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PaddleSpeech/runtime/engine/common/frontend/feature_cache.h

71 lines
2.1 KiB

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "base/common.h"
#include "frontend/frontend_itf.h"
namespace ppspeech {
class FeatureCache : public FrontendInterface {
public:
explicit FeatureCache(
size_t max_size = kint16max,
std::unique_ptr<FrontendInterface> base_extractor = NULL);
// Feed feats or waves
virtual void Accept(const std::vector<kaldi::BaseFloat>& inputs);
// feats size = num_frames * feat_dim
virtual bool Read(std::vector<kaldi::BaseFloat>* feats);
// feat dim
virtual size_t Dim() const { return dim_; }
virtual void SetFinished() {
std::unique_lock<std::mutex> lock(mutex_);
LOG(INFO) << "set finished";
// read the last chunk data
Compute();
base_extractor_->SetFinished();
LOG(INFO) << "compute last feats done.";
}
virtual bool IsFinished() const { return base_extractor_->IsFinished(); }
void Reset() override {
std::queue<std::vector<BaseFloat>> empty;
std::swap(cache_, empty);
nframe_ = 0;
base_extractor_->Reset();
VLOG(3) << "feature cache reset: cache size: " << cache_.size();
}
private:
bool Compute();
int32 dim_;
size_t max_size_; // cache capacity
std::unique_ptr<FrontendInterface> base_extractor_;
std::queue<std::vector<BaseFloat>> cache_; // feature cache
std::mutex mutex_;
int32 nframe_; // num of feature computed
DISALLOW_COPY_AND_ASSIGN(FeatureCache);
};
} // namespace ppspeech