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84 lines
2.5 KiB
84 lines
2.5 KiB
// 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 "frontend/feature_cache.h"
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namespace ppspeech {
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using kaldi::BaseFloat;
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using std::unique_ptr;
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using std::vector;
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FeatureCache::FeatureCache(size_t max_size,
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unique_ptr<FrontendInterface> base_extractor) {
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max_size_ = max_size;
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base_extractor_ = std::move(base_extractor);
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dim_ = base_extractor_->Dim();
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}
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void FeatureCache::Accept(const std::vector<kaldi::BaseFloat>& inputs) {
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// read inputs
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base_extractor_->Accept(inputs);
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}
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// pop feature chunk
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bool FeatureCache::Read(std::vector<kaldi::BaseFloat>* feats) {
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kaldi::Timer timer;
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std::unique_lock<std::mutex> lock(mutex_);
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// feed current data
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if (cache_.empty()) {
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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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if (cache_.empty()) return false;
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// read from cache
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*feats = cache_.front();
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cache_.pop();
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VLOG(2) << "FeatureCache::Read cost: " << timer.Elapsed() << " sec.";
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VLOG(1) << "FeatureCache::size : " << cache_.size();
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return true;
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}
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// read all data from base_feature_extractor_ into cache_
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bool FeatureCache::Compute() {
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// compute and feed
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vector<BaseFloat> feature;
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bool result = base_extractor_->Read(&feature);
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if (result == false || feature.size() == 0) return false;
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kaldi::Timer timer;
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int32 num_chunk = feature.size() / dim_;
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VLOG(3) << "nframe computed: " << nframe_;
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for (int chunk_idx = 0; chunk_idx < num_chunk; ++chunk_idx) {
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int32 start = chunk_idx * dim_;
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vector<BaseFloat> feature_chunk(feature.data() + start,
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feature.data() + start + dim_);
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// feed cache
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cache_.push(feature_chunk);
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++nframe_;
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}
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VLOG(2) << "FeatureCache::Compute cost: " << timer.Elapsed() << " sec. "
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<< num_chunk << " feats.";
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return true;
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}
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} // namespace ppspeech
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