code: def test_performance_speed(device, dtype):
      if device.type != "cuda" or not torch.cuda.is_available():
          pytest.skip("Cuda not available in system,")
  
      print("Benchmarking project_points")
      for input_shape in points_shapes:
          inpt = torch.rand(input_shape).to(device)
          pose = torch.rand((1, 4, 4)).to(device)
          torch.cuda.synchronize(device)
          t = time()
          kornia.geometry.transform_points(pose, inpt)
          torch.cuda.synchronize(device)
          print(f"inp={input_shape}, dev={device}, {time() - t}, sec")
  
imports: from time import time
  import pytest
  import torch
  import kornia
label_desc: Use image node_id 1 for calling a global function with example usage: test_performance_speed(device, dtype) without return types