code: def test_total_time(shapes):
      print(
          "shape; torch mm; triton mm; inductor aten mm; inductor triton mm"
      )
      for i in range(len(shapes)):
          a_shape, b_shape = shapes[i]
          print(a_shape, "x", b_shape, end="; ")
          a = torch.randn(a_shape, device="cuda", dtype=torch.float16)
          b = torch.randn(b_shape, device="cuda", dtype=a.dtype)
  
          config.triton.mm = "aten"
          inductor_aten_mm(a, b)
  
          config.triton.mm = "triton"
          inductor_triton_mm(a, b)
  
          torch_ms = time_with_torch_timer(torch_mm, (a, b)).mean * 1000
  
          triton_ms = (
              time_with_torch_timer(triton_mm, (a, b)).mean * 1000
          )
  
          config.triton.mm = "aten"
          ind_aten_ms = (
              time_with_torch_timer(inductor_aten_mm, (a, b)).mean
              * 1000
          )
  
          config.triton.mm = "triton"
          ind_triton_ms = (
              time_with_torch_timer(inductor_triton_mm, (a, b)).mean
              * 1000
          )
  
          print(
              torch_ms, triton_ms, ind_aten_ms, ind_triton_ms, sep="; "
          )
  
          torch._dynamo.reset()
  
file_path: pytorch/benchmarks/dynamo/microbenchmarks/inductor_mm.py
imports: import torch
  import torch._dynamo
  import torch._dynamo.config
  import torch._inductor.config
  import triton
  from benchmark_helper import time_with_torch_timer
label_desc: Use image node_id 5 for calling a global function with example usage: test_total_time(shapes) without return types