code: def test_summary(daily_data):
      """Checks summary function."""
      model = OneByOneEstimator(
          estimator="SimpleSilverkiteEstimator",
          forecast_horizon=3,
          estimator_map=2,
          estimator_params={
              "autoreg_dict": "auto",
              "yearly_seasonality": 2,
              "feature_sets_enabled": False,
          },
      )
      train_df = daily_data["train_df"].iloc[:365]
      model.fit(train_df)
      summary = model.summary()
      assert len(summary) == 2
  
file_path: greykite/greykite/tests/sklearn/estimator/test_one_by_one_estimator.py
imports: import datetime
  import sys
  import pandas
  import pytest
  from sklearn.metrics import mean_squared_error
  import greykite.common.constants
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.sklearn.estimator.one_by_one_estimator import OneByOneEstimator
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
label_desc: Use image node_id 8 for calling a global function with example usage: test_summary(daily_data) without return types