offline-paraformer-model.cc
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// sherpa-onnx/csrc/offline-paraformer-model.cc
//
// Copyright (c) 2022-2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/offline-paraformer-model.h"
#include <algorithm>
#include <string>
#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 OfflineParaformerModel::Impl {
public:
explicit Impl(const OfflineModelConfig &config)
: config_(config),
env_(ORT_LOGGING_LEVEL_ERROR),
sess_opts_(GetSessionOptions(config)),
allocator_{} {
Init();
}
std::pair<Ort::Value, Ort::Value> Forward(Ort::Value features,
Ort::Value features_length) {
std::array<Ort::Value, 2> inputs = {std::move(features),
std::move(features_length)};
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]), std::move(out[1])};
}
int32_t VocabSize() const { return vocab_size_; }
int32_t LfrWindowSize() const { return lfr_window_size_; }
int32_t LfrWindowShift() const { return lfr_window_shift_; }
const std::vector<float> &NegativeMean() const { return neg_mean_; }
const std::vector<float> &InverseStdDev() const { return inv_stddev_; }
OrtAllocator *Allocator() const { return allocator_; }
private:
void Init() {
auto buf = ReadFile(config_.paraformer.model);
sess_ = std::make_unique<Ort::Session>(env_, buf.data(), buf.size(),
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;
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_VEC_FLOAT(neg_mean_, "neg_mean");
SHERPA_ONNX_READ_META_DATA_VEC_FLOAT(inv_stddev_, "inv_stddev");
}
private:
OfflineModelConfig config_;
Ort::Env env_;
Ort::SessionOptions sess_opts_;
Ort::AllocatorWithDefaultOptions allocator_;
std::unique_ptr<Ort::Session> sess_;
std::vector<std::string> input_names_;
std::vector<const char *> input_names_ptr_;
std::vector<std::string> output_names_;
std::vector<const char *> 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;
};
OfflineParaformerModel::OfflineParaformerModel(const OfflineModelConfig &config)
: impl_(std::make_unique<Impl>(config)) {}
OfflineParaformerModel::~OfflineParaformerModel() = default;
std::pair<Ort::Value, Ort::Value> OfflineParaformerModel::Forward(
Ort::Value features, Ort::Value features_length) {
return impl_->Forward(std::move(features), std::move(features_length));
}
int32_t OfflineParaformerModel::VocabSize() const { return impl_->VocabSize(); }
int32_t OfflineParaformerModel::LfrWindowSize() const {
return impl_->LfrWindowSize();
}
int32_t OfflineParaformerModel::LfrWindowShift() const {
return impl_->LfrWindowShift();
}
const std::vector<float> &OfflineParaformerModel::NegativeMean() const {
return impl_->NegativeMean();
}
const std::vector<float> &OfflineParaformerModel::InverseStdDev() const {
return impl_->InverseStdDev();
}
OrtAllocator *OfflineParaformerModel::Allocator() const {
return impl_->Allocator();
}
} // namespace sherpa_onnx