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/*
* Copyright (c) 2020 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.
*/
#ifndef MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_GRU_H_
#define MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_GRU_H_
#include <array>
#include <vector>
#include "absl/strings/string_view.h"
#include "api/array_view.h"
#include "modules/audio_processing/agc2/cpu_features.h"
#include "modules/audio_processing/agc2/rnn_vad/vector_math.h"
namespace webrtc {
namespace rnn_vad {
// Maximum number of units for a GRU layer.
constexpr int kGruLayerMaxUnits = 24;
// Recurrent layer with gated recurrent units (GRUs) with sigmoid and ReLU as
// activation functions for the update/reset and output gates respectively.
class GatedRecurrentLayer {
public:
// Ctor. `output_size` cannot be greater than `kGruLayerMaxUnits`.
GatedRecurrentLayer(int input_size,
int output_size,
ArrayView<const int8_t> bias,
ArrayView<const int8_t> weights,
ArrayView<const int8_t> recurrent_weights,
const AvailableCpuFeatures& cpu_features,
absl::string_view layer_name);
GatedRecurrentLayer(const GatedRecurrentLayer&) = delete;
GatedRecurrentLayer& operator=(const GatedRecurrentLayer&) = delete;
~GatedRecurrentLayer();
// Returns the size of the input vector.
int input_size() const { return input_size_; }
// Returns the pointer to the first element of the output buffer.
const float* data() const { return state_.data(); }
// Returns the size of the output buffer.
int size() const { return output_size_; }
// Resets the GRU state.
void Reset();
// Computes the recurrent layer output and updates the status.
void ComputeOutput(ArrayView<const float> input);
private:
const int input_size_;
const int output_size_;
const std::vector<float> bias_;
const std::vector<float> weights_;
const std::vector<float> recurrent_weights_;
const VectorMath vector_math_;
// Over-allocated array with size equal to `output_size_`.
std::array<float, kGruLayerMaxUnits> state_;
};
} // namespace rnn_vad
} // namespace webrtc
#endif // MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_GRU_H_
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