code: def replicate_node_label(
      node_label, node_type, replication_factor, input_meta
  ):
      base_num_nodes = input_meta["num_nodes"][node_type]
  
      replicated_df = pd.DataFrame(
          {
              "node": pd.concat(
                  [
                      node_label.node + (r * base_num_nodes)
                      for r in range(1, replication_factor)
                  ]
              ),
              "label": pd.concat(
                  [
                      node_label.label
                      for _ in range(1, replication_factor)
                  ]
              ),
          }
      )
  
      return pd.concat([node_label, replicated_df]).reset_index(
          drop=True
      )
  
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 5 for calling a global function with example usage: replicate_node_label(node_label, node_type, replication_factor, input_meta) and returns: pd