code: def test_load_state_dict(self) -> None:
      gs_state_dict = self.grad_sample_module.state_dict()
      new_gs = GradSampleModule(
          SampleConvNet(), batch_first=False, loss_reduction="mean"
      )
      new_gs.load_state_dict(gs_state_dict)
      # wrapped module is the same
      for key in self.original_model.state_dict().keys():
          self.assertTrue(key in new_gs._module.state_dict())
          assert_close(
              self.original_model.state_dict()[key],
              new_gs._module.state_dict()[key],
          )
  
imports: import unittest
  import torch
  import torch.nn
  import torch.nn.functional
  from opacus.grad_sample import GradSampleModule
  from opacus.grad_sample.gsm_exp_weights import GradSampleModuleExpandedWeights
  from opacus.grad_sample.linear import compute_linear_grad_sample
  from opacus.grad_sample.utils import register_grad_sampler
  from torch.testing import assert_close
  from torch.utils.data import DataLoader
  from torchvision import transforms
  from torchvision.datasets import FakeData
  from torchvision.models import mobilenet_v3_small
label_desc: Use image node_id 13 for calling the GradSampleModuleTest obj's underlying member method code with example usage: obj.test_load_state_dict() without return types