205 lines
6.6 KiB
C++
205 lines
6.6 KiB
C++
// sherpa-onnx/csrc/rknn/online-recognizer-ctc-rknn-impl.h
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//
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// Copyright (c) 2025 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_CTC_RKNN_IMPL_H_
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#define SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_CTC_RKNN_IMPL_H_
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#include <algorithm>
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#include <ios>
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#include <memory>
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#include <sstream>
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#include <string>
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#include <utility>
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#include <vector>
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#include "sherpa-onnx/csrc/file-utils.h"
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#include "sherpa-onnx/csrc/macros.h"
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#include "sherpa-onnx/csrc/online-ctc-decoder.h"
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#include "sherpa-onnx/csrc/online-ctc-fst-decoder.h"
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#include "sherpa-onnx/csrc/online-ctc-greedy-search-decoder.h"
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#include "sherpa-onnx/csrc/online-recognizer-impl.h"
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#include "sherpa-onnx/csrc/rknn/online-stream-rknn.h"
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#include "sherpa-onnx/csrc/rknn/online-zipformer-ctc-model-rknn.h"
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#include "sherpa-onnx/csrc/symbol-table.h"
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namespace sherpa_onnx {
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// defined in ../online-recognizer-ctc-impl.h
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OnlineRecognizerResult ConvertCtc(const OnlineCtcDecoderResult &src,
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const SymbolTable &sym_table,
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float frame_shift_ms,
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int32_t subsampling_factor, int32_t segment,
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int32_t frames_since_start);
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class OnlineRecognizerCtcRknnImpl : public OnlineRecognizerImpl {
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public:
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explicit OnlineRecognizerCtcRknnImpl(const OnlineRecognizerConfig &config)
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: OnlineRecognizerImpl(config),
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config_(config),
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model_(
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std::make_unique<OnlineZipformerCtcModelRknn>(config.model_config)),
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endpoint_(config_.endpoint_config) {
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if (!config.model_config.tokens_buf.empty()) {
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sym_ = SymbolTable(config.model_config.tokens_buf, false);
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} else {
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/// assuming tokens_buf and tokens are guaranteed not being both empty
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sym_ = SymbolTable(config.model_config.tokens, true);
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}
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InitDecoder();
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}
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template <typename Manager>
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explicit OnlineRecognizerCtcRknnImpl(Manager *mgr,
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const OnlineRecognizerConfig &config)
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: OnlineRecognizerImpl(mgr, config),
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config_(config),
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model_(std::make_unique<OnlineZipformerCtcModelRknn>(
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mgr, config_.model_config)),
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sym_(mgr, config_.model_config.tokens),
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endpoint_(config_.endpoint_config) {
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InitDecoder();
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}
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std::unique_ptr<OnlineStream> CreateStream() const override {
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auto stream = std::make_unique<OnlineStreamRknn>(config_.feat_config);
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stream->SetZipformerEncoderStates(model_->GetInitStates());
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stream->SetFasterDecoder(decoder_->CreateFasterDecoder());
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return stream;
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}
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bool IsReady(OnlineStream *s) const override {
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return s->GetNumProcessedFrames() + model_->ChunkSize() <
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s->NumFramesReady();
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}
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void DecodeStreams(OnlineStream **ss, int32_t n) const override {
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for (int32_t i = 0; i != n; ++i) {
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DecodeStream(reinterpret_cast<OnlineStreamRknn *>(ss[i]));
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}
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}
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OnlineRecognizerResult GetResult(OnlineStream *s) const override {
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OnlineCtcDecoderResult decoder_result = s->GetCtcResult();
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// TODO(fangjun): Remember to change these constants if needed
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int32_t frame_shift_ms = 10;
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int32_t subsampling_factor = 4;
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auto r =
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ConvertCtc(decoder_result, sym_, frame_shift_ms, subsampling_factor,
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s->GetCurrentSegment(), s->GetNumFramesSinceStart());
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r.text = ApplyInverseTextNormalization(r.text);
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return r;
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}
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bool IsEndpoint(OnlineStream *s) const override {
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if (!config_.enable_endpoint) {
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return false;
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}
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int32_t num_processed_frames = s->GetNumProcessedFrames();
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// frame shift is 10 milliseconds
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float frame_shift_in_seconds = 0.01;
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// subsampling factor is 4
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int32_t trailing_silence_frames = s->GetCtcResult().num_trailing_blanks * 4;
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return endpoint_.IsEndpoint(num_processed_frames, trailing_silence_frames,
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frame_shift_in_seconds);
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}
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void Reset(OnlineStream *s) const override {
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// segment is incremented only when the last
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// result is not empty
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const auto &r = s->GetCtcResult();
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if (!r.tokens.empty()) {
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s->GetCurrentSegment() += 1;
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}
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// clear result
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s->SetCtcResult({});
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// clear states
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reinterpret_cast<OnlineStreamRknn *>(s)->SetZipformerEncoderStates(
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model_->GetInitStates());
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s->GetFasterDecoderProcessedFrames() = 0;
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// Note: We only update counters. The underlying audio samples
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// are not discarded.
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s->Reset();
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}
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private:
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void InitDecoder() {
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if (!sym_.Contains("<blk>") && !sym_.Contains("<eps>") &&
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!sym_.Contains("<blank>")) {
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SHERPA_ONNX_LOGE(
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"We expect that tokens.txt contains "
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"the symbol <blk> or <eps> or <blank> and its ID.");
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exit(-1);
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}
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int32_t blank_id = 0;
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if (sym_.Contains("<blk>")) {
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blank_id = sym_["<blk>"];
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} else if (sym_.Contains("<eps>")) {
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// for tdnn models of the yesno recipe from icefall
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blank_id = sym_["<eps>"];
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} else if (sym_.Contains("<blank>")) {
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// for WeNet CTC models
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blank_id = sym_["<blank>"];
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}
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if (!config_.ctc_fst_decoder_config.graph.empty()) {
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decoder_ = std::make_unique<OnlineCtcFstDecoder>(
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config_.ctc_fst_decoder_config, blank_id);
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} else if (config_.decoding_method == "greedy_search") {
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decoder_ = std::make_unique<OnlineCtcGreedySearchDecoder>(blank_id);
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} else {
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SHERPA_ONNX_LOGE(
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"Unsupported decoding method: %s for streaming CTC models",
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config_.decoding_method.c_str());
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exit(-1);
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}
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}
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void DecodeStream(OnlineStreamRknn *s) const {
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int32_t chunk_size = model_->ChunkSize();
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int32_t chunk_shift = model_->ChunkShift();
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int32_t feat_dim = s->FeatureDim();
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const auto num_processed_frames = s->GetNumProcessedFrames();
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std::vector<float> features =
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s->GetFrames(num_processed_frames, chunk_size);
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s->GetNumProcessedFrames() += chunk_shift;
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auto &states = s->GetZipformerEncoderStates();
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auto p = model_->Run(features, std::move(states));
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states = std::move(p.second);
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std::vector<OnlineCtcDecoderResult> results(1);
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results[0] = std::move(s->GetCtcResult());
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auto attr = model_->GetOutAttr();
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decoder_->Decode(p.first.data(), attr.dims[0], attr.dims[1], attr.dims[2],
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&results, reinterpret_cast<OnlineStream **>(&s), 1);
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s->SetCtcResult(results[0]);
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}
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private:
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OnlineRecognizerConfig config_;
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std::unique_ptr<OnlineZipformerCtcModelRknn> model_;
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std::unique_ptr<OnlineCtcDecoder> decoder_;
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SymbolTable sym_;
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Endpoint endpoint_;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_CTC_RKNN_IMPL_H_
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