code: def test_mse_loss(mse_param, arange_4d_image):
      rng = torch.Generator()
      rng.manual_seed(
          int(torch.prod(torch.tensor(arange_4d_image.shape)))
      )
  
      img = torch.randn(size=arange_4d_image.shape, generator=rng)
  
      loss_fn = MSELoss(mse_param)
  
      output = loss_fn(img, arange_4d_image)
  
      est = mse_param * torch.mean((img - arange_4d_image) ** 2)
  
      assert torch.allclose(output, est)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_mse_loss(mse_param, arange_4d_image) without return types