rnn_gru.h - mozsearch

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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,

                      rtc::ArrayView<const int8_t> bias,

                      rtc::ArrayView<const int8_t> weights,

                      rtc::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(rtc::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_