code: def track_time(graph_name, format, seed_nodes_num):
      device = utils.get_bench_device()
      graph = utils.get_graph(graph_name, format)
      graph = graph.to(device)
  
      seed_nodes = np.random.randint(
          0, graph.num_nodes(), seed_nodes_num
      )
      seed_nodes = torch.from_numpy(seed_nodes).to(device)
  
      # dry run
      for i in range(3):
          dgl.in_subgraph(graph, seed_nodes)
  
      # timing
      num_iters = 50
      with utils.Timer() as t:
          for i in range(num_iters):
              dgl.in_subgraph(graph, seed_nodes)
  
      return t.elapsed_secs / num_iters
  
imports: import time
  import dgl
  import dgl.function
  import numpy
  import torch
  from ..None import utils
label_desc: Use image node_id 1 for calling a global function with example usage: track_time(graph_name, format, seed_nodes_num) and returns: unknown