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ACNet_HDN_L1.glsl
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/*
MIT License
Copyright (c) 2020 TianZer
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
/*
description: Anime4KCPP Net HDN Level 1 GLSL
Author: TianZerL
*/
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L1
//!BIND LUMA
//!SAVE L1_1
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL1[9 * 4] = float[9 * 4]
(
-6.6326e-02, -2.2316e-01, 4.2471e-02,
1.7064e-02, -6.8305e-01, -1.5978e-01,
6.7568e-01, 3.2212e-01, 8.3561e-02,
-4.6649e-01, -6.8789e-02, 5.3455e-01,
-5.0941e-01, 7.0657e-02, 4.5647e-01,
-2.3657e-02, 3.5302e-02, -1.8316e-02,
-2.0316e-01, 4.7021e-02, -2.2313e-01,
5.3465e-02, 7.0750e-01, 9.1366e-02,
-2.8566e-01, -2.0521e-02, -7.1786e-02,
4.8186e-02, -9.3429e-02, 2.4493e-03,
3.4654e-01, 7.2625e-02, 1.6615e-01,
3.2101e-01, 3.2923e-01, -9.8548e-02
);
const float biasL1[4] = float[4]
(
-0.0264, -0.0229, -0.3021, -0.2579
);
vec4 hook()
{
vec4 tl = LUMA_texOff(vec2(-1,-1));
vec4 tc = LUMA_texOff(vec2(0,-1));
vec4 tr = LUMA_texOff(vec2(1,-1));
vec4 ml = LUMA_texOff(vec2(-1,0));
vec4 mc = LUMA_texOff(vec2(0,0));
vec4 mr = LUMA_texOff(vec2(1,0));
vec4 bl = LUMA_texOff(vec2(-1,1));
vec4 bc = LUMA_texOff(vec2(0,1));
vec4 br = LUMA_texOff(vec2(1,1));
vec4 c1234 = RELU(vec4(
tl.x * kernelsL1[0*9+0] + tc.x * kernelsL1[0*9+1] + tr.x * kernelsL1[0*9+2] +
ml.x * kernelsL1[0*9+3] + mc.x * kernelsL1[0*9+4] + mr.x * kernelsL1[0*9+5] +
bl.x * kernelsL1[0*9+6] + bc.x * kernelsL1[0*9+7] + br.x * kernelsL1[0*9+8] + biasL1[0],
tl.x * kernelsL1[1*9+0] + tc.x * kernelsL1[1*9+1] + tr.x * kernelsL1[1*9+2] +
ml.x * kernelsL1[1*9+3] + mc.x * kernelsL1[1*9+4] + mr.x * kernelsL1[1*9+5] +
bl.x * kernelsL1[1*9+6] + bc.x * kernelsL1[1*9+7] + br.x * kernelsL1[1*9+8] + biasL1[1],
tl.x * kernelsL1[2*9+0] + tc.x * kernelsL1[2*9+1] + tr.x * kernelsL1[2*9+2] +
ml.x * kernelsL1[2*9+3] + mc.x * kernelsL1[2*9+4] + mr.x * kernelsL1[2*9+5] +
bl.x * kernelsL1[2*9+6] + bc.x * kernelsL1[2*9+7] + br.x * kernelsL1[2*9+8] + biasL1[2],
tl.x * kernelsL1[3*9+0] + tc.x * kernelsL1[3*9+1] + tr.x * kernelsL1[3*9+2] +
ml.x * kernelsL1[3*9+3] + mc.x * kernelsL1[3*9+4] + mr.x * kernelsL1[3*9+5] +
bl.x * kernelsL1[3*9+6] + bc.x * kernelsL1[3*9+7] + br.x * kernelsL1[3*9+8] + biasL1[3]
));
return c1234;
}
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L1
//!BIND LUMA
//!SAVE L1_2
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL1[9 * 4] = float[9 * 4]
(
1.1916e-02, 2.0413e-01, -1.8920e-02,
6.0858e-02, 8.3548e-01, 1.4060e-01,
-9.1827e-01, -2.4551e-01, -4.6118e-02,
-5.2737e-02, 4.3151e-01, 1.7027e-01,
2.6647e-01, 5.5240e-01, 3.4745e-03,
5.3495e-02, -4.7059e-02, -2.6593e-02,
1.5691e-01, 4.7332e-01, 2.6651e-03,
1.7997e-02, 4.1367e-01, 1.3239e-02,
4.6932e-02, 1.0278e-01, 1.0699e-02,
-3.4319e-02, -7.6373e-01, -9.7022e-02,
-1.4160e-01, 2.9567e-01, 6.6220e-01,
7.3508e-05, 1.2683e-01, -6.3442e-02
);
const float biasL1[4] = float[4]
(
-0.0327, -0.0053, -0.7777, 0.0232
);
vec4 hook()
{
vec4 tl = LUMA_texOff(vec2(-1,-1));
vec4 tc = LUMA_texOff(vec2(0,-1));
vec4 tr = LUMA_texOff(vec2(1,-1));
vec4 ml = LUMA_texOff(vec2(-1,0));
vec4 mc = LUMA_texOff(vec2(0,0));
vec4 mr = LUMA_texOff(vec2(1,0));
vec4 bl = LUMA_texOff(vec2(-1,1));
vec4 bc = LUMA_texOff(vec2(0,1));
vec4 br = LUMA_texOff(vec2(1,1));
vec4 c5678 = RELU(vec4(
tl.x * kernelsL1[0*9+0] + tc.x * kernelsL1[0*9+1] + tr.x * kernelsL1[0*9+2] +
ml.x * kernelsL1[0*9+3] + mc.x * kernelsL1[0*9+4] + mr.x * kernelsL1[0*9+5] +
bl.x * kernelsL1[0*9+6] + bc.x * kernelsL1[0*9+7] + br.x * kernelsL1[0*9+8] + biasL1[0],
tl.x * kernelsL1[1*9+0] + tc.x * kernelsL1[1*9+1] + tr.x * kernelsL1[1*9+2] +
ml.x * kernelsL1[1*9+3] + mc.x * kernelsL1[1*9+4] + mr.x * kernelsL1[1*9+5] +
bl.x * kernelsL1[1*9+6] + bc.x * kernelsL1[1*9+7] + br.x * kernelsL1[1*9+8] + biasL1[1],
tl.x * kernelsL1[2*9+0] + tc.x * kernelsL1[2*9+1] + tr.x * kernelsL1[2*9+2] +
ml.x * kernelsL1[2*9+3] + mc.x * kernelsL1[2*9+4] + mr.x * kernelsL1[2*9+5] +
bl.x * kernelsL1[2*9+6] + bc.x * kernelsL1[2*9+7] + br.x * kernelsL1[2*9+8] + biasL1[2],
tl.x * kernelsL1[3*9+0] + tc.x * kernelsL1[3*9+1] + tr.x * kernelsL1[3*9+2] +
ml.x * kernelsL1[3*9+3] + mc.x * kernelsL1[3*9+4] + mr.x * kernelsL1[3*9+5] +
bl.x * kernelsL1[3*9+6] + bc.x * kernelsL1[3*9+7] + br.x * kernelsL1[3*9+8] + biasL1[3]
));
return c5678;
}
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L2
//!BIND L1_1
//!BIND L1_2
//!SAVE L2_1
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL[9 * 8 * 4] = float[9 * 8 * 4]
(
-7.8588e-41, -5.0770e-40, -2.3334e-40,
5.7174e-40, 6.9060e-41, 2.2264e-40,
-4.1631e-40, 4.5667e-40, -1.8115e-40,
-3.1000e-40, 3.1019e-40, 5.5423e-40,
-5.8518e-40, 2.1290e-40, -5.4579e-40,
-3.7753e-40, 3.6029e-40, -1.7875e-40,
4.2296e-40, 6.5672e-41, 1.4976e-40,
-3.1479e-40, -3.2881e-40, -5.9818e-40,
3.2053e-40, 3.0821e-40, 5.1321e-40,
-2.6557e-17, -3.8205e-17, -3.7077e-17,
-2.5168e-17, -3.4817e-17, -3.4186e-17,
-1.8056e-17, -2.3105e-17, -2.2581e-17,
5.9355e-40, 2.4052e-40, -1.0027e-40,
2.2060e-40, 3.4864e-40, -5.7403e-40,
4.6936e-40, -3.3951e-40, -4.7715e-40,
-9.7917e-11, -1.0331e-10, -9.6141e-11,
-1.0581e-10, -1.1173e-10, -1.0317e-10,
-1.0192e-10, -1.0681e-10, -9.8738e-11,
-1.0402e-29, -2.3233e-29, -1.7882e-29,
-1.4804e-29, -3.7821e-29, -3.0750e-29,
-1.0448e-29, -2.6740e-29, -2.1676e-29,
4.2124e-40, 2.5024e-40, 4.5312e-40,
-2.4880e-40, 2.9838e-41, -2.7215e-41,
-2.6347e-40, 1.5950e-40, 9.3734e-41,
-1.4936e-01, -1.0438e-01, 2.9827e-02,
1.4751e-02, -1.6854e-01, -8.8101e-02,
4.9228e-02, -3.0744e-02, -1.1512e-01,
-3.4996e-02, -2.5024e-02, -1.8880e-02,
3.0008e-02, 4.8689e-02, -1.3415e-01,
-9.1698e-03, -1.1019e-02, -5.0655e-02,
-6.6579e-02, -2.6447e-02, 1.9791e-02,
-4.1727e-02, 3.6433e-02, 3.1516e-02,
-5.7619e-02, 2.3401e-02, 3.0785e-02,
-3.3610e-02, 1.2263e-01, 2.4351e-02,
1.7148e-02, 1.7144e-01, 4.0305e-02,
8.7902e-03, -7.0077e-02, -1.0688e-01,
4.7460e-02, -1.4093e-03, -1.5911e-02,
-2.2978e-02, 9.9025e-02, 1.2867e-02,
3.4704e-02, 1.4672e-01, 7.9188e-02,
-4.4222e-02, -3.9480e-02, -1.9193e-01,
-3.1897e-02, 1.0776e-01, -5.2742e-02,
8.0377e-02, 2.5764e-01, -9.7330e-02,
-1.1593e-01, -5.3753e-02, -2.8918e-02,
6.7939e-02, 2.3963e-01, 2.0856e-01,
2.7964e-02, 2.7781e-01, 2.1859e-01,
-1.5196e-02, 9.6704e-03, -8.0136e-02,
8.9441e-02, 1.0314e-01, -2.0204e-02,
-3.3970e-02, -1.4562e-02, 3.4723e-02,
2.3357e-40, -1.4361e-40, 2.0498e-40,
-5.2355e-40, -6.0151e-40, -2.9264e-40,
1.9715e-41, 5.9793e-41, -1.3675e-40,
5.3771e-40, 6.5637e-41, -3.8471e-40,
-3.0820e-40, -1.7004e-40, -1.9371e-40,
-5.1159e-40, 7.3244e-41, 3.5861e-41,
2.8441e-40, 4.5248e-41, 1.9771e-40,
-2.4681e-40, 3.6054e-40, 3.3496e-40,
-6.5048e-42, -1.6001e-40, 4.8243e-41,
-1.0165e-08, -9.9140e-09, -9.6054e-09,
-1.0511e-08, -1.0256e-08, -9.9066e-09,
-1.0521e-08, -1.0320e-08, -9.9896e-09,
2.6042e-40, 4.2016e-40, 5.3537e-40,
1.4594e-40, 1.1344e-40, 3.5144e-40,
-2.5736e-37, -1.3591e-39, 2.1029e-40,
-3.1420e-07, -3.0309e-07, -2.9630e-07,
-3.1196e-07, -2.9967e-07, -2.9249e-07,
-3.1296e-07, -3.0086e-07, -2.9332e-07,
-6.1256e-12, -5.9283e-12, -5.6508e-12,
-6.5297e-12, -6.4118e-12, -6.0667e-12,
-6.8382e-12, -6.8547e-12, -6.5225e-12,
-5.0327e-26, -1.0795e-25, -1.8952e-25,
-2.4220e-26, -5.9067e-26, -1.1323e-25,
-2.1499e-27, -5.5342e-27, -1.0333e-26,
4.5039e-03, -1.3303e-02, 1.6183e-01,
6.5951e-02, -7.1353e-02, 1.7254e-01,
-1.8671e-03, 1.0593e-01, -3.6872e-02,
4.9102e-02, -2.4075e-03, 4.8194e-02,
-7.0892e-02, -1.8948e-01, -1.6586e-01,
-2.8102e-02, 2.0870e-02, 5.9228e-02,
1.2673e-02, 3.3908e-02, 4.8282e-02,
4.4369e-02, 5.6304e-02, 1.2225e-02,
4.1855e-02, 1.1990e-01, 6.3799e-02,
-7.3884e-02, 1.4153e-02, 9.5825e-02,
4.2850e-02, -3.5337e-02, 1.3615e-01,
-2.0900e-01, -2.2835e-02, -8.6987e-02,
-6.7793e-02, 1.3547e-01, -9.9666e-02,
3.5498e-02, 5.3725e-02, 1.1501e-01,
-1.2238e-01, 3.5354e-02, 7.4216e-02,
-3.5288e-02, 7.0111e-03, 2.4820e-02,
-1.0649e-02, 1.6715e-01, 1.2825e-01,
3.1145e-02, 1.2097e-01, -1.2073e-02,
-7.0603e-02, 5.5574e-02, -5.0025e-02,
-8.2885e-02, 1.0957e-01, 1.3311e-01,
2.9147e-02, -1.1849e-02, 8.9953e-02,
-3.2247e-02, -1.0747e-02, 9.1431e-03,
1.2114e-01, -5.9780e-02, 5.4821e-02,
-5.2592e-02, -6.9082e-02, -7.5981e-02
);
const float biasL[4] = float[4]
(
-3.1869e-08, -3.8279e-01, -6.3693e-05, -5.9054e-02
);
vec4 hook()
{
vec4 tl1 = L1_1_texOff(vec2(-1,-1));
vec4 tc1 = L1_1_texOff(vec2(0,-1));
vec4 tr1 = L1_1_texOff(vec2(1,-1));
vec4 ml1 = L1_1_texOff(vec2(-1,0));
vec4 mc1 = L1_1_texOff(vec2(0,0));
vec4 mr1 = L1_1_texOff(vec2(1,0));
vec4 bl1 = L1_1_texOff(vec2(-1,1));
vec4 bc1 = L1_1_texOff(vec2(0,1));
vec4 br1 = L1_1_texOff(vec2(1,1));
vec4 tl2 = L1_2_texOff(vec2(-1,-1));
vec4 tc2 = L1_2_texOff(vec2(0,-1));
vec4 tr2 = L1_2_texOff(vec2(1,-1));
vec4 ml2 = L1_2_texOff(vec2(-1,0));
vec4 mc2 = L1_2_texOff(vec2(0,0));
vec4 mr2 = L1_2_texOff(vec2(1,0));
vec4 bl2 = L1_2_texOff(vec2(-1,1));
vec4 bc2 = L1_2_texOff(vec2(0,1));
vec4 br2 = L1_2_texOff(vec2(1,1));
vec4 c1234 = RELU(vec4(
tl1.x * kernelsL[0*72+0*9+0] + tc1.x * kernelsL[0*72+0*9+1] + tr1.x * kernelsL[0*72+0*9+2] +
ml1.x * kernelsL[0*72+0*9+3] + mc1.x * kernelsL[0*72+0*9+4] + mr1.x * kernelsL[0*72+0*9+5] +
bl1.x * kernelsL[0*72+0*9+6] + bc1.x * kernelsL[0*72+0*9+7] + br1.x * kernelsL[0*72+0*9+8] +
tl1.y * kernelsL[0*72+1*9+0] + tc1.y * kernelsL[0*72+1*9+1] + tr1.y * kernelsL[0*72+1*9+2] +
ml1.y * kernelsL[0*72+1*9+3] + mc1.y * kernelsL[0*72+1*9+4] + mr1.y * kernelsL[0*72+1*9+5] +
bl1.y * kernelsL[0*72+1*9+6] + bc1.y * kernelsL[0*72+1*9+7] + br1.y * kernelsL[0*72+1*9+8] +
tl1.z * kernelsL[0*72+2*9+0] + tc1.z * kernelsL[0*72+2*9+1] + tr1.z * kernelsL[0*72+2*9+2] +
ml1.z * kernelsL[0*72+2*9+3] + mc1.z * kernelsL[0*72+2*9+4] + mr1.z * kernelsL[0*72+2*9+5] +
bl1.z * kernelsL[0*72+2*9+6] + bc1.z * kernelsL[0*72+2*9+7] + br1.z * kernelsL[0*72+2*9+8] +
tl1.w * kernelsL[0*72+3*9+0] + tc1.w * kernelsL[0*72+3*9+1] + tr1.w * kernelsL[0*72+3*9+2] +
ml1.w * kernelsL[0*72+3*9+3] + mc1.w * kernelsL[0*72+3*9+4] + mr1.w * kernelsL[0*72+3*9+5] +
bl1.w * kernelsL[0*72+3*9+6] + bc1.w * kernelsL[0*72+3*9+7] + br1.w * kernelsL[0*72+3*9+8] +
tl2.x * kernelsL[0*72+4*9+0] + tc2.x * kernelsL[0*72+4*9+1] + tr2.x * kernelsL[0*72+4*9+2] +
ml2.x * kernelsL[0*72+4*9+3] + mc2.x * kernelsL[0*72+4*9+4] + mr2.x * kernelsL[0*72+4*9+5] +
bl2.x * kernelsL[0*72+4*9+6] + bc2.x * kernelsL[0*72+4*9+7] + br2.x * kernelsL[0*72+4*9+8] +
tl2.y * kernelsL[0*72+5*9+0] + tc2.y * kernelsL[0*72+5*9+1] + tr2.y * kernelsL[0*72+5*9+2] +
ml2.y * kernelsL[0*72+5*9+3] + mc2.y * kernelsL[0*72+5*9+4] + mr2.y * kernelsL[0*72+5*9+5] +
bl2.y * kernelsL[0*72+5*9+6] + bc2.y * kernelsL[0*72+5*9+7] + br2.y * kernelsL[0*72+5*9+8] +
tl2.z * kernelsL[0*72+6*9+0] + tc2.z * kernelsL[0*72+6*9+1] + tr2.z * kernelsL[0*72+6*9+2] +
ml2.z * kernelsL[0*72+6*9+3] + mc2.z * kernelsL[0*72+6*9+4] + mr2.z * kernelsL[0*72+6*9+5] +
bl2.z * kernelsL[0*72+6*9+6] + bc2.z * kernelsL[0*72+6*9+7] + br2.z * kernelsL[0*72+6*9+8] +
tl2.w * kernelsL[0*72+7*9+0] + tc2.w * kernelsL[0*72+7*9+1] + tr2.w * kernelsL[0*72+7*9+2] +
ml2.w * kernelsL[0*72+7*9+3] + mc2.w * kernelsL[0*72+7*9+4] + mr2.w * kernelsL[0*72+7*9+5] +
bl2.w * kernelsL[0*72+7*9+6] + bc2.w * kernelsL[0*72+7*9+7] + br2.w * kernelsL[0*72+7*9+8] + biasL[0]
,
tl1.x * kernelsL[1*72+0*9+0] + tc1.x * kernelsL[1*72+0*9+1] + tr1.x * kernelsL[1*72+0*9+2] +
ml1.x * kernelsL[1*72+0*9+3] + mc1.x * kernelsL[1*72+0*9+4] + mr1.x * kernelsL[1*72+0*9+5] +
bl1.x * kernelsL[1*72+0*9+6] + bc1.x * kernelsL[1*72+0*9+7] + br1.x * kernelsL[1*72+0*9+8] +
tl1.y * kernelsL[1*72+1*9+0] + tc1.y * kernelsL[1*72+1*9+1] + tr1.y * kernelsL[1*72+1*9+2] +
ml1.y * kernelsL[1*72+1*9+3] + mc1.y * kernelsL[1*72+1*9+4] + mr1.y * kernelsL[1*72+1*9+5] +
bl1.y * kernelsL[1*72+1*9+6] + bc1.y * kernelsL[1*72+1*9+7] + br1.y * kernelsL[1*72+1*9+8] +
tl1.z * kernelsL[1*72+2*9+0] + tc1.z * kernelsL[1*72+2*9+1] + tr1.z * kernelsL[1*72+2*9+2] +
ml1.z * kernelsL[1*72+2*9+3] + mc1.z * kernelsL[1*72+2*9+4] + mr1.z * kernelsL[1*72+2*9+5] +
bl1.z * kernelsL[1*72+2*9+6] + bc1.z * kernelsL[1*72+2*9+7] + br1.z * kernelsL[1*72+2*9+8] +
tl1.w * kernelsL[1*72+3*9+0] + tc1.w * kernelsL[1*72+3*9+1] + tr1.w * kernelsL[1*72+3*9+2] +
ml1.w * kernelsL[1*72+3*9+3] + mc1.w * kernelsL[1*72+3*9+4] + mr1.w * kernelsL[1*72+3*9+5] +
bl1.w * kernelsL[1*72+3*9+6] + bc1.w * kernelsL[1*72+3*9+7] + br1.w * kernelsL[1*72+3*9+8] +
tl2.x * kernelsL[1*72+4*9+0] + tc2.x * kernelsL[1*72+4*9+1] + tr2.x * kernelsL[1*72+4*9+2] +
ml2.x * kernelsL[1*72+4*9+3] + mc2.x * kernelsL[1*72+4*9+4] + mr2.x * kernelsL[1*72+4*9+5] +
bl2.x * kernelsL[1*72+4*9+6] + bc2.x * kernelsL[1*72+4*9+7] + br2.x * kernelsL[1*72+4*9+8] +
tl2.y * kernelsL[1*72+5*9+0] + tc2.y * kernelsL[1*72+5*9+1] + tr2.y * kernelsL[1*72+5*9+2] +
ml2.y * kernelsL[1*72+5*9+3] + mc2.y * kernelsL[1*72+5*9+4] + mr2.y * kernelsL[1*72+5*9+5] +
bl2.y * kernelsL[1*72+5*9+6] + bc2.y * kernelsL[1*72+5*9+7] + br2.y * kernelsL[1*72+5*9+8] +
tl2.z * kernelsL[1*72+6*9+0] + tc2.z * kernelsL[1*72+6*9+1] + tr2.z * kernelsL[1*72+6*9+2] +
ml2.z * kernelsL[1*72+6*9+3] + mc2.z * kernelsL[1*72+6*9+4] + mr2.z * kernelsL[1*72+6*9+5] +
bl2.z * kernelsL[1*72+6*9+6] + bc2.z * kernelsL[1*72+6*9+7] + br2.z * kernelsL[1*72+6*9+8] +
tl2.w * kernelsL[1*72+7*9+0] + tc2.w * kernelsL[1*72+7*9+1] + tr2.w * kernelsL[1*72+7*9+2] +
ml2.w * kernelsL[1*72+7*9+3] + mc2.w * kernelsL[1*72+7*9+4] + mr2.w * kernelsL[1*72+7*9+5] +
bl2.w * kernelsL[1*72+7*9+6] + bc2.w * kernelsL[1*72+7*9+7] + br2.w * kernelsL[1*72+7*9+8] + biasL[1]
,
tl1.x * kernelsL[2*72+0*9+0] + tc1.x * kernelsL[2*72+0*9+1] + tr1.x * kernelsL[2*72+0*9+2] +
ml1.x * kernelsL[2*72+0*9+3] + mc1.x * kernelsL[2*72+0*9+4] + mr1.x * kernelsL[2*72+0*9+5] +
bl1.x * kernelsL[2*72+0*9+6] + bc1.x * kernelsL[2*72+0*9+7] + br1.x * kernelsL[2*72+0*9+8] +
tl1.y * kernelsL[2*72+1*9+0] + tc1.y * kernelsL[2*72+1*9+1] + tr1.y * kernelsL[2*72+1*9+2] +
ml1.y * kernelsL[2*72+1*9+3] + mc1.y * kernelsL[2*72+1*9+4] + mr1.y * kernelsL[2*72+1*9+5] +
bl1.y * kernelsL[2*72+1*9+6] + bc1.y * kernelsL[2*72+1*9+7] + br1.y * kernelsL[2*72+1*9+8] +
tl1.z * kernelsL[2*72+2*9+0] + tc1.z * kernelsL[2*72+2*9+1] + tr1.z * kernelsL[2*72+2*9+2] +
ml1.z * kernelsL[2*72+2*9+3] + mc1.z * kernelsL[2*72+2*9+4] + mr1.z * kernelsL[2*72+2*9+5] +
bl1.z * kernelsL[2*72+2*9+6] + bc1.z * kernelsL[2*72+2*9+7] + br1.z * kernelsL[2*72+2*9+8] +
tl1.w * kernelsL[2*72+3*9+0] + tc1.w * kernelsL[2*72+3*9+1] + tr1.w * kernelsL[2*72+3*9+2] +
ml1.w * kernelsL[2*72+3*9+3] + mc1.w * kernelsL[2*72+3*9+4] + mr1.w * kernelsL[2*72+3*9+5] +
bl1.w * kernelsL[2*72+3*9+6] + bc1.w * kernelsL[2*72+3*9+7] + br1.w * kernelsL[2*72+3*9+8] +
tl2.x * kernelsL[2*72+4*9+0] + tc2.x * kernelsL[2*72+4*9+1] + tr2.x * kernelsL[2*72+4*9+2] +
ml2.x * kernelsL[2*72+4*9+3] + mc2.x * kernelsL[2*72+4*9+4] + mr2.x * kernelsL[2*72+4*9+5] +
bl2.x * kernelsL[2*72+4*9+6] + bc2.x * kernelsL[2*72+4*9+7] + br2.x * kernelsL[2*72+4*9+8] +
tl2.y * kernelsL[2*72+5*9+0] + tc2.y * kernelsL[2*72+5*9+1] + tr2.y * kernelsL[2*72+5*9+2] +
ml2.y * kernelsL[2*72+5*9+3] + mc2.y * kernelsL[2*72+5*9+4] + mr2.y * kernelsL[2*72+5*9+5] +
bl2.y * kernelsL[2*72+5*9+6] + bc2.y * kernelsL[2*72+5*9+7] + br2.y * kernelsL[2*72+5*9+8] +
tl2.z * kernelsL[2*72+6*9+0] + tc2.z * kernelsL[2*72+6*9+1] + tr2.z * kernelsL[2*72+6*9+2] +
ml2.z * kernelsL[2*72+6*9+3] + mc2.z * kernelsL[2*72+6*9+4] + mr2.z * kernelsL[2*72+6*9+5] +
bl2.z * kernelsL[2*72+6*9+6] + bc2.z * kernelsL[2*72+6*9+7] + br2.z * kernelsL[2*72+6*9+8] +
tl2.w * kernelsL[2*72+7*9+0] + tc2.w * kernelsL[2*72+7*9+1] + tr2.w * kernelsL[2*72+7*9+2] +
ml2.w * kernelsL[2*72+7*9+3] + mc2.w * kernelsL[2*72+7*9+4] + mr2.w * kernelsL[2*72+7*9+5] +
bl2.w * kernelsL[2*72+7*9+6] + bc2.w * kernelsL[2*72+7*9+7] + br2.w * kernelsL[2*72+7*9+8] + biasL[2]
,
tl1.x * kernelsL[3*72+0*9+0] + tc1.x * kernelsL[3*72+0*9+1] + tr1.x * kernelsL[3*72+0*9+2] +
ml1.x * kernelsL[3*72+0*9+3] + mc1.x * kernelsL[3*72+0*9+4] + mr1.x * kernelsL[3*72+0*9+5] +
bl1.x * kernelsL[3*72+0*9+6] + bc1.x * kernelsL[3*72+0*9+7] + br1.x * kernelsL[3*72+0*9+8] +
tl1.y * kernelsL[3*72+1*9+0] + tc1.y * kernelsL[3*72+1*9+1] + tr1.y * kernelsL[3*72+1*9+2] +
ml1.y * kernelsL[3*72+1*9+3] + mc1.y * kernelsL[3*72+1*9+4] + mr1.y * kernelsL[3*72+1*9+5] +
bl1.y * kernelsL[3*72+1*9+6] + bc1.y * kernelsL[3*72+1*9+7] + br1.y * kernelsL[3*72+1*9+8] +
tl1.z * kernelsL[3*72+2*9+0] + tc1.z * kernelsL[3*72+2*9+1] + tr1.z * kernelsL[3*72+2*9+2] +
ml1.z * kernelsL[3*72+2*9+3] + mc1.z * kernelsL[3*72+2*9+4] + mr1.z * kernelsL[3*72+2*9+5] +
bl1.z * kernelsL[3*72+2*9+6] + bc1.z * kernelsL[3*72+2*9+7] + br1.z * kernelsL[3*72+2*9+8] +
tl1.w * kernelsL[3*72+3*9+0] + tc1.w * kernelsL[3*72+3*9+1] + tr1.w * kernelsL[3*72+3*9+2] +
ml1.w * kernelsL[3*72+3*9+3] + mc1.w * kernelsL[3*72+3*9+4] + mr1.w * kernelsL[3*72+3*9+5] +
bl1.w * kernelsL[3*72+3*9+6] + bc1.w * kernelsL[3*72+3*9+7] + br1.w * kernelsL[3*72+3*9+8] +
tl2.x * kernelsL[3*72+4*9+0] + tc2.x * kernelsL[3*72+4*9+1] + tr2.x * kernelsL[3*72+4*9+2] +
ml2.x * kernelsL[3*72+4*9+3] + mc2.x * kernelsL[3*72+4*9+4] + mr2.x * kernelsL[3*72+4*9+5] +
bl2.x * kernelsL[3*72+4*9+6] + bc2.x * kernelsL[3*72+4*9+7] + br2.x * kernelsL[3*72+4*9+8] +
tl2.y * kernelsL[3*72+5*9+0] + tc2.y * kernelsL[3*72+5*9+1] + tr2.y * kernelsL[3*72+5*9+2] +
ml2.y * kernelsL[3*72+5*9+3] + mc2.y * kernelsL[3*72+5*9+4] + mr2.y * kernelsL[3*72+5*9+5] +
bl2.y * kernelsL[3*72+5*9+6] + bc2.y * kernelsL[3*72+5*9+7] + br2.y * kernelsL[3*72+5*9+8] +
tl2.z * kernelsL[3*72+6*9+0] + tc2.z * kernelsL[3*72+6*9+1] + tr2.z * kernelsL[3*72+6*9+2] +
ml2.z * kernelsL[3*72+6*9+3] + mc2.z * kernelsL[3*72+6*9+4] + mr2.z * kernelsL[3*72+6*9+5] +
bl2.z * kernelsL[3*72+6*9+6] + bc2.z * kernelsL[3*72+6*9+7] + br2.z * kernelsL[3*72+6*9+8] +
tl2.w * kernelsL[3*72+7*9+0] + tc2.w * kernelsL[3*72+7*9+1] + tr2.w * kernelsL[3*72+7*9+2] +
ml2.w * kernelsL[3*72+7*9+3] + mc2.w * kernelsL[3*72+7*9+4] + mr2.w * kernelsL[3*72+7*9+5] +
bl2.w * kernelsL[3*72+7*9+6] + bc2.w * kernelsL[3*72+7*9+7] + br2.w * kernelsL[3*72+7*9+8] + biasL[3]
));
return c1234;
}
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L2
//!BIND L1_1
//!BIND L1_2
//!SAVE L2_2
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL[9 * 8 * 4] = float[9 * 8 * 4]
(
-7.8533e-02, 1.3658e-01, 1.0923e-01,
-3.2530e-02, -2.1342e-01, -1.2200e-01,
-1.9196e-02, 1.0450e-01, -8.9044e-02,
-2.0110e-02, 6.1439e-02, -2.7405e-02,
6.0823e-02, -6.4268e-03, -9.1778e-03,
6.4877e-02, -6.1227e-02, -5.4466e-02,
9.6375e-02, 1.7519e-01, 5.0725e-03,
1.9159e-01, 3.9725e-01, 1.2851e-01,
-6.9197e-02, 4.9372e-02, -3.4221e-02,
1.1583e-01, 1.3389e-01, 2.9135e-01,
1.0290e-02, 1.1214e-01, 1.7560e-01,
-1.8048e-02, 8.4782e-02, 4.9925e-02,
-3.8447e-02, -1.3156e-01, -1.1072e-01,
1.8256e-01, 2.2831e-01, -1.6508e-01,
4.6781e-02, 1.4913e-01, -8.6956e-02,
5.1365e-04, 6.7873e-02, -3.4787e-03,
1.7689e-01, 1.8414e-01, 2.2286e-01,
1.2571e-01, 1.7687e-01, 1.5949e-01,
5.9904e-02, 1.6259e-01, 1.4313e-01,
2.2234e-01, 4.0943e-01, 3.1469e-01,
1.9799e-01, 4.3052e-01, 3.0510e-01,
1.2259e-01, -1.0778e-02, 6.2284e-03,
1.4508e-02, -6.9073e-02, 5.0998e-02,
5.2962e-02, -1.5291e-01, -1.0491e-02,
-8.6903e-02, -1.0430e-01, 3.0130e-02,
4.1691e-02, -1.2675e-01, -5.5169e-01,
8.9644e-02, 3.6910e-02, -1.5459e-01,
5.3656e-03, 6.7936e-02, 1.0793e-01,
-2.7424e-02, -1.7652e-01, -3.5776e-01,
2.4593e-02, -5.6237e-01, -5.9038e-01,
-9.4807e-02, -7.5681e-02, -3.6990e-02,
8.7385e-03, -5.7989e-02, -4.9573e-02,
-7.7422e-02, -1.1899e-01, -7.4023e-02,
9.1539e-03, -1.1760e-01, 4.6825e-02,
1.9901e-02, -3.9718e-02, 1.2997e-02,
4.2209e-02, -5.2119e-02, -1.2255e-01,
2.4262e-02, 5.3676e-02, -2.4767e-01,
-4.2933e-02, -2.2473e-01, -4.0310e-01,
-3.5160e-02, 1.9858e-01, -1.5943e-01,
1.3208e-01, -1.0493e-01, -6.7076e-02,
-2.5244e-01, 1.1175e-02, 2.5568e-01,
-3.3867e-01, 3.1953e-02, 5.9426e-01,
4.0551e-02, 4.4914e-03, -1.9348e-02,
-6.7386e-02, -1.5543e-01, -3.0883e-02,
8.9177e-02, -4.6432e-02, 6.8227e-02,
8.7784e-02, 3.6127e-02, -2.0375e-02,
4.5461e-02, -4.9071e-02, 9.9435e-02,
-2.5700e-01, -2.7706e-01, 6.2776e-02,
-6.9571e-02, -5.7888e-03, 9.3852e-02,
2.8490e-02, -2.7854e-01, 1.4209e-01,
1.5373e-02, -4.3503e-02, 9.6895e-02,
1.1682e-02, 1.5608e-01, 1.5844e-01,
5.8027e-02, 2.6632e-02, -8.5479e-03,
1.2836e-01, 2.0714e-01, 1.0228e-01,
1.4647e-02, 5.7609e-02, -1.6728e-02,
2.1212e-01, 3.2673e-01, 4.5670e-02,
-6.0844e-02, -1.1768e-01, -1.1233e-01,
5.0123e-04, 6.3947e-02, -1.8356e-01,
1.4091e-01, -2.1568e-02, 8.5933e-02,
-3.9406e-02, 8.2921e-02, -1.0601e-01,
4.1284e-02, -7.3138e-02, 1.7264e-01,
2.5883e-02, 5.2945e-01, 2.4510e-01,
2.7291e-03, 4.0173e-02, 7.8221e-03,
-3.5795e-02, -4.8631e-03, -2.2715e-01,
1.2330e-01, 7.1739e-01, -4.1725e-01,
7.5106e-02, 2.5267e-02, -2.8655e-01,
-7.8731e-02, -7.5747e-03, -5.5601e-02,
7.9764e-02, 1.0524e-01, 8.6742e-03,
2.1791e-02, 3.7304e-02, -1.1534e-01,
-1.2011e-01, -7.5160e-02, 1.3737e-02,
-2.9470e-01, 2.6613e-01, -2.3740e-02,
1.2957e-01, 1.4752e-01, -9.3655e-02,
2.9828e-02, 2.0664e-01, 1.9731e-02,
-8.0378e-02, -3.9481e-01, -1.5395e-01,
-5.7944e-02, -8.6343e-02, -5.4324e-02,
7.1664e-02, 1.5294e-01, -1.2112e-02,
2.1023e-02, 1.1945e-01, -7.2998e-02,
-1.1693e-02, -1.8818e-01, -9.8693e-02,
-6.7017e-02, 6.9767e-02, -5.0268e-02,
-9.1106e-03, 2.4267e-01, 6.0277e-02,
3.5269e-02, 7.7376e-02, 1.6642e-02,
-5.2600e-02, -1.8864e-01, -1.1195e-01,
3.2119e-01, -9.7913e-02, 1.4734e-01,
8.6988e-02, -5.3563e-03, -2.6136e-03,
-9.1528e-03, 2.8186e-01, -1.5933e-01,
4.8499e-02, 4.5189e-01, -1.6399e-01,
5.8164e-02, 6.3251e-02, -2.8738e-02,
2.0424e-01, -7.2819e-02, 2.1903e-02,
-3.5630e-01, 1.3171e-01, -7.6749e-02,
3.8848e-02, 1.7902e-01, -1.1902e-01,
-4.4221e-02, 1.5032e-02, 2.9078e-02,
-1.9738e-01, -1.4878e-02, 1.3315e-02,
1.3956e-02, 1.2856e-01, 7.0688e-02,
2.0933e-01, 1.7286e-01, 6.7601e-02,
5.5136e-01, 4.6866e-01, 1.8402e-01,
2.2362e-01, 2.4124e-01, 1.3167e-01
);
const float biasL[4] = float[4]
(
9.3774e-04, -2.9944e-02, -1.1156e-03, -7.5635e-02
);
vec4 hook()
{
vec4 tl1 = L1_1_texOff(vec2(-1,-1));
vec4 tc1 = L1_1_texOff(vec2(0,-1));
vec4 tr1 = L1_1_texOff(vec2(1,-1));
vec4 ml1 = L1_1_texOff(vec2(-1,0));
vec4 mc1 = L1_1_texOff(vec2(0,0));
vec4 mr1 = L1_1_texOff(vec2(1,0));
vec4 bl1 = L1_1_texOff(vec2(-1,1));
vec4 bc1 = L1_1_texOff(vec2(0,1));
vec4 br1 = L1_1_texOff(vec2(1,1));
vec4 tl2 = L1_2_texOff(vec2(-1,-1));
vec4 tc2 = L1_2_texOff(vec2(0,-1));
vec4 tr2 = L1_2_texOff(vec2(1,-1));
vec4 ml2 = L1_2_texOff(vec2(-1,0));
vec4 mc2 = L1_2_texOff(vec2(0,0));
vec4 mr2 = L1_2_texOff(vec2(1,0));
vec4 bl2 = L1_2_texOff(vec2(-1,1));
vec4 bc2 = L1_2_texOff(vec2(0,1));
vec4 br2 = L1_2_texOff(vec2(1,1));
vec4 c5678 = RELU(vec4(
tl1.x * kernelsL[0*72+0*9+0] + tc1.x * kernelsL[0*72+0*9+1] + tr1.x * kernelsL[0*72+0*9+2] +
ml1.x * kernelsL[0*72+0*9+3] + mc1.x * kernelsL[0*72+0*9+4] + mr1.x * kernelsL[0*72+0*9+5] +
bl1.x * kernelsL[0*72+0*9+6] + bc1.x * kernelsL[0*72+0*9+7] + br1.x * kernelsL[0*72+0*9+8] +
tl1.y * kernelsL[0*72+1*9+0] + tc1.y * kernelsL[0*72+1*9+1] + tr1.y * kernelsL[0*72+1*9+2] +
ml1.y * kernelsL[0*72+1*9+3] + mc1.y * kernelsL[0*72+1*9+4] + mr1.y * kernelsL[0*72+1*9+5] +
bl1.y * kernelsL[0*72+1*9+6] + bc1.y * kernelsL[0*72+1*9+7] + br1.y * kernelsL[0*72+1*9+8] +
tl1.z * kernelsL[0*72+2*9+0] + tc1.z * kernelsL[0*72+2*9+1] + tr1.z * kernelsL[0*72+2*9+2] +
ml1.z * kernelsL[0*72+2*9+3] + mc1.z * kernelsL[0*72+2*9+4] + mr1.z * kernelsL[0*72+2*9+5] +
bl1.z * kernelsL[0*72+2*9+6] + bc1.z * kernelsL[0*72+2*9+7] + br1.z * kernelsL[0*72+2*9+8] +
tl1.w * kernelsL[0*72+3*9+0] + tc1.w * kernelsL[0*72+3*9+1] + tr1.w * kernelsL[0*72+3*9+2] +
ml1.w * kernelsL[0*72+3*9+3] + mc1.w * kernelsL[0*72+3*9+4] + mr1.w * kernelsL[0*72+3*9+5] +
bl1.w * kernelsL[0*72+3*9+6] + bc1.w * kernelsL[0*72+3*9+7] + br1.w * kernelsL[0*72+3*9+8] +
tl2.x * kernelsL[0*72+4*9+0] + tc2.x * kernelsL[0*72+4*9+1] + tr2.x * kernelsL[0*72+4*9+2] +
ml2.x * kernelsL[0*72+4*9+3] + mc2.x * kernelsL[0*72+4*9+4] + mr2.x * kernelsL[0*72+4*9+5] +
bl2.x * kernelsL[0*72+4*9+6] + bc2.x * kernelsL[0*72+4*9+7] + br2.x * kernelsL[0*72+4*9+8] +
tl2.y * kernelsL[0*72+5*9+0] + tc2.y * kernelsL[0*72+5*9+1] + tr2.y * kernelsL[0*72+5*9+2] +
ml2.y * kernelsL[0*72+5*9+3] + mc2.y * kernelsL[0*72+5*9+4] + mr2.y * kernelsL[0*72+5*9+5] +
bl2.y * kernelsL[0*72+5*9+6] + bc2.y * kernelsL[0*72+5*9+7] + br2.y * kernelsL[0*72+5*9+8] +
tl2.z * kernelsL[0*72+6*9+0] + tc2.z * kernelsL[0*72+6*9+1] + tr2.z * kernelsL[0*72+6*9+2] +
ml2.z * kernelsL[0*72+6*9+3] + mc2.z * kernelsL[0*72+6*9+4] + mr2.z * kernelsL[0*72+6*9+5] +
bl2.z * kernelsL[0*72+6*9+6] + bc2.z * kernelsL[0*72+6*9+7] + br2.z * kernelsL[0*72+6*9+8] +
tl2.w * kernelsL[0*72+7*9+0] + tc2.w * kernelsL[0*72+7*9+1] + tr2.w * kernelsL[0*72+7*9+2] +
ml2.w * kernelsL[0*72+7*9+3] + mc2.w * kernelsL[0*72+7*9+4] + mr2.w * kernelsL[0*72+7*9+5] +
bl2.w * kernelsL[0*72+7*9+6] + bc2.w * kernelsL[0*72+7*9+7] + br2.w * kernelsL[0*72+7*9+8] + biasL[0]
,
tl1.x * kernelsL[1*72+0*9+0] + tc1.x * kernelsL[1*72+0*9+1] + tr1.x * kernelsL[1*72+0*9+2] +
ml1.x * kernelsL[1*72+0*9+3] + mc1.x * kernelsL[1*72+0*9+4] + mr1.x * kernelsL[1*72+0*9+5] +
bl1.x * kernelsL[1*72+0*9+6] + bc1.x * kernelsL[1*72+0*9+7] + br1.x * kernelsL[1*72+0*9+8] +
tl1.y * kernelsL[1*72+1*9+0] + tc1.y * kernelsL[1*72+1*9+1] + tr1.y * kernelsL[1*72+1*9+2] +
ml1.y * kernelsL[1*72+1*9+3] + mc1.y * kernelsL[1*72+1*9+4] + mr1.y * kernelsL[1*72+1*9+5] +
bl1.y * kernelsL[1*72+1*9+6] + bc1.y * kernelsL[1*72+1*9+7] + br1.y * kernelsL[1*72+1*9+8] +
tl1.z * kernelsL[1*72+2*9+0] + tc1.z * kernelsL[1*72+2*9+1] + tr1.z * kernelsL[1*72+2*9+2] +
ml1.z * kernelsL[1*72+2*9+3] + mc1.z * kernelsL[1*72+2*9+4] + mr1.z * kernelsL[1*72+2*9+5] +
bl1.z * kernelsL[1*72+2*9+6] + bc1.z * kernelsL[1*72+2*9+7] + br1.z * kernelsL[1*72+2*9+8] +
tl1.w * kernelsL[1*72+3*9+0] + tc1.w * kernelsL[1*72+3*9+1] + tr1.w * kernelsL[1*72+3*9+2] +
ml1.w * kernelsL[1*72+3*9+3] + mc1.w * kernelsL[1*72+3*9+4] + mr1.w * kernelsL[1*72+3*9+5] +
bl1.w * kernelsL[1*72+3*9+6] + bc1.w * kernelsL[1*72+3*9+7] + br1.w * kernelsL[1*72+3*9+8] +
tl2.x * kernelsL[1*72+4*9+0] + tc2.x * kernelsL[1*72+4*9+1] + tr2.x * kernelsL[1*72+4*9+2] +
ml2.x * kernelsL[1*72+4*9+3] + mc2.x * kernelsL[1*72+4*9+4] + mr2.x * kernelsL[1*72+4*9+5] +
bl2.x * kernelsL[1*72+4*9+6] + bc2.x * kernelsL[1*72+4*9+7] + br2.x * kernelsL[1*72+4*9+8] +
tl2.y * kernelsL[1*72+5*9+0] + tc2.y * kernelsL[1*72+5*9+1] + tr2.y * kernelsL[1*72+5*9+2] +
ml2.y * kernelsL[1*72+5*9+3] + mc2.y * kernelsL[1*72+5*9+4] + mr2.y * kernelsL[1*72+5*9+5] +
bl2.y * kernelsL[1*72+5*9+6] + bc2.y * kernelsL[1*72+5*9+7] + br2.y * kernelsL[1*72+5*9+8] +
tl2.z * kernelsL[1*72+6*9+0] + tc2.z * kernelsL[1*72+6*9+1] + tr2.z * kernelsL[1*72+6*9+2] +
ml2.z * kernelsL[1*72+6*9+3] + mc2.z * kernelsL[1*72+6*9+4] + mr2.z * kernelsL[1*72+6*9+5] +
bl2.z * kernelsL[1*72+6*9+6] + bc2.z * kernelsL[1*72+6*9+7] + br2.z * kernelsL[1*72+6*9+8] +
tl2.w * kernelsL[1*72+7*9+0] + tc2.w * kernelsL[1*72+7*9+1] + tr2.w * kernelsL[1*72+7*9+2] +
ml2.w * kernelsL[1*72+7*9+3] + mc2.w * kernelsL[1*72+7*9+4] + mr2.w * kernelsL[1*72+7*9+5] +
bl2.w * kernelsL[1*72+7*9+6] + bc2.w * kernelsL[1*72+7*9+7] + br2.w * kernelsL[1*72+7*9+8] + biasL[1]
,
tl1.x * kernelsL[2*72+0*9+0] + tc1.x * kernelsL[2*72+0*9+1] + tr1.x * kernelsL[2*72+0*9+2] +
ml1.x * kernelsL[2*72+0*9+3] + mc1.x * kernelsL[2*72+0*9+4] + mr1.x * kernelsL[2*72+0*9+5] +
bl1.x * kernelsL[2*72+0*9+6] + bc1.x * kernelsL[2*72+0*9+7] + br1.x * kernelsL[2*72+0*9+8] +
tl1.y * kernelsL[2*72+1*9+0] + tc1.y * kernelsL[2*72+1*9+1] + tr1.y * kernelsL[2*72+1*9+2] +
ml1.y * kernelsL[2*72+1*9+3] + mc1.y * kernelsL[2*72+1*9+4] + mr1.y * kernelsL[2*72+1*9+5] +
bl1.y * kernelsL[2*72+1*9+6] + bc1.y * kernelsL[2*72+1*9+7] + br1.y * kernelsL[2*72+1*9+8] +
tl1.z * kernelsL[2*72+2*9+0] + tc1.z * kernelsL[2*72+2*9+1] + tr1.z * kernelsL[2*72+2*9+2] +
ml1.z * kernelsL[2*72+2*9+3] + mc1.z * kernelsL[2*72+2*9+4] + mr1.z * kernelsL[2*72+2*9+5] +
bl1.z * kernelsL[2*72+2*9+6] + bc1.z * kernelsL[2*72+2*9+7] + br1.z * kernelsL[2*72+2*9+8] +
tl1.w * kernelsL[2*72+3*9+0] + tc1.w * kernelsL[2*72+3*9+1] + tr1.w * kernelsL[2*72+3*9+2] +
ml1.w * kernelsL[2*72+3*9+3] + mc1.w * kernelsL[2*72+3*9+4] + mr1.w * kernelsL[2*72+3*9+5] +
bl1.w * kernelsL[2*72+3*9+6] + bc1.w * kernelsL[2*72+3*9+7] + br1.w * kernelsL[2*72+3*9+8] +
tl2.x * kernelsL[2*72+4*9+0] + tc2.x * kernelsL[2*72+4*9+1] + tr2.x * kernelsL[2*72+4*9+2] +
ml2.x * kernelsL[2*72+4*9+3] + mc2.x * kernelsL[2*72+4*9+4] + mr2.x * kernelsL[2*72+4*9+5] +
bl2.x * kernelsL[2*72+4*9+6] + bc2.x * kernelsL[2*72+4*9+7] + br2.x * kernelsL[2*72+4*9+8] +
tl2.y * kernelsL[2*72+5*9+0] + tc2.y * kernelsL[2*72+5*9+1] + tr2.y * kernelsL[2*72+5*9+2] +
ml2.y * kernelsL[2*72+5*9+3] + mc2.y * kernelsL[2*72+5*9+4] + mr2.y * kernelsL[2*72+5*9+5] +
bl2.y * kernelsL[2*72+5*9+6] + bc2.y * kernelsL[2*72+5*9+7] + br2.y * kernelsL[2*72+5*9+8] +
tl2.z * kernelsL[2*72+6*9+0] + tc2.z * kernelsL[2*72+6*9+1] + tr2.z * kernelsL[2*72+6*9+2] +
ml2.z * kernelsL[2*72+6*9+3] + mc2.z * kernelsL[2*72+6*9+4] + mr2.z * kernelsL[2*72+6*9+5] +
bl2.z * kernelsL[2*72+6*9+6] + bc2.z * kernelsL[2*72+6*9+7] + br2.z * kernelsL[2*72+6*9+8] +
tl2.w * kernelsL[2*72+7*9+0] + tc2.w * kernelsL[2*72+7*9+1] + tr2.w * kernelsL[2*72+7*9+2] +
ml2.w * kernelsL[2*72+7*9+3] + mc2.w * kernelsL[2*72+7*9+4] + mr2.w * kernelsL[2*72+7*9+5] +
bl2.w * kernelsL[2*72+7*9+6] + bc2.w * kernelsL[2*72+7*9+7] + br2.w * kernelsL[2*72+7*9+8] + biasL[2]
,
tl1.x * kernelsL[3*72+0*9+0] + tc1.x * kernelsL[3*72+0*9+1] + tr1.x * kernelsL[3*72+0*9+2] +
ml1.x * kernelsL[3*72+0*9+3] + mc1.x * kernelsL[3*72+0*9+4] + mr1.x * kernelsL[3*72+0*9+5] +
bl1.x * kernelsL[3*72+0*9+6] + bc1.x * kernelsL[3*72+0*9+7] + br1.x * kernelsL[3*72+0*9+8] +
tl1.y * kernelsL[3*72+1*9+0] + tc1.y * kernelsL[3*72+1*9+1] + tr1.y * kernelsL[3*72+1*9+2] +
ml1.y * kernelsL[3*72+1*9+3] + mc1.y * kernelsL[3*72+1*9+4] + mr1.y * kernelsL[3*72+1*9+5] +
bl1.y * kernelsL[3*72+1*9+6] + bc1.y * kernelsL[3*72+1*9+7] + br1.y * kernelsL[3*72+1*9+8] +
tl1.z * kernelsL[3*72+2*9+0] + tc1.z * kernelsL[3*72+2*9+1] + tr1.z * kernelsL[3*72+2*9+2] +
ml1.z * kernelsL[3*72+2*9+3] + mc1.z * kernelsL[3*72+2*9+4] + mr1.z * kernelsL[3*72+2*9+5] +
bl1.z * kernelsL[3*72+2*9+6] + bc1.z * kernelsL[3*72+2*9+7] + br1.z * kernelsL[3*72+2*9+8] +
tl1.w * kernelsL[3*72+3*9+0] + tc1.w * kernelsL[3*72+3*9+1] + tr1.w * kernelsL[3*72+3*9+2] +
ml1.w * kernelsL[3*72+3*9+3] + mc1.w * kernelsL[3*72+3*9+4] + mr1.w * kernelsL[3*72+3*9+5] +
bl1.w * kernelsL[3*72+3*9+6] + bc1.w * kernelsL[3*72+3*9+7] + br1.w * kernelsL[3*72+3*9+8] +
tl2.x * kernelsL[3*72+4*9+0] + tc2.x * kernelsL[3*72+4*9+1] + tr2.x * kernelsL[3*72+4*9+2] +
ml2.x * kernelsL[3*72+4*9+3] + mc2.x * kernelsL[3*72+4*9+4] + mr2.x * kernelsL[3*72+4*9+5] +
bl2.x * kernelsL[3*72+4*9+6] + bc2.x * kernelsL[3*72+4*9+7] + br2.x * kernelsL[3*72+4*9+8] +
tl2.y * kernelsL[3*72+5*9+0] + tc2.y * kernelsL[3*72+5*9+1] + tr2.y * kernelsL[3*72+5*9+2] +
ml2.y * kernelsL[3*72+5*9+3] + mc2.y * kernelsL[3*72+5*9+4] + mr2.y * kernelsL[3*72+5*9+5] +
bl2.y * kernelsL[3*72+5*9+6] + bc2.y * kernelsL[3*72+5*9+7] + br2.y * kernelsL[3*72+5*9+8] +
tl2.z * kernelsL[3*72+6*9+0] + tc2.z * kernelsL[3*72+6*9+1] + tr2.z * kernelsL[3*72+6*9+2] +
ml2.z * kernelsL[3*72+6*9+3] + mc2.z * kernelsL[3*72+6*9+4] + mr2.z * kernelsL[3*72+6*9+5] +
bl2.z * kernelsL[3*72+6*9+6] + bc2.z * kernelsL[3*72+6*9+7] + br2.z * kernelsL[3*72+6*9+8] +
tl2.w * kernelsL[3*72+7*9+0] + tc2.w * kernelsL[3*72+7*9+1] + tr2.w * kernelsL[3*72+7*9+2] +
ml2.w * kernelsL[3*72+7*9+3] + mc2.w * kernelsL[3*72+7*9+4] + mr2.w * kernelsL[3*72+7*9+5] +
bl2.w * kernelsL[3*72+7*9+6] + bc2.w * kernelsL[3*72+7*9+7] + br2.w * kernelsL[3*72+7*9+8] + biasL[3]
));
return c5678;
}
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L3
//!BIND L2_1
//!BIND L2_2
//!SAVE L1_1
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL[9 * 8 * 4] = float[9 * 8 * 4]
(
-5.2308e-12, -5.4024e-12, -5.0039e-12,
-5.4553e-12, -5.6928e-12, -5.2812e-12,
-5.0230e-12, -5.2150e-12, -4.9133e-12,
5.7994e-02, 1.0051e-01, -1.0618e-01,
6.8090e-02, 1.2789e-01, 1.1380e-01,
-1.5882e-01, 8.2323e-03, -9.1424e-02,
2.0132e-07, 2.0907e-07, 2.1344e-07,
2.1179e-07, 2.2018e-07, 2.2381e-07,
2.1095e-07, 2.1920e-07, 2.2150e-07,
2.9336e-02, 5.4427e-02, -1.2082e-01,
5.8399e-02, 2.2261e-01, 1.1165e-01,
-9.6098e-02, 8.3175e-02, -6.5909e-02,
1.2007e-01, 1.9776e-01, 7.7464e-02,
6.7018e-02, 3.6536e-01, 1.3796e-01,
6.0724e-02, 4.6161e-02, 2.3740e-01,
-2.1117e-02, -2.0200e-02, 9.3703e-02,
-4.6932e-02, -1.5910e-01, 8.8094e-02,
-5.6641e-02, -1.7146e-01, -1.0502e-01,
-2.5624e-01, 1.6049e-01, -3.3267e-02,
-2.3248e-01, 5.4036e-01, 1.0027e-01,
-2.1680e-01, -7.0096e-03, -1.0692e-01,
-4.8357e-02, 2.5107e-01, 4.8323e-02,
9.7245e-02, 5.5015e-01, -3.4641e-01,
1.2458e-02, -1.3626e-01, -4.1992e-01,
-2.1359e-40, -1.4250e-40, -4.7123e-40,
-5.9433e-41, 1.9903e-41, -1.7701e-40,
-5.9941e-40, -5.8562e-40, -5.0226e-40,
-2.6581e-40, 1.3006e-40, -1.4201e-40,
5.4264e-40, 2.3848e-40, 5.6412e-40,
-2.6378e-41, -5.7132e-40, -4.1343e-40,
-3.2848e-22, -3.6697e-22, -3.4147e-22,
-3.5780e-22, -3.9435e-22, -3.5989e-22,
-3.1212e-22, -3.4305e-22, -3.0670e-22,
-1.1749e-08, -1.1602e-08, -1.1494e-08,
-1.2125e-08, -1.1918e-08, -1.1718e-08,
-1.1779e-08, -1.1623e-08, -1.1559e-08,
-5.0237e-07, -4.9179e-07, -4.6744e-07,
-5.1967e-07, -5.0826e-07, -4.8421e-07,
-5.0226e-07, -4.9668e-07, -4.8019e-07,
5.6433e-41, -3.0514e-40, -5.4526e-40,
1.1125e-41, 2.9485e-40, 5.5282e-40,
3.0229e-40, 1.5915e-40, 5.3759e-40,
-6.1144e-27, -9.2380e-26, -2.4302e-25,
-9.3834e-25, -1.0289e-23, -1.9513e-23,
-4.3746e-24, -4.4359e-23, -7.0505e-23,
-8.1604e-36, -3.2928e-37, -2.2994e-40,
-3.9543e-37, -9.9513e-39, 7.4616e-41,
-4.0044e-39, 4.4392e-40, 4.8856e-40,
-3.3447e-40, -3.9935e-40, 2.4649e-40,
2.0207e-40, -3.0245e-40, -7.1986e-41,
6.2938e-40, -3.6922e-40, 1.5296e-40,
-6.4982e-41, 5.0849e-41, 5.7873e-40,
1.4327e-40, -4.2163e-40, 1.3807e-40,
2.8569e-40, 1.9139e-40, 3.2985e-40,
-5.4410e-40, 2.3070e-40, 2.1690e-40,
-1.5964e-40, -2.2781e-40, 5.6766e-40,
2.2533e-42, -2.5532e-40, -5.5822e-40,
5.7249e-40, 5.3555e-40, -4.9107e-41,
1.7538e-40, -1.2312e-40, 5.0077e-40,
6.1500e-40, 1.9980e-40, 6.2953e-40,
-7.5314e-23, -9.4299e-23, -7.1342e-23,
-8.5139e-23, -1.1237e-22, -9.0478e-23,
-6.2038e-23, -8.5180e-23, -7.3015e-23,
5.0613e-40, 1.5224e-40, -1.8977e-40,
2.4108e-41, -5.1771e-40, 6.2317e-40,
1.0465e-40, 2.8816e-41, 6.2500e-40,
3.5727e-40, 4.2717e-40, -3.5900e-40,
-4.4831e-40, 3.4260e-40, -4.8293e-40,
-2.4133e-40, 3.1140e-40, -2.0777e-40,
-2.2906e-41, 3.5923e-40, -4.4443e-40,
-4.6615e-40, -2.1123e-40, 4.5700e-40,
-4.6360e-40, -3.6052e-40, -3.4319e-40,
-3.6575e-40, -3.5707e-40, -3.0530e-41,
4.2531e-40, -1.2255e-40, -3.9607e-40,
3.5903e-40, -5.4630e-40, -3.1460e-40,
2.8820e-40, 4.9460e-40, 6.1461e-40,
8.9118e-41, -4.6579e-40, -2.4172e-40,
-5.5474e-40, -8.1848e-41, -1.6910e-40,
-1.6272e-25, -1.8802e-25, -1.7229e-25,
-1.7850e-25, -2.0338e-25, -1.8235e-25,
-1.4715e-25, -1.6733e-25, -1.4681e-25,
-5.5471e-09, -5.6862e-09, -5.7043e-09,
-5.8727e-09, -5.9823e-09, -5.8983e-09,
-5.8040e-09, -5.8670e-09, -5.7388e-09,
-9.7253e-07, -9.7248e-07, -9.4623e-07,
-1.0149e-06, -1.0042e-06, -9.6709e-07,
-1.0139e-06, -9.9930e-07, -9.5295e-07,
-4.5042e-40, 2.6725e-40, 2.3181e-40,
-4.6274e-41, -1.1799e-40, 5.0685e-40,
-1.0765e-40, 3.3322e-40, -6.1905e-40,
-1.3653e-34, -3.4690e-33, -1.1578e-32,
-1.4444e-31, -2.1995e-30, -4.8668e-30,
-1.2965e-30, -2.0189e-29, -3.3962e-29,
-2.5057e-40, 7.2876e-41, 4.5731e-41,
-1.6525e-40, 5.0987e-40, -5.4683e-40,
8.1836e-41, 6.2722e-40, -3.1057e-40
);
const float biasL[4] = float[4]
(
-1.7701e-01, -1.3417e-06, -3.0706e-40, -1.9022e-06
);
vec4 hook()
{
vec4 tl1 = L2_1_texOff(vec2(-1,-1));
vec4 tc1 = L2_1_texOff(vec2(0,-1));
vec4 tr1 = L2_1_texOff(vec2(1,-1));
vec4 ml1 = L2_1_texOff(vec2(-1,0));
vec4 mc1 = L2_1_texOff(vec2(0,0));
vec4 mr1 = L2_1_texOff(vec2(1,0));
vec4 bl1 = L2_1_texOff(vec2(-1,1));
vec4 bc1 = L2_1_texOff(vec2(0,1));
vec4 br1 = L2_1_texOff(vec2(1,1));
vec4 tl2 = L2_2_texOff(vec2(-1,-1));
vec4 tc2 = L2_2_texOff(vec2(0,-1));
vec4 tr2 = L2_2_texOff(vec2(1,-1));
vec4 ml2 = L2_2_texOff(vec2(-1,0));
vec4 mc2 = L2_2_texOff(vec2(0,0));
vec4 mr2 = L2_2_texOff(vec2(1,0));
vec4 bl2 = L2_2_texOff(vec2(-1,1));
vec4 bc2 = L2_2_texOff(vec2(0,1));
vec4 br2 = L2_2_texOff(vec2(1,1));
vec4 c1234 = RELU(vec4(
tl1.x * kernelsL[0*72+0*9+0] + tc1.x * kernelsL[0*72+0*9+1] + tr1.x * kernelsL[0*72+0*9+2] +
ml1.x * kernelsL[0*72+0*9+3] + mc1.x * kernelsL[0*72+0*9+4] + mr1.x * kernelsL[0*72+0*9+5] +
bl1.x * kernelsL[0*72+0*9+6] + bc1.x * kernelsL[0*72+0*9+7] + br1.x * kernelsL[0*72+0*9+8] +
tl1.y * kernelsL[0*72+1*9+0] + tc1.y * kernelsL[0*72+1*9+1] + tr1.y * kernelsL[0*72+1*9+2] +
ml1.y * kernelsL[0*72+1*9+3] + mc1.y * kernelsL[0*72+1*9+4] + mr1.y * kernelsL[0*72+1*9+5] +
bl1.y * kernelsL[0*72+1*9+6] + bc1.y * kernelsL[0*72+1*9+7] + br1.y * kernelsL[0*72+1*9+8] +
tl1.z * kernelsL[0*72+2*9+0] + tc1.z * kernelsL[0*72+2*9+1] + tr1.z * kernelsL[0*72+2*9+2] +
ml1.z * kernelsL[0*72+2*9+3] + mc1.z * kernelsL[0*72+2*9+4] + mr1.z * kernelsL[0*72+2*9+5] +
bl1.z * kernelsL[0*72+2*9+6] + bc1.z * kernelsL[0*72+2*9+7] + br1.z * kernelsL[0*72+2*9+8] +
tl1.w * kernelsL[0*72+3*9+0] + tc1.w * kernelsL[0*72+3*9+1] + tr1.w * kernelsL[0*72+3*9+2] +
ml1.w * kernelsL[0*72+3*9+3] + mc1.w * kernelsL[0*72+3*9+4] + mr1.w * kernelsL[0*72+3*9+5] +
bl1.w * kernelsL[0*72+3*9+6] + bc1.w * kernelsL[0*72+3*9+7] + br1.w * kernelsL[0*72+3*9+8] +
tl2.x * kernelsL[0*72+4*9+0] + tc2.x * kernelsL[0*72+4*9+1] + tr2.x * kernelsL[0*72+4*9+2] +
ml2.x * kernelsL[0*72+4*9+3] + mc2.x * kernelsL[0*72+4*9+4] + mr2.x * kernelsL[0*72+4*9+5] +
bl2.x * kernelsL[0*72+4*9+6] + bc2.x * kernelsL[0*72+4*9+7] + br2.x * kernelsL[0*72+4*9+8] +
tl2.y * kernelsL[0*72+5*9+0] + tc2.y * kernelsL[0*72+5*9+1] + tr2.y * kernelsL[0*72+5*9+2] +
ml2.y * kernelsL[0*72+5*9+3] + mc2.y * kernelsL[0*72+5*9+4] + mr2.y * kernelsL[0*72+5*9+5] +
bl2.y * kernelsL[0*72+5*9+6] + bc2.y * kernelsL[0*72+5*9+7] + br2.y * kernelsL[0*72+5*9+8] +
tl2.z * kernelsL[0*72+6*9+0] + tc2.z * kernelsL[0*72+6*9+1] + tr2.z * kernelsL[0*72+6*9+2] +
ml2.z * kernelsL[0*72+6*9+3] + mc2.z * kernelsL[0*72+6*9+4] + mr2.z * kernelsL[0*72+6*9+5] +
bl2.z * kernelsL[0*72+6*9+6] + bc2.z * kernelsL[0*72+6*9+7] + br2.z * kernelsL[0*72+6*9+8] +
tl2.w * kernelsL[0*72+7*9+0] + tc2.w * kernelsL[0*72+7*9+1] + tr2.w * kernelsL[0*72+7*9+2] +
ml2.w * kernelsL[0*72+7*9+3] + mc2.w * kernelsL[0*72+7*9+4] + mr2.w * kernelsL[0*72+7*9+5] +
bl2.w * kernelsL[0*72+7*9+6] + bc2.w * kernelsL[0*72+7*9+7] + br2.w * kernelsL[0*72+7*9+8] + biasL[0]
,
tl1.x * kernelsL[1*72+0*9+0] + tc1.x * kernelsL[1*72+0*9+1] + tr1.x * kernelsL[1*72+0*9+2] +
ml1.x * kernelsL[1*72+0*9+3] + mc1.x * kernelsL[1*72+0*9+4] + mr1.x * kernelsL[1*72+0*9+5] +
bl1.x * kernelsL[1*72+0*9+6] + bc1.x * kernelsL[1*72+0*9+7] + br1.x * kernelsL[1*72+0*9+8] +
tl1.y * kernelsL[1*72+1*9+0] + tc1.y * kernelsL[1*72+1*9+1] + tr1.y * kernelsL[1*72+1*9+2] +
ml1.y * kernelsL[1*72+1*9+3] + mc1.y * kernelsL[1*72+1*9+4] + mr1.y * kernelsL[1*72+1*9+5] +
bl1.y * kernelsL[1*72+1*9+6] + bc1.y * kernelsL[1*72+1*9+7] + br1.y * kernelsL[1*72+1*9+8] +
tl1.z * kernelsL[1*72+2*9+0] + tc1.z * kernelsL[1*72+2*9+1] + tr1.z * kernelsL[1*72+2*9+2] +
ml1.z * kernelsL[1*72+2*9+3] + mc1.z * kernelsL[1*72+2*9+4] + mr1.z * kernelsL[1*72+2*9+5] +
bl1.z * kernelsL[1*72+2*9+6] + bc1.z * kernelsL[1*72+2*9+7] + br1.z * kernelsL[1*72+2*9+8] +
tl1.w * kernelsL[1*72+3*9+0] + tc1.w * kernelsL[1*72+3*9+1] + tr1.w * kernelsL[1*72+3*9+2] +
ml1.w * kernelsL[1*72+3*9+3] + mc1.w * kernelsL[1*72+3*9+4] + mr1.w * kernelsL[1*72+3*9+5] +
bl1.w * kernelsL[1*72+3*9+6] + bc1.w * kernelsL[1*72+3*9+7] + br1.w * kernelsL[1*72+3*9+8] +
tl2.x * kernelsL[1*72+4*9+0] + tc2.x * kernelsL[1*72+4*9+1] + tr2.x * kernelsL[1*72+4*9+2] +
ml2.x * kernelsL[1*72+4*9+3] + mc2.x * kernelsL[1*72+4*9+4] + mr2.x * kernelsL[1*72+4*9+5] +
bl2.x * kernelsL[1*72+4*9+6] + bc2.x * kernelsL[1*72+4*9+7] + br2.x * kernelsL[1*72+4*9+8] +
tl2.y * kernelsL[1*72+5*9+0] + tc2.y * kernelsL[1*72+5*9+1] + tr2.y * kernelsL[1*72+5*9+2] +
ml2.y * kernelsL[1*72+5*9+3] + mc2.y * kernelsL[1*72+5*9+4] + mr2.y * kernelsL[1*72+5*9+5] +
bl2.y * kernelsL[1*72+5*9+6] + bc2.y * kernelsL[1*72+5*9+7] + br2.y * kernelsL[1*72+5*9+8] +
tl2.z * kernelsL[1*72+6*9+0] + tc2.z * kernelsL[1*72+6*9+1] + tr2.z * kernelsL[1*72+6*9+2] +
ml2.z * kernelsL[1*72+6*9+3] + mc2.z * kernelsL[1*72+6*9+4] + mr2.z * kernelsL[1*72+6*9+5] +
bl2.z * kernelsL[1*72+6*9+6] + bc2.z * kernelsL[1*72+6*9+7] + br2.z * kernelsL[1*72+6*9+8] +
tl2.w * kernelsL[1*72+7*9+0] + tc2.w * kernelsL[1*72+7*9+1] + tr2.w * kernelsL[1*72+7*9+2] +
ml2.w * kernelsL[1*72+7*9+3] + mc2.w * kernelsL[1*72+7*9+4] + mr2.w * kernelsL[1*72+7*9+5] +
bl2.w * kernelsL[1*72+7*9+6] + bc2.w * kernelsL[1*72+7*9+7] + br2.w * kernelsL[1*72+7*9+8] + biasL[1]
,
tl1.x * kernelsL[2*72+0*9+0] + tc1.x * kernelsL[2*72+0*9+1] + tr1.x * kernelsL[2*72+0*9+2] +
ml1.x * kernelsL[2*72+0*9+3] + mc1.x * kernelsL[2*72+0*9+4] + mr1.x * kernelsL[2*72+0*9+5] +
bl1.x * kernelsL[2*72+0*9+6] + bc1.x * kernelsL[2*72+0*9+7] + br1.x * kernelsL[2*72+0*9+8] +
tl1.y * kernelsL[2*72+1*9+0] + tc1.y * kernelsL[2*72+1*9+1] + tr1.y * kernelsL[2*72+1*9+2] +
ml1.y * kernelsL[2*72+1*9+3] + mc1.y * kernelsL[2*72+1*9+4] + mr1.y * kernelsL[2*72+1*9+5] +
bl1.y * kernelsL[2*72+1*9+6] + bc1.y * kernelsL[2*72+1*9+7] + br1.y * kernelsL[2*72+1*9+8] +
tl1.z * kernelsL[2*72+2*9+0] + tc1.z * kernelsL[2*72+2*9+1] + tr1.z * kernelsL[2*72+2*9+2] +
ml1.z * kernelsL[2*72+2*9+3] + mc1.z * kernelsL[2*72+2*9+4] + mr1.z * kernelsL[2*72+2*9+5] +
bl1.z * kernelsL[2*72+2*9+6] + bc1.z * kernelsL[2*72+2*9+7] + br1.z * kernelsL[2*72+2*9+8] +
tl1.w * kernelsL[2*72+3*9+0] + tc1.w * kernelsL[2*72+3*9+1] + tr1.w * kernelsL[2*72+3*9+2] +
ml1.w * kernelsL[2*72+3*9+3] + mc1.w * kernelsL[2*72+3*9+4] + mr1.w * kernelsL[2*72+3*9+5] +
bl1.w * kernelsL[2*72+3*9+6] + bc1.w * kernelsL[2*72+3*9+7] + br1.w * kernelsL[2*72+3*9+8] +
tl2.x * kernelsL[2*72+4*9+0] + tc2.x * kernelsL[2*72+4*9+1] + tr2.x * kernelsL[2*72+4*9+2] +
ml2.x * kernelsL[2*72+4*9+3] + mc2.x * kernelsL[2*72+4*9+4] + mr2.x * kernelsL[2*72+4*9+5] +
bl2.x * kernelsL[2*72+4*9+6] + bc2.x * kernelsL[2*72+4*9+7] + br2.x * kernelsL[2*72+4*9+8] +
tl2.y * kernelsL[2*72+5*9+0] + tc2.y * kernelsL[2*72+5*9+1] + tr2.y * kernelsL[2*72+5*9+2] +
ml2.y * kernelsL[2*72+5*9+3] + mc2.y * kernelsL[2*72+5*9+4] + mr2.y * kernelsL[2*72+5*9+5] +
bl2.y * kernelsL[2*72+5*9+6] + bc2.y * kernelsL[2*72+5*9+7] + br2.y * kernelsL[2*72+5*9+8] +
tl2.z * kernelsL[2*72+6*9+0] + tc2.z * kernelsL[2*72+6*9+1] + tr2.z * kernelsL[2*72+6*9+2] +
ml2.z * kernelsL[2*72+6*9+3] + mc2.z * kernelsL[2*72+6*9+4] + mr2.z * kernelsL[2*72+6*9+5] +
bl2.z * kernelsL[2*72+6*9+6] + bc2.z * kernelsL[2*72+6*9+7] + br2.z * kernelsL[2*72+6*9+8] +
tl2.w * kernelsL[2*72+7*9+0] + tc2.w * kernelsL[2*72+7*9+1] + tr2.w * kernelsL[2*72+7*9+2] +
ml2.w * kernelsL[2*72+7*9+3] + mc2.w * kernelsL[2*72+7*9+4] + mr2.w * kernelsL[2*72+7*9+5] +
bl2.w * kernelsL[2*72+7*9+6] + bc2.w * kernelsL[2*72+7*9+7] + br2.w * kernelsL[2*72+7*9+8] + biasL[2]
,
tl1.x * kernelsL[3*72+0*9+0] + tc1.x * kernelsL[3*72+0*9+1] + tr1.x * kernelsL[3*72+0*9+2] +
ml1.x * kernelsL[3*72+0*9+3] + mc1.x * kernelsL[3*72+0*9+4] + mr1.x * kernelsL[3*72+0*9+5] +
bl1.x * kernelsL[3*72+0*9+6] + bc1.x * kernelsL[3*72+0*9+7] + br1.x * kernelsL[3*72+0*9+8] +
tl1.y * kernelsL[3*72+1*9+0] + tc1.y * kernelsL[3*72+1*9+1] + tr1.y * kernelsL[3*72+1*9+2] +
ml1.y * kernelsL[3*72+1*9+3] + mc1.y * kernelsL[3*72+1*9+4] + mr1.y * kernelsL[3*72+1*9+5] +
bl1.y * kernelsL[3*72+1*9+6] + bc1.y * kernelsL[3*72+1*9+7] + br1.y * kernelsL[3*72+1*9+8] +
tl1.z * kernelsL[3*72+2*9+0] + tc1.z * kernelsL[3*72+2*9+1] + tr1.z * kernelsL[3*72+2*9+2] +
ml1.z * kernelsL[3*72+2*9+3] + mc1.z * kernelsL[3*72+2*9+4] + mr1.z * kernelsL[3*72+2*9+5] +
bl1.z * kernelsL[3*72+2*9+6] + bc1.z * kernelsL[3*72+2*9+7] + br1.z * kernelsL[3*72+2*9+8] +
tl1.w * kernelsL[3*72+3*9+0] + tc1.w * kernelsL[3*72+3*9+1] + tr1.w * kernelsL[3*72+3*9+2] +
ml1.w * kernelsL[3*72+3*9+3] + mc1.w * kernelsL[3*72+3*9+4] + mr1.w * kernelsL[3*72+3*9+5] +
bl1.w * kernelsL[3*72+3*9+6] + bc1.w * kernelsL[3*72+3*9+7] + br1.w * kernelsL[3*72+3*9+8] +
tl2.x * kernelsL[3*72+4*9+0] + tc2.x * kernelsL[3*72+4*9+1] + tr2.x * kernelsL[3*72+4*9+2] +
ml2.x * kernelsL[3*72+4*9+3] + mc2.x * kernelsL[3*72+4*9+4] + mr2.x * kernelsL[3*72+4*9+5] +
bl2.x * kernelsL[3*72+4*9+6] + bc2.x * kernelsL[3*72+4*9+7] + br2.x * kernelsL[3*72+4*9+8] +
tl2.y * kernelsL[3*72+5*9+0] + tc2.y * kernelsL[3*72+5*9+1] + tr2.y * kernelsL[3*72+5*9+2] +
ml2.y * kernelsL[3*72+5*9+3] + mc2.y * kernelsL[3*72+5*9+4] + mr2.y * kernelsL[3*72+5*9+5] +
bl2.y * kernelsL[3*72+5*9+6] + bc2.y * kernelsL[3*72+5*9+7] + br2.y * kernelsL[3*72+5*9+8] +
tl2.z * kernelsL[3*72+6*9+0] + tc2.z * kernelsL[3*72+6*9+1] + tr2.z * kernelsL[3*72+6*9+2] +
ml2.z * kernelsL[3*72+6*9+3] + mc2.z * kernelsL[3*72+6*9+4] + mr2.z * kernelsL[3*72+6*9+5] +
bl2.z * kernelsL[3*72+6*9+6] + bc2.z * kernelsL[3*72+6*9+7] + br2.z * kernelsL[3*72+6*9+8] +
tl2.w * kernelsL[3*72+7*9+0] + tc2.w * kernelsL[3*72+7*9+1] + tr2.w * kernelsL[3*72+7*9+2] +
ml2.w * kernelsL[3*72+7*9+3] + mc2.w * kernelsL[3*72+7*9+4] + mr2.w * kernelsL[3*72+7*9+5] +
bl2.w * kernelsL[3*72+7*9+6] + bc2.w * kernelsL[3*72+7*9+7] + br2.w * kernelsL[3*72+7*9+8] + biasL[3]
));
return c1234;
}
//!HOOK LUMA
//!WHEN OUTPUT.w LUMA.w / 1.200 > OUTPUT.h LUMA.h / 1.200 > *
//!DESC [ACNet_HDN_L1] L3
//!BIND L2_1
//!BIND L2_2
//!SAVE L1_2
//!COMPONENTS 4
#define RELU(x) max(x, vec4(0.0f))
const float kernelsL[9 * 8 * 4] = float[9 * 8 * 4]
(
4.0987e-40, 3.5941e-40, 5.1680e-40,
5.5563e-40, 3.1011e-40, 4.7068e-40,
1.0426e-40, -1.0803e-40, 4.4867e-40,
-4.9675e-03, 1.5412e-01, -4.1930e-03,
-6.1089e-02, 2.0405e-01, 1.9587e-01,
3.8772e-02, 1.6894e-01, -2.6163e-02,
1.0839e-30, 1.8608e-30, 1.1386e-30,
1.4863e-29, 1.9422e-29, 1.1639e-29,
1.7504e-29, 2.2177e-29, 1.3629e-29,
6.4484e-02, 6.6296e-02, 2.2838e-01,
-1.0213e-01, 7.5883e-02, -1.7531e-01,
-1.4869e-01, 1.0736e-01, 1.4129e-01,
-2.8235e-02, -2.9232e-02, -9.3912e-02,
5.1317e-02, 9.0256e-02, -2.4669e-02,
-3.2465e-02, 5.8099e-02, 9.8402e-02,
-2.3135e-01, -1.3786e-01, 2.8581e-01,