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The FixedGainController is used in two places. One is the AudioMixer. There it's used to limit the audio level after adding streams. The other is GainController2, where it's placed after steps that could boost the audio level outside the allowed range. We log metrics from the FGC. To avoid confusion, this CL makes the two use cases log to different histograms. Chromium histogram CL is https://chromium-review.googlesource.com/c/chromium/src/+/1170833 Bug: webrtc:7494 Change-Id: I1abe60fd8e96556f144d2ee576254b15beca1174 Reviewed-on: https://webrtc-review.googlesource.com/93464 Commit-Queue: Alex Loiko <aleloi@webrtc.org> Reviewed-by: Ivo Creusen <ivoc@webrtc.org> Reviewed-by: Åsa Persson <asapersson@webrtc.org> Cr-Commit-Position: refs/heads/master@{#24284}
202 lines
7.2 KiB
C++
202 lines
7.2 KiB
C++
/*
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* Copyright (c) 2018 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 <array>
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#include <vector>
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#include "api/array_view.h"
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#include "common_audio/include/audio_util.h"
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#include "modules/audio_processing/agc2/agc2_common.h"
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#include "modules/audio_processing/agc2/compute_interpolated_gain_curve.h"
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#include "modules/audio_processing/agc2/interpolated_gain_curve.h"
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#include "modules/audio_processing/agc2/limiter.h"
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#include "modules/audio_processing/logging/apm_data_dumper.h"
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#include "rtc_base/checks.h"
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#include "rtc_base/gunit.h"
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namespace webrtc {
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namespace {
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constexpr double kLevelEpsilon = 1e-2 * kMaxAbsFloatS16Value;
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constexpr float kInterpolatedGainCurveTolerance = 1.f / 32768.f;
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ApmDataDumper apm_data_dumper(0);
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const Limiter limiter;
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} // namespace
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TEST(AutomaticGainController2InterpolatedGainCurve, CreateUse) {
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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kLevelEpsilon, DbfsToFloatS16(limiter.max_input_level_db() + 1), 500);
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for (const auto level : levels) {
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EXPECT_GE(igc.LookUpGainToApply(level), 0.0f);
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}
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckValidOutput) {
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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kLevelEpsilon, limiter.max_input_level_linear() * 2.0, 500);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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const float gain = igc.LookUpGainToApply(level);
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EXPECT_LE(0.0f, gain);
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EXPECT_LE(gain, 1.0f);
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}
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckMonotonicity) {
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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kLevelEpsilon, limiter.max_input_level_linear() + kLevelEpsilon + 0.5,
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500);
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float prev_gain = igc.LookUpGainToApply(0.0f);
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for (const auto level : levels) {
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const float gain = igc.LookUpGainToApply(level);
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EXPECT_GE(prev_gain, gain);
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prev_gain = gain;
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}
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckApproximation) {
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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kLevelEpsilon, limiter.max_input_level_linear() - kLevelEpsilon, 500);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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EXPECT_LT(
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std::fabs(limiter.GetGainLinear(level) - igc.LookUpGainToApply(level)),
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kInterpolatedGainCurveTolerance);
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}
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckRegionBoundaries) {
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const std::vector<double> levels{
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{kLevelEpsilon, limiter.knee_start_linear() + kLevelEpsilon,
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limiter.limiter_start_linear() + kLevelEpsilon,
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limiter.max_input_level_linear() + kLevelEpsilon}};
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for (const auto level : levels) {
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igc.LookUpGainToApply(level);
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}
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const auto stats = igc.get_stats();
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EXPECT_EQ(1ul, stats.look_ups_identity_region);
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EXPECT_EQ(1ul, stats.look_ups_knee_region);
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EXPECT_EQ(1ul, stats.look_ups_limiter_region);
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EXPECT_EQ(1ul, stats.look_ups_saturation_region);
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckIdentityRegion) {
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constexpr size_t kNumSteps = 10;
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels =
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test::LinSpace(kLevelEpsilon, limiter.knee_start_linear(), kNumSteps);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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EXPECT_EQ(1.0f, igc.LookUpGainToApply(level));
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}
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const auto stats = igc.get_stats();
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EXPECT_EQ(kNumSteps - 1, stats.look_ups_identity_region);
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EXPECT_EQ(1ul, stats.look_ups_knee_region);
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EXPECT_EQ(0ul, stats.look_ups_limiter_region);
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EXPECT_EQ(0ul, stats.look_ups_saturation_region);
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}
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TEST(AutomaticGainController2InterpolatedGainCurve,
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CheckNoOverApproximationKnee) {
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constexpr size_t kNumSteps = 10;
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels =
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test::LinSpace(limiter.knee_start_linear() + kLevelEpsilon,
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limiter.limiter_start_linear(), kNumSteps);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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// Small tolerance added (needed because comparing a float with a double).
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EXPECT_LE(igc.LookUpGainToApply(level),
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limiter.GetGainLinear(level) + 1e-7);
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}
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const auto stats = igc.get_stats();
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EXPECT_EQ(0ul, stats.look_ups_identity_region);
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EXPECT_EQ(kNumSteps - 1, stats.look_ups_knee_region);
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EXPECT_EQ(1ul, stats.look_ups_limiter_region);
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EXPECT_EQ(0ul, stats.look_ups_saturation_region);
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}
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TEST(AutomaticGainController2InterpolatedGainCurve,
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CheckNoOverApproximationBeyondKnee) {
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constexpr size_t kNumSteps = 10;
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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limiter.limiter_start_linear() + kLevelEpsilon,
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limiter.max_input_level_linear() - kLevelEpsilon, kNumSteps);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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// Small tolerance added (needed because comparing a float with a double).
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EXPECT_LE(igc.LookUpGainToApply(level),
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limiter.GetGainLinear(level) + 1e-7);
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}
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const auto stats = igc.get_stats();
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EXPECT_EQ(0ul, stats.look_ups_identity_region);
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EXPECT_EQ(0ul, stats.look_ups_knee_region);
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EXPECT_EQ(kNumSteps, stats.look_ups_limiter_region);
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EXPECT_EQ(0ul, stats.look_ups_saturation_region);
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}
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TEST(AutomaticGainController2InterpolatedGainCurve,
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CheckNoOverApproximationWithSaturation) {
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constexpr size_t kNumSteps = 3;
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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const auto levels = test::LinSpace(
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limiter.max_input_level_linear() + kLevelEpsilon,
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limiter.max_input_level_linear() + kLevelEpsilon + 0.5, kNumSteps);
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for (const auto level : levels) {
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SCOPED_TRACE(std::to_string(level));
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EXPECT_LE(igc.LookUpGainToApply(level), limiter.GetGainLinear(level));
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}
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const auto stats = igc.get_stats();
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EXPECT_EQ(0ul, stats.look_ups_identity_region);
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EXPECT_EQ(0ul, stats.look_ups_knee_region);
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EXPECT_EQ(0ul, stats.look_ups_limiter_region);
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EXPECT_EQ(kNumSteps, stats.look_ups_saturation_region);
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}
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TEST(AutomaticGainController2InterpolatedGainCurve, CheckApproximationParams) {
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test::InterpolatedParameters parameters =
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test::ComputeInterpolatedGainCurveApproximationParams();
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InterpolatedGainCurve igc(&apm_data_dumper, "");
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for (size_t i = 0; i < kInterpolatedGainCurveTotalPoints; ++i) {
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// The tolerance levels are chosen to account for deviations due
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// to computing with single precision floating point numbers.
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EXPECT_NEAR(igc.approximation_params_x_[i],
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parameters.computed_approximation_params_x[i], 0.9f);
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EXPECT_NEAR(igc.approximation_params_m_[i],
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parameters.computed_approximation_params_m[i], 0.00001f);
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EXPECT_NEAR(igc.approximation_params_q_[i],
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parameters.computed_approximation_params_q[i], 0.001f);
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}
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}
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} // namespace webrtc
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