// sherpa-onnx/csrc/offline-tts-vits-model.cc // // Copyright (c) 2023 Xiaomi Corporation #include "sherpa-onnx/csrc/offline-tts-vits-model.h" #include #include #include #include #include "sherpa-onnx/csrc/macros.h" #include "sherpa-onnx/csrc/onnx-utils.h" #include "sherpa-onnx/csrc/session.h" namespace sherpa_onnx { class OfflineTtsVitsModel::Impl { public: explicit Impl(const OfflineTtsModelConfig &config) : config_(config), env_(ORT_LOGGING_LEVEL_WARNING), sess_opts_(GetSessionOptions(config)), allocator_{} { auto buf = ReadFile(config.vits.model); Init(buf.data(), buf.size()); } Ort::Value Run(Ort::Value x, int64_t sid) { auto memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault); std::vector x_shape = x.GetTensorTypeAndShapeInfo().GetShape(); if (x_shape[0] != 1) { SHERPA_ONNX_LOGE("Support only batch_size == 1. Given: %d", static_cast(x_shape[0])); exit(-1); } int64_t len = x_shape[1]; int64_t len_shape = 1; Ort::Value x_length = Ort::Value::CreateTensor(memory_info, &len, 1, &len_shape, 1); int64_t scale_shape = 1; float noise_scale = config_.vits.noise_scale; float length_scale = config_.vits.length_scale; float noise_scale_w = config_.vits.noise_scale_w; Ort::Value noise_scale_tensor = Ort::Value::CreateTensor(memory_info, &noise_scale, 1, &scale_shape, 1); Ort::Value length_scale_tensor = Ort::Value::CreateTensor( memory_info, &length_scale, 1, &scale_shape, 1); Ort::Value noise_scale_w_tensor = Ort::Value::CreateTensor( memory_info, &noise_scale_w, 1, &scale_shape, 1); Ort::Value sid_tensor = Ort::Value::CreateTensor(memory_info, &sid, 1, &scale_shape, 1); std::vector inputs; inputs.reserve(6); inputs.push_back(std::move(x)); inputs.push_back(std::move(x_length)); inputs.push_back(std::move(noise_scale_tensor)); inputs.push_back(std::move(length_scale_tensor)); inputs.push_back(std::move(noise_scale_w_tensor)); if (input_names_.size() == 6 && input_names_.back() == "sid") { inputs.push_back(std::move(sid_tensor)); } auto out = sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(), output_names_ptr_.data(), output_names_ptr_.size()); return std::move(out[0]); } int32_t SampleRate() const { return sample_rate_; } bool AddBlank() const { return add_blank_; } std::string Punctuations() const { return punctuations_; } private: void Init(void *model_data, size_t model_data_length) { sess_ = std::make_unique(env_, model_data, model_data_length, sess_opts_); GetInputNames(sess_.get(), &input_names_, &input_names_ptr_); GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_); // get meta data Ort::ModelMetadata meta_data = sess_->GetModelMetadata(); if (config_.debug) { std::ostringstream os; os << "---vits model---\n"; PrintModelMetadata(os, meta_data); SHERPA_ONNX_LOGE("%s\n", os.str().c_str()); } Ort::AllocatorWithDefaultOptions allocator; // used in the macro below SHERPA_ONNX_READ_META_DATA(sample_rate_, "sample_rate"); SHERPA_ONNX_READ_META_DATA(add_blank_, "add_blank"); SHERPA_ONNX_READ_META_DATA(n_speakers_, "n_speakers"); SHERPA_ONNX_READ_META_DATA_STR(punctuations_, "punctuation"); } private: OfflineTtsModelConfig config_; Ort::Env env_; Ort::SessionOptions sess_opts_; Ort::AllocatorWithDefaultOptions allocator_; std::unique_ptr sess_; std::vector input_names_; std::vector input_names_ptr_; std::vector output_names_; std::vector output_names_ptr_; int32_t sample_rate_; int32_t add_blank_; int32_t n_speakers_; std::string punctuations_; }; OfflineTtsVitsModel::OfflineTtsVitsModel(const OfflineTtsModelConfig &config) : impl_(std::make_unique(config)) {} OfflineTtsVitsModel::~OfflineTtsVitsModel() = default; Ort::Value OfflineTtsVitsModel::Run(Ort::Value x, int64_t sid /*=0*/) { return impl_->Run(std::move(x), sid); } int32_t OfflineTtsVitsModel::SampleRate() const { return impl_->SampleRate(); } bool OfflineTtsVitsModel::AddBlank() const { return impl_->AddBlank(); } std::string OfflineTtsVitsModel::Punctuations() const { return impl_->Punctuations(); } } // namespace sherpa_onnx