deep learning - Initializing layers in Caffe Convolutional Neural Network -


i working on constitutional neural network using caffe. have prototxt file layer "hungarian". layer has 2 additional top layers box_confidences , box_assignments.

layer {   name: "hungarian"   type: "hungarianloss"   bottom: "bbox_concat"   bottom: "boxes"   bottom: "box_flags"   top: "hungarian"   top: "box_confidences"   top: "box_assignments"   loss_weight: 0.03   hungarian_loss_param {      match_ratio: 0.5      permute_matches: true   } }

then box_confidences used in layer box_loss bottom 

layer{   name: "box_loss"   type: "softmaxwithloss"   bottom: "score_concat"   bottom: "box_confidences"   top: "box_loss" }

my queries

(1)do need setup layers these box_confidences , box_assignments?

(2)if necessary, how setup layer in prototxt file? layer holding blob data , how these 2 layers used in hungarianlosslayer class member function can seen as

void hungarianlosslayer<dtype>::forward_cpu(const vector<blob<dtype>*>& bottom, const vector<blob<dtype>*>& top){     ...............     ...............     ...............     dtype* top_confidences = top[1]->mutable_cpu_data();     ...............     ...............     ...............     (int = 0; < num_pred; ++i) {         top_confidences[n * num_pred + i] =           assignment[i] < num_gt_[n] ? dtype(1) : dtype(0);         dtype* top_assignments = top[2]->mutable_cpu_data();         top_assignments[n * num_pred + i] =           assignment[i] < num_gt_[n] ? assignment[i] : dtype(-1);     }     ...............     ...............  }

i put ..... other codes not messy.

so box_confidences , box_assignments data blobs , size num_pred. without running code, hard me know value of num_pred.

what best way setup these 2 layers in prototxt file?

box_confidences , box_assignments feature maps (or intermediate activations) output hungarianloss layer. no manual setup memory necessary , can safely provide them bottom blobs subsequent layers (like softmaxwithloss) in network


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