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5247070f5d
Bug: webrtc:10480 Change-Id: I6c49e728ed61647b098c20a6d8a856005066ab75 Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/200840 Reviewed-by: Alessio Bazzica <alessiob@webrtc.org> Reviewed-by: Sam Zackrisson <saza@webrtc.org> Commit-Queue: Alessio Bazzica <alessiob@webrtc.org> Cr-Commit-Position: refs/heads/master@{#32930}
111 lines
4.4 KiB
C++
111 lines
4.4 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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#include "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 "api/array_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/test_utils.h"
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#include "modules/audio_processing/test/performance_timer.h"
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#include "rtc_base/logging.h"
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#include "rtc_base/system/arch.h"
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#include "test/gtest.h"
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#include "third_party/rnnoise/src/rnn_vad_weights.h"
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namespace webrtc {
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namespace rnn_vad {
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namespace {
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using ::rnnoise::kInputDenseBias;
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using ::rnnoise::kInputDenseWeights;
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using ::rnnoise::kInputLayerInputSize;
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using ::rnnoise::kInputLayerOutputSize;
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// Fully connected layer test data.
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constexpr std::array<float, 42> kFullyConnectedInputVector = {
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-1.00131f, -0.627069f, -7.81097f, 7.86285f, -2.87145f, 3.32365f,
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-0.653161f, 0.529839f, -0.425307f, 0.25583f, 0.235094f, 0.230527f,
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-0.144687f, 0.182785f, 0.57102f, 0.125039f, 0.479482f, -0.0255439f,
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-0.0073141f, -0.147346f, -0.217106f, -0.0846906f, -8.34943f, 3.09065f,
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1.42628f, -0.85235f, -0.220207f, -0.811163f, 2.09032f, -2.01425f,
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-0.690268f, -0.925327f, -0.541354f, 0.58455f, -0.606726f, -0.0372358f,
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0.565991f, 0.435854f, 0.420812f, 0.162198f, -2.13f, 10.0089f};
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constexpr std::array<float, 24> kFullyConnectedExpectedOutput = {
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-0.623293f, -0.988299f, 0.999378f, 0.967168f, 0.103087f, -0.978545f,
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-0.856347f, 0.346675f, 1.f, -0.717442f, -0.544176f, 0.960363f,
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0.983443f, 0.999991f, -0.824335f, 0.984742f, 0.990208f, 0.938179f,
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0.875092f, 0.999846f, 0.997707f, -0.999382f, 0.973153f, -0.966605f};
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class RnnFcParametrization
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: public ::testing::TestWithParam<AvailableCpuFeatures> {};
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// Checks that the output of a fully connected layer is within tolerance given
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// test input data.
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TEST_P(RnnFcParametrization, CheckFullyConnectedLayerOutput) {
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FullyConnectedLayer fc(kInputLayerInputSize, kInputLayerOutputSize,
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kInputDenseBias, kInputDenseWeights,
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ActivationFunction::kTansigApproximated,
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/*cpu_features=*/GetParam(),
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/*layer_name=*/"FC");
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fc.ComputeOutput(kFullyConnectedInputVector);
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ExpectNearAbsolute(kFullyConnectedExpectedOutput, fc, 1e-5f);
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}
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TEST_P(RnnFcParametrization, DISABLED_BenchmarkFullyConnectedLayer) {
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const AvailableCpuFeatures cpu_features = GetParam();
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FullyConnectedLayer fc(kInputLayerInputSize, kInputLayerOutputSize,
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kInputDenseBias, kInputDenseWeights,
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ActivationFunction::kTansigApproximated, cpu_features,
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/*layer_name=*/"FC");
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constexpr int kNumTests = 10000;
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::webrtc::test::PerformanceTimer perf_timer(kNumTests);
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for (int k = 0; k < kNumTests; ++k) {
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perf_timer.StartTimer();
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fc.ComputeOutput(kFullyConnectedInputVector);
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perf_timer.StopTimer();
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}
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RTC_LOG(LS_INFO) << "CPU features: " << cpu_features.ToString() << " | "
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<< (perf_timer.GetDurationAverage() / 1000) << " +/- "
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<< (perf_timer.GetDurationStandardDeviation() / 1000)
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<< " ms";
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}
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// Finds the relevant CPU features combinations to test.
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std::vector<AvailableCpuFeatures> GetCpuFeaturesToTest() {
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std::vector<AvailableCpuFeatures> v;
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v.push_back(NoAvailableCpuFeatures());
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AvailableCpuFeatures available = GetAvailableCpuFeatures();
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if (available.sse2) {
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v.push_back({/*sse2=*/true, /*avx2=*/false, /*neon=*/false});
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}
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if (available.avx2) {
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v.push_back({/*sse2=*/false, /*avx2=*/true, /*neon=*/false});
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}
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if (available.neon) {
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v.push_back({/*sse2=*/false, /*avx2=*/false, /*neon=*/true});
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}
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return v;
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}
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INSTANTIATE_TEST_SUITE_P(
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RnnVadTest,
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RnnFcParametrization,
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::testing::ValuesIn(GetCpuFeaturesToTest()),
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[](const ::testing::TestParamInfo<AvailableCpuFeatures>& info) {
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return info.param.ToString();
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});
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} // namespace
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} // namespace rnn_vad
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} // namespace webrtc
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