| | |
| | | session_options_.DisableCpuMemArena(); |
| | | |
| | | try { |
| | | m_session_ = std::make_unique<Ort::Session>(env_, am_model.c_str(), session_options_); |
| | | m_session_ = std::make_unique<Ort::Session>(env_, ORTSTRING(am_model).c_str(), session_options_); |
| | | LOG(INFO) << "Successfully load model from " << am_model; |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load am onnx model: " << e.what(); |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | |
| | | string strName; |
| | |
| | | for (auto& item : m_strOutputNames) |
| | | m_szOutputNames.push_back(item.c_str()); |
| | | vocab = new Vocab(am_config.c_str()); |
| | | LoadConfigFromYaml(am_config.c_str()); |
| | | LoadCmvn(am_cmvn.c_str()); |
| | | } |
| | | |
| | |
| | | session_options_.DisableCpuMemArena(); |
| | | |
| | | try { |
| | | encoder_session_ = std::make_unique<Ort::Session>(env_, en_model.c_str(), session_options_); |
| | | encoder_session_ = std::make_unique<Ort::Session>(env_, ORTSTRING(en_model).c_str(), session_options_); |
| | | LOG(INFO) << "Successfully load model from " << en_model; |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load am encoder model: " << e.what(); |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | |
| | | try { |
| | | decoder_session_ = std::make_unique<Ort::Session>(env_, de_model.c_str(), session_options_); |
| | | decoder_session_ = std::make_unique<Ort::Session>(env_, ORTSTRING(de_model).c_str(), session_options_); |
| | | LOG(INFO) << "Successfully load model from " << de_model; |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load am decoder model: " << e.what(); |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | |
| | | // encoder |
| | |
| | | |
| | | // offline |
| | | try { |
| | | m_session_ = std::make_unique<Ort::Session>(env_, am_model.c_str(), session_options_); |
| | | m_session_ = std::make_unique<Ort::Session>(env_, ORTSTRING(am_model).c_str(), session_options_); |
| | | LOG(INFO) << "Successfully load model from " << am_model; |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load am onnx model: " << e.what(); |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | |
| | | string strName; |
| | |
| | | m_strInputNames.push_back(strName.c_str()); |
| | | GetInputName(m_session_.get(), strName,1); |
| | | m_strInputNames.push_back(strName); |
| | | |
| | | if (use_hotword) { |
| | | GetInputName(m_session_.get(), strName, 2); |
| | | m_strInputNames.push_back(strName); |
| | | } |
| | | |
| | | GetOutputName(m_session_.get(), strName); |
| | | m_strOutputNames.push_back(strName); |
| | | GetOutputName(m_session_.get(), strName,1); |
| | | m_strOutputNames.push_back(strName); |
| | | // support time stamp |
| | | size_t numOutputNodes = m_session_->GetOutputCount(); |
| | | for(int index=0; index<numOutputNodes; index++){ |
| | | GetOutputName(m_session_.get(), strName, index); |
| | | m_strOutputNames.push_back(strName); |
| | | } |
| | | |
| | | for (auto& item : m_strInputNames) |
| | | m_szInputNames.push_back(item.c_str()); |
| | | for (auto& item : m_strOutputNames) |
| | | m_szOutputNames.push_back(item.c_str()); |
| | | } |
| | | |
| | | void Paraformer::LoadConfigFromYaml(const char* filename){ |
| | | |
| | | YAML::Node config; |
| | | try{ |
| | | config = YAML::LoadFile(filename); |
| | | }catch(exception const &e){ |
| | | LOG(ERROR) << "Error loading file, yaml file error or not exist."; |
| | | exit(-1); |
| | | } |
| | | |
| | | try{ |
| | | YAML::Node lang_conf = config["lang"]; |
| | | if (lang_conf.IsDefined()){ |
| | | language = lang_conf.as<string>(); |
| | | } |
| | | }catch(exception const &e){ |
| | | LOG(ERROR) << "Error when load argument from vad config YAML."; |
| | | exit(-1); |
| | | } |
| | | } |
| | | |
| | | void Paraformer::LoadOnlineConfigFromYaml(const char* filename){ |
| | |
| | | hw_session_options.DisableCpuMemArena(); |
| | | |
| | | try { |
| | | hw_m_session = std::make_unique<Ort::Session>(hw_env_, hw_model.c_str(), hw_session_options); |
| | | hw_m_session = std::make_unique<Ort::Session>(hw_env_, ORTSTRING(hw_model).c_str(), hw_session_options); |
| | | LOG(INFO) << "Successfully load model from " << hw_model; |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load hw compiler onnx model: " << e.what(); |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | |
| | | string strName; |
| | |
| | | ifstream cmvn_stream(filename); |
| | | if (!cmvn_stream.is_open()) { |
| | | LOG(ERROR) << "Failed to open file: " << filename; |
| | | exit(0); |
| | | exit(-1); |
| | | } |
| | | string line; |
| | | |
| | |
| | | hyps.push_back(max_idx); |
| | | } |
| | | if(!is_stamp){ |
| | | return vocab->Vector2StringV2(hyps); |
| | | return vocab->Vector2StringV2(hyps, language); |
| | | }else{ |
| | | std::vector<string> char_list; |
| | | std::vector<std::vector<float>> timestamp_list; |
| | |
| | | if (char_list.back() == "</s>") { |
| | | char_list.pop_back(); |
| | | } |
| | | |
| | | if (char_list.empty()) { |
| | | return ; |
| | | } |
| | | vector<vector<float>> timestamp_list; |
| | | vector<string> new_char_list; |
| | | vector<float> fire_place; |
| | |
| | | if(num_peak != (int)char_list.size() + 1){ |
| | | float sum = std::accumulate(us_alphas.begin(), us_alphas.end(), 0.0f); |
| | | float scale = sum/((int)char_list.size() + 1); |
| | | if(scale == 0){ |
| | | return; |
| | | } |
| | | cif_peak.clear(); |
| | | sum = 0.0; |
| | | for(auto &alpha:us_alphas){ |
| | |
| | | fire_place.push_back(i + total_offset); |
| | | } |
| | | } |
| | | } |
| | | |
| | | num_peak = fire_place.size(); |
| | | if(fire_place.size() == 0){ |
| | | return; |
| | | } |
| | | |
| | | // begin silence |
| | |
| | | } |
| | | |
| | | // tail token and end silence |
| | | if(timestamp_list.size()==0){ |
| | | LOG(ERROR)<<"timestamp_list's size is 0!"; |
| | | return; |
| | | } |
| | | if (num_frames - fire_place.back() > START_END_THRESHOLD) { |
| | | float _end = (num_frames + fire_place.back()) / 2.0; |
| | | timestamp_list.back()[1] = _end * TIME_RATE; |
| | |
| | | return ""; |
| | | } |
| | | //PrintMat(hw_emb, "input_clas_emb"); |
| | | const int64_t hotword_shape[3] = {1, hw_emb.size(), hw_emb[0].size()}; |
| | | const int64_t hotword_shape[3] = {1, static_cast<int64_t>(hw_emb.size()), static_cast<int64_t>(hw_emb[0].size())}; |
| | | embedding.reserve(hw_emb.size() * hw_emb[0].size()); |
| | | for (auto item : hw_emb) { |
| | | embedding.insert(embedding.end(), item.begin(), item.end()); |
| | |
| | | }else{ |
| | | result = GreedySearch(floatData, *encoder_out_lens, outputShape[2]); |
| | | } |
| | | // int pos = 0; |
| | | // std::vector<std::vector<float>> logits; |
| | | // for (int j = 0; j < outputShape[1]; j++) |
| | | // { |
| | | // std::vector<float> vec_token; |
| | | // vec_token.insert(vec_token.begin(), floatData + pos, floatData + pos + outputShape[2]); |
| | | // logits.push_back(vec_token); |
| | | // pos += outputShape[2]; |
| | | // } |
| | | // //PrintMat(logits, "logits_out"); |
| | | // result = GreedySearch(floatData, *encoder_out_lens, outputShape[2]); |
| | | } |
| | | catch (std::exception const &e) |
| | | { |