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/*
* 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,
-0.805199f, -0.643391f, -0.304100f, 0.797599f, -0.172157f, 0.429085f,
-0.750676f, 0.149227f, -0.207898f, -0.022534f, -0.341448f, -0.247976f,
0.095325f, -0.561120f, 0.599694f, -0.025236f, 0.292346f, -0.312001f,
0.517478f, 0.301457f, -0.106415f, 0.226263f, -0.184163f, -0.114419f,
-0.322702f, 0.172541f, 0.445573f, 0.157213f, 0.670704f, 0.102174f,
-0.234667f, -0.293311f, 0.769852f, 0.038028f, -0.036741f, -0.228060f,
-0.253335f, 0.424054f, -0.597980f, 0.221007f, -0.114741f, -0.411557f,
-0.592201f, 0.442684f, 0.115491f, -0.106896f, -0.028110f, 0.354751f,
-0.248375f, 0.242570f, -0.155856f, 0.280528f, -0.198742f, 0.588725f,
0.371065f, 0.078197f, 0.114706f, -0.448021f, 0.065255f, 0.133741f,
-0.227522f, -0.047339f, -0.052849f, 0.309480f, 0.597185f, 0.209182f,
0.226108f, -0.601036f, -0.431672f, -0.172601f, -0.000174f, 0.194292f,
-0.133937f, 0.130676f, 0.059372f, 0.091381f, 0.098751f, -0.150996f,
0.170514f, -0.085494f, 0.336576f, 0.484004f, 0.033862f, 0.277473f,
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0.167556f, 0.106071f, 0.172254f, -0.163790f, -0.142205f, -0.043182f,
0.096145f, 0.145037f, -0.066015f, -0.073194f, 0.132237f, -0.088522f,
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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,
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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,
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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,
0.020182f, 0.052114f, 0.017878f, 0.010478f, -0.001381f, -0.034644f,
0.025135f, -0.037748f, 0.004973f, 0.024778f, 0.041816f, 0.032111f,
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0.229289f, 0.282418f, 0.250945f, 0.197273f, 0.045131f, -0.008305f,
0.072024f, 0.044547f, -0.050010f, 0.055504f, 0.001343f, -0.014445f,
0.254909f, 0.309091f, 0.228249f, 0.274843f, 0.089778f, -0.046581f,
0.072714f, 0.126814f, -0.048931f, -0.045743f, -0.151333f, -0.004490f,
0.179966f, 0.058150f, -0.178622f, -0.088159f, -0.074416f, -0.005821f,
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0.253792f, 0.301039f, 0.219163f, 0.256027f, 0.058007f, -0.041431f,
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};
static const float weights_layer_3[] = {
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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);
}
}