code: def test_regvgg_optimize_for_deployment(device, dtype):
      module = RepVggBlock(64, 64).to(device, dtype).eval()
      x = torch.randn(2, 64, 9, 9, device=device, dtype=dtype)
  
      expected = module(x)
      module.optimize_for_deployment()
      actual = module(x)
      assert_close(actual, expected)
  
imports: from functools import partial
  import pytest
  import torch
  from kornia.contrib.models.rt_detr.architecture.hgnetv2 import PPHGNetV2
  from kornia.contrib.models.rt_detr.architecture.hybrid_encoder import HybridEncoder, RepVggBlock
  from kornia.contrib.models.rt_detr.architecture.resnet_d import ResNetD
  from kornia.contrib.models.rt_detr.architecture.rtdetr_head import RTDETRHead
  from kornia.contrib.models.rt_detr.model import RTDETR, RTDETRConfig
  from kornia.testing import BaseTester, assert_close
label_desc: Use image node_id 4 for calling a global function with example usage: test_regvgg_optimize_for_deployment(device, dtype) without return types