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fix-for-extreme-verbose-while-training #8110

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4 changes: 2 additions & 2 deletions src/network.c
Original file line number Diff line number Diff line change
Expand Up @@ -375,8 +375,8 @@ float train_network_datum(network net, float *x, float *y)
backward_network(net, state);
float error = get_network_cost(net);
//if(((*net.seen)/net.batch)%net.subdivisions == 0) update_network(net);
if(*(state.net.total_bbox) > 0)
fprintf(stderr, " total_bbox = %d, rewritten_bbox = %f %% \n", *(state.net.total_bbox), 100 * (float)*(state.net.rewritten_bbox) / *(state.net.total_bbox));
//if(*(state.net.total_bbox) > 0)
//fprintf(stderr, " total_bbox = %d, rewritten_bbox = %f %% \n", *(state.net.total_bbox), 100 * (float)*(state.net.rewritten_bbox) / *(state.net.total_bbox));
return error;
}

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4 changes: 2 additions & 2 deletions src/network_kernels.cu
Original file line number Diff line number Diff line change
Expand Up @@ -363,8 +363,8 @@ void forward_backward_network_gpu(network net, float *x, float *y)
cuda_free(state.delta);
cuda_pull_array(*net.input_gpu, x, x_size);
}
if(*(state.net.total_bbox) > 0)
fprintf(stderr, " total_bbox = %d, rewritten_bbox = %f %% \n", *(state.net.total_bbox), 100 * (float)*(state.net.rewritten_bbox) / *(state.net.total_bbox));
//if(*(state.net.total_bbox) > 0)
// fprintf(stderr, " total_bbox = %d, rewritten_bbox = %f %% \n", *(state.net.total_bbox), 100 * (float)*(state.net.rewritten_bbox) / *(state.net.total_bbox));
}

float train_network_datum_gpu(network net, float *x, float *y)
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8 changes: 4 additions & 4 deletions src/yolo_layer.c
Original file line number Diff line number Diff line change
Expand Up @@ -861,8 +861,8 @@ void forward_yolo_layer(const layer l, network_state state)

loss /= l.batch;

fprintf(stderr, "v3 (%s loss, Normalizer: (iou: %.2f, obj: %.2f, cls: %.2f) Region %d Avg (IOU: %f), count: %d, total_loss = %f \n",
(l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.obj_normalizer, l.cls_normalizer, state.index, tot_iou / count, count, loss);
//fprintf(stderr, "v3 (%s loss, Normalizer: (iou: %.2f, obj: %.2f, cls: %.2f) Region %d Avg (IOU: %f), count: %d, total_loss = %f \n",
// (l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.obj_normalizer, l.cls_normalizer, state.index, tot_iou / count, count, loss);
}
else {
// show detailed output
Expand Down Expand Up @@ -917,8 +917,8 @@ void forward_yolo_layer(const layer l, network_state state)
classification_loss /= l.batch;
iou_loss /= l.batch;

fprintf(stderr, "v3 (%s loss, Normalizer: (iou: %.2f, obj: %.2f, cls: %.2f) Region %d Avg (IOU: %f), count: %d, class_loss = %f, iou_loss = %f, total_loss = %f \n",
(l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.obj_normalizer, l.cls_normalizer, state.index, tot_iou / count, count, classification_loss, iou_loss, loss);
//fprintf(stderr, "v3 (%s loss, Normalizer: (iou: %.2f, obj: %.2f, cls: %.2f) Region %d Avg (IOU: %f), count: %d, class_loss = %f, iou_loss = %f, total_loss = %f \n",
// (l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.obj_normalizer, l.cls_normalizer, state.index, tot_iou / count, count, classification_loss, iou_loss, loss);

//fprintf(stderr, "v3 (%s loss, Normalizer: (iou: %.2f, cls: %.2f) Region %d Avg (IOU: %f, GIOU: %f), Class: %f, Obj: %f, No Obj: %f, .5R: %f, .75R: %f, count: %d, class_loss = %f, iou_loss = %f, total_loss = %f \n",
// (l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.obj_normalizer, state.index, tot_iou / count, tot_giou / count, avg_cat / class_count, avg_obj / count, avg_anyobj / (l.w*l.h*l.n*l.batch), recall / count, recall75 / count, count,
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