code: def test_convolution(tmpdir, auto_padding):
      pytest.skip(
          "Needs to be fixed after removal of batch axis change."
      )
      img_shape = (1, 5, 5)
      img = np.asarray(
          np.random.uniform(-1, 1, img_shape), dtype=np.float32
      )
  
      x = C.input_variable(img.shape)
      filter = np.reshape(
          np.array([2, -1, -1, 2], dtype=np.float32), (1, 1, 2, 2)
      )
      kernel = C.constant(value=filter)
      root_node = C.convolution(kernel, x, auto_padding=auto_padding)
  
      filename = os.path.join(str(tmpdir), R"conv.onnx")
      root_node.save(filename, format=C.ModelFormat.ONNX)
  
      loaded_node = C.Function.load(filename, format=C.ModelFormat.ONNX)
      assert root_node.shape == loaded_node.shape
  
      x_ = loaded_node.arguments[0]
      assert np.allclose(
          loaded_node.eval({x_: [img]}), root_node.eval({x: [img]})
      )
  
file_path: CNTK/bindings/python/cntk/tests/onnx_format_test.py
imports: import os
  import numpy
  import cntk
  from cntk.ops.tests.ops_test_utils import cntk_device
  import pytest
label_desc: Use image node_id 3 for calling a global function with example usage: test_convolution(tmpdir, auto_padding) without return types