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enginex_bi_series-sherpa-onnx/sherpa-onnx/csrc/online-recognizer.cc
2023-02-24 21:39:51 +08:00

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C++

// sherpa-onnx/csrc/online-recognizer.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/online-recognizer.h"
#include <assert.h>
#include <algorithm>
#include <memory>
#include <sstream>
#include <utility>
#include <vector>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/online-transducer-greedy-search-decoder.h"
#include "sherpa-onnx/csrc/online-transducer-model.h"
#include "sherpa-onnx/csrc/symbol-table.h"
namespace sherpa_onnx {
static OnlineRecognizerResult Convert(const OnlineTransducerDecoderResult &src,
const SymbolTable &sym_table) {
std::string text;
for (auto t : src.tokens) {
text += sym_table[t];
}
OnlineRecognizerResult ans;
ans.text = std::move(text);
return ans;
}
void OnlineRecognizerConfig::Register(ParseOptions *po) {
feat_config.Register(po);
model_config.Register(po);
endpoint_config.Register(po);
po->Register("enable-endpoint", &enable_endpoint,
"True to enable endpoint detection. False to disable it.");
}
bool OnlineRecognizerConfig::Validate() const {
return model_config.Validate();
}
std::string OnlineRecognizerConfig::ToString() const {
std::ostringstream os;
os << "OnlineRecognizerConfig(";
os << "feat_config=" << feat_config.ToString() << ", ";
os << "model_config=" << model_config.ToString() << ", ";
os << "endpoint_config=" << endpoint_config.ToString() << ", ";
os << "enable_endpoint=" << (enable_endpoint ? "True" : "False") << ")";
return os.str();
}
class OnlineRecognizer::Impl {
public:
explicit Impl(const OnlineRecognizerConfig &config)
: config_(config),
model_(OnlineTransducerModel::Create(config.model_config)),
sym_(config.model_config.tokens),
endpoint_(config_.endpoint_config) {
decoder_ =
std::make_unique<OnlineTransducerGreedySearchDecoder>(model_.get());
}
#if __ANDROID_API__ >= 9
explicit Impl(AAssetManager *mgr, const OnlineRecognizerConfig &config)
: config_(config),
model_(OnlineTransducerModel::Create(mgr, config.model_config)),
sym_(mgr, config.model_config.tokens),
endpoint_(config_.endpoint_config) {
decoder_ =
std::make_unique<OnlineTransducerGreedySearchDecoder>(model_.get());
}
#endif
std::unique_ptr<OnlineStream> CreateStream() const {
auto stream = std::make_unique<OnlineStream>(config_.feat_config);
stream->SetResult(decoder_->GetEmptyResult());
stream->SetStates(model_->GetEncoderInitStates());
return stream;
}
bool IsReady(OnlineStream *s) const {
return s->GetNumProcessedFrames() + model_->ChunkSize() <
s->NumFramesReady();
}
void DecodeStreams(OnlineStream **ss, int32_t n) const {
int32_t chunk_size = model_->ChunkSize();
int32_t chunk_shift = model_->ChunkShift();
int32_t feature_dim = ss[0]->FeatureDim();
std::vector<OnlineTransducerDecoderResult> results(n);
std::vector<float> features_vec(n * chunk_size * feature_dim);
std::vector<std::vector<Ort::Value>> states_vec(n);
for (int32_t i = 0; i != n; ++i) {
std::vector<float> features =
ss[i]->GetFrames(ss[i]->GetNumProcessedFrames(), chunk_size);
ss[i]->GetNumProcessedFrames() += chunk_shift;
std::copy(features.begin(), features.end(),
features_vec.data() + i * chunk_size * feature_dim);
results[i] = std::move(ss[i]->GetResult());
states_vec[i] = std::move(ss[i]->GetStates());
}
auto memory_info =
Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
std::array<int64_t, 3> x_shape{n, chunk_size, feature_dim};
Ort::Value x = Ort::Value::CreateTensor(memory_info, features_vec.data(),
features_vec.size(), x_shape.data(),
x_shape.size());
auto states = model_->StackStates(states_vec);
auto pair = model_->RunEncoder(std::move(x), std::move(states));
decoder_->Decode(std::move(pair.first), &results);
std::vector<std::vector<Ort::Value>> next_states =
model_->UnStackStates(pair.second);
for (int32_t i = 0; i != n; ++i) {
ss[i]->SetResult(results[i]);
ss[i]->SetStates(std::move(next_states[i]));
}
}
OnlineRecognizerResult GetResult(OnlineStream *s) const {
OnlineTransducerDecoderResult decoder_result = s->GetResult();
decoder_->StripLeadingBlanks(&decoder_result);
return Convert(decoder_result, sym_);
}
bool IsEndpoint(OnlineStream *s) const {
if (!config_.enable_endpoint) return false;
int32_t num_processed_frames = s->GetNumProcessedFrames();
// frame shift is 10 milliseconds
float frame_shift_in_seconds = 0.01;
// subsampling factor is 4
int32_t trailing_silence_frames = s->GetResult().num_trailing_blanks * 4;
return endpoint_.IsEndpoint(num_processed_frames, trailing_silence_frames,
frame_shift_in_seconds);
}
void Reset(OnlineStream *s) const {
// reset result and neural network model state,
// but keep the feature extractor state
// reset result
s->SetResult(decoder_->GetEmptyResult());
// reset neural network model state
s->SetStates(model_->GetEncoderInitStates());
}
private:
OnlineRecognizerConfig config_;
std::unique_ptr<OnlineTransducerModel> model_;
std::unique_ptr<OnlineTransducerDecoder> decoder_;
SymbolTable sym_;
Endpoint endpoint_;
};
OnlineRecognizer::OnlineRecognizer(const OnlineRecognizerConfig &config)
: impl_(std::make_unique<Impl>(config)) {}
#if __ANDROID_API__ >= 9
OnlineRecognizer::OnlineRecognizer(AAssetManager *mgr,
const OnlineRecognizerConfig &config)
: impl_(std::make_unique<Impl>(mgr, config)) {}
#endif
OnlineRecognizer::~OnlineRecognizer() = default;
std::unique_ptr<OnlineStream> OnlineRecognizer::CreateStream() const {
return impl_->CreateStream();
}
bool OnlineRecognizer::IsReady(OnlineStream *s) const {
return impl_->IsReady(s);
}
void OnlineRecognizer::DecodeStreams(OnlineStream **ss, int32_t n) const {
impl_->DecodeStreams(ss, n);
}
OnlineRecognizerResult OnlineRecognizer::GetResult(OnlineStream *s) const {
return impl_->GetResult(s);
}
bool OnlineRecognizer::IsEndpoint(OnlineStream *s) const {
return impl_->IsEndpoint(s);
}
void OnlineRecognizer::Reset(OnlineStream *s) const { impl_->Reset(s); }
} // namespace sherpa_onnx