Hi all,
I tried to implement U-Net 3D on MRI Dataset with a custom shape and ı modified the strides and padding to match the sizes at skip connection processes. But when I train the network all layers have zero-grads but last. As a result of that, my loss stuck at a level that random parameters can provide. I tried to change the activation functions, shapes, and many maaaany other things. I am exhausted. Can somebody help ?
UNET has [1,4,240,240,155] input and [1,7,240,240,155] output. I use generalised dice loss with softmax. Model depth is 4. Because of the size of the process I use half and fp16 on model and input,output.