code: def benchmark_simple_fn(
      args, config, module_config, module_type, result
  ):
      """Benchmarks a PyTorch traceable function specified in the config.
      Instantiates a wrapper object that wraps the object of module_type and runs the forward
      method using benchmark_module.
      Args:
          config:         contains number of warmup and benchmark iterations.
          module_config:  module_config which contains op, number of parameters that op takes
                      and whether graph mode is enabled or not.
          module_type:    Type of the module to be wrapped. e.g. SimpleAddModule for add op.
          result:         dictionary instance to be populated with the benchmark result (latency per iter).
      """
      benchmark_c2_net = args.benchmark_c2_net
      print(f"Benchmarking {module_type.__name__}")
      if benchmark_c2_net:
          op_name = module_config.c2_op
          num_inputs = module_config.num_params
          module = C2SimpleNet(
              op_name, num_inputs=num_inputs, debug=args.debug
          )
          latency_per_iter_ms = benchmark_module(config, module)
          result[op_name] = latency_per_iter_ms
      else:
          f_name = (
              module_config.pt_fn.__name__
              + ":Num Operands="
              + str(module_config.num_params)
          )
          graph_mode_str = (
              "Graph mode" + ":" + str(module_config.graph_mode)
          )
          result_key = ",".join((f_name, graph_mode_str))
          module = WrapperModule(
              module_type, module_config, args.debug, args.save
          )
          latency_per_iter_ms = benchmark_module(
              config, module, args.use_throughput_benchmark
          )
          result[result_key] = latency_per_iter_ms
  
file_path: pytorch/benchmarks/framework_overhead_benchmark/framework_overhead_benchmark.py
imports: import argparse
  from C2Module import C2SimpleNet
  from pt_wrapper_module import WrapperModule
  from SimpleAddModule import add_tensors_loop, SimpleAddModule
  from utils import benchmark_module, BenchmarkConfig, ModuleConfig, ms_to_us
label_desc: Use image node_id 3 for calling a global function with example usage: benchmark_simple_fn(args, config, module_config, module_type, result) without return types