code: def test_tcn_forecaster_onnx_methods(self):
      train_data, val_data, test_data = create_data()
      forecaster = LSTMForecaster(
          past_seq_len=24,
          input_feature_num=2,
          output_feature_num=2,
          loss="mae",
          lr=0.01,
      )
      forecaster.fit(train_data, epochs=2)
      try:
          import onnx
          import onnxruntime
  
          pred = forecaster.predict(test_data[0])
          pred_onnx = forecaster.predict_with_onnx(test_data[0])
          np.testing.assert_almost_equal(pred, pred_onnx, decimal=5)
          mse = forecaster.evaluate(test_data, multioutput="raw_values")
          mse_onnx = forecaster.evaluate_with_onnx(
              test_data, multioutput="raw_values"
          )
          np.testing.assert_almost_equal(mse, mse_onnx, decimal=5)
          with pytest.raises(RuntimeError):
              forecaster.build_onnx(sess_options=1)
          sess_options = onnxruntime.SessionOptions()
          sess_options.intra_op_num_threads = 1
          forecaster.build_onnx(sess_options=sess_options)
          mse = forecaster.evaluate(test_data)
          mse_onnx = forecaster.evaluate_with_onnx(test_data)
          np.testing.assert_almost_equal(mse, mse_onnx, decimal=5)
      except ImportError:
          pass
  
imports: import numpy
  import tempfile
  import os
  import torch
  from zoo.chronos.forecaster.lstm_forecaster import LSTMForecaster
  from zoo.orca import init_orca_context, stop_orca_context
  from unittest import TestCase
  import pytest
label_desc: Use image node_id 4 for calling the TestChronosModelLSTMForecaster obj's underlying member method code with example usage: obj.test_tcn_forecaster_onnx_methods() without return types