code: def test_tabular_nn_regression_compile_onnx(fit_helper):
      fit_args = dict(
          hyperparameters={TabularNeuralNetTorchModel: {}},
          time_limit=20,  # TabularNN trains for a long time on ames
      )
      dataset_name = "ames"
      compiler_configs = {
          TabularNeuralNetTorchModel: {"compiler": "onnx"}
      }
      predictor = fit_helper.fit_and_validate_dataset(
          dataset_name=dataset_name,
          fit_args=fit_args,
          compile=True,
          compiler_configs=compiler_configs,
      )
      from autogluon.tabular.models.tabular_nn.compilers.onnx import (
          TabularNeuralNetTorchOnnxTransformer,
      )
  
      assert isinstance(
          predictor._learner.trainer.models["NeuralNetTorch"].processor,
          TabularNeuralNetTorchOnnxTransformer,
      )
  
file_path: autogluon/tabular/tests/unittests/models/test_tabular_nn.py
imports: import pytest
  from autogluon.tabular.models.tabular_nn.torch.tabular_nn_torch import TabularNeuralNetTorchModel
label_desc: Use image node_id 7 for calling a global function with example usage: test_tabular_nn_regression_compile_onnx(fit_helper) without return types