ef4353bd24b9d781c2dfa9cd2146d9b87e63b6f1,nn_dataflow/Scheduling.py,Scheduling,schedule_search,#Scheduling#Any#Any#,103

Before Change

                                            options):
            // Ifmap partitioning.
            part_src = condition.part_src
            if not all(sd <= mrsd for sd, mrsd
                       in zip(part_src.dim(), mem_region_src.dim)):
                raise ValueError("Scheduling: ifmap partitioning {} is "
                                 "invalid within memory region {}."
                                 .format(part_src, str(mem_region_src)))

            // Ofmap partitioning.
            part_dst = Partition.get_ofmap_part(part, mem_region_dst)

            // Partition NoC hop cost.
            unit_nhops = Partition.part_layer_unit_nhops(

After Change

        // Filter nodes. All memory nodes can store filters. Deduplicate.
        filter_node_coord_list = [c for c in mem_region_src.node_iter()] \
                               + [c for c in mem_region_dst.node_iter()]
        filter_node_coord_list = list(set(filter_node_coord_list))

        // Explore parallel partitioning schemes.
        for part in Partition.gen_partition(self.layer, self.batch_size,
                                            condition.resource.dim_nodes,
                                            options):
            // Ofmap layout.
            ofmap_layout = Partition.get_ofmap_layout(
                self.layer, self.batch_size, part, mem_region_dst)

            // Partition NoC hop cost.
            unit_nhops = Partition.part_layer_unit_nhops(
                self.layer, self.batch_size, part, filter_node_coord_list,
                ifmap_layout, ofmap_layout, options)
            if math.isinf(sum(unit_nhops)):
                continue

            // Partitioned layer.

Instances