code: def test_forecaster_from_tsdataset_data_loader_onnx(self):
      train, test = create_tsdataset(roll=False)
      train.gen_dt_feature(one_hot_features=["WEEK"])
      test.gen_dt_feature(one_hot_features=["WEEK"])
      loader = train.to_torch_data_loader(lookback=24, horizon=5)
      test_loader = test.to_torch_data_loader(lookback=24, horizon=5)
      s2s = Seq2SeqForecaster.from_tsdataset(train)
      s2s.fit(loader, epochs=2)
      yhat = s2s.predict(test, acceleration=False)
      onnx_yhat = s2s.predict_with_onnx(test)
      assert yhat.shape == onnx_yhat.shape
  
      res = s2s.evaluate(test_loader, acceleration=False)
      onnx_res = s2s.evaluate_with_onnx(test_loader)
  
imports: import numpy
  import tempfile
  import os
  from bigdl.chronos.utils import LazyImport
  from unittest import TestCase
  import pytest
  from ..None import op_torch, op_distributed, op_inference, op_automl
label_desc: Use image node_id 19 for calling the TestChronosModelSeq2SeqForecaster obj's underlying member method code with example usage: obj.test_forecaster_from_tsdataset_data_loader_onnx() without return types