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The implementations for the fully connected layer can be simlpified by using `VectorMath:DotProduct()`. In this way, it is also possible to remove (nearly) duplicated SIMD code, reduce the binary size and more easily maintain the code. This CL also forces unoptimized code for the output layer of the VAD, which is a FC 24x1 layer. A slight improvement of the realtime has been measured (delta ~ +5x). Bug: webrtc:10480 Change-Id: Iee93bd59f7905ebf96275dbbfeb3c921baf4e8db Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/195580 Commit-Queue: Alessio Bazzica <alessiob@webrtc.org> Reviewed-by: Ivo Creusen <ivoc@webrtc.org> Cr-Commit-Position: refs/heads/master@{#32806}
72 lines
2.6 KiB
C++
72 lines
2.6 KiB
C++
/*
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* Copyright (c) 2020 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#ifndef MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_FC_H_
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#define MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_FC_H_
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#include <array>
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#include <vector>
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#include "absl/strings/string_view.h"
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#include "api/array_view.h"
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#include "api/function_view.h"
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#include "modules/audio_processing/agc2/cpu_features.h"
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#include "modules/audio_processing/agc2/rnn_vad/vector_math.h"
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namespace webrtc {
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namespace rnn_vad {
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// Activation function for a neural network cell.
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enum class ActivationFunction { kTansigApproximated, kSigmoidApproximated };
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// Maximum number of units for an FC layer.
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constexpr int kFullyConnectedLayerMaxUnits = 24;
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// Fully-connected layer with a custom activation function which owns the output
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// buffer.
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class FullyConnectedLayer {
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public:
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// Ctor. `output_size` cannot be greater than `kFullyConnectedLayerMaxUnits`.
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FullyConnectedLayer(int input_size,
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int output_size,
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rtc::ArrayView<const int8_t> bias,
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rtc::ArrayView<const int8_t> weights,
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ActivationFunction activation_function,
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const AvailableCpuFeatures& cpu_features,
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absl::string_view layer_name);
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FullyConnectedLayer(const FullyConnectedLayer&) = delete;
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FullyConnectedLayer& operator=(const FullyConnectedLayer&) = delete;
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~FullyConnectedLayer();
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// Returns the size of the input vector.
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int input_size() const { return input_size_; }
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// Returns the pointer to the first element of the output buffer.
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const float* data() const { return output_.data(); }
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// Returns the size of the output buffer.
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int size() const { return output_size_; }
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// Computes the fully-connected layer output.
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void ComputeOutput(rtc::ArrayView<const float> input);
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private:
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const int input_size_;
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const int output_size_;
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const std::vector<float> bias_;
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const std::vector<float> weights_;
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const VectorMath vector_math_;
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rtc::FunctionView<float(float)> activation_function_;
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// Over-allocated array with size equal to `output_size_`.
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std::array<float, kFullyConnectedLayerMaxUnits> output_;
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};
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} // namespace rnn_vad
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} // namespace webrtc
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#endif // MODULES_AUDIO_PROCESSING_AGC2_RNN_VAD_RNN_FC_H_
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