code: def track_time(graph_name, format, fraction):
      device = utils.get_bench_device()
      graph = utils.get_graph(graph_name, format)
      graph = graph.to(device)
      nids = np.random.choice(
          np.arange(graph.num_nodes(), dtype=np.int64),
          int(graph.num_nodes() * fraction),
      )
      nids = torch.tensor(nids, device=device, dtype=torch.int64)
  
      # dry run
      for i in range(10):
          out = graph.in_degrees(i)
  
      # timing
      with utils.Timer() as t:
          for i in range(10):
              edges = graph.in_degrees(nids)
  
      return t.elapsed_secs / 10
  
imports: import time
  import dgl
  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, fraction) and returns: unknown