mirror of
https://github.com/BoardWare-Genius/jarvis-models.git
synced 2025-12-13 16:53:24 +00:00
121 lines
4.0 KiB
C++
121 lines
4.0 KiB
C++
#include <iostream>
|
|
#include <torch/torch.h>
|
|
#include <torch/script.h>
|
|
#include <string>
|
|
#include <vector>
|
|
#include <locale>
|
|
#include <codecvt>
|
|
#include <direct.h>
|
|
#include <fstream>
|
|
typedef int64_t int64;
|
|
namespace Shirakana {
|
|
|
|
struct WavHead {
|
|
char RIFF[4];
|
|
long int size0;
|
|
char WAVE[4];
|
|
char FMT[4];
|
|
long int size1;
|
|
short int fmttag;
|
|
short int channel;
|
|
long int samplespersec;
|
|
long int bytepersec;
|
|
short int blockalign;
|
|
short int bitpersamples;
|
|
char DATA[4];
|
|
long int size2;
|
|
};
|
|
|
|
int conArr2Wav(int64 size, int16_t* input, const char* filename) {
|
|
WavHead head = { {'R','I','F','F'},0,{'W','A','V','E'},{'f','m','t',' '},16,
|
|
1,1,22050,22050 * 2,2,16,{'d','a','t','a'},
|
|
0 };
|
|
head.size0 = size * 2 + 36;
|
|
head.size2 = size * 2;
|
|
std::ofstream ocout;
|
|
char* outputData = (char*)input;
|
|
ocout.open(filename, std::ios::out | std::ios::binary);
|
|
ocout.write((char*)&head, 44);
|
|
ocout.write(outputData, (int32_t)(size * 2));
|
|
ocout.close();
|
|
return 0;
|
|
}
|
|
|
|
inline std::wstring to_wide_string(const std::string& input)
|
|
{
|
|
std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
|
|
return converter.from_bytes(input);
|
|
}
|
|
|
|
inline std::string to_byte_string(const std::wstring& input)
|
|
{
|
|
std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
|
|
return converter.to_bytes(input);
|
|
}
|
|
}
|
|
|
|
#define val const auto
|
|
int main()
|
|
{
|
|
torch::jit::Module Vits;
|
|
std::string buffer;
|
|
std::vector<int64> text;
|
|
std::vector<int16_t> data;
|
|
while(true)
|
|
{
|
|
while (true)
|
|
{
|
|
std::cin >> buffer;
|
|
if (buffer == "end")
|
|
return 0;
|
|
if(buffer == "model")
|
|
{
|
|
std::cin >> buffer;
|
|
Vits = torch::jit::load(buffer);
|
|
continue;
|
|
}
|
|
if (buffer == "endinfer")
|
|
{
|
|
Shirakana::conArr2Wav(data.size(), data.data(), "temp\\tmp.wav");
|
|
data.clear();
|
|
std::cout << "endofinfe";
|
|
continue;
|
|
}
|
|
if (buffer == "line")
|
|
{
|
|
std::cin >> buffer;
|
|
while (buffer.find("endline")==std::string::npos)
|
|
{
|
|
text.push_back(std::atoi(buffer.c_str()));
|
|
std::cin >> buffer;
|
|
}
|
|
val InputTensor = torch::from_blob(text.data(), { 1,static_cast<int64>(text.size()) }, torch::kInt64);
|
|
std::array<int64, 1> TextLength{ static_cast<int64>(text.size()) };
|
|
val InputTensor_length = torch::from_blob(TextLength.data(), { 1 }, torch::kInt64);
|
|
std::vector<torch::IValue> inputs;
|
|
inputs.push_back(InputTensor);
|
|
inputs.push_back(InputTensor_length);
|
|
if (buffer.length() > 7)
|
|
{
|
|
std::array<int64, 1> speakerIndex{ (int64)atoi(buffer.substr(7).c_str()) };
|
|
inputs.push_back(torch::from_blob(speakerIndex.data(), { 1 }, torch::kLong));
|
|
}
|
|
val output = Vits.forward(inputs).toTuple()->elements()[0].toTensor().multiply(32276.0F);
|
|
val outputSize = output.sizes().at(2);
|
|
val floatOutput = output.data_ptr<float>();
|
|
int16_t* outputTmp = (int16_t*)malloc(sizeof(float) * outputSize);
|
|
if (outputTmp == nullptr) {
|
|
throw std::exception("内存不足");
|
|
}
|
|
for (int i = 0; i < outputSize; i++) {
|
|
*(outputTmp + i) = (int16_t) * (floatOutput + i);
|
|
}
|
|
data.insert(data.end(), outputTmp, outputTmp+outputSize);
|
|
free(outputTmp);
|
|
text.clear();
|
|
std::cout << "endofline";
|
|
}
|
|
}
|
|
}
|
|
//model S:\VSGIT\ShirakanaTTSUI\build\x64\Release\Mods\AtriVITS\AtriVITS_LJS.pt
|
|
} |