We highly recommend to proceed a sanity check to test the compliance of OTO onto target DNN. The sanity check will randomly pick up a set of minimally removal structures as redundant
oto.random_set_zero_groups()and produce compact subnetwork, as presented in sanity_check. If sanity check does not pass, please mark illed node groups as unprunable via
oto.mark_unprunable_by_node_ids()For example, in YOLOv5, we mark the node groups corresponding to detection heads as unprunable.
If all variable groups of pruning minimally removal structures are pruning zero-invariant groups (PZIGs), the returned sub-network should return the exact same output as the full group sparse model given random inputs.
Run the sanity check by the below command
python sanity_check.pyNote some sanity checks may require additional dependency, thereby comment off the ones that you do not need.