code: def track_time(size, dim, k, algorithm):
      device = utils.get_bench_device()
      features = np.random.RandomState(42).randn(size, dim)
      feat = torch.tensor(features, dtype=torch.float, device=device)
      # dry run
      for i in range(1):
          dgl.knn_graph(feat, k, algorithm=algorithm)
      # timing
      with utils.Timer() as t:
          for i in range(5):
              dgl.knn_graph(feat, k, algorithm=algorithm)
  
      return t.elapsed_secs / 5
  
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(size, dim, k, algorithm) and returns: unknown