code: def create_dgl_graph_from_disk(dataset_path, replication_factor=1):
      """
      Create a DGL graph from a dataset on disk.
      Args:
          dataset_path: Path to the dataset on disk.
          replication_factor: Number of times to replicate the edges.
      Returns:
          DGLGraph: DGLGraph with the loaded dataset.
      """
      with open(os.path.join(dataset_path, "meta.json"), "r") as f:
          input_meta = json.load(f)
  
      parquet_path = os.path.join(dataset_path, "parquet")
      graph_data = load_edges_from_disk(
          parquet_path, replication_factor, input_meta
      )
      node_data = load_node_labels(
          dataset_path, replication_factor, input_meta
      )
      g = dgl.heterograph(graph_data)
  
      return g, node_data
  
file_path: cugraph/benchmarks/cugraph-dgl/python-script/dgl_dataloading_benchmark/dgl_benchmark.py
imports: import dgl
  import torch
  import pandas
  import os
  import time
  import json
  import random
  import numpy
  from argparse import ArgumentParser
label_desc: Use image node_id 3 for calling a global function with example usage: create_dgl_graph_from_disk(dataset_path, replication_factor) and returns: g,  node_data