code: def test_ktrx_coef_knot_dates(make_daily_data, regression_knot_dates):
      train_df, test_df, coef = make_daily_data
  
      ktr = KTR(
          response_col="response",
          date_col="date",
          seasonality=[7, 365.25],
          seasonality_fs_order=[2, 5],
          regressor_col=["a", "b", "c"],
          regression_knot_dates=regression_knot_dates,
          estimator="pyro-svi",
          num_steps=100,
          num_sample=100,
          n_bootstrap_draws=-1,
      )
  
      ktr.fit(train_df)
      predict_df = ktr.predict(test_df)
  
      expected_columns = [
          "date",
          "prediction_5",
          "prediction",
          "prediction_95",
      ]
      expected_shape = (364, len(expected_columns))
      expected_num_parameters = 7
  
      assert predict_df.shape == expected_shape
      assert predict_df.columns.tolist() == expected_columns
      assert len(ktr.get_posterior_samples()) == expected_num_parameters
      assert np.all(np.isfinite(predict_df["prediction"].values))
  
file_path: orbit/tests/orbit/models/test_ktr.py
imports: import pytest
  import numpy
  import pandas
  from orbit.models import KTR
  from orbit.diagnostics.metrics import smape
label_desc: Use image node_id 4 for calling a global function with example usage: test_ktrx_coef_knot_dates(make_daily_data, regression_knot_dates) without return types