Thank you for share your code, it's a really good work. But there are some problems in your project.
In frame_wise_softmax_loss_layer.cpp:86, you want to take into account ambiguous frame, that works fine on the dataset with ambiguous. But if I want to use this project on my data, that will be confused. I think it's better to ignore ambiguous in preprocess, not in caffe layer.
During my training, I found that some -nan appears randomly, even I set my lr=1e-9. And I find that there is a typo in voxel_wise_softmax_layer.cpp:66.
It should be max(scaledata[scale.offset(i,0,l,h,w)],
since the bottom[0] and the scale_ have different shape. It may subtract a huge number in the next step, and -nan appears.
Thank you for share your code, it's a really good work. But there are some problems in your project.
In frame_wise_softmax_loss_layer.cpp:86, you want to take into account ambiguous frame, that works fine on the dataset with ambiguous. But if I want to use this project on my data, that will be confused. I think it's better to ignore ambiguous in preprocess, not in caffe layer.
During my training, I found that some -nan appears randomly, even I set my lr=1e-9. And I find that there is a typo in voxel_wise_softmax_layer.cpp:66. It should be max(scaledata[scale.offset(i,0,l,h,w)], since the bottom[0] and the scale_ have different shape. It may subtract a huge number in the next step, and -nan appears.