network_t* make_network() {
network_t* net = (network_t*)malloc(sizeof(network_t));
net->v[0] = make_vol(32, 32, 3, 0.0);
net->l0 = make_conv_layer(32, 32, 3, 5, 16, 1, 2);
net->v[1] = make_vol(net->l0->out_sx, net->l0->out_sy, net->l0->out_depth, 0.0);
net->l1 = make_relu_layer(net->v[1]->sx, net->v[1]->sy, net->v[1]->depth);
net->v[2] = make_vol(net->l1->out_sx, net->l1->out_sy, net->l1->out_depth, 0.0);
net->l2 = make_pool_layer(net->v[2]->sx, net->v[2]->sy, net->v[2]->depth, 2, 2);
net->v[3] = make_vol(net->l2->out_sx, net->l2->out_sy, net->l2->out_depth, 0.0);
net->l3 = make_conv_layer(net->v[3]->sx, net->v[3]->sy, net->v[3]->depth, 5, 20, 1, 2);
net->v[4] = make_vol(net->l3->out_sx, net->l3->out_sy, net->l3->out_depth, 0.0);
net->l4 = make_relu_layer(net->v[4]->sx, net->v[4]->sy, net->v[4]->depth);
net->v[5] = make_vol(net->l4->out_sx, net->l4->out_sy, net->l4->out_depth, 0.0);
net->l5 = make_pool_layer(net->v[5]->sx, net->v[5]->sy, net->v[5]->depth, 2, 2);
net->v[6] = make_vol(net->l5->out_sx, net->l5->out_sy, net->l5->out_depth, 0.0);
net->l6 = make_conv_layer(net->v[6]->sx, net->v[6]->sy, net->v[6]->depth, 5, 20, 1, 2);
net->v[7] = make_vol(net->l6->out_sx, net->l6->out_sy, net->l6->out_depth, 0.0);
net->l7 = make_relu_layer(net->v[7]->sx, net->v[7]->sy, net->v[7]->depth);
net->v[8] = make_vol(net->l7->out_sx, net->l7->out_sy, net->l7->out_depth, 0.0);
net->l8 = make_pool_layer(net->v[8]->sx, net->v[8]->sy, net->v[8]->depth, 2, 2);
net->v[9] = make_vol(net->l8->out_sx, net->l8->out_sy, net->l8->out_depth, 0.0);
net->l9 = make_fc_layer(net->v[9]->sx, net->v[9]->sy, net->v[9]->depth, 10);
net->v[10] = make_vol(net->l9->out_sx, net->l9->out_sy, net->l9->out_depth, 0.0);
net->l10 = make_softmax_layer(net->v[10]->sx, net->v[10]->sy, net->v[10]->depth);
net->v[11] = make_vol(net->l10->out_sx, net->l10->out_sy, net->l10->out_depth, 0.0);
return net;
}
// Neural Network -------------------------------------------------------------
// Load the snapshot of the CNN we are going to run.
Network* construct_gtsrb_net() {
fprintf(stderr, "Constructing GTSRB Network \n");
Network* net = make_network(12);
network_add(net, make_conv_layer(48, 48, 3, 3, 100, 1, 0));
network_add(net, make_relu_layer(net->layers[0]->out_sx, net->layers[0]->out_sy, net->layers[0]->out_depth));
network_add(net, make_max_pool_layer(net->layers[1]->out_sx, net->layers[1]->out_sy, net->layers[1]->out_depth, 2, 2));
network_add(net, make_conv_layer(net->layers[2]->out_sx, net->layers[2]->out_sy, net->layers[2]->out_depth, 4, 150, 1, 0));
network_add(net, make_relu_layer(net->layers[3]->out_sx, net->layers[3]->out_sy, net->layers[3]->out_depth));
network_add(net, make_max_pool_layer(net->layers[4]->out_sx, net->layers[4]->out_sy, net->layers[4]->out_depth, 2, 2));
network_add(net, make_conv_layer(net->layers[5]->out_sx, net->layers[5]->out_sy, net->layers[5]->out_depth, 3, 250, 1, 0));
network_add(net, make_relu_layer(net->layers[6]->out_sx, net->layers[6]->out_sy, net->layers[6]->out_depth));
network_add(net, make_max_pool_layer(net->layers[7]->out_sx, net->layers[7]->out_sy, net->layers[7]->out_depth, 2, 2));
network_add(net, make_fc_layer(net->layers[8]->out_sx, net->layers[8]->out_sy, net->layers[8]->out_depth, 200));
network_add(net, make_fc_layer(net->layers[9]->out_sx, net->layers[9]->out_sy, net->layers[9]->out_depth, 43));
network_add(net, make_softmax_layer(net->layers[10]->out_sx, net->layers[10]->out_sy, net->layers[10]->out_depth));
// load pre-trained weights
conv_load(net->layers[0], conv1_params, conv1_data);
conv_load(net->layers[3], conv2_params, conv2_data);
conv_load(net->layers[6], conv3_params, conv3_data);
fc_load(net->layers[9], ip1_params, ip1_data);
fc_load(net->layers[10], ip2_params, ip2_data);
return net;
}
// Model referenced in paper: http://delivery.acm.org/10.1145/2750000/2744788/a108-cavigelli.pdf?ip=131.111.184.18&id=2744788&acc=ACTIVE%20SERVICE&key=BF07A2EE685417C5%2E6CDC43D2A5950A53%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=693103990&CFTOKEN=72630065&__acm__=1436879082_abb335b0c6bff6ea2d573dafecbbe01a
// Used as a benchmark in Origami paper
Network* construct_scene_labeling_net() {
Network* net = make_network(1);
network_add(net, make_conv_layer(28, 28, 1, 5, 6, 1, 0));
/*
network_add(net, make_max_pool_layer(net->layers[0]->out_sx, net->layers[0]->out_sy, net->layers[0]->out_depth, 2, 2));
network_add(net, make_relu_layer(net->layers[1]->out_sx, net->layers[1]->out_sy, net->layers[1]->out_depth));
network_add(net, make_conv_layer(net->layers[2]->out_sx, net->layers[2]->out_sy, net->layers[2]->out_depth, 7, 64, 1, 0));
network_add(net, make_max_pool_layer(net->layers[3]->out_sx, net->layers[3]->out_sy, net->layers[3]->out_depth, 2, 2));
network_add(net, make_relu_layer(net->layers[4]->out_sx, net->layers[4]->out_sy, net->layers[4]->out_depth));
network_add(net, make_conv_layer(net->layers[5]->out_sx, net->layers[5]->out_sy, net->layers[5]->out_depth, 7, 256, 1, 0));
network_add(net, make_relu_layer(net->layers[6]->out_sx, net->layers[6]->out_sy, net->layers[6]->out_depth));
network_add(net, make_fc_layer(net->layers[7]->out_sx, net->layers[7]->out_sy, net->layers[7]->out_depth, 64));
network_add(net, make_relu_layer(net->layers[8]->out_sx, net->layers[8]->out_sy, net->layers[8]->out_depth));
network_add(net, make_fc_layer(net->layers[9]->out_sx, net->layers[9]->out_sy, net->layers[9]->out_depth, 8));
network_add(net, make_softmax_layer(net->layers[10]->out_sx, net->layers[10]->out_sy, net->layers[10]->out_depth));
*/
return net;
}
