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54 lines
1.8 KiB
54 lines
1.8 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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#pragma once
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#include "base/common.h"
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#include "frontend/feature_extractor_interface.h"
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namespace ppspeech {
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class FeatureCache : public FeatureExtractorInterface {
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public:
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explicit FeatureCache(
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int32 max_size = kint16max,
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std::unique_ptr<FeatureExtractorInterface> base_extractor = NULL);
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virtual void Accept(
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const kaldi::VectorBase<kaldi::BaseFloat>& inputs);
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// output_feats dim = num_frames * feature_dim
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virtual bool Read(kaldi::Vector<kaldi::BaseFloat>* output_feats);
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// feature cache only cache feature which from base extractor
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virtual size_t Dim() const { return base_extractor_->Dim(); }
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virtual void SetFinished() {
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base_extractor_->SetFinished();
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// read the last chunk data
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Compute();
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}
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virtual bool IsFinished() const { return base_extractor_->IsFinished(); }
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private:
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bool Compute();
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bool finished_;
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std::mutex mutex_;
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size_t max_size_;
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std::queue<kaldi::Vector<BaseFloat>> cache_;
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std::unique_ptr<FeatureExtractorInterface> base_extractor_;
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std::condition_variable ready_feed_condition_;
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std::condition_variable ready_read_condition_;
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//DISALLOW_COPY_AND_ASSGIN(FeatureCache);
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};
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} // namespace ppspeech
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