384 lines
12 KiB
C++
384 lines
12 KiB
C++
// sherpa-onnx/csrc/offline-tts-vits-model.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#include "sherpa-onnx/csrc/offline-tts-vits-model.h"
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#include <algorithm>
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#include <string>
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#include <utility>
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#include <vector>
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#if __ANDROID_API__ >= 9
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#include "android/asset_manager.h"
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#include "android/asset_manager_jni.h"
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#endif
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#if __OHOS__
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#include "rawfile/raw_file_manager.h"
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#endif
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#include "sherpa-onnx/csrc/macros.h"
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#include "sherpa-onnx/csrc/onnx-utils.h"
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#include "sherpa-onnx/csrc/session.h"
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namespace sherpa_onnx {
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class OfflineTtsVitsModel::Impl {
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public:
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explicit Impl(const OfflineTtsModelConfig &config)
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: config_(config),
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env_(ORT_LOGGING_LEVEL_ERROR),
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sess_opts_(GetSessionOptions(config)),
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allocator_{} {
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auto buf = ReadFile(config.vits.model);
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Init(buf.data(), buf.size());
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}
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template <typename Manager>
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Impl(Manager *mgr, const OfflineTtsModelConfig &config)
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: config_(config),
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env_(ORT_LOGGING_LEVEL_ERROR),
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sess_opts_(GetSessionOptions(config)),
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allocator_{} {
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auto buf = ReadFile(mgr, config.vits.model);
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Init(buf.data(), buf.size());
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}
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Ort::Value Run(Ort::Value x, int64_t sid, float speed) {
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if (meta_data_.is_piper || meta_data_.is_coqui) {
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return RunVitsPiperOrCoqui(std::move(x), sid, speed);
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}
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return RunVits(std::move(x), sid, speed);
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}
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Ort::Value Run(Ort::Value x, Ort::Value tones, int64_t sid, float speed) {
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if (meta_data_.num_speakers == 1) {
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// For MeloTTS, we hardcode sid to the one contained in the meta data
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sid = meta_data_.speaker_id;
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}
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auto memory_info =
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Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
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std::vector<int64_t> x_shape = x.GetTensorTypeAndShapeInfo().GetShape();
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if (x_shape[0] != 1) {
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SHERPA_ONNX_LOGE("Support only batch_size == 1. Given: %d",
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static_cast<int32_t>(x_shape[0]));
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exit(-1);
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}
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int64_t len = x_shape[1];
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int64_t len_shape = 1;
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Ort::Value x_length =
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Ort::Value::CreateTensor(memory_info, &len, 1, &len_shape, 1);
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int64_t scale_shape = 1;
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float noise_scale = config_.vits.noise_scale;
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float length_scale = config_.vits.length_scale;
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float noise_scale_w = config_.vits.noise_scale_w;
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if (speed != 1 && speed > 0) {
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length_scale = 1. / speed;
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}
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Ort::Value noise_scale_tensor =
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Ort::Value::CreateTensor(memory_info, &noise_scale, 1, &scale_shape, 1);
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Ort::Value length_scale_tensor = Ort::Value::CreateTensor(
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memory_info, &length_scale, 1, &scale_shape, 1);
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Ort::Value noise_scale_w_tensor = Ort::Value::CreateTensor(
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memory_info, &noise_scale_w, 1, &scale_shape, 1);
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Ort::Value sid_tensor =
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Ort::Value::CreateTensor(memory_info, &sid, 1, &scale_shape, 1);
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std::vector<Ort::Value> inputs;
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inputs.reserve(7);
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inputs.push_back(std::move(x));
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inputs.push_back(std::move(x_length));
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inputs.push_back(std::move(tones));
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inputs.push_back(std::move(sid_tensor));
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inputs.push_back(std::move(noise_scale_tensor));
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inputs.push_back(std::move(length_scale_tensor));
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inputs.push_back(std::move(noise_scale_w_tensor));
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auto out =
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sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(),
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output_names_ptr_.data(), output_names_ptr_.size());
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return std::move(out[0]);
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}
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const OfflineTtsVitsModelMetaData &GetMetaData() const { return meta_data_; }
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private:
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void Init(void *model_data, size_t model_data_length) {
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sess_ = std::make_unique<Ort::Session>(env_, model_data, model_data_length,
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sess_opts_);
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GetInputNames(sess_.get(), &input_names_, &input_names_ptr_);
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GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_);
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// get meta data
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Ort::ModelMetadata meta_data = sess_->GetModelMetadata();
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if (config_.debug) {
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std::ostringstream os;
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os << "---vits model---\n";
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PrintModelMetadata(os, meta_data);
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os << "----------input names----------\n";
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int32_t i = 0;
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for (const auto &s : input_names_) {
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os << i << " " << s << "\n";
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++i;
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}
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os << "----------output names----------\n";
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i = 0;
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for (const auto &s : output_names_) {
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os << i << " " << s << "\n";
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++i;
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}
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#if __OHOS__
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SHERPA_ONNX_LOGE("%{public}s\n", os.str().c_str());
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#else
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SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
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#endif
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}
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Ort::AllocatorWithDefaultOptions allocator; // used in the macro below
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SHERPA_ONNX_READ_META_DATA(meta_data_.sample_rate, "sample_rate");
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.add_blank, "add_blank",
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0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.speaker_id, "speaker_id",
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0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.version, "version", 0);
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SHERPA_ONNX_READ_META_DATA(meta_data_.num_speakers, "n_speakers");
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SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(meta_data_.punctuations,
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"punctuation", "");
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SHERPA_ONNX_READ_META_DATA_STR(meta_data_.language, "language");
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SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(meta_data_.voice, "voice", "");
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SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(meta_data_.frontend, "frontend",
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"");
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.jieba, "jieba", 0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.blank_id, "blank_id", 0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.bos_id, "bos_id", 0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.eos_id, "eos_id", 0);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.use_eos_bos,
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"use_eos_bos", 1);
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SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.pad_id, "pad_id", 0);
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std::string comment;
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SHERPA_ONNX_READ_META_DATA_STR(comment, "comment");
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if (comment.find("piper") != std::string::npos) {
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meta_data_.is_piper = true;
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}
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if (comment.find("coqui") != std::string::npos) {
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meta_data_.is_coqui = true;
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}
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if (comment.find("icefall") != std::string::npos) {
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meta_data_.is_icefall = true;
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}
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if (comment.find("melo") != std::string::npos) {
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meta_data_.is_melo_tts = true;
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int32_t expected_version = 2;
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if (meta_data_.version < expected_version) {
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SHERPA_ONNX_LOGE(
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"Please download the latest MeloTTS model and retry. Current "
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"version: %d. Expected version: %d",
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meta_data_.version, expected_version);
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exit(-1);
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}
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// NOTE(fangjun):
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// version 0 is the first version
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// version 2: add jieba=1 to the metadata
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}
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}
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Ort::Value RunVitsPiperOrCoqui(Ort::Value x, int64_t sid, float speed) {
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auto memory_info =
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Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
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std::vector<int64_t> x_shape = x.GetTensorTypeAndShapeInfo().GetShape();
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if (x_shape[0] != 1) {
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SHERPA_ONNX_LOGE("Support only batch_size == 1. Given: %d",
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static_cast<int32_t>(x_shape[0]));
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exit(-1);
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}
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int64_t len = x_shape[1];
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int64_t len_shape = 1;
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Ort::Value x_length =
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Ort::Value::CreateTensor(memory_info, &len, 1, &len_shape, 1);
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float noise_scale = config_.vits.noise_scale;
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float length_scale = config_.vits.length_scale;
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float noise_scale_w = config_.vits.noise_scale_w;
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if (speed != 1 && speed > 0) {
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length_scale = 1. / speed;
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}
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std::array<float, 3> scales = {noise_scale, length_scale, noise_scale_w};
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int64_t scale_shape = 3;
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Ort::Value scales_tensor = Ort::Value::CreateTensor(
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memory_info, scales.data(), scales.size(), &scale_shape, 1);
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int64_t sid_shape = 1;
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Ort::Value sid_tensor =
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Ort::Value::CreateTensor(memory_info, &sid, 1, &sid_shape, 1);
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int64_t lang_id_shape = 1;
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int64_t lang_id = 0;
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Ort::Value lang_id_tensor =
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Ort::Value::CreateTensor(memory_info, &lang_id, 1, &lang_id_shape, 1);
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std::vector<Ort::Value> inputs;
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inputs.reserve(5);
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inputs.push_back(std::move(x));
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inputs.push_back(std::move(x_length));
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inputs.push_back(std::move(scales_tensor));
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if (input_names_.size() >= 4 && input_names_[3] == "sid") {
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inputs.push_back(std::move(sid_tensor));
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}
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if (input_names_.size() >= 5 && input_names_[4] == "langid") {
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inputs.push_back(std::move(lang_id_tensor));
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}
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auto out =
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sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(),
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output_names_ptr_.data(), output_names_ptr_.size());
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return std::move(out[0]);
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}
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Ort::Value RunVits(Ort::Value x, int64_t sid, float speed) {
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auto memory_info =
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Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
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std::vector<int64_t> x_shape = x.GetTensorTypeAndShapeInfo().GetShape();
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if (x_shape[0] != 1) {
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SHERPA_ONNX_LOGE("Support only batch_size == 1. Given: %d",
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static_cast<int32_t>(x_shape[0]));
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exit(-1);
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}
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int64_t len = x_shape[1];
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int64_t len_shape = 1;
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Ort::Value x_length =
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Ort::Value::CreateTensor(memory_info, &len, 1, &len_shape, 1);
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int64_t scale_shape = 1;
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float noise_scale = config_.vits.noise_scale;
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float length_scale = config_.vits.length_scale;
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float noise_scale_w = config_.vits.noise_scale_w;
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if (speed != 1 && speed > 0) {
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length_scale = 1. / speed;
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}
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Ort::Value noise_scale_tensor =
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Ort::Value::CreateTensor(memory_info, &noise_scale, 1, &scale_shape, 1);
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Ort::Value length_scale_tensor = Ort::Value::CreateTensor(
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memory_info, &length_scale, 1, &scale_shape, 1);
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Ort::Value noise_scale_w_tensor = Ort::Value::CreateTensor(
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memory_info, &noise_scale_w, 1, &scale_shape, 1);
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Ort::Value sid_tensor =
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Ort::Value::CreateTensor(memory_info, &sid, 1, &scale_shape, 1);
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std::vector<Ort::Value> inputs;
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inputs.reserve(6);
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inputs.push_back(std::move(x));
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inputs.push_back(std::move(x_length));
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inputs.push_back(std::move(noise_scale_tensor));
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inputs.push_back(std::move(length_scale_tensor));
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inputs.push_back(std::move(noise_scale_w_tensor));
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if (input_names_.size() == 6 &&
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(input_names_.back() == "sid" || input_names_.back() == "speaker")) {
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inputs.push_back(std::move(sid_tensor));
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}
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auto out =
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sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(),
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output_names_ptr_.data(), output_names_ptr_.size());
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return std::move(out[0]);
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}
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private:
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OfflineTtsModelConfig config_;
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Ort::Env env_;
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Ort::SessionOptions sess_opts_;
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Ort::AllocatorWithDefaultOptions allocator_;
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std::unique_ptr<Ort::Session> sess_;
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std::vector<std::string> input_names_;
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std::vector<const char *> input_names_ptr_;
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std::vector<std::string> output_names_;
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std::vector<const char *> output_names_ptr_;
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OfflineTtsVitsModelMetaData meta_data_;
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};
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OfflineTtsVitsModel::OfflineTtsVitsModel(const OfflineTtsModelConfig &config)
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: impl_(std::make_unique<Impl>(config)) {}
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template <typename Manager>
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OfflineTtsVitsModel::OfflineTtsVitsModel(Manager *mgr,
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const OfflineTtsModelConfig &config)
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: impl_(std::make_unique<Impl>(mgr, config)) {}
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OfflineTtsVitsModel::~OfflineTtsVitsModel() = default;
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Ort::Value OfflineTtsVitsModel::Run(Ort::Value x, int64_t sid /*=0*/,
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float speed /*= 1.0*/) {
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return impl_->Run(std::move(x), sid, speed);
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}
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Ort::Value OfflineTtsVitsModel::Run(Ort::Value x, Ort::Value tones,
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int64_t sid /*= 0*/,
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float speed /*= 1.0*/) const {
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return impl_->Run(std::move(x), std::move(tones), sid, speed);
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}
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const OfflineTtsVitsModelMetaData &OfflineTtsVitsModel::GetMetaData() const {
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return impl_->GetMetaData();
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}
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#if __ANDROID_API__ >= 9
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template OfflineTtsVitsModel::OfflineTtsVitsModel(
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AAssetManager *mgr, const OfflineTtsModelConfig &config);
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#endif
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#if __OHOS__
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template OfflineTtsVitsModel::OfflineTtsVitsModel(
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NativeResourceManager *mgr, const OfflineTtsModelConfig &config);
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#endif
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} // namespace sherpa_onnx
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