code: def track_time(graph_name, format):
      from_format, to_format = format
      device = utils.get_bench_device()
      graph = utils.get_graph(graph_name, from_format)
      graph = graph.to(device)
      if format == ("coo", "csr") and graph_name == "friendster":
          # Mark graph as sorted to check performance for COO matrix marked as
          # sorted. Note that friendster dataset is already sorted.
          graph = dgl.graph(graph.edges(), row_sorted=True)
      graph = graph.formats([from_format])
      # dry run
      graph.formats([to_format])
  
      # timing
      with utils.Timer() as t:
          for i in range(10):
              gg = graph.formats([to_format])
  
      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) and returns: unknown