code: def test_fit_BayesRecipe(self):
      from zoo.chronos.autots.deprecated.config.recipe import (
          BayesRecipe,
      )
  
      train_df, _, future_seq_len = self.create_dataset()
      tsp = TimeSequencePredictor(
          dt_col="datetime",
          target_col="value",
          future_seq_len=future_seq_len,
          extra_features_col=None,
          search_alg="BayesOpt",
          search_alg_params={
              "utility_kwargs": {"kind": "ucb", "kappa": 2.5, "xi": 0.0}
          },
      )
      pipeline = tsp.fit(
          train_df,
          recipe=BayesRecipe(
              num_samples=1,
              training_iteration=2,
              epochs=1,
              look_back=(3, 5),
          ),
      )
      assert isinstance(pipeline, TimeSequencePipeline)
      assert isinstance(pipeline.model, TimeSequenceModel)
      assert pipeline.config is not None
      assert "epochs" in pipeline.config
      assert [
          config_name
          for config_name in pipeline.config
          if config_name.endswith("float")
      ] == []
      assert "past_seq_len" in pipeline.config
      assert 3 <= pipeline.config["past_seq_len"] <= 5
  
file_path: analytics-zoo/pyzoo/test/zoo/chronos/autots/deprecated/regression/test_time_sequence_predictor.py
imports: import pytest
  from test.zoo.pipeline.utils.test_utils import ZooTestCase
  from zoo.chronos.autots.deprecated.model.time_sequence import TimeSequenceModel
  from zoo.chronos.autots.deprecated.regression.time_sequence_predictor import TimeSequencePredictor
  import pandas
  import numpy
  from zoo.chronos.autots.deprecated.pipeline.time_sequence import TimeSequencePipeline
label_desc: Use image node_id 6 for calling the TestTimeSequencePredictor obj's underlying member method code with example usage: obj.test_fit_BayesRecipe() without return types