code: def test_onnx(self, device, dtype):
      inputs = torch.rand(2, 3, 30, 30, dtype=dtype, device=device)
      model = StraightThroughEstimator(
          torch.nn.PixelShuffle(1), grad_fn=None
      )
  
      input_names = ["input"]
      output_names = ["output1"]
  
      torch.onnx.export(
          model,
          inputs,
          "t.onnx",
          verbose=True,
          input_names=input_names,
          output_names=output_names,
      )
  
file_path: kornia/test/grad_estimator/test_ste.py
imports: import pytest
  import torch
  import torch.nn.functional
  from torch.testing import assert_close
  import kornia.augmentation
  from kornia.grad_estimator import STEFunction, StraightThroughEstimator
label_desc: Use image node_id 5 for calling the TestSTE obj's underlying member method code with example usage: obj.test_onnx(device, dtype) without return types