code: def bench(t1, t2):
      bench_times = []
      for _ in range(NUM_REPEAT_OF_REPEATS):
          time_start = time.time()
          for _ in range(NUM_REPEATS):
              torch.add(t1, t2)
          bench_times.append(time.time() - time_start)
  
      bench_time = float(torch.min(torch.tensor(bench_times))) / 1000
      bench_std = float(torch.std(torch.tensor(bench_times))) / 1000
  
      return bench_time, bench_std
  
imports: import argparse
  import time
  import torch
  from common import SubTensor, SubWithTorchFunction, WithTorchFunction
label_desc: Use image node_id 1 for calling a global function with example usage: bench(t1, t2) and returns: bench_time,  bench_std