code: def benchmark(arg_values={}):
      args_list = product(*arg_values.values())
      runs = [dict(zip(arg_values.keys(), x)) for x in args_list]
  
      def wrapper(cls):
          ALL_SUITES[cls.__name__] = (cls, runs)
  
      return wrapper
  
file_path: ffcv/ffcv/benchmarks/decorator.py
imports: from itertools import product
  from time import time
  from collections import defaultdict
  from contextlib import redirect_stderr
  import pathlib
  import numpy
  from tqdm import tqdm
  from .benchmark import Benchmark
label_desc: Use image node_id 1 for calling a global function with example usage: benchmark(arg_values) and returns: wrapper