Thanks for the reply! The ideia is mentioned in the paper https://arxiv.org/pdf/1904.03076.pdf section 3.2.

Thus, it is reasonable to share weights between the parallel convolutions within one SDC block. The only requirement is that the parallel convolutions are of the same shape. By sharing weights, the amount of parameters gets divided by the number of parallel convolutions (factor 4 in our case). This allows to construct very light-weight feature networks with a comparatively large receptive field.

Maybe my implementation of this idea was quite wrong?