def METHOD_NAME(tmp_path):
    config = NNCFConfig.from_dict(
        {
            "input_info": [
                {
                    "sample_size": [1, 1, 1],
                },
                {
                    "sample_size": [1, 1],
                },
                {"sample_size": [1, 1], "type": "long", "filler": "zeros"},
            ]
        }
    )
    onnx_model_proto = load_exported_onnx_version(config, ModelForIONamingTest(), tmp_path)
    conv_node = next(iter(get_nodes_by_type(onnx_model_proto, "Conv")))
    linear_node = next(iter(get_nodes_by_type(onnx_model_proto, "Gemm")))
    embedding_node = next(iter(get_nodes_by_type(onnx_model_proto, "Gather")))
    for idx, node in enumerate([conv_node, linear_node, embedding_node]):
        input_tensor_ids = [x for x in node.input if "input" in x]
        assert len(input_tensor_ids) == 1
        assert input_tensor_ids[0] == f"input.{idx}"
        assert len(node.output) == 1
        assert node.output[0] == f"output.{idx}"