code: def replicate_edges(
      edge_index, canonical_edge_type, replication_factor, input_meta
  ):
      src_list = [edge_index["src"]]
      dst_list = [edge_index["dst"]]
  
      for r in range(1, replication_factor):
          new_src = edge_index["src"] + (
              r * input_meta["num_nodes"][canonical_edge_type[0]]
          )
          new_dst = edge_index["dst"] + (
              r * input_meta["num_nodes"][canonical_edge_type[2]]
          )
          src_list.append(new_src)
          dst_list.append(new_dst)
  
      return src_list, dst_list
  
file_path: cugraph/benchmarks/cugraph-dgl/scale-benchmarks/load_graph_feats.py
imports: import numpy
  import pandas
  import torch
  import os
label_desc: Use image node_id 2 for calling a global function with example usage: replicate_edges(edge_index, canonical_edge_type, replication_factor, input_meta) and returns: src_list,  dst_list