code: def bm_mesh_normal_consistency() -> None:
      devices = ["cpu"]
      if torch.cuda.is_available():
          devices.append("cuda")
  
      kwargs_list = []
      num_meshes = [16, 32, 64]
      levels = [2, 3]
      test_cases = product(num_meshes, levels, devices)
      for case in test_cases:
          n, l, d = case
          kwargs_list.append({"num_meshes": n, "level": l, "device": d})
  
      benchmark(
          TestMeshNormalConsistency.mesh_normal_consistency_with_ico,
          "MESH_NORMAL_CONSISTENCY_ICO",
          kwargs_list,
          warmup_iters=1,
      )
  
imports: from itertools import product
  import torch
  from fvcore.common.benchmark import benchmark
  from tests.test_mesh_normal_consistency import TestMeshNormalConsistency
label_desc: Use image node_id 1 for calling a global function with example usage: bm_mesh_normal_consistency() without return types