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[update] fix llm generate bug

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This commit is contained in:
LittleMouse
2025-11-04 18:13:37 +08:00
parent f9de469ee5
commit 4e3d7f3666
2 changed files with 14 additions and 32 deletions
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projects/llm_framework/main_cosy_voice/src/main.cpp
+10 -30
View File
@@ -411,45 +411,42 @@ public:
timer time_total;
time_total.start();
try {
auto llm_thread_func = [this, &text, &prompt_text_embeds, &prompt_speech_embeds]() {
lLaMa_->Run(text, prompt_text_embeds, prompt_speech_embeds, g_token_buffer, g_buffer_mutex, g_buffer_cv,
g_llm_finished);
int llm_ret = 0;
auto llm_thread_func = [this, &text, &prompt_text_embeds, &prompt_speech_embeds, &llm_ret]() {
llm_ret = lLaMa_->Run(text, prompt_text_embeds, prompt_speech_embeds, g_token_buffer, g_buffer_mutex,
g_buffer_cv, g_llm_finished);
};
std::thread llm_thread(llm_thread_func);
int token_offset = 0;
llm_thread.detach();
int prompt_token_len = prompt_speech_embeds_flow.size() / lToken2Wav._attr.flow_embed_size;
if (prompt_token_len < 75) {
SLOGE("Error, prompt speech token len %d < 75", prompt_token_len);
if (llm_thread.joinable()) llm_thread.join();
return -1;
}
if (llm_ret == -1) {
return llm_ret;
}
int prompt_token_align_len = 75;
std::vector<float> prompt_speech_embeds_flow1;
prompt_speech_embeds_flow1.insert(prompt_speech_embeds_flow1.begin(), prompt_speech_embeds_flow.begin(),
prompt_speech_embeds_flow.begin() + prompt_token_align_len * 512);
std::vector<float> prompt_feat1;
prompt_feat1.insert(prompt_feat1.begin(), prompt_feat.begin(),
prompt_feat.begin() + prompt_token_align_len * 2 * 80);
int promot_token_pad = 0;
int this_token_hop_len;
int i = 0;
int token_offset = 0;
int i = 0;
while (true) {
this_token_hop_len = (token_offset == 0) ? lToken2Wav._attr.token_hop_len + promot_token_pad
: lToken2Wav._attr.token_hop_len;
std::unique_lock<std::mutex> lock(g_buffer_mutex);
g_buffer_cv.wait(lock, [&] {
return (g_token_buffer.size() - token_offset >=
this_token_hop_len + lToken2Wav._attr.pre_lookahead_len) ||
g_llm_finished.load() || g_stop.load();
});
if (g_stop) {
lock.unlock();
break;
@@ -460,9 +457,7 @@ public:
lToken2Wav._attr.max_infer_chunk_num - 1) *
lToken2Wav._attr.token_hop_len;
int end = token_offset + this_token_hop_len + lToken2Wav._attr.pre_lookahead_len;
token.insert(token.end(), g_token_buffer.begin() + start, g_token_buffer.begin() + end);
lock.unlock();
auto speech = lToken2Wav.infer(token, prompt_speech_embeds_flow1, prompt_feat1, spk_embeds,
token_offset, false);
@@ -481,7 +476,6 @@ public:
if (val < -1.0f) val = -1.0f;
wav_pcm_data.push_back(static_cast<int16_t>(val * 32767.0f));
}
if (out_callback_) {
out_callback_(std::string(reinterpret_cast<char *>(wav_pcm_data.data()),
wav_pcm_data.size() * sizeof(int16_t)),
@@ -496,10 +490,6 @@ public:
}
}
if (llm_thread.joinable()) {
llm_thread.join();
}
if (g_stop) {
g_token_buffer.erase(g_token_buffer.begin(), g_token_buffer.end());
return 1;
@@ -518,7 +508,6 @@ public:
std::vector<float> resampled_pcm(static_cast<size_t>(speech.size() * src_ratio + 1));
int resampled_len = 0;
resample_audio(speech.data(), speech.size(), resampled_pcm.data(), &resampled_len, src_ratio);
std::vector<int16_t> wav_pcm_data;
wav_pcm_data.reserve(resampled_len);
for (int i = 0; i < resampled_len; i++) {
@@ -538,7 +527,6 @@ public:
std::vector<float> resampled_pcm(static_cast<size_t>(output.size() * src_ratio + 1));
int resampled_len = 0;
resample_audio(output.data(), output.size(), resampled_pcm.data(), &resampled_len, src_ratio);
std::vector<int16_t> wav_pcm_data_full;
wav_pcm_data_full.reserve(resampled_len);
for (int i = 0; i < resampled_len; i++) {
@@ -547,7 +535,6 @@ public:
if (val < -1.0f) val = -1.0f;
wav_pcm_data_full.push_back(static_cast<int16_t>(val * 32767.0f));
}
std::string wav_path;
if (mode_config_.output_path.empty()) {
wav_path = generateFilename("/tmp");
@@ -561,14 +548,12 @@ public:
}
saveVectorAsWavFloat(resampled_pcm, wav_path, mode_config_.audio_rate, 1);
}
SLOGI("tts total use time: %.3f s", time_total.cost() / 1000);
reset();
} catch (const std::exception &e) {
std::cerr << "Error in pipeline: " << e.what() << std::endl;
return 1;
}
return 0;
}
@@ -599,12 +584,7 @@ public:
void inference(const std::string &msg)
{
try {
// std::string out = lLaMa_->Run(prompt_complete(msg));
// if (out_callback_) out_callback_(out, true);
tts(msg, prompt_text_embeds, prompt_speech_embeds, prompt_feat, prompt_speech_embeds_flow, spk_embeds);
std::string out = "finish";
if (out_callback_) out_callback_(out, true);
} catch (...) {
SLOGW("lLaMa_->Run have error!");
}
projects/llm_framework/main_cosy_voice/src/runner/LLM.hpp
+4 -2
View File
@@ -342,7 +342,7 @@ public:
{
std::vector<unsigned short> text_embed;
std::vector<std::vector<int>> position_ids;
Encode(text_embed, position_ids, input_str, prompt_text_embeds, prompt_speech_embeds);
if (Encode(text_embed, position_ids, input_str, prompt_text_embeds, prompt_speech_embeds)) return -1;
return Run(text_embed, position_ids, token_buffer, buffer_mutex, buffer_cv, llm_finished);
}
@@ -560,7 +560,9 @@ public:
if (b_stop) {
break;
}
if (indices >= _attr.kv_cache_num) {
break;
}
speech_embed_selector.getByIndex(next_token, embed.data());
memcpy((void *)llama_layers[0].layer.get_input(decode_grpid, "input").pVirAddr, embed.data(),
llama_layers[0].layer.get_input(decode_grpid, "input").nSize);