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/*
* Copyright (c) 2018 The WebRTC project authors. All Rights Reserved.
*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#include "modules/audio_processing/agc2/rnn_vad/rnn.h"
#include "rtc_base/checks.h"
#include "third_party/rnnoise/src/rnn_vad_weights.h"
namespace webrtc {
namespace rnn_vad {
namespace {
using ::rnnoise::kInputLayerInputSize;
static_assert(kFeatureVectorSize == kInputLayerInputSize, "");
using ::rnnoise::kInputDenseBias;
using ::rnnoise::kInputDenseWeights;
using ::rnnoise::kInputLayerOutputSize;
static_assert(kInputLayerOutputSize <= kFullyConnectedLayerMaxUnits, "");
using ::rnnoise::kHiddenGruBias;
using ::rnnoise::kHiddenGruRecurrentWeights;
using ::rnnoise::kHiddenGruWeights;
using ::rnnoise::kHiddenLayerOutputSize;
static_assert(kHiddenLayerOutputSize <= kGruLayerMaxUnits, "");
using ::rnnoise::kOutputDenseBias;
using ::rnnoise::kOutputDenseWeights;
using ::rnnoise::kOutputLayerOutputSize;
static_assert(kOutputLayerOutputSize <= kFullyConnectedLayerMaxUnits, "");
} // namespace
RnnVad::RnnVad(const AvailableCpuFeatures& cpu_features)
: input_(kInputLayerInputSize,
kInputLayerOutputSize,
kInputDenseBias,
kInputDenseWeights,
ActivationFunction::kTansigApproximated,
cpu_features,
/*layer_name=*/"FC1"),
hidden_(kInputLayerOutputSize,
kHiddenLayerOutputSize,
kHiddenGruBias,
kHiddenGruWeights,
kHiddenGruRecurrentWeights,
cpu_features,
/*layer_name=*/"GRU1"),
output_(kHiddenLayerOutputSize,
kOutputLayerOutputSize,
kOutputDenseBias,
kOutputDenseWeights,
ActivationFunction::kSigmoidApproximated,
// The output layer is just 24x1. The unoptimized code is faster.
NoAvailableCpuFeatures(),
/*layer_name=*/"FC2") {
// Input-output chaining size checks.
RTC_DCHECK_EQ(input_.size(), hidden_.input_size())
<< "The input and the hidden layers sizes do not match.";
RTC_DCHECK_EQ(hidden_.size(), output_.input_size())
<< "The hidden and the output layers sizes do not match.";
}
RnnVad::~RnnVad() = default;
void RnnVad::Reset() {
hidden_.Reset();
}
float RnnVad::ComputeVadProbability(
ArrayView<const float, kFeatureVectorSize> feature_vector,
bool is_silence) {
if (is_silence) {
Reset();
return 0.f;
}
input_.ComputeOutput(feature_vector);
hidden_.ComputeOutput(input_);
output_.ComputeOutput(hidden_);
RTC_DCHECK_EQ(output_.size(), 1);
return output_.data()[0];
}
} // namespace rnn_vad
} // namespace webrtc
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