.clear();
prompt_add(prompt, model, "<|im_start|>\n", true, true);
}
static std::vector<llama_token> prepare_guide_tokens(const llama_model * model, const std::string& str)
{
const std::string& delimiter = "<|text_sep|>";
std::vector<llama_token> result;
size_t start = 0;
size_t end = str.find(delimiter);
while (end != std::string::npos) {
std::string current_word = str.substr(start, end - start);
auto tmp = common_tokenize(model, current_word, false, true);
result.push_back(tmp[0]);
start = end + delimiter.length();
end = str.find(delimiter, start);
}
// Add the last part
std::string current_word = str.substr(start);
auto tmp = common_tokenize(model, current_word, false, true);
result.push_back(tmp[0]);
return result;
prompt_add(prompt, vocab, "<|im_start|>\n", true, true);
}
int main(int argc, char ** argv) {
@ -485,6 +462,8 @@ int main(int argc, char ** argv) {
model_ttc = llama_init_ttc.model.get();
ctx_ttc = llama_init_ttc.context.get();
const llama_vocab * vocab = llama_model_get_vocab(model_ttc);
// TODO: refactor in a common struct
params.model = params.vocoder.model;
params.model_url = params.vocoder.model_url;
@ -515,7 +494,6 @@ int main(int argc, char ** argv) {
const auto t_main_start = ggml_time_us();
std::vector<llama_token> codes;
std::vector<llama_token> guide_tokens;
// process prompt and generate voice codes
{
@ -523,24 +501,20 @@ int main(int argc, char ** argv) {
std::vector<llama_token> prompt_inp;
prompt_init(prompt_inp, model_ttc);
prompt_init(prompt_inp, vocab);
prompt_add(prompt_inp, model_ttc, "<|text_start|>the<|text_sep|>overall<|text_sep|>package<|text_sep|>from<|text_sep|>just<|text_sep|>two<|text_sep|>people<|text_sep|>is<|text_sep|>pretty<|text_sep|>remarkable<|text_sep|>sure<|text_sep|>i<|text_sep|>have<|text_sep|>some<|text_sep|>critiques<|text_sep|>about<|text_sep|>some<|text_sep|>of<|text_sep|>the<|text_sep|>gameplay<|text_sep|>aspects<|text_sep|>but<|text_sep|>its<|text_sep|>still<|text_sep|>really<|text_sep|>enjoyable<|text_sep|>and<|text_sep|>it<|text_sep|>looks<|text_sep|>lovely<|text_sep|>", false, true);
prompt_add(prompt_inp, vocab, "<|text_start|>the<|text_sep|>overall<|text_sep|>package<|text_sep|>from<|text_sep|>just<|text_sep|>two<|text_sep|>people<|text_sep|>is<|text_sep|>pretty<|text_sep|>remarkable<|text_sep|>sure<|text_sep|>i<|text_sep|>have<|text_sep|>some<|text_sep|>critiques<|text_sep|>about<|text_sep|>some<|text_sep|>of<|text_sep|>the<|text_sep|>gameplay<|text_sep|>aspects<|text_sep|>but<|text_sep|>its<|text_sep|>still<|text_sep|>really<|text_sep|>enjoyable<|text_sep|>and<|text_sep|>it<|text_sep|>looks<|text_sep|>lovely<|text_sep|>", false, true);
// convert the input text into the necessary format expected by OuteTTS
{
std::string prompt_clean = process_text(params.prompt);
if(params.vocoder.use_guide_tokens)
{
guide_tokens = prepare_guide_tokens(model_ttc,prompt_clean);
}
LOG_INF("%s: prompt: '%s'\n", __func__, prompt_clean.c_str());
prompt_add(prompt_inp, model_ttc, prompt_clean, false, true);
prompt_add(prompt_inp, vocab, prompt_clean, false, true);
}
prompt_add(prompt_inp, model_ttc, "<|text_end|>\n", false, true);
prompt_add(prompt_inp, vocab, "<|text_end|>\n", false, true);
// disabled to save time on tokenizing each time
// TODO: load voices from the json files
@ -577,7 +551,7 @@ it<|t_0.09|><|code_start|><|848|><|1366|><|395|><|1601|><|1513|><|593|><|1302|><
looks<|t_0.27|><|code_start|><|1281|><|1266|><|1755|><|572|><|248|><|1751|><|1257|><|695|><|1380|><|457|><|659|><|585|><|1315|><|1105|><|1776|><|736|><|24|><|736|><|654|><|1027|><|code_end|>
lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|1481|><|1721|><|1123|><|438|><|1246|><|1251|><|795|><|659|><|1381|><|1658|><|217|><|1772|><|562|><|952|><|107|><|1129|><|1112|><|467|><|550|><|1079|><|840|><|1615|><|1469|><|1380|><|168|><|917|><|836|><|1827|><|437|><|583|><|67|><|595|><|1087|><|1646|><|1493|><|1677|><|code_end|>)";
auto tmp = common_tokenize(model_ttc, voice_data, false, true);
auto tmp = common_tokenize(vocab, voice_data, false, true);
printf("\n\n");
for (int i = 0; i < tmp.size(); ++i) {
printf("%d, ", tmp[i]);
@ -743,8 +717,6 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
int n_past = batch.n_tokens;
int n_decode = 0;
bool next_token_uses_guide_token = true;
while (n_decode <= n_predict) {
// prepare the next batch
common_batch_clear(batch);
@ -756,18 +728,7 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
continue;
}
llama_token new_token_id = common_sampler_sample(smpl[i], ctx_ttc, i_batch[i]);
//guide tokens help prevent hallucinations by forcing the TTS to use the correct word
if(!guide_tokens.empty() && next_token_uses_guide_token && !llama_token_is_control(model_ttc, new_token_id) && !llama_token_is_eog(model_ttc, new_token_id))
{
llama_token guide_token = guide_tokens[0];
guide_tokens.erase(guide_tokens.begin());
new_token_id = guide_token; //ensure correct word fragment is used
}
//this is the token id that always precedes a new word
next_token_uses_guide_token = (new_token_id == 198);
const llama_token new_token_id = common_sampler_sample(smpl[i], ctx_ttc, i_batch[i]);
common_sampler_accept(smpl[i], new_token_id, true);
@ -776,9 +737,9 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
const auto * cands = common_sampler_get_candidates(smpl[i]);
// is it an end of generation? -> mark the stream as finished
if (llama_token_is_eog(model_ttc, new_token_id) || n_decode == n_predict) {
if (llama_vocab_is_eog(vocab, new_token_id) || n_decode == n_predict) {
std::string reason;
if (llama_token_is_eog(model_ttc, new_token_id)) {
if (llama_vocab_is_eog(vocab, new_token_id)) {
reason = "eos";
} else {
reason = "n_predict";
@ -914,7 +875,7 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
#if 1
// spectral operations
const int n_embd = llama_n_embd(model_cts);
const int n_embd = llama_model_n_embd(model_cts);
const float * embd = llama_get_embeddings(ctx_cts);
auto audio = embd_to_audio(embd, n_codes, n_embd, params.cpuparams.n_threads);
@ -966,4 +927,4 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
llama_backend_free();
return 0;
}
}