code: def create_dataloader(g, train_idx, batch_size, fanouts, use_uva):
      print("Creating dataloader", flush=True)
      st = time.time()
      if use_uva:
          train_idx = {k: v.to("cuda") for k, v in train_idx.items()}
      sampler = MultiLayerNeighborSampler(fanouts=fanouts)
      dataloader = DataLoader(
          g,
          train_idx,
          sampler,
          num_workers=0,
          batch_size=batch_size,
          use_uva=use_uva,
          shuffle=False,
          drop_last=False,
      )
      et = time.time()
      print(
          f"Time to create dataloader = {et - st:.2f} seconds",
          flush=True,
      )
      return dataloader
  
file_path: cugraph/benchmarks/cugraph-dgl/scale-benchmarks/dgl_benchmark.py
imports: import json
  import os
  import time
  import dgl
  from dgl.dataloading import MultiLayerNeighborSampler, DataLoader
  import pandas
  import torch
  from model import run_1_epoch
  from argparse import ArgumentParser
  from load_graph_feats import load_edges_from_disk, load_node_labels, load_node_features
label_desc: Use image node_id 1 for calling a global function with example usage: create_dataloader(g, train_idx, batch_size, fanouts, use_uva) and returns: dataloader