Following is smooth L1 Loss layer used in PVANet
<https://github.com/sanghoon/pva-faster-rcnn/blob/master/models/pvanet/example_train/train.prototxt>
:
layer {
name: "rpn_loss_bbox"
type: "SmoothL1Loss"
bottom: "rpn_bbox_pred"
bottom: "rpn_bbox_targets"
bottom: "rpn_bbox_inside_weights"
bottom: "rpn_bbox_outside_weights"
top: "rpn_loss_bbox"
include { phase: TRAIN }
loss_weight: 1
smooth_l1_loss_param { sigma: 3.0 }
}
This seems to be a custom loss layer that takes four inputs. I'm trying to
use this in MXNet using 'mx.symbol.CaffeLoss'. I see that 'CaffeLoss' only
takes 2 inputs (data and label). Does anybody know how I can I use
'CaffeLoss' to use the above loss layer in MXNet?
Thanks,
Indu
