[Speechx] add nnet prob cache && make 2 thread decode work (#2769)
* add nnet cache && make 2 thread work * do not compile websocketpull/2854/head
YangZhou
2 years ago
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GitHub
parent
f8caaf46c8
commit
5046d8ee94
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "nnet/nnet_producer.h"
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namespace ppspeech {
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using kaldi::Vector;
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using kaldi::BaseFloat;
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NnetProducer::NnetProducer(std::shared_ptr<NnetBase> nnet,
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std::shared_ptr<FrontendInterface> frontend)
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: nnet_(nnet), frontend_(frontend) {}
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void NnetProducer::Accept(const kaldi::VectorBase<kaldi::BaseFloat>& inputs) {
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frontend_->Accept(inputs);
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bool result = false;
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do {
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result = Compute();
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} while (result);
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}
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void NnetProducer::Acceptlikelihood(
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const kaldi::Matrix<BaseFloat>& likelihood) {
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std::vector<BaseFloat> prob;
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prob.resize(likelihood.NumCols());
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for (size_t idx = 0; idx < likelihood.NumRows(); ++idx) {
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for (size_t col = 0; col < likelihood.NumCols(); ++col) {
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prob[col] = likelihood(idx, col);
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cache_.push_back(prob);
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}
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}
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}
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bool NnetProducer::Read(std::vector<kaldi::BaseFloat>* nnet_prob) {
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bool flag = cache_.pop(nnet_prob);
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return flag;
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}
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bool NnetProducer::Compute() {
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Vector<BaseFloat> features;
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if (frontend_ == NULL || frontend_->Read(&features) == false) {
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// no feat or frontend_ not init.
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VLOG(3) << "no feat avalible";
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return false;
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}
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CHECK_GE(frontend_->Dim(), 0);
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VLOG(2) << "Forward in " << features.Dim() / frontend_->Dim() << " feats.";
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NnetOut out;
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nnet_->FeedForward(features, frontend_->Dim(), &out);
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int32& vocab_dim = out.vocab_dim;
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Vector<BaseFloat>& logprobs = out.logprobs;
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size_t nframes = logprobs.Dim() / vocab_dim;
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VLOG(2) << "Forward out " << nframes << " decoder frames.";
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std::vector<BaseFloat> logprob(vocab_dim);
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// remove later.
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for (size_t idx = 0; idx < nframes; ++idx) {
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for (size_t prob_idx = 0; prob_idx < vocab_dim; ++prob_idx) {
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logprob[prob_idx] = logprobs(idx * vocab_dim + prob_idx);
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}
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cache_.push_back(logprob);
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}
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return true;
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}
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void NnetProducer::AttentionRescoring(const std::vector<std::vector<int>>& hyps,
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float reverse_weight,
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std::vector<float>* rescoring_score) {
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nnet_->AttentionRescoring(hyps, reverse_weight, rescoring_score);
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}
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} // namespace ppspeech
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@ -0,0 +1,73 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "base/common.h"
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#include "base/safe_queue.h"
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#include "frontend/audio/frontend_itf.h"
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#include "nnet/nnet_itf.h"
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namespace ppspeech {
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class NnetProducer {
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public:
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explicit NnetProducer(std::shared_ptr<NnetBase> nnet,
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std::shared_ptr<FrontendInterface> frontend = NULL);
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// Feed feats or waves
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void Accept(const kaldi::VectorBase<kaldi::BaseFloat>& inputs);
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void Acceptlikelihood(const kaldi::Matrix<BaseFloat>& likelihood);
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// nnet
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bool Read(std::vector<kaldi::BaseFloat>* nnet_prob);
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bool Empty() const { return cache_.empty(); }
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void SetFinished() {
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LOG(INFO) << "set finished";
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// std::unique_lock<std::mutex> lock(mutex_);
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frontend_->SetFinished();
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// read the last chunk data
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Compute();
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// ready_feed_condition_.notify_one();
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LOG(INFO) << "compute last feats done.";
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}
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bool IsFinished() const { return frontend_->IsFinished(); }
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void Reset() {
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frontend_->Reset();
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nnet_->Reset();
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VLOG(3) << "feature cache reset: cache size: " << cache_.size();
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cache_.clear();
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}
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void AttentionRescoring(const std::vector<std::vector<int>>& hyps,
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float reverse_weight,
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std::vector<float>* rescoring_score);
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private:
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bool Compute();
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std::shared_ptr<FrontendInterface> frontend_;
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std::shared_ptr<NnetBase> nnet_;
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SafeQueue<std::vector<kaldi::BaseFloat>> cache_;
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DISALLOW_COPY_AND_ASSIGN(NnetProducer);
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};
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} // namespace ppspeech
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@ -0,0 +1,123 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "recognizer/u2_recognizer.h"
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#include "decoder/param.h"
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#include "kaldi/feat/wave-reader.h"
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#include "kaldi/util/table-types.h"
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DEFINE_string(wav_rspecifier, "", "test feature rspecifier");
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DEFINE_string(result_wspecifier, "", "test result wspecifier");
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DEFINE_double(streaming_chunk, 0.36, "streaming feature chunk size");
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DEFINE_int32(sample_rate, 16000, "sample rate");
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void decode_func(std::shared_ptr<ppspeech::U2Recognizer> recognizer) {
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while (!recognizer->IsFinished()) {
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recognizer->Decode();
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usleep(100);
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}
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recognizer->Decode();
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recognizer->Rescoring();
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}
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int main(int argc, char* argv[]) {
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gflags::SetUsageMessage("Usage:");
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gflags::ParseCommandLineFlags(&argc, &argv, false);
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google::InitGoogleLogging(argv[0]);
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google::InstallFailureSignalHandler();
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FLAGS_logtostderr = 1;
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int32 num_done = 0, num_err = 0;
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double tot_wav_duration = 0.0;
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double tot_decode_time = 0.0;
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kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
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FLAGS_wav_rspecifier);
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kaldi::TokenWriter result_writer(FLAGS_result_wspecifier);
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int sample_rate = FLAGS_sample_rate;
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float streaming_chunk = FLAGS_streaming_chunk;
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int chunk_sample_size = streaming_chunk * sample_rate;
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LOG(INFO) << "sr: " << sample_rate;
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LOG(INFO) << "chunk size (s): " << streaming_chunk;
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LOG(INFO) << "chunk size (sample): " << chunk_sample_size;
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ppspeech::U2RecognizerResource resource =
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ppspeech::U2RecognizerResource::InitFromFlags();
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std::shared_ptr<ppspeech::U2Recognizer> recognizer_ptr(
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new ppspeech::U2Recognizer(resource));
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for (; !wav_reader.Done(); wav_reader.Next()) {
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std::thread recognizer_thread(decode_func, recognizer_ptr);
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std::string utt = wav_reader.Key();
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const kaldi::WaveData& wave_data = wav_reader.Value();
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LOG(INFO) << "utt: " << utt;
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LOG(INFO) << "wav dur: " << wave_data.Duration() << " sec.";
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double dur = wave_data.Duration();
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tot_wav_duration += dur;
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int32 this_channel = 0;
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kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
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this_channel);
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int tot_samples = waveform.Dim();
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LOG(INFO) << "wav len (sample): " << tot_samples;
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int sample_offset = 0;
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kaldi::Timer timer;
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kaldi::Timer local_timer;
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while (sample_offset < tot_samples) {
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int cur_chunk_size =
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std::min(chunk_sample_size, tot_samples - sample_offset);
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kaldi::Vector<kaldi::BaseFloat> wav_chunk(cur_chunk_size);
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for (int i = 0; i < cur_chunk_size; ++i) {
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wav_chunk(i) = waveform(sample_offset + i);
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}
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// wav_chunk = waveform.Range(sample_offset + i, cur_chunk_size);
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recognizer_ptr->Accept(wav_chunk);
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if (cur_chunk_size < chunk_sample_size) {
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recognizer_ptr->SetFinished();
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}
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// no overlap
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sample_offset += cur_chunk_size;
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}
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CHECK(sample_offset == tot_samples);
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recognizer_thread.join();
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std::string result = recognizer_ptr->GetFinalResult();
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recognizer_ptr->Reset();
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if (result.empty()) {
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// the TokenWriter can not write empty string.
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++num_err;
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LOG(INFO) << " the result of " << utt << " is empty";
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continue;
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}
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LOG(INFO) << utt << " " << result;
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LOG(INFO) << " RTF: " << local_timer.Elapsed() / dur << " dur: " << dur
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<< " cost: " << local_timer.Elapsed();
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result_writer.Write(utt, result);
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++num_done;
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}
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LOG(INFO) << "Done " << num_done << " out of " << (num_err + num_done);
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LOG(INFO) << "total wav duration is: " << tot_wav_duration << " sec";
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LOG(INFO) << "total decode cost:" << tot_decode_time << " sec";
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LOG(INFO) << "RTF is: " << tot_decode_time / tot_wav_duration;
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}
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@ -1 +1 @@
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add_subdirectory(websocket)
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#add_subdirectory(websocket)
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@ -0,0 +1,71 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "base/common.h"
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namespace ppspeech {
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template <typename T>
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class SafeQueue {
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public:
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explicit SafeQueue(size_t capacity = 0);
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void push_back(const T& in);
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bool pop(T* out);
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bool empty() const { return buffer_.empty(); }
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size_t size() const { return buffer_.size(); }
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void clear();
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private:
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std::mutex mutex_;
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std::condition_variable condition_;
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std::deque<T> buffer_;
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size_t capacity_;
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};
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template <typename T>
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SafeQueue<T>::SafeQueue(size_t capacity) : capacity_(capacity) {}
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template <typename T>
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void SafeQueue<T>::push_back(const T& in) {
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std::unique_lock<std::mutex> lock(mutex_);
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if (capacity_ > 0 && buffer_.size() == capacity_) {
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condition_.wait(lock, [this] { return capacity_ >= buffer_.size(); });
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}
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buffer_.push_back(in);
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condition_.notify_one();
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}
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template <typename T>
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bool SafeQueue<T>::pop(T* out) {
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if (buffer_.empty()) {
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return false;
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}
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std::unique_lock<std::mutex> lock(mutex_);
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condition_.wait(lock, [this] { return buffer_.size() > 0; });
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*out = std::move(buffer_.front());
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buffer_.pop_front();
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condition_.notify_one();
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return true;
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}
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template <typename T>
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void SafeQueue<T>::clear() {
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std::unique_lock<std::mutex> lock(mutex_);
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buffer_.clear();
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condition_.notify_one();
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}
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} // namespace ppspeech
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