230 lines
6.7 KiB
C++
230 lines
6.7 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 SqrtAVX2(rtc::ArrayView<float> x);
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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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case Aec3Optimization::kAvx2:
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SqrtAVX2(x);
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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 MultiplyAVX2(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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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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case Aec3Optimization::kAvx2:
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MultiplyAVX2(x, y, z);
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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 AccumulateAVX2(rtc::ArrayView<const float> x, rtc::ArrayView<float> z);
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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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case Aec3Optimization::kAvx2:
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AccumulateAVX2(x, z);
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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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