code: def test_score_default(X):
      """Tests default score function with no null model"""
      model = ConstantBaseForecastEstimator()
      model.fit(X)
      y = np.repeat(2, X.shape[0])
      score = model.score(X, y=y)
      # ConstantBaseForecastEstimator always returns 1.0
      y_pred = np.repeat(1.0, X.shape[0])
      assert score == mean_squared_error(y, y_pred)
  
imports: import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import mean_squared_error
  from testfixtures import LogCapture
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import PREDICTED_LOWER_COL
  from greykite.common.constants import PREDICTED_UPPER_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.evaluation import r2_null_model_score
  from greykite.sklearn.estimator.base_forecast_estimator import BaseForecastEstimator
  from greykite.sklearn.uncertainty.uncertainty_methods import UncertaintyMethodEnum
label_desc: Use image node_id 7 for calling a global function with example usage: test_score_default(X) without return types