xref: /aosp_15_r20/external/libaom/av1/encoder/arm/cnn_neon.c (revision 77c1e3ccc04c968bd2bc212e87364f250e820521)

/*
 * Copyright (c) 2023, Alliance for Open Media. All rights reserved.
 *
 * This source code is subject to the terms of the BSD 2 Clause License and
 * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
 * was not distributed with this source code in the LICENSE file, you can
 * obtain it at www.aomedia.org/license/software. If the Alliance for Open
 * Media Patent License 1.0 was not distributed with this source code in the
 * PATENTS file, you can obtain it at www.aomedia.org/license/patent.
 */

#include <arm_neon.h>
#include <assert.h>
#include <math.h>
#include <stdbool.h>

#include "config/aom_config.h"
#include "config/av1_rtcd.h"

#include "aom_dsp/aom_dsp_common.h"
#include "aom_dsp/arm/sum_neon.h"
#include "av1/common/av1_common_int.h"
#include "av1/encoder/cnn.h"
#include "av1/encoder/partition_cnn_weights.h"

// The CNN weights used in av1_cnn_convolve_no_maxpool_padding_valid are
// declared (av1_intra_mode_cnn_partition_cnn_layer_[01234]_kernel) in
// partition_cnn_weights.h. However, to enable linear memory access, rearrange
// the weight tables here.
static const float weights_layer_1[] = {
  0.228403f,  0.031690f,  -0.251710f, -0.046230f, 0.413294f,  -0.236732f,
  -0.038291f, 0.210766f,  0.427196f,  -0.384319f, -0.439463f, 0.366015f,
  0.112263f,  -0.144168f, -0.075017f, 0.119629f,  0.325200f,  -0.678246f,
  -0.370826f, -0.341362f, -0.503392f, 0.400884f,  0.465214f,  -0.360847f,
  0.187100f,  -0.190757f, -0.131906f, 0.121492f,  -0.303556f, -0.007658f,
  0.380077f,  -0.066394f, -0.016043f, -1.490730f, -0.120682f, 0.132062f,
  0.086185f,  -0.042766f, -0.087069f, 0.029426f,  0.309583f,  -0.029985f,
  -0.297429f, -0.018139f, -0.688828f, 0.756607f,  0.706410f,  -0.696826f,
  -0.087793f, -0.023304f, -0.012332f, -0.018043f, -0.410268f, 0.352143f,
  0.391284f,  -0.363178f, -0.295034f, 0.160246f,  -0.149446f, 0.260145f,
  -0.252249f, 0.190826f,  0.251206f,  -0.270796f, -0.979219f, 0.884880f,
  0.962057f,  -0.847601f, -0.011053f, 0.118765f,  -0.028428f, -0.020138f,
  0.400274f,  -0.382845f, -0.462766f, 0.390654f,  0.361223f,  -0.320068f,
  -0.372084f, 0.313196f,  0.241933f,  -0.416614f, -0.008722f, -0.255078f,
  0.078730f,  -0.381935f, -0.204577f, 0.159768f,  0.071853f,  -0.126294f,
  -0.036186f, -0.007900f, 0.380071f,  -0.298882f, 0.387941f,  -0.267350f,
  -0.586802f, 0.477785f,  -0.000013f, 0.197296f,  -0.079154f, -0.005811f,
  -0.044300f, -0.021192f, -0.020879f, -0.005265f, 0.082277f,  -0.139132f,
  -0.239237f, 0.440234f,  -0.542342f, 0.378360f,  -0.070974f, 0.272702f,
  -0.278939f, -0.044948f, -0.134197f, -0.007172f, -0.353628f, -0.128091f,
  0.357458f,  -0.037614f, -0.144983f, 0.220623f,  -0.003394f, -0.070166f,
  0.200370f,  -0.166037f, 0.224448f,  -0.012990f, -0.098853f, 0.008613f,
  -0.017669f, 0.070641f,  0.174530f,  -0.119822f, -0.065096f, 0.118487f,
  -0.024764f, -0.050466f, 0.066631f,  -0.075896f, -0.062363f, 0.212604f,
  -0.377322f, 0.306306f,  -0.399733f, 0.238624f,  0.233571f,  -0.344080f,
  0.462491f,  -0.565210f, -0.035074f, -0.010459f, 0.084382f,  0.052294f,
  0.065714f,  0.013716f,  0.135036f,  0.000588f,  0.181079f,  -0.566344f,
  0.395561f,  -0.398509f, 0.450017f,  -1.462710f, 1.138280f,  -0.447774f,
  0.247936f,  -0.417067f, 0.165997f,  -0.458632f, -0.018527f, 0.308461f,
  0.541266f,  0.162257f,  0.601786f,  -1.275840f, -0.373404f, -0.589747f,
  0.026539f,  -0.219327f, 0.142972f,  -0.018496f, 0.075204f,  -0.775190f,
  0.237307f,  -0.348252f, 0.117792f,  -0.094332f, 0.363101f,  -0.065025f,
  0.816662f,  0.590110f,  0.752202f,  -0.308599f, 0.258337f,  -0.842085f,
  0.695788f,  -0.205615f, 0.093930f,  -0.392536f, 0.463093f,  -0.432456f,
  0.041660f,  -0.827264f, 0.309128f,  -0.354658f, 0.451957f,  -1.406640f,
  0.773192f,  -0.892943f, 0.134856f,  -0.467808f, 0.306003f,  -0.226560f,
  0.086865f,  -0.104102f, 0.148098f,  -0.082658f, 0.316655f,  -1.028310f,
  0.741566f,  -0.345326f, 0.052379f,  -0.275613f, 0.191765f,  -0.162391f,
  0.000976f,  0.093061f,  0.068649f,  0.033582f,  0.239727f,  -0.647769f,
  0.218493f,  -0.397120f, 0.268229f,  -0.303424f, 0.185393f,  -0.314189f,
  0.101728f,  -0.163083f, -0.084989f, 0.136783f,  -0.264346f, 0.465914f,
  0.220395f,  -0.252968f, -0.326661f, 0.271483f,  0.374717f,  -0.311570f,
  -0.082119f, 0.020870f,  0.091975f,  -0.030582f, -0.487148f, 0.198912f,
  0.024554f,  -0.749363f, -0.102267f, 0.097787f,  0.141459f,  -0.110706f,
  0.079467f,  -0.082570f, -0.347567f, 0.341043f,  -0.137871f, 0.112319f,
  0.064733f,  -0.082869f, 0.269999f,  -0.408184f, -0.183443f, 0.180608f,
  0.223345f,  -0.357376f, -0.244593f, 0.355348f,  -0.072701f, -0.034311f,
  0.096544f,  0.016407f,  0.417550f,  -0.367772f, -0.484535f, 0.405977f,
  0.314243f,  -0.099622f, -0.192218f, -0.012780f, 0.434551f,  -0.399047f,
  -0.531499f, 0.484513f,  -0.691352f, 0.872823f,  1.207720f,  -1.377490f,
  0.006872f,  -0.041453f, 0.007845f,  0.007463f,  0.467299f,  -0.476372f,
  -0.452606f, 0.452357f,  0.447332f,  -0.365632f, -0.332435f, 0.300284f,
  -0.290504f, 0.255410f,  0.310921f,  -0.293717f, -0.616299f, 0.594207f,
  0.461347f,  -0.449439f, 0.278455f,  0.285085f,  -1.201340f, -0.016463f,
  0.549095f,  0.610375f,  -4.608530f, -1.727390f, 0.150404f,  -0.012846f,
  -0.481148f, -0.182257f, 0.918796f,  0.213872f,  1.050410f,  0.681526f,
  -0.458777f, -0.710395f, -2.347200f, -0.277197f, 0.213294f,  0.337551f,
  -0.177710f, -0.152136f, 0.167666f,  0.308403f,  -1.248500f, -0.565367f,
  0.122054f,  0.087874f,  -0.476556f, -0.083548f, -0.358734f, -0.073131f,
  -0.146320f, -2.241960f, 0.697639f,  0.545581f,  -1.889700f, -0.267725f,
  0.433045f,  0.298224f,  -0.338508f, 0.250226f,  0.405675f,  0.447201f,
  -1.184690f, -0.473447f, 0.307403f,  0.711236f,  -3.191560f, -1.663980f,
  0.165201f,  0.101360f,  -0.624451f, -0.173269f, 0.089795f,  0.227478f,
  -0.136664f, 0.007907f,  0.131079f,  0.605374f,  -2.991620f, -1.723790f,
  0.082428f,  0.006781f,  -0.348732f, -0.019271f, -0.032040f, -0.067078f,
  -0.437166f, -0.144472f, 0.069844f,  0.194625f,  -0.162284f, -0.374656f,
  0.056472f,  -0.236524f, -0.114241f, -0.029161f, -0.222078f, -0.053435f,
  -0.313938f, -0.555472f, 1.037550f,  0.689968f,  0.575694f,  0.065826f,
  -0.659979f, -0.881351f, -0.626417f, -0.953975f, -0.576106f, -0.258708f,
  0.263004f,  -0.229847f, 0.463835f,  1.390960f,  -2.614480f, -1.272910f,
  0.065780f,  -0.058603f, 0.015612f,  0.104703f,  0.198028f,  0.262792f,
  0.253616f,  -0.079126f, -0.587381f, -0.739021f, -0.822676f, -0.795512f,
  0.193644f,  0.234643f,  -0.034407f, 0.421478f,  -0.572610f, -0.290714f,
  -0.257803f, -0.644835f, -0.536938f, -0.375899f, -0.651077f, -0.522576f,
  0.562564f,  0.834616f,  0.513893f,  0.649689f,  0.356530f,  0.400716f,
  0.300606f,  0.290505f,  0.584608f,  0.671574f,  0.564584f,  0.419870f,
  0.062061f,  0.018263f,  0.009831f,  0.084103f,  -0.128281f, -0.018818f,
  -0.187244f, 0.067210f,  0.437147f,  0.442029f,  0.444939f,  0.226661f,
  0.541609f,  0.444280f,  0.302795f,  0.633026f,  -0.180374f, 0.265197f,
  0.210404f,  -0.118916f, -0.294013f, -0.692627f, -0.402347f, -0.356287f,
  0.387578f,  0.385496f,  0.789542f,  0.690396f,  -0.203542f, -0.688546f,
  0.045319f,  -0.448747f, -0.157148f, 0.152581f,  0.022360f,  0.058358f,
  0.593007f,  1.131860f,  0.289006f,  1.015560f,  0.144942f,  -0.411577f,
  0.264794f,  -0.085791f, 0.156996f,  0.200340f,  0.169264f,  0.267615f,
  -0.361015f, -0.601842f, -0.442217f, -0.781086f, 0.112938f,  0.385305f,
  0.482454f,  0.470268f,  1.193390f,  0.589642f,  0.127638f,  -0.640946f,
  0.540310f,  0.741498f,  0.686937f,  0.435879f,  0.534523f,  0.693119f,
  0.817577f,  0.783109f,  0.021681f,  -0.004973f, 0.201236f,  -0.086311f,
  0.028628f,  0.227871f,  0.462751f,  0.126832f,  -0.389997f, -0.553965f,
  -0.343953f, -0.448517f, 0.053129f,  -0.115083f, 0.018138f,  -0.067131f,
  -0.293468f, -0.220700f, 0.074348f,  -0.273153f, 0.263637f,  0.122049f,
  0.153025f,  0.076292f,  0.142320f,  0.286734f,  0.100542f,  0.308660f,
  -0.759591f, -0.750938f, -0.788799f, -0.853076f, -0.588019f, -0.990063f,
  -0.692327f, -0.722904f, 0.084736f,  0.151068f,  0.159606f,  0.147715f,
  1.610180f,  1.950330f,  1.765670f,  2.265110f,  0.008262f,  0.185584f,
  0.039337f,  0.164721f,  0.479446f,  0.314083f,  0.043969f,  0.291320f,
  0.003400f,  -0.551190f, 0.060158f,  -0.147591f, 0.089117f,  0.042994f,
  0.042802f,  0.127392f,  -0.066172f, 0.078370f,  0.051408f,  0.014004f,
  0.086726f,  0.133334f,  -0.046733f, 0.155100f,  -0.118223f, -0.100778f,
  -0.225245f, -0.460397f, 0.892644f,  1.003770f,  0.405155f,  0.517477f,
  0.184585f,  0.279090f,  -0.036477f, 0.198703f,  0.027139f,  -0.055728f,
  -0.022396f, -0.147319f, 2.275540f,  2.014990f,  2.296800f,  2.081730f,
  -0.088713f, 0.105729f,  -0.027871f, -0.095047f, 0.012429f,  0.014244f,
  -0.014755f, -0.003017f, 1.332700f,  1.300040f,  1.464250f,  1.305030f,
  0.032568f,  0.118042f,  0.079632f,  -0.089405f, 0.163905f,  0.146608f,
  0.026502f,  0.065307f,  -0.056909f, -0.065052f, 0.069851f,  -0.082958f,
  0.023419f,  -0.026293f, 0.037616f,  -0.048096f, -0.073701f, -0.208295f,
  -0.782095f, 0.000523f,  0.374131f,  0.420946f,  0.466151f,  0.349651f,
  -0.679275f, -0.745827f, -0.379918f, -0.900107f, 0.044070f,  -0.347536f,
  -1.224390f, 0.740113f,  -0.779966f, 0.510920f,  -0.968597f, -0.095630f,
  0.120805f,  0.676803f,  -0.164827f, 0.172996f,  -0.106720f, 0.197527f,
  0.337561f,  0.571094f,  -0.279090f, -0.396697f, -0.253083f, -0.690170f,
  -0.363291f, 0.516921f,  0.489391f,  -0.920628f, 0.497572f,  0.483864f,
  -0.125696f, -0.338123f, -0.041517f, -0.534630f, -0.388465f, -0.784554f,
  0.215227f,  0.055088f,  0.179638f,  0.086997f,  0.569313f,  0.572926f,
  0.137182f,  -0.045485f, 0.118087f,  0.210383f,  0.212664f,  0.482443f,
  0.151921f,  0.307947f,  -0.084656f, -0.386206f, 0.542277f,  -0.207005f,
  0.073792f,  -1.013240f, 0.303581f,  0.270527f,  0.265985f,  0.332702f,
  0.848609f,  0.686757f,  0.767212f,  0.316901f,  -0.502460f, -0.567092f,
  -0.484799f, -0.173350f, -0.426863f, 0.222375f,  -0.200267f, -0.523758f,
  0.265180f,  -0.175648f, -0.229754f, 0.148740f,  0.402515f,  0.028243f,
  -0.366109f, 0.157232f,  -0.131564f, 0.055136f,  0.211046f,  -0.115542f,
  0.322379f,  -0.137768f, -0.247832f, 0.070394f,  0.058530f,  -0.295023f,
  -0.196022f, -0.109097f, 0.261285f,  -0.273585f, -0.240632f, 0.258326f,
  -0.077364f, 0.071405f,  -0.014766f, -0.008751f, -0.203622f, 0.177818f,
  0.116726f,  -0.116735f, -0.723616f, -0.700154f, 0.145082f,  -0.184949f,
  -0.287076f, 0.150405f,  0.258075f,  -0.157764f, -0.120909f, 0.105459f,
  0.113288f,  -0.092963f, 0.328183f,  -0.300115f, -0.361289f, 0.319792f,
  -0.048875f, 0.135673f,  0.132539f,  -0.162481f, 0.002109f,  0.065048f,
  -0.135969f, 0.061558f,  1.510670f,  -0.884925f, -0.827022f, 0.190311f,
  -0.060088f, -0.033362f, 0.013354f,  0.002847f,  0.353479f,  -0.462538f,
  -0.319638f, 0.424484f,  0.199540f,  -0.073843f, -0.140621f, 0.072133f,
  -0.098662f, 0.070613f,  0.031150f,  -0.021869f, -0.511253f, 0.503412f,
  0.565963f,  -0.576146f, -1.081700f, 0.047670f,  0.266687f,  0.524804f,
  -2.361150f, 0.147823f,  0.594717f,  0.956842f,  -1.048220f, 0.127083f,
  0.079581f,  0.065419f,  0.176783f,  0.653953f,  0.260967f,  0.537892f,
  -1.207580f, 0.245983f,  -0.727067f, 0.071755f,  -0.343025f, -0.173435f,
  0.215289f,  0.268578f,  -1.158560f, 0.039263f,  -0.132888f, 0.217132f,
  -0.622195f, -0.071256f, 0.317333f,  0.157614f,  -1.588250f, 0.316432f,
  -0.736720f, -0.041698f, -1.959280f, 0.083451f,  0.570584f,  0.327620f,
  -1.262200f, -0.026738f, 0.231198f,  0.326861f,  -1.644200f, -0.143833f,
  -0.079495f, 0.493026f,  -2.488090f, -0.034046f, 0.165884f,  1.074260f,
  -1.076980f, 0.248198f,  -0.017987f, 0.421900f,  -0.105860f, 0.076710f,
  0.002072f,  0.070264f,  -1.734750f, 0.227145f,  0.209220f,  0.851459f,
  -0.142369f, 0.066502f,  0.027816f,  0.044321f,  -0.186591f, -0.100340f,
  0.115580f,  0.192252f,  -0.892114f, 0.209531f,  -0.308243f, 0.367968f,
  -0.721770f, 0.220224f,  -0.062744f, 0.133754f,  0.040416f,  0.190428f,
  -0.035428f, 0.162974f,  0.116427f,  0.669393f,  0.278891f,  0.856676f,
  1.060390f,  0.936983f,  0.863355f,  0.990560f,  -0.147111f, -0.217883f,
  0.355794f,  -0.186530f, -0.275614f, -0.095719f, 0.167346f,  0.359078f,
  -0.079223f, -0.581596f, -0.213134f, -0.431123f, -0.516443f, -0.388628f,
  -0.643821f, -0.202345f, 0.426230f,  0.516923f,  0.548131f,  0.555973f,
  0.022286f,  0.361170f,  0.980065f,  0.648400f,  -0.056813f, -0.100310f,
  -0.439481f, -0.166454f, 0.412449f,  0.509400f,  0.316208f,  0.470293f,
  -0.827838f, -1.078380f, -1.047040f, -1.074560f, 0.274555f,  -0.316736f,
  0.128818f,  0.228566f,  -0.520967f, -0.731674f, -0.687887f, -0.536388f,
  -0.031187f, 0.041404f,  0.047821f,  0.064397f,  0.054230f,  0.105059f,
  -0.178671f, 0.176847f,  -0.394797f, -0.260255f, -0.333734f, -0.162345f,
  -0.444650f, -0.928438f, -0.705840f, -0.833162f, 0.306737f,  0.429699f,
  0.417298f,  0.478469f,  0.420903f,  0.676871f,  0.429677f,  0.616921f,
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  -0.137832f, 0.041197f,  0.410265f,  0.345129f,  0.653338f,  0.047050f,
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  -0.031349f, 0.151944f,  -0.160340f, 0.326798f,  -0.458067f, 0.636235f,
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  -0.104817f, -0.141882f, -0.026395f, 0.053014f,  0.143885f,  -0.207774f,
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  -0.684924f, 0.061105f,  -0.315884f, -0.392624f, 0.009805f,  -0.256597f,
  -0.146732f, 0.331039f,  0.362342f,  0.270851f,  0.067679f,  -0.071331f,
  -0.222423f, 0.081286f,  -0.208192f, -0.193816f, -0.008201f, -0.309340f,
  0.167556f,  0.106071f,  0.172254f,  -0.163790f, -0.142205f, -0.043182f,
  0.096145f,  0.145037f,  -0.066015f, -0.073194f, 0.132237f,  -0.088522f,
  -0.044292f, -0.487128f, 0.033389f,  -0.573548f, 0.185449f,  0.273593f,
  0.147503f,  0.457049f,  -0.021539f, 0.090786f,  0.009147f,  0.000899f,
  0.018088f,  0.115791f,  -0.079165f, 0.139388f,
};

static const float weights_layer_2[] = {
  0.153048f,  0.112901f,  0.136781f,  0.154580f,  0.091610f,  0.045165f,
  0.088490f,  0.116991f,  -0.463766f, -0.596567f, -0.567008f, -0.630565f,
  0.141874f,  0.095726f,  0.175427f,  0.145027f,  -0.969824f, -1.018190f,
  -1.073300f, -1.041130f, -0.070545f, -0.123600f, -0.114967f, -0.169453f,
  -0.267458f, -0.147730f, -0.161419f, -0.164894f, -0.117508f, -0.204389f,
  -0.122695f, -0.163107f, -0.003903f, -0.030470f, -0.037433f, -0.059568f,
  0.138243f,  0.091019f,  0.160372f,  0.141650f,  -0.544565f, -0.620004f,
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  0.084923f,  0.038345f,  0.066706f,  0.122083f,  0.267087f,  0.184419f,
  0.261478f,  0.255746f,  -0.245894f, -0.114980f, -0.193880f, -0.227785f,
  0.087536f,  0.095712f,  0.106105f,  0.099353f,  -0.059473f, -0.173247f,
  -0.202386f, -0.076010f, 0.125928f,  0.100793f,  0.119638f,  0.129623f,
  0.136593f,  0.102984f,  0.156550f,  0.140558f,  0.122524f,  0.051596f,
  0.084164f,  0.123630f,  0.072542f,  0.096063f,  0.083236f,  0.087630f,
  0.025900f,  0.023738f,  0.036385f,  0.053077f,  -0.029501f, 0.010544f,
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  0.129052f,  0.208112f,  0.145582f,  0.175502f,  0.018476f,  0.036349f,
  0.072417f,  0.061194f,  0.086985f,  0.117086f,  0.072465f,  0.129068f,
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  0.025135f,  -0.037748f, 0.004973f,  0.024778f,  0.041816f,  0.032111f,
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  0.309013f,  0.364376f,  0.361102f,  0.271566f,  0.116552f,  0.091160f,
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  -0.475608f, 0.077358f,  -0.002872f, 0.163890f,  -0.420298f, 0.072114f,
  0.121601f,  -0.016727f, 0.573853f,  -0.080196f, 0.193053f,  0.053012f,
  -0.454179f, 0.058563f,  0.067265f,  0.141154f,  0.412541f,  0.086933f,
  0.030407f,  -0.030413f, 0.478757f,  -0.097731f, 0.277072f,  -0.086393f,
  0.552604f,  -0.334201f, 0.091765f,  -0.270262f, -1.395060f, 0.271837f,
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  -0.459273f, 0.096183f,  0.153046f,  0.135818f,  0.759028f,  -0.177673f,
  -0.099966f, 0.103363f,  0.697289f,  -0.234184f, -0.048706f, -0.116099f,
  -0.282575f, 0.025655f,  -0.184759f, 0.040658f,  -0.558267f, 0.214087f,
  -0.095620f, 0.200522f,  0.278996f,  0.031959f,  0.122936f,  -0.209196f,
  -0.308217f, 0.092917f,  0.113269f,  0.136274f,  -0.037046f, 0.017263f,
  -0.194183f, 0.089133f,  -0.161244f, 0.042799f,  0.030557f,  0.153545f,
  -0.355048f, 0.070928f,  -0.152852f, 0.102875f,  -0.193649f, 0.007916f,
  -0.062952f, 0.050602f,  0.073671f,  0.143045f,  -5.978970f, -7.013850f,
  0.058713f,  0.076116f,  0.026445f,  -0.056599f, -0.005966f, 0.032234f,
  0.006753f,  -0.024528f, 0.120308f,  0.179939f,  -6.624630f, -7.638680f,
  0.026359f,  0.020758f,  0.194274f,  0.051489f,  -0.008491f, -0.028248f,
  -0.061328f, -0.134423f, -0.103951f, -0.110877f, 0.042263f,  0.127016f,
  0.012473f,  -0.008595f, 0.031357f,  0.087476f,  -0.084022f, -0.015590f,
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  0.301887f,  0.259556f,  -0.194127f, -0.090440f, -0.257959f, -0.259572f,
  -0.012273f, -0.049993f, -0.099431f, 0.012506f,  0.081526f,  0.166279f,
  0.042594f,  0.185121f,  0.148830f,  0.073161f,  0.201728f,  0.125747f,
  -0.295065f, -0.187585f, -0.333066f, -0.312291f, 0.253458f,  0.321585f,
  0.178844f,  0.219944f,  -0.763475f, -0.943374f, -0.816825f, -0.709901f,
  -0.166132f, 0.129186f,  0.015405f,  -0.065623f, -0.246006f, -0.340385f,
  -0.118155f, -0.384905f, -0.233883f, -0.400666f, -0.228597f, -0.228428f,
  -0.559083f, -0.377784f, -0.541458f, -0.542870f, 0.067400f,  0.122987f,
  0.180901f,  0.186004f,  -0.482910f, -0.424823f, -0.477831f, -0.394719f,
  0.091558f,  0.049248f,  0.049370f,  0.160429f,  0.133641f,  0.096625f,
  0.104429f,  0.100782f,  -0.238252f, -0.221459f, -0.196974f, -0.250393f,
  -3.071750f, -2.418450f, -0.861410f, -1.051580f, 0.071263f,  0.118014f,
  -0.028430f, -0.072073f, -0.074463f, 0.034168f,  0.044089f,  -0.091109f,
  -3.153840f, -2.945850f, -1.977360f, -1.498850f, -0.083429f, 0.131835f,
  -0.063865f, -0.065785f, -0.069346f, -0.015520f, -0.119551f, 0.044881f,
  -0.105280f, 0.127516f,  0.005255f,  -0.142777f, 0.061055f,  -0.117250f,
  0.020454f,  0.157879f,  -0.213812f, -0.151783f, 0.028583f,  0.137759f,
  -3.248250f, -3.005940f, -1.510540f, -1.475390f, 0.081874f,  -0.171465f,
  -0.135690f, -0.001989f, -0.227574f, -0.132799f, -0.359742f, -0.137197f,
  0.066324f,  0.039194f,  -0.050857f, 0.095166f,  0.044475f,  0.011221f,
  0.054904f,  0.061414f,  -0.039189f, 0.123751f,  -0.017171f, -0.008494f,
  -2.598220f, -2.832670f, -1.622030f, -1.201990f, 0.154313f,  -0.021436f,
  0.042190f,  0.143947f,  -0.090623f, 0.086853f,  0.143137f,  0.099821f,
  -1.732820f, -1.429730f, -0.775125f, -0.648036f, 0.082176f,  0.079448f,
  -0.040575f, 0.024511f,  -0.064105f, -0.117122f, -0.190323f, -0.182589f,
  -0.076430f, -0.095615f, -0.112513f, -0.101581f, 0.143037f,  0.148180f,
  0.430958f,  0.359225f,  0.001403f,  -0.080541f, -0.295001f, -0.156706f,
  0.426623f,  0.475597f,  0.455210f,  0.454352f,  0.074365f,  0.099440f,
  0.066348f,  -0.007078f, 0.008335f,  -0.097116f, -0.133687f, -0.110535f,
  0.204145f,  0.281478f,  0.078886f,  0.112857f,  -0.103620f, -0.068247f,
  0.191147f,  0.227593f,  -0.011816f, -0.058755f, -0.149477f, -0.101828f,
  0.079878f,  0.304949f,  0.557555f,  0.305288f,  -0.150955f, -0.118610f,
  0.052073f,  0.064707f,  -0.121728f, -0.151132f, -0.193987f, -0.175046f,
  0.043655f,  0.105270f,  -0.120715f, -0.040976f, 0.047776f,  -0.004443f,
  0.149606f,  0.111240f,  -0.047502f, -0.064146f, -0.151858f, -0.151872f,
  -0.160207f, -0.113846f, -0.081585f, -0.006708f, -0.203760f, -0.068597f,
  -0.179979f, -0.127779f, -0.062460f, -0.064513f, -0.121479f, -0.111122f,
  -0.212384f, -0.229157f, -0.283428f, -0.184891f,
};

static const float weights_layer_3[] = {
  -0.039388f, 0.033048f,  -0.113003f, -0.011642f, 0.170478f,  0.145713f,
  0.040189f,  -0.280129f, -0.049050f, -0.043788f, -0.157425f, 0.323829f,
  -0.250725f, -0.166349f, 0.101650f,  -0.049690f, 0.205606f,  0.281131f,
  0.623204f,  0.993452f,  -0.015115f, -0.138995f, 0.009473f,  0.157673f,
  -0.024687f, -0.067214f, 0.125566f,  -0.317619f, 0.057002f,  0.031202f,
  -0.018167f, 0.068542f,  0.011609f,  -0.020233f, -0.000428f, -0.035956f,
  -0.843274f, -0.800587f, -0.214917f, -0.221250f, 0.031255f,  -0.077330f,
  -0.074902f, -0.063979f, -0.055562f, 0.679495f,  0.146609f,  1.315330f,
  -0.118399f, -0.034539f, -0.050377f, 0.172867f,  -0.204607f, -0.034930f,
  0.176014f,  0.089747f,  -0.003889f, 0.044980f,  0.002386f,  -0.141723f,
  -0.035828f, -0.204701f, 0.099813f,  0.123580f,  0.209851f,  -0.110989f,
  -0.043655f, -0.461118f, -0.139664f, 0.026855f,  -0.081714f, 0.207623f,
  0.089942f,  0.253082f,  0.680568f,  0.811360f,  -0.090528f, -0.116818f,
  -0.432361f, -0.075588f, -0.269924f, -0.276810f, -0.289192f, -0.282570f,
  0.245566f,  0.267216f,  0.238622f,  0.286528f,  -0.157605f, -0.200401f,
  -0.138924f, -0.185006f, 0.215203f,  0.203316f,  0.209532f,  0.293135f,
  0.928046f,  0.733323f,  -0.094120f, 0.036918f,  -0.126643f, -0.083371f,
  -0.147530f, -0.153195f, 0.097097f,  0.101852f,  0.109160f,  0.105129f,
  -0.051869f, -0.064359f, -0.073469f, -0.059591f, 0.102431f,  0.109444f,
  0.113614f,  0.105617f,  0.383311f,  0.325783f,  0.393234f,  0.382508f,
  0.194720f,  0.189672f,  0.217477f,  0.177786f,  0.326461f,  0.114789f,
  0.317061f,  0.048291f,  -0.061143f, -0.134641f, -0.067895f, -0.108446f,
  0.082592f,  0.029918f,  -0.006580f, 0.015533f,  -0.053583f, -0.055540f,
  -0.063395f, -0.023157f, -0.064955f, -0.073981f, -0.115452f, -0.086626f,
  -0.036616f, 0.008454f,  0.012029f,  -0.008039f, -0.207395f, -0.216419f,
  -0.205363f, -0.249099f, 0.343308f,  0.413215f,  -0.009918f, -0.109978f,
  -0.059711f, -0.045089f, -0.029130f, -0.038483f, -0.070323f, -0.099409f,
  -0.008849f, -0.063527f, 0.175963f,  0.185335f,  0.149151f,  0.199997f,
  -0.027516f, -0.039812f, -0.027760f, -0.047910f, -0.007337f, 0.071065f,
  0.086225f,  0.125539f,  0.151390f,  0.215488f,  0.203450f,  0.045380f,
  0.095761f,  0.107809f,  0.103918f,  0.122383f,  0.116287f,  0.135455f,
  0.115446f,  0.155673f,  -0.044648f, -0.027455f, -0.015473f, -0.026657f,
  0.089852f,  0.077459f,  0.077631f,  0.082507f,  -0.102761f, -0.054669f,
  -0.132223f, -0.024768f, 0.111573f,  0.060467f,  0.107883f,  0.056621f,
  0.219357f,  -0.161153f, 0.074379f,  -0.118743f, -0.169931f, -0.153995f,
  -0.220003f, -0.200186f, 0.032318f,  -0.060687f, -0.087550f, -0.038022f,
  0.026633f,  -0.005534f, 0.029532f,  0.027081f,  0.011926f,  0.058412f,
  0.010631f,  0.003068f,  -0.014911f, 0.063070f,  0.065271f,  0.089550f,
  0.012885f,  0.005320f,  -0.037494f, -0.019849f, -0.009624f, -0.059090f,
  -0.021222f, -0.088033f, -0.055261f, -0.055113f, -0.047598f, -0.055478f,
  -0.023648f, -0.046827f, -0.036572f, -0.057655f, 0.104194f,  0.179800f,
  0.175751f,  0.192851f,  -0.016950f, -0.073650f, -0.028592f, -0.088219f,
  0.011130f,  0.061825f,  0.025643f,  0.034183f,  0.095548f,  0.001457f,
  -0.132869f, 0.032981f,  -0.140178f, -0.105343f, -0.161799f, -0.161983f,
  0.177746f,  0.132903f,  0.135627f,  0.152489f,  -0.012532f, -0.068747f,
  -0.085849f, -0.095434f, 0.087037f,  0.139497f,  0.111899f,  0.100189f,
  -0.024649f, -0.092003f, 0.020783f,  -0.115807f, 0.092039f,  0.093943f,
  0.109466f,  0.049639f,  -0.133727f, 0.128430f,  -0.050546f, 0.190632f,
  0.123733f,  0.082305f,  0.114878f,  0.122572f,  0.201618f,  0.137588f,
  0.065582f,  0.125161f,  -0.095179f, -0.120719f, -0.127126f, -0.101961f,
  -0.118120f, -0.104833f, -0.179632f, -0.131764f, -0.138096f, -0.147861f,
  -0.131512f, -0.153905f, -0.201816f, -0.206641f, -0.196707f, -0.160013f,
  -0.212605f, -0.093998f, -0.186258f, -0.076137f, -0.065340f, -0.006969f,
  -0.071383f, -0.075005f,
};

static const float weights_layer_4[] = {
  -0.016102f, -0.022836f, 0.624049f,  0.273485f,  0.222800f,  -0.290175f,
  -0.518415f, 0.413484f,  -0.264495f, 0.498083f,  -0.450145f, -0.106419f,
  0.095103f,  -0.187451f, 0.145933f,  -0.371542f, -0.088871f, 0.184017f,
  -0.429625f, -0.110882f, 0.292781f,  0.289588f,  0.185127f,  0.326017f,
  -0.432009f, -0.342663f, -0.312206f, 0.004004f,  -1.114290f, 0.028497f,
  -0.264944f, -0.419611f, 0.046336f,  0.138232f,  -0.869528f, 0.425557f,
  -0.954838f, -0.186830f, -0.464622f, -0.757107f, -0.432686f, -0.125978f,
  -0.402633f, -0.172266f, -0.041749f, -0.822238f, -0.118486f, 0.238617f,
  -0.198037f, 0.146347f,  0.405257f,  0.513303f,  -0.078876f, -0.300385f,
  -0.010293f, -0.183962f, 0.155738f,  0.186797f,  -0.086814f, 0.000179f,
  0.123467f,  0.362523f,  0.068805f,  0.371834f,  0.038122f,  -0.117867f,
  -0.120445f, -0.422322f, -0.131402f, 0.285449f,  0.038957f,  0.008844f,
  -0.020197f, 0.187723f,  0.190433f,  0.146532f,  -0.091068f, -0.270865f,
  -0.194231f, -0.226777f, 0.013548f,  0.248351f,  0.537685f,  0.056316f,
  -0.171540f, -0.003865f, 0.406439f,  0.126507f,  0.192780f,  0.149335f,
  -0.149602f, 0.255202f,  -0.015426f, 0.032335f,  -1.791330f, -0.894602f,
  -0.196641f, -0.282846f, -0.391100f, -0.040969f, 0.049934f,  0.056348f,
  -0.041426f, -0.075159f, -0.658335f, -0.827270f, -0.175029f, -0.427235f,
  0.311201f,  0.560413f,  0.363408f,  0.374580f,  -0.433531f, -0.180580f,
  0.142142f,  0.194768f,  -0.054118f, -0.376541f, -0.366185f, -0.308782f,
  -0.273143f, -0.074097f, 0.009000f,  -0.182198f, -0.015616f, -0.003882f,
  -0.174340f, -0.354866f, 0.527972f,  0.348355f,  0.091381f,  -0.419828f,
  -0.530529f, 0.159899f,  -0.511867f, -0.104237f, -0.286079f, -0.659039f,
  -0.266596f, -0.256557f, -0.600437f, -0.446333f, -0.229629f, 0.024931f,
  -0.143716f, -0.415754f, -0.003760f, -0.107195f, -0.666165f, -0.697312f,
  -0.650255f, -0.703877f, 0.243402f,  0.426710f,  0.217210f,  0.260255f,
  0.027416f,  0.163147f,  0.132188f,  0.142374f,  0.558627f,  0.065717f,
  0.382781f,  -1.192240f, 0.195492f,  0.028439f,  0.278252f,  -0.491806f,
  0.497701f,  -0.448835f, -0.245079f, -0.014336f, -0.174907f, -0.409633f,
  0.207548f,  0.433813f,  0.459889f,  0.431728f,  0.605050f,  0.485520f,
  0.218548f,  0.437307f,  0.027023f,  -0.204251f, 0.012100f,  0.150677f,
  -1.097980f, 0.086866f,  -1.293130f, -0.372575f, -0.876264f, -0.021818f,
  0.322864f,  -0.231043f, -0.271608f, 0.132782f,  -0.314895f, 0.396800f,
  0.262788f,  -0.317212f, -0.666308f, 0.830742f,  0.319409f,  -0.564373f,
  -0.178656f, 0.306993f,  0.265634f,  -0.332480f, -0.491514f, -0.186745f,
  -0.063044f, -0.009321f, 0.074944f,  -0.372082f, -0.029479f, 0.081548f,
  0.028172f,  -0.233148f, -0.337938f, -0.087695f, 0.596556f,  0.559530f,
  0.139332f,  0.107223f,  -0.190915f, 0.137401f,  -0.150625f, -0.225484f,
  -0.191344f, -0.232535f, 0.126510f,  0.296323f,  -0.547901f, -0.653080f,
  0.358514f,  0.726289f,  -0.421725f, -0.243620f, 0.236206f,  0.390823f,
  -0.076560f, -0.282329f, -0.012460f, -0.428484f, 0.349469f,  0.394629f,
  0.421537f,  0.219632f,  -0.117550f, -0.087894f, 0.077155f,  0.016000f,
  -0.289137f, -0.092937f, -0.014518f, -0.027111f, 0.210329f,  -0.159678f,
  0.013288f,  -0.039268f, 0.008112f,  0.003152f,  0.030084f,  -0.039859f,
  0.322028f,  -0.407797f, 0.447087f,  -0.381562f, 0.529297f,  -0.520298f,
  0.562865f,  -0.616878f, 0.689389f,  0.754262f,  0.138475f,  0.750697f,
  -0.760157f, -0.383740f, 0.074219f,  0.556257f,  0.087827f,  -0.511826f,
  -0.305507f, -0.638214f, 0.114833f,  -0.444022f, 0.526612f,  -0.604984f,
  -0.100415f, 0.037824f,  -0.106264f, 0.337615f,  0.070743f,  0.031129f,
  0.281954f,  0.176144f,  -0.032833f, -0.073902f, -0.285492f, -0.803803f,
  -0.015589f, 0.186077f,  -0.033351f, 0.517269f,  -1.878800f, -1.685210f,
  -0.416581f, 0.158476f,  -0.071929f, -0.624353f, -0.122069f, -0.075065f,
  0.311816f,  0.506305f,  0.383896f,  0.259450f,  -0.308232f, -0.094221f,
  -0.421885f, -0.293573f,
};

static const float weights_layer_5[] = {
  0.131894f,  0.078431f,  0.323121f,  -0.230680f, -0.684740f, 0.020895f,
  0.364983f,  0.121656f,  0.132448f,  -0.731198f, 0.071148f,  0.739642f,
  0.318437f,  -0.033021f, -1.037080f, 0.135335f,  0.383582f,  0.287332f,
  0.054042f,  -0.825482f, 0.418533f,  0.305606f,  0.041549f,  0.432422f,
  -0.826878f, -0.593536f, 0.105657f,  0.125357f,  0.408567f,  -0.293338f,
  0.233905f,  -0.039609f, 0.547727f,  -0.435806f, 0.036160f,  0.220275f,
  -0.020337f, -0.619403f, -0.455858f, 0.681455f,  0.543846f,  -0.495084f,
  0.251496f,  -0.085686f, 0.091395f,  -0.476696f, 0.453628f,  -0.109663f,
  0.383493f,  -0.456563f, -0.212935f, 0.020567f,  -0.719564f, -0.377813f,
  -0.737511f, 0.765965f,  0.624309f,  -0.063679f, -0.055681f, -0.475969f,
  -0.069902f, 0.725690f,  0.641094f,  0.439922f,  -0.111544f, -0.309061f,
  0.280091f,  0.381416f,  0.481168f,  0.483543f,  -0.901267f, -0.499230f,
  0.043449f,  -0.372395f, 0.021216f,  -0.002200f, -0.524089f, -0.071485f,
  -0.273974f, -0.462654f, 0.042369f,  -0.138679f, -0.330060f, 0.021886f,
  -0.306075f, -0.011130f, -0.260224f, -0.288435f, -0.104039f, -0.183563f,
  0.118990f,  -0.531160f, 0.339632f,  -0.028374f, 0.159084f,  -0.008824f,
  -0.791388f, 0.245242f,  0.356510f,  0.469867f,  -0.396949f, -0.476146f,
  -0.168472f, 1.068400f,  0.474629f,  -0.117554f, -0.142453f, -0.306604f,
  0.348525f,  -0.111929f, -0.435384f, 0.019952f,  -0.260185f, 0.373376f,
  0.109729f,  -0.639168f, 0.033392f,  -0.082573f, -0.196018f, 0.301637f,
  -0.124210f, -0.202515f, -1.221920f, -0.253690f, -0.144864f, 0.287753f,
  -0.161206f, -0.213246f, 0.373968f,  0.141397f,  -0.248237f, 0.283090f,
  -0.008977f, -0.172960f, -0.234146f, -0.720014f, -0.322451f, 0.181083f,
  0.310659f,  -0.422646f, -0.719994f, -0.354339f, 0.352739f,  0.230923f,
  0.427013f,  -0.660316f, 0.232140f,  0.685896f,  0.660208f,  0.225748f,
  -0.918750f, -0.650790f, -0.674525f, -0.450305f, -0.152529f, 0.498480f,
  0.895092f,  0.688242f,  0.669057f,  0.612669f,  0.593484f,  0.318204f,
  -0.169294f, 0.388789f,  -0.529777f, -0.219706f, -0.044916f, 0.161697f,
  -0.145288f, 0.196153f,  -0.022212f, -0.434209f, -0.208115f, -0.117745f,
  -0.279029f, -0.009506f, 0.137474f,  0.330148f,  0.439258f,  0.345879f,
  -0.845131f, -0.215713f, 0.094463f,  0.638604f,  0.882254f,  -0.964082f,
  -0.383920f, 0.292645f,  0.266341f,  0.747473f,  -0.645631f, -0.538896f,
  -0.319764f, 0.521880f,  0.460091f,  -0.470898f, -0.778283f, -0.061622f,
  -0.142433f, 0.210520f,  0.804197f,  0.285840f,  -0.138414f, -0.381846f,
  -0.499991f, 0.223648f,  0.439025f,  0.321508f,  -0.099560f, -0.622893f,
  0.750925f,  0.740994f,  0.140405f,  0.074631f,  -0.270223f, -0.829049f,
  -0.753355f, -0.258015f, 0.006285f,  -0.730573f, -1.107390f, -0.538015f,
  -1.005520f, -0.724115f, -0.440183f, -0.395239f, 0.508768f,  0.204620f,
  -0.267331f, 0.001740f,  -0.838709f, 0.659333f,  0.043739f,  -0.024099f,
  0.262431f,  0.252433f,  -0.265215f, 0.057289f,  -0.428192f, -0.114350f,
  -0.011475f, 0.463995f,  0.668833f,  -0.604556f, -0.122780f, -0.441645f,
  0.145769f,  0.310450f,  -1.003500f, 0.936069f,  0.516604f,  -0.643386f,
  -0.518571f, 0.306130f,  0.337387f,  0.583400f,  -0.366025f, -0.560035f,
  -0.262332f, 0.465242f,  0.964332f,  -0.545410f, -0.637428f, -0.202695f,
  0.378931f,  0.834604f,  0.000970f,  -0.553303f, -0.562879f, 0.221665f,
  0.395160f,  0.446281f,  -0.184394f, -0.591780f, 0.170595f,  1.164390f,
  0.227068f,  -0.150910f, -0.393690f, -0.131151f, 0.309956f,  -0.413518f,
  -0.768334f, -0.548975f, 0.245384f,  -0.256904f, -0.514790f, -0.102616f,
  -0.347625f, 0.420456f,  0.037804f,  -0.283200f, -0.578815f, 0.319282f,
  0.674622f,  -0.011791f, -0.339329f, 0.466705f,  0.563444f,  0.409660f,
  0.445784f,  -0.899507f, -0.605116f, 0.622438f,  0.427385f,  -0.062509f,
  0.666570f,  0.057105f,  0.357894f,  -0.811016f, -0.421715f, -0.458397f,
  0.288955f,  0.005857f,  0.236331f,  0.107957f,  0.587276f,  -0.375800f,
  0.323799f,  -0.623363f, 0.254122f,  -0.198478f, -0.098436f, -0.282531f,
  0.452453f,  -0.163349f, -0.413382f, -0.448732f, -0.528770f, -0.457449f,
  -0.619619f, -0.265919f, -0.042760f, 0.438730f,  0.501798f,  -0.403851f,
  0.519564f,  0.817314f,  0.366203f,  0.492610f,  0.546929f,  0.853094f,
  0.289000f,  0.453941f,  -0.076152f, 0.007226f,  -0.183717f, -0.506252f,
  -0.599989f, -0.576006f, 0.746488f,  0.631466f,  -0.475599f, -0.334991f,
  -0.879614f, 0.918957f,  0.473471f,  -0.043781f, -0.688234f, -0.925875f,
  -0.188081f, 0.050918f,  0.116855f,  0.221413f,  -0.066680f, -0.674395f,
  -0.481985f, 0.247368f,  0.271129f,  0.637979f,  -1.006970f, -0.855441f,
  0.144874f,  0.507424f,  1.506960f,  -0.338910f, 0.398203f,  0.738000f,
  0.263193f,  -0.425908f, 0.358271f,  -1.072900f, -0.816209f, -0.425519f,
  0.264373f,  0.694014f,  0.036333f,  0.635532f,  0.518856f,  0.047585f,
  -0.854817f, -0.138202f, 0.006811f,  -0.052020f, -0.468498f, 0.489080f,
  -0.105778f, 0.357038f,  -0.782875f, 0.649049f,  -0.562652f, -0.544392f,
  -0.328526f, -0.402121f, -0.263172f, -0.668459f, -0.526702f, -0.395829f,
  0.190986f,  0.307766f,  -1.001830f, -0.293051f, 0.283334f,  0.572450f,
  0.906095f,  -1.144300f, 0.180989f,  0.421092f,  0.684571f,  0.527276f,
  -0.122287f, 0.575067f,  0.675221f,  0.755029f,  0.094957f,  0.481403f,
  0.825155f,  0.755035f,  0.641420f,  0.034497f,  0.518783f,  0.283800f,
  0.293733f,  -0.074778f, -0.268720f, 0.798921f,  0.317714f,  -0.236391f,
  -0.375071f, -0.414600f, 0.223413f,  -0.349044f, -0.191033f, -0.391779f,
  -0.596894f, -0.378608f, -0.185920f, -0.822171f, -0.754962f, -0.167706f,
  0.755378f,  0.671847f,  0.969414f,  0.793048f,  1.078610f,  -0.418963f,
  0.367648f,  0.217645f,  0.294232f,  0.113027f,  0.060312f,  -0.327488f,
  -0.305035f, -0.243600f, -0.020588f, -0.326324f, -0.417534f, -0.425868f,
  -0.404614f, -0.346750f, -0.339145f, -0.348094f, -0.527290f, -0.617825f,
  -0.258342f, -0.200753f, -0.249779f, -0.321039f, -0.023117f, -0.004167f,
  -0.206788f, -0.612420f, -0.646428f, -0.548969f, -0.158875f, 0.213814f,
  -0.084040f, -0.217365f, -0.511895f, -0.653285f, 0.440971f,  0.455591f,
  -0.123900f, 0.134097f,  -0.251241f, 0.682463f,  0.740614f,  0.991212f,
  0.565984f,  0.592690f,
};

static inline float32x4_t add_f32x4_x4(const float32x4_t a[4]) {
  float32x4_t sum01 = vaddq_f32(a[0], a[1]);
  float32x4_t sum23 = vaddq_f32(a[2], a[3]);
  return vaddq_f32(sum01, sum23);
}

static inline void av1_cnn_convolve_no_maxpool_padding_valid_2x2_large_neon(
    const float **input, int in_width, int in_height, int in_stride,
    const float *bias, const int skip_width, const int skip_height,
    const int filter_width, const int filter_height, const int in_channels,
    const int out_channels, float **output, int out_stride, int start_idx,
    const float *weights) {
  assert(filter_height == 2 && filter_width == 2);
  assert(skip_width == 2 && skip_height == 2);
  assert(in_width >= 16);
  const int in_size = in_height * in_width;

  do {
    const float32x4_t bias_v = vdupq_n_f32(bias[0]);
    const float *weight_ptr0 = weights;
    const float *in_ptr0 = *input;
    float *out_ptr0 = *output;
    int h = 0;

    do {
      const float *in_ptr1 = in_ptr0;
      float *out_ptr1 = out_ptr0;
      int w = 0;

      do {
        const float *weight_ptr1 = weight_ptr0;
        const float *in_ptr2 = in_ptr1;
        int k = 0;
        float32x4_t sum0[4] = { bias_v, vdupq_n_f32(0), vdupq_n_f32(0),
                                vdupq_n_f32(0) };
        float32x4_t sum1[4] = { bias_v, vdupq_n_f32(0), vdupq_n_f32(0),
                                vdupq_n_f32(0) };

        do {
          const float32x4_t weights0 = vld1q_f32(weight_ptr1);
          const float32x4_t weights1 = vld1q_f32(weight_ptr1 + 4);
          const float32x2_t weights0_lo = vget_low_f32(weights0);
          const float32x2_t weights0_hi = vget_high_f32(weights0);
          const float32x2_t weights1_lo = vget_low_f32(weights1);
          const float32x2_t weights1_hi = vget_high_f32(weights1);

          const float32x4x2_t in0_lo_0 = vld2q_f32(in_ptr2);
          const float32x4x2_t in0_hi_0 = vld2q_f32(in_ptr2 + in_stride);
          const float32x4x2_t in1_lo_0 = vld2q_f32(in_ptr2 + in_size);
          const float32x4x2_t in1_hi_0 =
              vld2q_f32(in_ptr2 + in_size + in_stride);

          sum0[0] = vmlaq_lane_f32(sum0[0], in0_lo_0.val[0], weights0_lo, 0);
          sum0[0] = vmlaq_lane_f32(sum0[0], in0_lo_0.val[1], weights0_lo, 1);

          sum0[1] = vmlaq_lane_f32(sum0[1], in0_hi_0.val[0], weights0_hi, 0);
          sum0[1] = vmlaq_lane_f32(sum0[1], in0_hi_0.val[1], weights0_hi, 1);

          sum0[2] = vmlaq_lane_f32(sum0[2], in1_lo_0.val[0], weights1_lo, 0);
          sum0[2] = vmlaq_lane_f32(sum0[2], in1_lo_0.val[1], weights1_lo, 1);

          sum0[3] = vmlaq_lane_f32(sum0[3], in1_hi_0.val[0], weights1_hi, 0);
          sum0[3] = vmlaq_lane_f32(sum0[3], in1_hi_0.val[1], weights1_hi, 1);

          const float32x4x2_t in0_lo_1 = vld2q_f32(in_ptr2 + 8);
          const float32x4x2_t in0_hi_1 = vld2q_f32(in_ptr2 + in_stride + 8);
          const float32x4x2_t in1_lo_1 = vld2q_f32(in_ptr2 + in_size + 8);
          const float32x4x2_t in1_hi_1 =
              vld2q_f32(in_ptr2 + in_size + in_stride + 8);

          sum1[0] = vmlaq_lane_f32(sum1[0], in0_lo_1.val[0], weights0_lo, 0);
          sum1[0] = vmlaq_lane_f32(sum1[0], in0_lo_1.val[1], weights0_lo, 1);

          sum1[1] = vmlaq_lane_f32(sum1[1], in0_hi_1.val[0], weights0_hi, 0);
          sum1[1] = vmlaq_lane_f32(sum1[1], in0_hi_1.val[1], weights0_hi, 1);

          sum1[2] = vmlaq_lane_f32(sum1[2], in1_lo_1.val[0], weights1_lo, 0);
          sum1[2] = vmlaq_lane_f32(sum1[2], in1_lo_1.val[1], weights1_lo, 1);

          sum1[3] = vmlaq_lane_f32(sum1[3], in1_hi_1.val[0], weights1_hi, 0);
          sum1[3] = vmlaq_lane_f32(sum1[3], in1_hi_1.val[1], weights1_hi, 1);

          weight_ptr1 += 8;
          in_ptr2 += 2 * in_size;
          k += 2;
        } while (k < in_channels);

        vst1q_f32(out_ptr1, add_f32x4_x4(sum0));
        vst1q_f32(out_ptr1 + 4, add_f32x4_x4(sum1));

        out_ptr1 += 8;
        in_ptr1 += 8 * skip_width;
        w += 8 * skip_width;
      } while (w < in_width - filter_width + 1);

      out_ptr0 += out_stride;
      in_ptr0 += skip_height * in_stride;
      h += skip_height;
    } while (h < in_height - filter_height + 1);

    ++bias;
    ++output;
    weights += in_channels * filter_height * filter_width;
  } while (++start_idx < out_channels);
}

static inline void av1_cnn_convolve_no_maxpool_padding_valid_2x2_neon(
    const float **input, int in_width, int in_height, int in_stride,
    const float *bias, const int skip_width, const int skip_height,
    const int filter_width, const int filter_height, const int in_channels,
    const int out_channels, float **output, int out_stride, int start_idx,
    const float *weights) {
  assert(filter_height == 2 && filter_width == 2);
  assert(skip_width == 2 && skip_height == 2);
  assert(in_width == 8);
  const int in_size = in_height * in_width;
  do {
    const float32x4_t bias_v = vdupq_n_f32(*bias);
    const float *weight_ptr0 = weights;
    const float *in_ptr0 = *input;
    float *out_ptr0 = *output;
    int h = 0;

    do {
      const float *in_ptr1 = in_ptr0;
      float *out_ptr1 = out_ptr0;
      int w = 0;

      do {
        const float *weight_ptr1 = weight_ptr0;
        const float *in_ptr2 = in_ptr1;
        int k = 0;
        float32x4_t sum[4] = { bias_v, vdupq_n_f32(0), vdupq_n_f32(0),
                               vdupq_n_f32(0) };

        do {
          const float32x4_t weights0 = vld1q_f32(weight_ptr1);
          const float32x4_t weights1 = vld1q_f32(weight_ptr1 + 4);
          const float32x2_t weights0_lo = vget_low_f32(weights0);
          const float32x2_t weights0_hi = vget_high_f32(weights0);
          const float32x2_t weights1_lo = vget_low_f32(weights1);
          const float32x2_t weights1_hi = vget_high_f32(weights1);

          const float32x4x2_t in0_lo = vld2q_f32(in_ptr2);
          const float32x4x2_t in0_hi = vld2q_f32(in_ptr2 + in_stride);
          const float32x4x2_t in1_lo = vld2q_f32(in_ptr2 + in_size);
          const float32x4x2_t in1_hi = vld2q_f32(in_ptr2 + in_size + in_stride);

          sum[0] = vmlaq_lane_f32(sum[0], in0_lo.val[0], weights0_lo, 0);
          sum[0] = vmlaq_lane_f32(sum[0], in0_lo.val[1], weights0_lo, 1);

          sum[1] = vmlaq_lane_f32(sum[1], in0_hi.val[0], weights0_hi, 0);
          sum[1] = vmlaq_lane_f32(sum[1], in0_hi.val[1], weights0_hi, 1);

          sum[2] = vmlaq_lane_f32(sum[2], in1_lo.val[0], weights1_lo, 0);
          sum[2] = vmlaq_lane_f32(sum[2], in1_lo.val[1], weights1_lo, 1);

          sum[3] = vmlaq_lane_f32(sum[3], in1_hi.val[0], weights1_hi, 0);
          sum[3] = vmlaq_lane_f32(sum[3], in1_hi.val[1], weights1_hi, 1);

          weight_ptr1 += 8;
          in_ptr2 += 2 * in_size;
          k += 2;
        } while (k < in_channels);

        vst1q_f32(out_ptr1, add_f32x4_x4(sum));

        out_ptr1 += 4;
        in_ptr1 += 4 * skip_width;
        w += 4 * skip_width;
      } while (w < in_width - filter_width + 1);

      out_ptr0 += out_stride;
      in_ptr0 += skip_height * in_stride;
      h += skip_height;
    } while (h < in_height - filter_height + 1);

    ++bias;
    ++output;
    weights += in_channels * filter_height * filter_width;
  } while (++start_idx < out_channels);
}

static inline void av1_cnn_convolve_no_maxpool_padding_valid_5x5_neon(
    const float **input, int in_width, int in_height, int in_stride,
    const float *bias, const int skip_width, const int skip_height,
    const int filter_width, const int filter_height, const int in_channels,
    const int out_channels, float **output, int out_stride, int start_idx,
    const float *weights) {
  assert(filter_height == 5 && filter_width == 5);
  assert(skip_width == 4 && skip_height == 4);
  assert(in_width >= 16);
  assert(in_channels == 1);
  (void)in_channels;

  do {
    const float32x4_t bias_v = vdupq_n_f32(*bias);
    const float *in_ptr0 = *input;
    const float *weights_ptr0 = weights;
    float *out_ptr0 = *output;
    int h = 0;

    do {
      const float *in_ptr1 = in_ptr0;
      float *out_ptr1 = out_ptr0;
      int w = 0;

      do {
        float32x4_t sum[2] = { bias_v, vdupq_n_f32(0) };

        const float32x4_t weight_0_3 = vld1q_f32(weights_ptr0);
        const float32x4_t weight_4_7 = vld1q_f32(weights_ptr0 + 4);
        const float32x4_t weight_8_11 = vld1q_f32(weights_ptr0 + 8);
        const float32x4_t weight_12_15 = vld1q_f32(weights_ptr0 + 12);
        const float32x4_t weight_16_19 = vld1q_f32(weights_ptr0 + 16);
        const float32x4_t weight_20_23 = vld1q_f32(weights_ptr0 + 20);

        const float32x2_t weight_0_3_lo = vget_low_f32(weight_0_3);
        const float32x2_t weight_0_3_hi = vget_high_f32(weight_0_3);
        const float32x2_t weight_4_7_lo = vget_low_f32(weight_4_7);
        const float32x2_t weight_4_7_hi = vget_high_f32(weight_4_7);
        const float32x2_t weight_8_11_lo = vget_low_f32(weight_8_11);
        const float32x2_t weight_8_11_hi = vget_high_f32(weight_8_11);
        const float32x2_t weight_12_15_lo = vget_low_f32(weight_12_15);
        const float32x2_t weight_12_15_hi = vget_high_f32(weight_12_15);
        const float32x2_t weight_16_19_lo = vget_low_f32(weight_16_19);
        const float32x2_t weight_16_19_hi = vget_high_f32(weight_16_19);
        const float32x2_t weight_20_23_lo = vget_low_f32(weight_20_23);
        const float32x2_t weight_20_23_hi = vget_high_f32(weight_20_23);

        const float32x4x4_t in0 = vld4q_f32(in_ptr1 + 0 * in_stride);
        const float32x4x4_t in1 = vld4q_f32(in_ptr1 + 1 * in_stride);
        const float32x4x4_t in2 = vld4q_f32(in_ptr1 + 2 * in_stride);
        const float32x4x4_t in3 = vld4q_f32(in_ptr1 + 3 * in_stride);
        const float32x4x4_t in4 = vld4q_f32(in_ptr1 + 4 * in_stride);

        const float32x4_t in0_4 = vextq_f32(
            in0.val[0], vdupq_n_f32(*(in_ptr1 + 16 + 0 * in_stride)), 1);
        const float32x4_t in1_4 = vextq_f32(
            in1.val[0], vdupq_n_f32(*(in_ptr1 + 16 + 1 * in_stride)), 1);
        const float32x4_t in2_4 = vextq_f32(
            in2.val[0], vdupq_n_f32(*(in_ptr1 + 16 + 2 * in_stride)), 1);
        const float32x4_t in3_4 = vextq_f32(
            in3.val[0], vdupq_n_f32(*(in_ptr1 + 16 + 3 * in_stride)), 1);
        const float32x4_t in4_4 = vextq_f32(
            in4.val[0], vdupq_n_f32(*(in_ptr1 + 16 + 4 * in_stride)), 1);

        // Kernel row 0.
        sum[0] = vmlaq_lane_f32(sum[0], in0.val[0], weight_0_3_lo, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in0.val[1], weight_0_3_lo, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in0.val[2], weight_0_3_hi, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in0.val[3], weight_0_3_hi, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in0_4, weight_4_7_lo, 0);

        // Kernel row 1.
        sum[1] = vmlaq_lane_f32(sum[1], in1.val[0], weight_4_7_lo, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in1.val[1], weight_4_7_hi, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in1.val[2], weight_4_7_hi, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in1.val[3], weight_8_11_lo, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in1_4, weight_8_11_lo, 1);

        // Kernel row 2.
        sum[0] = vmlaq_lane_f32(sum[0], in2.val[0], weight_8_11_hi, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in2.val[1], weight_8_11_hi, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in2.val[2], weight_12_15_lo, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in2.val[3], weight_12_15_lo, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in2_4, weight_12_15_hi, 0);

        // Kernel row 3.
        sum[1] = vmlaq_lane_f32(sum[1], in3.val[0], weight_12_15_hi, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in3.val[1], weight_16_19_lo, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in3.val[2], weight_16_19_lo, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in3.val[3], weight_16_19_hi, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in3_4, weight_16_19_hi, 1);

        // Kernel row 4.
        sum[0] = vmlaq_lane_f32(sum[0], in4.val[0], weight_20_23_lo, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in4.val[1], weight_20_23_lo, 1);
        sum[0] = vmlaq_lane_f32(sum[0], in4.val[2], weight_20_23_hi, 0);
        sum[1] = vmlaq_lane_f32(sum[1], in4.val[3], weight_20_23_hi, 1);
        sum[0] = vmlaq_f32(sum[0], vdupq_n_f32(*(weights_ptr0 + 24)), in4_4);

        vst1q_f32(out_ptr1, vaddq_f32(sum[0], sum[1]));

        out_ptr1 += 4;
        in_ptr1 += 4 * skip_width;
        w += 4 * skip_width;
      } while (w < in_width - filter_width + 1);

      out_ptr0 += out_stride;
      in_ptr0 += skip_height * in_stride;
      h += skip_height;
    } while (h < in_height - filter_height + 1);

    ++output;
    ++bias;
    weights += 25;
  } while (++start_idx < out_channels);
}

// Neon variant of av1_cnn_convolve_no_maxpool_padding_valid_c().
// As per the current encoder, av1_cnn_convolve function gets called for
// block size equal to 64x64. av1_cnn_convolve() uses layer config values
// set by av1_intra_mode_cnn_partition_cnn_config. The following are a few
// details related to each layer's config parameters.
// Layer_Number in_size out_size filter_wd filter_ht skip_wd skip_ht
//     0         64x64    16x16      5         5         4       4
//     1         16x16    8x8        2         2         2       2
//     2         8x8      4x4        2         2         2       2
//     3         4x4      2x2        2         2         2       2
//     4         2x2      1x1        2         2         2       2
// Here,
// filter_wd = filter_width and filter_ht = filter_height,
// skip_wd = skip_width and skip_ht = skip_height.
void av1_cnn_convolve_no_maxpool_padding_valid_neon(
    const float **input, int in_width, int in_height, int in_stride,
    const CNN_LAYER_CONFIG *layer_config, float **output, int out_stride,
    int start_idx, int cstep, int channel_step) {
  assert((layer_config->skip_height == 1 && layer_config->skip_width == 1) ||
         !layer_config->maxpool);
  assert(layer_config->filter_height > 1 || layer_config->filter_width > 1);
  assert(layer_config->pad == PADDING_VALID);
  assert(channel_step == 1);
  assert(cstep == layer_config->in_channels * layer_config->out_channels);

  if (layer_config->filter_width == 5 && layer_config->filter_height == 5 &&
      layer_config->skip_width == 4 && layer_config->skip_height == 4) {
    av1_cnn_convolve_no_maxpool_padding_valid_5x5_neon(
        input, in_width, in_height, in_stride, layer_config->bias,
        layer_config->skip_width, layer_config->skip_height,
        layer_config->filter_width, layer_config->filter_height,
        layer_config->in_channels, layer_config->out_channels, output,
        out_stride, start_idx, weights_layer_5);
  } else if (layer_config->filter_width == 2 &&
             layer_config->filter_height == 2 &&
             layer_config->skip_width == 2 && layer_config->skip_height == 2) {
    const float *weights = weights_layer_1;
    if (layer_config->output_num ==
        av1_intra_mode_cnn_partition_cnn_config.layer_config[2].output_num) {
      weights = weights_layer_2;
    } else if ((layer_config->output_num ==
                av1_intra_mode_cnn_partition_cnn_config.layer_config[3]
                    .output_num)) {
      weights = weights_layer_3;
    } else if ((layer_config->output_num ==
                av1_intra_mode_cnn_partition_cnn_config.layer_config[4]
                    .output_num)) {
      weights = weights_layer_4;
    }
    if (in_width >= 16) {
      av1_cnn_convolve_no_maxpool_padding_valid_2x2_large_neon(
          input, in_width, in_height, in_stride, layer_config->bias,
          layer_config->skip_width, layer_config->skip_height,
          layer_config->filter_width, layer_config->filter_height,
          layer_config->in_channels, layer_config->out_channels, output,
          out_stride, start_idx, weights);
    } else if (in_width == 8) {
      av1_cnn_convolve_no_maxpool_padding_valid_2x2_neon(
          input, in_width, in_height, in_stride, layer_config->bias,
          layer_config->skip_width, layer_config->skip_height,
          layer_config->filter_width, layer_config->filter_height,
          layer_config->in_channels, layer_config->out_channels, output,
          out_stride, start_idx, weights);
    } else {
      av1_cnn_convolve_no_maxpool_padding_valid_c(
          input, in_width, in_height, in_stride, layer_config, output,
          out_stride, start_idx, cstep, channel_step);
    }
  } else {
    av1_cnn_convolve_no_maxpool_padding_valid_c(
        input, in_width, in_height, in_stride, layer_config, output, out_stride,
        start_idx, cstep, channel_step);
  }
}