mmr/tkDNN
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Remove the final parameter from the layers

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
This commit is contained in:
Davide Sapienza
2020-04-09 18:48:03 +02:00
parent af761786ea
commit 8a575f6447
14 changed files with 130 additions and 115 deletions
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tests/mobilenetv2ssd/mobilenetv2ssd.cpp
+39 -35
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@@ -147,14 +147,14 @@ int main()
//Inverted Residual 1
tk::dnn::Conv2d conv2(&net, 32, 3, 3, 1, 1, 1, 1, inverted_residual1[0], true, false, false, 32);
tk::dnn::Conv2d conv2(&net, 32, 3, 3, 1, 1, 1, 1, inverted_residual1[0], true, false, 32);
tk::dnn::Activation relu5(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d conv3(&net, 16, 1, 1, 1, 1, 0, 0, inverted_residual1[1], true);
//Inverted Residual 2
tk::dnn::Conv2d ir_2_conv1(&net, 96, 1, 1, 1, 1, 0, 0, inverted_residual2[0], true);
tk::dnn::Activation relu_2_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_2_conv2(&net, 96, 3, 3, 2, 2, 1, 1, inverted_residual2[1], true, false, false, 96);
tk::dnn::Conv2d ir_2_conv2(&net, 96, 3, 3, 2, 2, 1, 1, inverted_residual2[1], true, false, 96);
tk::dnn::Activation relu_2_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_2_conv3(&net, 24, 1, 1, 1, 1, 0, 0, inverted_residual2[2], true);
@@ -162,7 +162,7 @@ int main()
tk::dnn::Layer *last = &ir_2_conv3;
tk::dnn::Conv2d ir_3_conv1(&net, 144, 1, 1, 1, 1, 0, 0, inverted_residual3[0], true);
tk::dnn::Activation relu_3_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_3_conv2(&net, 144, 3, 3, 1, 1, 1, 1, inverted_residual3[1], true, false, false, 144);
tk::dnn::Conv2d ir_3_conv2(&net, 144, 3, 3, 1, 1, 1, 1, inverted_residual3[1], true, false, 144);
tk::dnn::Activation relu_3_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_3_conv3(&net, 24, 1, 1, 1, 1, 0, 0, inverted_residual3[2], true);
@@ -170,7 +170,7 @@ int main()
// //Inverted Residual 4
tk::dnn::Conv2d ir_4_conv1(&net, 144, 1, 1, 1, 1, 0, 0, inverted_residual4[0], true);
tk::dnn::Activation relu_4_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_4_conv2(&net, 144, 3, 3, 2, 2, 1, 1, inverted_residual4[1], true, false, false, 144);
tk::dnn::Conv2d ir_4_conv2(&net, 144, 3, 3, 2, 2, 1, 1, inverted_residual4[1], true, false, 144);
tk::dnn::Activation relu_4_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_4_conv3(&net, 32, 1, 1, 1, 1, 0, 0, inverted_residual4[2], true);
@@ -178,7 +178,7 @@ int main()
last = &ir_4_conv3;
tk::dnn::Conv2d ir_5_conv1(&net, 192, 1, 1, 1, 1, 0, 0, inverted_residual5[0], true);
tk::dnn::Activation relu_5_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_5_conv2(&net, 192, 3, 3, 1, 1, 1, 1, inverted_residual5[1], true, false, false, 192);
tk::dnn::Conv2d ir_5_conv2(&net, 192, 3, 3, 1, 1, 1, 1, inverted_residual5[1], true, false, 192);
tk::dnn::Activation relu_5_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_5_conv3(&net, 32, 1, 1, 1, 1, 0, 0, inverted_residual5[2], true);
@@ -187,7 +187,7 @@ int main()
last = &s5_0;
tk::dnn::Conv2d ir_6_conv1(&net, 192, 1, 1, 1, 1, 0, 0, inverted_residual6[0], true);
tk::dnn::Activation relu_6_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_6_conv2(&net, 192, 3, 3, 1, 1, 1, 1, inverted_residual6[1], true, false, false, 192);
tk::dnn::Conv2d ir_6_conv2(&net, 192, 3, 3, 1, 1, 1, 1, inverted_residual6[1], true, false, 192);
tk::dnn::Activation relu_6_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_6_conv3(&net, 32, 1, 1, 1, 1, 0, 0, inverted_residual6[2], true);
@@ -195,7 +195,7 @@ int main()
//Inverted Residual 7
tk::dnn::Conv2d ir_7_conv1(&net, 192, 1, 1, 1, 1, 0, 0, inverted_residual7[0], true);
tk::dnn::Activation relu_7_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_7_conv2(&net, 192, 3, 3, 2, 2, 1, 1, inverted_residual7[1], true, false, false, 192);
tk::dnn::Conv2d ir_7_conv2(&net, 192, 3, 3, 2, 2, 1, 1, inverted_residual7[1], true, false, 192);
tk::dnn::Activation relu_7_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_7_conv3(&net, 64, 1, 1, 1, 1, 0, 0, inverted_residual7[2], true);
@@ -203,7 +203,7 @@ int main()
last = &ir_7_conv3;
tk::dnn::Conv2d ir_8_conv1(&net, 384, 1, 1, 1, 1, 0, 0, inverted_residual8[0], true);
tk::dnn::Activation relu_8_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_8_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual8[1], true, false, false, 384);
tk::dnn::Conv2d ir_8_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual8[1], true, false, 384);
tk::dnn::Activation relu_8_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_8_conv3(&net, 64, 1, 1, 1, 1, 0, 0, inverted_residual8[2], true);
@@ -212,7 +212,7 @@ int main()
last = &s8_0;
tk::dnn::Conv2d ir_9_conv1(&net, 384, 1, 1, 1, 1, 0, 0, inverted_residual9[0], true);
tk::dnn::Activation relu_9_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_9_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual9[1], true, false, false, 384);
tk::dnn::Conv2d ir_9_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual9[1], true, false, 384);
tk::dnn::Activation relu_9_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_9_conv3(&net, 64, 1, 1, 1, 1, 0, 0, inverted_residual9[2], true);
@@ -221,7 +221,7 @@ int main()
last = &s9_0;
tk::dnn::Conv2d ir_10_conv1(&net, 384, 1, 1, 1, 1, 0, 0, inverted_residual10[0], true);
tk::dnn::Activation relu_10_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_10_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual10[1], true, false, false, 384);
tk::dnn::Conv2d ir_10_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual10[1], true, false, 384);
tk::dnn::Activation relu_10_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_10_conv3(&net, 64, 1, 1, 1, 1, 0, 0, inverted_residual10[2], true);
@@ -229,7 +229,7 @@ int main()
//Inverted Residual 11
tk::dnn::Conv2d ir_11_conv1(&net, 384, 1, 1, 1, 1, 0, 0, inverted_residual11[0], true);
tk::dnn::Activation relu_11_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_11_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual11[1], true, false, false, 384);
tk::dnn::Conv2d ir_11_conv2(&net, 384, 3, 3, 1, 1, 1, 1, inverted_residual11[1], true, false, 384);
tk::dnn::Activation relu_11_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_11_conv3(&net, 96, 1, 1, 1, 1, 0, 0, inverted_residual11[2], true);
@@ -237,7 +237,7 @@ int main()
//Inverted Residual 12
tk::dnn::Conv2d ir_12_conv1(&net, 576, 1, 1, 1, 1, 0, 0, inverted_residual12[0], true);
tk::dnn::Activation relu_12_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_12_conv2(&net, 576, 3, 3, 1, 1, 1, 1, inverted_residual12[1], true, false, false, 576);
tk::dnn::Conv2d ir_12_conv2(&net, 576, 3, 3, 1, 1, 1, 1, inverted_residual12[1], true, false, 576);
tk::dnn::Activation relu_12_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_12_conv3(&net, 96, 1, 1, 1, 1, 0, 0, inverted_residual12[2], true);
@@ -246,7 +246,7 @@ int main()
//Inverted Residual 13
tk::dnn::Conv2d ir_13_conv1(&net, 576, 1, 1, 1, 1, 0, 0, inverted_residual13[0], true);
tk::dnn::Activation relu_13_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_13_conv2(&net, 576, 3, 3, 1, 1, 1, 1, inverted_residual13[1], true, false, false, 576);
tk::dnn::Conv2d ir_13_conv2(&net, 576, 3, 3, 1, 1, 1, 1, inverted_residual13[1], true, false, 576);
tk::dnn::Activation relu_13_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_13_conv3(&net, 96, 1, 1, 1, 1, 0, 0, inverted_residual13[2], true);
@@ -254,7 +254,7 @@ int main()
// //Inverted Residual 14
tk::dnn::Conv2d ir_14_conv1(&net, 576, 1, 1, 1, 1, 0, 0, inverted_residual14[0], true);
tk::dnn::Activation relu_14_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_14_conv2(&net, 576, 3, 3, 2, 2, 1, 1, inverted_residual14[1], true, false, false, 576);
tk::dnn::Conv2d ir_14_conv2(&net, 576, 3, 3, 2, 2, 1, 1, inverted_residual14[1], true, false, 576);
tk::dnn::Activation relu_14_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_14_conv3(&net, 160, 1, 1, 1, 1, 0, 0, inverted_residual14[2], true);
@@ -262,7 +262,7 @@ int main()
last = &ir_14_conv3;
tk::dnn::Conv2d ir_15_conv1(&net, 960, 1, 1, 1, 1, 0, 0, inverted_residual15[0], true);
tk::dnn::Activation relu_15_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_15_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual15[1], true, false, false, 960);
tk::dnn::Conv2d ir_15_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual15[1], true, false, 960);
tk::dnn::Activation relu_15_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_15_conv3(&net, 160, 1, 1, 1, 1, 0, 0, inverted_residual15[2], true);
@@ -271,7 +271,7 @@ int main()
last = &s15_0;
tk::dnn::Conv2d ir_16_conv1(&net, 960, 1, 1, 1, 1, 0, 0, inverted_residual16[0], true);
tk::dnn::Activation relu_16_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_16_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual16[1], true, false, false, 960);
tk::dnn::Conv2d ir_16_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual16[1], true, false, 960);
tk::dnn::Activation relu_16_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_16_conv3(&net, 160, 1, 1, 1, 1, 0, 0, inverted_residual16[2], true);
@@ -279,7 +279,7 @@ int main()
//Inverted Residual 17
tk::dnn::Conv2d ir_17_conv1(&net, 960, 1, 1, 1, 1, 0, 0, inverted_residual17[0], true);
tk::dnn::Activation relu_17_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_17_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual17[1], true, false, false, 960);
tk::dnn::Conv2d ir_17_conv2(&net, 960, 3, 3, 1, 1, 1, 1, inverted_residual17[1], true, false, 960);
tk::dnn::Activation relu_17_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d ir_17_conv3(&net, 320, 1, 1, 1, 1, 0, 0, inverted_residual17[2], true);
@@ -291,7 +291,7 @@ int main()
// //extras Inverted Residual 0
tk::dnn::Conv2d e_0_conv1(&net, 256, 1, 1, 1, 1, 0, 0, extras0[0], true);
tk::dnn::Activation e_relu_0_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_0_conv2(&net, 256, 3, 3, 2, 2, 1, 1, extras0[1], true, false, false, 256);
tk::dnn::Conv2d e_0_conv2(&net, 256, 3, 3, 2, 2, 1, 1, extras0[1], true, false, 256);
tk::dnn::Activation e_relu_0_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_0_conv3(&net, 512, 1, 1, 1, 1, 0, 0, extras0[2], true);
tk::dnn::Layer *header_2[1] = {&e_0_conv3};
@@ -299,7 +299,7 @@ int main()
// //extras Inverted Residual 1
tk::dnn::Conv2d e_1_conv1(&net, 128, 1, 1, 1, 1, 0, 0, extras1[0], true);
tk::dnn::Activation e_relu_1_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_1_conv2(&net, 128, 3, 3, 2, 2, 1, 1, extras1[1], true, false, false, 128);
tk::dnn::Conv2d e_1_conv2(&net, 128, 3, 3, 2, 2, 1, 1, extras1[1], true, false, 128);
tk::dnn::Activation e_relu_1_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_1_conv3(&net, 256, 1, 1, 1, 1, 0, 0, extras1[2], true);
tk::dnn::Layer *header_3[1] = {&e_1_conv3};
@@ -307,7 +307,7 @@ int main()
//extras Inverted Residual 2
tk::dnn::Conv2d e_2_conv1(&net, 128, 1, 1, 1, 1, 0, 0, extras2[0], true);
tk::dnn::Activation e_relu_2_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_2_conv2(&net, 128, 3, 3, 2, 2, 1, 1, extras2[1], true, false, false, 128);
tk::dnn::Conv2d e_2_conv2(&net, 128, 3, 3, 2, 2, 1, 1, extras2[1], true, false, 128);
tk::dnn::Activation e_relu_2_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_2_conv3(&net, 256, 1, 1, 1, 1, 0, 0, extras2[2], true);
tk::dnn::Layer *header_4[1] = {&e_2_conv3};
@@ -315,7 +315,7 @@ int main()
//extras Inverted Residual 3
tk::dnn::Conv2d e_3_conv1(&net, 64, 1, 1, 1, 1, 0, 0, extras3[0], true);
tk::dnn::Activation e_relu_3_1(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_3_conv2(&net, 64, 3, 3, 2, 2, 1, 1, extras3[1], true, false, false, 64);
tk::dnn::Conv2d e_3_conv2(&net, 64, 3, 3, 2, 2, 1, 1, extras3[1], true, false, 64);
tk::dnn::Activation e_relu_3_2(&net, CUDNN_ACTIVATION_RELU);
tk::dnn::Conv2d e_3_conv3(&net, 64, 1, 1, 1, 1, 0, 0, extras3[2], true);
tk::dnn::Layer *header_5[1] = {&e_3_conv3};
@@ -323,68 +323,69 @@ int main()
// classification header 0
tk::dnn::Layer *header_0[1] = {&relu_14_1};
tk::dnn::Route rout_ch_0(&net, header_0, 1);
tk::dnn::Conv2d ch_0_conv1(&net, 576, 3, 3, 1, 1, 1, 1, classification_header0[0], true, false, false, 576, true);
tk::dnn::Conv2d ch_0_conv1(&net, 576, 3, 3, 1, 1, 1, 1, classification_header0[0], true, false, 576, true);
tk::dnn::Activation ch_relu_0_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d ch_0_conv2(&net, 126, 1, 1, 1, 1, 0, 0, classification_header0[1], false);
tk::dnn::Layer *conf0[1] = {&ch_0_conv2};
// // classification header 1
tk::dnn::Route rout_ch_1(&net, header_1, 1);
tk::dnn::Conv2d ch_1_conv1(&net, 1280, 3, 3, 1, 1, 1, 1, classification_header1[0], true, false, false, 1280, true);
tk::dnn::Conv2d ch_1_conv1(&net, 1280, 3, 3, 1, 1, 1, 1, classification_header1[0], true, false, 1280, true);
tk::dnn::Activation ch_relu_1_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d ch_1_conv2(&net, 126, 1, 1, 1, 1, 0, 0, classification_header1[1], false);
tk::dnn::Layer *conf1[1] = {&ch_1_conv2};
// //classification header 2
tk::dnn::Route rout_ch_2(&net, header_2, 1);
tk::dnn::Conv2d ch_2_conv1(&net, 512, 3, 3, 1, 1, 1, 1, classification_header2[0], true, false, false, 512, true);
tk::dnn::Conv2d ch_2_conv1(&net, 512, 3, 3, 1, 1, 1, 1, classification_header2[0], true, false, 512, true);
tk::dnn::Activation ch_relu_2_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d ch_2_conv2(&net, 126, 1, 1, 1, 1, 0, 0, classification_header2[1], false);
tk::dnn::Layer *conf2[1] = {&ch_2_conv2};
// //classification header 3
tk::dnn::Route rout_ch_3(&net, header_3, 1);
tk::dnn::Conv2d ch_3_conv1(&net, 256, 3, 3, 1, 1, 1, 1, classification_header3[0], true, false, false, 256, true);
tk::dnn::Conv2d ch_3_conv1(&net, 256, 3, 3, 1, 1, 1, 1, classification_header3[0], true, false, 256, true);
tk::dnn::Activation ch_relu_3_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d ch_3_conv2(&net, 126, 1, 1, 1, 1, 0, 0, classification_header3[1], false);
tk::dnn::Layer *conf3[1] = {&ch_3_conv2};
// //classification header 4
tk::dnn::Route rout_ch_4(&net, header_4, 1);
tk::dnn::Conv2d ch_4_conv1(&net, 256, 3, 3, 1, 1, 1, 1, classification_header4[0], true, false, false, 256, true);
tk::dnn::Conv2d ch_4_conv1(&net, 256, 3, 3, 1, 1, 1, 1, classification_header4[0], true, false, 256, true);
tk::dnn::Activation ch_relu_4_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d ch_4_conv2(&net, 126, 1, 1, 1, 1, 0, 0, classification_header4[1], false);
tk::dnn::Layer *conf4[1] = {&ch_4_conv2};
// //classification header 5
tk::dnn::Route rout_ch_5(&net, header_5, 1);
tk::dnn::Conv2d ch_5_conv(&net, 126, 1, 1, 1, 1, 0, 0, classification_header5, false, false, true);
tk::dnn::Conv2d ch_5_conv(&net, 126, 1, 1, 1, 1, 0, 0, classification_header5, false);
ch_5_conv.setFinal();
tk::dnn::Layer *conf5[1] = {&ch_5_conv};
//regression header 0
tk::dnn::Route rout_rh_0(&net, header_0, 1);
tk::dnn::Conv2d rh_0_conv1(&net, 576, 3, 3, 1, 1, 1, 1, regression_header0[0], true, false, false, 576, true);
tk::dnn::Conv2d rh_0_conv1(&net, 576, 3, 3, 1, 1, 1, 1, regression_header0[0], true, false, 576, true);
tk::dnn::Activation rh_relu_0_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d rh_0_conv2(&net, 24, 1, 1, 1, 1, 0, 0, regression_header0[1], false);
tk::dnn::Layer *loc0[1] = {&rh_0_conv2};
// //regression header 1
tk::dnn::Route rout_rh_1(&net, header_1, 1);
tk::dnn::Conv2d rh_1_conv1(&net, 1280, 3, 3, 1, 1, 1, 1, regression_header1[0], true, false, false, 1280, true);
tk::dnn::Conv2d rh_1_conv1(&net, 1280, 3, 3, 1, 1, 1, 1, regression_header1[0], true, false, 1280, true);
tk::dnn::Activation rh_relu_1_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d rh_1_conv2(&net, 24, 1, 1, 1, 1, 0, 0, regression_header1[1], false);
tk::dnn::Layer *loc1[1] = {&rh_1_conv2};
//regression header 2
tk::dnn::Route rout_rh_2(&net, header_2, 1);
tk::dnn::Conv2d rh_2_conv1(&net, 512, 3, 3, 1, 1, 1, 1, regression_header2[0], true, false, false, 512, true);
tk::dnn::Conv2d rh_2_conv1(&net, 512, 3, 3, 1, 1, 1, 1, regression_header2[0], true, false, 512, true);
tk::dnn::Activation rh_relu_2_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d rh_2_conv2(&net, 24, 1, 1, 1, 1, 0, 0, regression_header2[1], false);
tk::dnn::Layer *loc2[1] = {&rh_2_conv2};
//regression header 3
tk::dnn::Route rout_rh_3(&net, header_3, 1);
tk::dnn::Conv2d rh_3_conv1(&net, 256, 3, 3, 1, 1, 1, 1, regression_header3[0], true, false, false, 256, true);
tk::dnn::Conv2d rh_3_conv1(&net, 256, 3, 3, 1, 1, 1, 1, regression_header3[0], true, false, 256, true);
tk::dnn::Activation rh_relu_3_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d rh_3_conv2(&net, 24, 1, 1, 1, 1, 0, 0, regression_header3[1], false);
tk::dnn::Layer *loc3[1] = {&rh_3_conv2};
@@ -392,14 +393,15 @@ int main()
//regression header 4
tk::dnn::Route rout_rh_4(&net, header_4, 1);
tk::dnn::Conv2d rh_4_conv1(&net, 256, 3, 3, 1, 1, 1, 1, regression_header4[0], true, false, false, 256, true);
tk::dnn::Conv2d rh_4_conv1(&net, 256, 3, 3, 1, 1, 1, 1, regression_header4[0], true, false, 256, true);
tk::dnn::Activation rh_relu_4_1(&net, CUDNN_ACTIVATION_CLIPPED_RELU, 6);
tk::dnn::Conv2d rh_4_conv2(&net, 24, 1, 1, 1, 1, 0, 0, regression_header4[1], false);
tk::dnn::Layer *loc4[1] = {&rh_4_conv2};
//regression header 5
tk::dnn::Route rout_rh_5(&net, header_5, 1);
tk::dnn::Conv2d rh_5_conv(&net, 24, 1, 1, 1, 1, 0, 0, regression_header5, false, false, true);
tk::dnn::Conv2d rh_5_conv(&net, 24, 1, 1, 1, 1, 0, 0, regression_header5, false);
rh_5_conv.setFinal();
tk::dnn::Layer *loc5[1] = {&rh_5_conv};
last = &rh_5_conv;
@@ -444,7 +446,8 @@ int main()
tk::dnn::Reshape reshape_conf2(&net, newdim_c);
tk::dnn::Softmax sm_1(&net, &newdim_c, true);
tk::dnn::Softmax sm_1(&net, &newdim_c);
sm_1.setFinal();
// tk::dnn::Flatten fl_l_7(&net);
// tk::dnn::Reshape reshape_conf3(&net,dim_resh, true);
tk::dnn::Layer *conf = &sm_1;
@@ -454,7 +457,8 @@ int main()
tk::dnn::Route rout_loc(&net, locations, 6);
tk::dnn::dataDim_t olddim_l = net.layers[net.num_layers - 1]->output_dim;
tk::dnn::dataDim_t newdim_l(1, olddim_l.c * olddim_l.h * olddim_l.w / 4, 1, 4, 1);
tk::dnn::Reshape reshape_loc(&net, newdim_l, true);
tk::dnn::Reshape reshape_loc(&net, newdim_l);
reshape_loc.setFinal();
tk::dnn::Layer *loc = &reshape_loc;
// Load input