online-paraformer-model.cc
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// sherpa-onnx/csrc/online-paraformer-model.cc
//
// Copyright (c) 2022-2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/online-paraformer-model.h"
#include <algorithm>
#include <cmath>
#include <string>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {
class OnlineParaformerModel::Impl {
public:
explicit Impl(const OnlineModelConfig &config)
: config_(config),
env_(ORT_LOGGING_LEVEL_ERROR),
sess_opts_(GetSessionOptions(config)),
allocator_{} {
{
auto buf = ReadFile(config.paraformer.encoder);
InitEncoder(buf.data(), buf.size());
}
{
auto buf = ReadFile(config.paraformer.decoder);
InitDecoder(buf.data(), buf.size());
}
}
#if __ANDROID_API__ >= 9
Impl(AAssetManager *mgr, const OnlineModelConfig &config)
: config_(config),
env_(ORT_LOGGING_LEVEL_ERROR),
sess_opts_(GetSessionOptions(config)),
allocator_{} {
{
auto buf = ReadFile(mgr, config.paraformer.encoder);
InitEncoder(buf.data(), buf.size());
}
{
auto buf = ReadFile(mgr, config.paraformer.decoder);
InitDecoder(buf.data(), buf.size());
}
}
#endif
std::vector<Ort::Value> ForwardEncoder(Ort::Value features,
Ort::Value features_length) {
std::array<Ort::Value, 2> inputs = {std::move(features),
std::move(features_length)};
return encoder_sess_->Run(
{}, encoder_input_names_ptr_.data(), inputs.data(), inputs.size(),
encoder_output_names_ptr_.data(), encoder_output_names_ptr_.size());
}
std::vector<Ort::Value> ForwardDecoder(Ort::Value encoder_out,
Ort::Value encoder_out_length,
Ort::Value acoustic_embedding,
Ort::Value acoustic_embedding_length,
std::vector<Ort::Value> states) {
std::vector<Ort::Value> decoder_inputs;
decoder_inputs.reserve(4 + states.size());
decoder_inputs.push_back(std::move(encoder_out));
decoder_inputs.push_back(std::move(encoder_out_length));
decoder_inputs.push_back(std::move(acoustic_embedding));
decoder_inputs.push_back(std::move(acoustic_embedding_length));
for (auto &v : states) {
decoder_inputs.push_back(std::move(v));
}
return decoder_sess_->Run({}, decoder_input_names_ptr_.data(),
decoder_inputs.data(), decoder_inputs.size(),
decoder_output_names_ptr_.data(),
decoder_output_names_ptr_.size());
}
int32_t VocabSize() const { return vocab_size_; }
int32_t LfrWindowSize() const { return lfr_window_size_; }
int32_t LfrWindowShift() const { return lfr_window_shift_; }
int32_t EncoderOutputSize() const { return encoder_output_size_; }
int32_t DecoderKernelSize() const { return decoder_kernel_size_; }
int32_t DecoderNumBlocks() const { return decoder_num_blocks_; }
const std::vector<float> &NegativeMean() const { return neg_mean_; }
const std::vector<float> &InverseStdDev() const { return inv_stddev_; }
OrtAllocator *Allocator() { return allocator_; }
private:
void InitEncoder(void *model_data, size_t model_data_length) {
encoder_sess_ = std::make_unique<Ort::Session>(
env_, model_data, model_data_length, sess_opts_);
GetInputNames(encoder_sess_.get(), &encoder_input_names_,
&encoder_input_names_ptr_);
GetOutputNames(encoder_sess_.get(), &encoder_output_names_,
&encoder_output_names_ptr_);
// get meta data
Ort::ModelMetadata meta_data = encoder_sess_->GetModelMetadata();
if (config_.debug) {
std::ostringstream os;
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(vocab_size_, "vocab_size");
SHERPA_ONNX_READ_META_DATA(lfr_window_size_, "lfr_window_size");
SHERPA_ONNX_READ_META_DATA(lfr_window_shift_, "lfr_window_shift");
SHERPA_ONNX_READ_META_DATA(encoder_output_size_, "encoder_output_size");
SHERPA_ONNX_READ_META_DATA(decoder_num_blocks_, "decoder_num_blocks");
SHERPA_ONNX_READ_META_DATA(decoder_kernel_size_, "decoder_kernel_size");
SHERPA_ONNX_READ_META_DATA_VEC_FLOAT(neg_mean_, "neg_mean");
SHERPA_ONNX_READ_META_DATA_VEC_FLOAT(inv_stddev_, "inv_stddev");
float scale = std::sqrt(encoder_output_size_);
for (auto &f : inv_stddev_) {
f *= scale;
}
}
void InitDecoder(void *model_data, size_t model_data_length) {
decoder_sess_ = std::make_unique<Ort::Session>(
env_, model_data, model_data_length, sess_opts_);
GetInputNames(decoder_sess_.get(), &decoder_input_names_,
&decoder_input_names_ptr_);
GetOutputNames(decoder_sess_.get(), &decoder_output_names_,
&decoder_output_names_ptr_);
}
private:
OnlineModelConfig config_;
Ort::Env env_;
Ort::SessionOptions sess_opts_;
Ort::AllocatorWithDefaultOptions allocator_;
std::unique_ptr<Ort::Session> encoder_sess_;
std::vector<std::string> encoder_input_names_;
std::vector<const char *> encoder_input_names_ptr_;
std::vector<std::string> encoder_output_names_;
std::vector<const char *> encoder_output_names_ptr_;
std::unique_ptr<Ort::Session> decoder_sess_;
std::vector<std::string> decoder_input_names_;
std::vector<const char *> decoder_input_names_ptr_;
std::vector<std::string> decoder_output_names_;
std::vector<const char *> decoder_output_names_ptr_;
std::vector<float> neg_mean_;
std::vector<float> inv_stddev_;
int32_t vocab_size_ = 0; // initialized in Init
int32_t lfr_window_size_ = 0;
int32_t lfr_window_shift_ = 0;
int32_t encoder_output_size_ = 0;
int32_t decoder_num_blocks_ = 0;
int32_t decoder_kernel_size_ = 0;
};
OnlineParaformerModel::OnlineParaformerModel(const OnlineModelConfig &config)
: impl_(std::make_unique<Impl>(config)) {}
#if __ANDROID_API__ >= 9
OnlineParaformerModel::OnlineParaformerModel(AAssetManager *mgr,
const OnlineModelConfig &config)
: impl_(std::make_unique<Impl>(mgr, config)) {}
#endif
OnlineParaformerModel::~OnlineParaformerModel() = default;
std::vector<Ort::Value> OnlineParaformerModel::ForwardEncoder(
Ort::Value features, Ort::Value features_length) const {
return impl_->ForwardEncoder(std::move(features), std::move(features_length));
}
std::vector<Ort::Value> OnlineParaformerModel::ForwardDecoder(
Ort::Value encoder_out, Ort::Value encoder_out_length,
Ort::Value acoustic_embedding, Ort::Value acoustic_embedding_length,
std::vector<Ort::Value> states) const {
return impl_->ForwardDecoder(
std::move(encoder_out), std::move(encoder_out_length),
std::move(acoustic_embedding), std::move(acoustic_embedding_length),
std::move(states));
}
int32_t OnlineParaformerModel::VocabSize() const { return impl_->VocabSize(); }
int32_t OnlineParaformerModel::LfrWindowSize() const {
return impl_->LfrWindowSize();
}
int32_t OnlineParaformerModel::LfrWindowShift() const {
return impl_->LfrWindowShift();
}
int32_t OnlineParaformerModel::EncoderOutputSize() const {
return impl_->EncoderOutputSize();
}
int32_t OnlineParaformerModel::DecoderKernelSize() const {
return impl_->DecoderKernelSize();
}
int32_t OnlineParaformerModel::DecoderNumBlocks() const {
return impl_->DecoderNumBlocks();
}
const std::vector<float> &OnlineParaformerModel::NegativeMean() const {
return impl_->NegativeMean();
}
const std::vector<float> &OnlineParaformerModel::InverseStdDev() const {
return impl_->InverseStdDev();
}
OrtAllocator *OnlineParaformerModel::Allocator() const {
return impl_->Allocator();
}
} // namespace sherpa_onnx