mirror of
https://github.com/danog/libtgvoip.git
synced 2024-12-02 17:51:06 +01:00
5caaaafa42
I'm now using the entire audio processing module from WebRTC as opposed to individual DSP algorithms pulled from there before. Seems to work better this way.
215 lines
6.3 KiB
C++
215 lines
6.3 KiB
C++
/*
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* Copyright (c) 2017 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_AEC3_VECTOR_MATH_H_
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#define MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
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// Defines WEBRTC_ARCH_X86_FAMILY, used below.
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#include "rtc_base/system/arch.h"
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#if defined(WEBRTC_HAS_NEON)
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#include <arm_neon.h>
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#endif
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#if defined(WEBRTC_ARCH_X86_FAMILY)
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#include <emmintrin.h>
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#endif
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#include <math.h>
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#include <algorithm>
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#include <array>
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#include <functional>
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#include "api/array_view.h"
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#include "modules/audio_processing/aec3/aec3_common.h"
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#include "rtc_base/checks.h"
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namespace webrtc {
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namespace aec3 {
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// Provides optimizations for mathematical operations based on vectors.
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class VectorMath {
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public:
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explicit VectorMath(Aec3Optimization optimization)
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: optimization_(optimization) {}
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// Elementwise square root.
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void Sqrt(rtc::ArrayView<float> x) {
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switch (optimization_) {
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#if defined(WEBRTC_ARCH_X86_FAMILY)
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case Aec3Optimization::kSse2: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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__m128 g = _mm_loadu_ps(&x[j]);
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g = _mm_sqrt_ps(g);
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_mm_storeu_ps(&x[j], g);
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}
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for (; j < x_size; ++j) {
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x[j] = sqrtf(x[j]);
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}
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} break;
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#endif
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#if defined(WEBRTC_HAS_NEON)
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case Aec3Optimization::kNeon: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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float32x4_t g = vld1q_f32(&x[j]);
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#if !defined(WEBRTC_ARCH_ARM64)
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float32x4_t y = vrsqrteq_f32(g);
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// Code to handle sqrt(0).
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// If the input to sqrtf() is zero, a zero will be returned.
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// If the input to vrsqrteq_f32() is zero, positive infinity is
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// returned.
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const uint32x4_t vec_p_inf = vdupq_n_u32(0x7F800000);
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// check for divide by zero
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const uint32x4_t div_by_zero =
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vceqq_u32(vec_p_inf, vreinterpretq_u32_f32(y));
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// zero out the positive infinity results
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y = vreinterpretq_f32_u32(
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vandq_u32(vmvnq_u32(div_by_zero), vreinterpretq_u32_f32(y)));
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// from arm documentation
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// The Newton-Raphson iteration:
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// y[n+1] = y[n] * (3 - d * (y[n] * y[n])) / 2)
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// converges to (1/√d) if y0 is the result of VRSQRTE applied to d.
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//
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// Note: The precision did not improve after 2 iterations.
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for (int i = 0; i < 2; i++) {
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y = vmulq_f32(vrsqrtsq_f32(vmulq_f32(y, y), g), y);
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}
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// sqrt(g) = g * 1/sqrt(g)
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g = vmulq_f32(g, y);
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#else
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g = vsqrtq_f32(g);
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#endif
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vst1q_f32(&x[j], g);
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}
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for (; j < x_size; ++j) {
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x[j] = sqrtf(x[j]);
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}
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}
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#endif
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break;
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default:
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std::for_each(x.begin(), x.end(), [](float& a) { a = sqrtf(a); });
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}
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}
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// Elementwise vector multiplication z = x * y.
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void Multiply(rtc::ArrayView<const float> x,
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rtc::ArrayView<const float> y,
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rtc::ArrayView<float> z) {
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RTC_DCHECK_EQ(z.size(), x.size());
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RTC_DCHECK_EQ(z.size(), y.size());
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switch (optimization_) {
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#if defined(WEBRTC_ARCH_X86_FAMILY)
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case Aec3Optimization::kSse2: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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const __m128 x_j = _mm_loadu_ps(&x[j]);
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const __m128 y_j = _mm_loadu_ps(&y[j]);
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const __m128 z_j = _mm_mul_ps(x_j, y_j);
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_mm_storeu_ps(&z[j], z_j);
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}
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for (; j < x_size; ++j) {
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z[j] = x[j] * y[j];
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}
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} break;
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#endif
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#if defined(WEBRTC_HAS_NEON)
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case Aec3Optimization::kNeon: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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const float32x4_t x_j = vld1q_f32(&x[j]);
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const float32x4_t y_j = vld1q_f32(&y[j]);
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const float32x4_t z_j = vmulq_f32(x_j, y_j);
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vst1q_f32(&z[j], z_j);
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}
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for (; j < x_size; ++j) {
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z[j] = x[j] * y[j];
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}
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} break;
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#endif
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default:
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std::transform(x.begin(), x.end(), y.begin(), z.begin(),
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std::multiplies<float>());
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}
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}
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// Elementwise vector accumulation z += x.
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void Accumulate(rtc::ArrayView<const float> x, rtc::ArrayView<float> z) {
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RTC_DCHECK_EQ(z.size(), x.size());
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switch (optimization_) {
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#if defined(WEBRTC_ARCH_X86_FAMILY)
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case Aec3Optimization::kSse2: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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const __m128 x_j = _mm_loadu_ps(&x[j]);
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__m128 z_j = _mm_loadu_ps(&z[j]);
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z_j = _mm_add_ps(x_j, z_j);
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_mm_storeu_ps(&z[j], z_j);
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}
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for (; j < x_size; ++j) {
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z[j] += x[j];
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}
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} break;
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#endif
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#if defined(WEBRTC_HAS_NEON)
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case Aec3Optimization::kNeon: {
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const int x_size = static_cast<int>(x.size());
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const int vector_limit = x_size >> 2;
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int j = 0;
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for (; j < vector_limit * 4; j += 4) {
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const float32x4_t x_j = vld1q_f32(&x[j]);
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float32x4_t z_j = vld1q_f32(&z[j]);
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z_j = vaddq_f32(z_j, x_j);
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vst1q_f32(&z[j], z_j);
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}
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for (; j < x_size; ++j) {
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z[j] += x[j];
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}
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} break;
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#endif
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default:
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std::transform(x.begin(), x.end(), z.begin(), z.begin(),
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std::plus<float>());
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}
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}
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private:
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Aec3Optimization optimization_;
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};
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} // namespace aec3
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} // namespace webrtc
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#endif // MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
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