code: def test_fit_predict1():
      """Tests sample_weight parameter and different train/test set"""
      model = DummyEstimator()
  
      X = pd.DataFrame(
          {
              TIME_COL: pd.date_range(
                  "2018-01-01", periods=3, freq="1D"
              ),
              VALUE_COL: [2, 3, 5],
          }
      )
  
      df_test = pd.DataFrame(
          {TIME_COL: pd.date_range("2018-01-01", periods=4, freq="1D")}
      )
  
      model.fit(X, sample_weight=[1, 1, 2])
      predicted = model.predict(df_test)
  
      expected = pd.DataFrame(
          {
              TIME_COL: df_test[TIME_COL],
              PREDICTED_COL: np.repeat(3.75, df_test.shape[0]),
          }
      )
  
      assert predicted.equals(expected)
  
file_path: greykite/greykite/tests/sklearn/estimator/test_null_model.py
imports: import numpy
  import pandas
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import mean_squared_error
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.sklearn.estimator.null_model import DummyEstimator
label_desc: Use image node_id 3 for calling a global function with example usage: test_fit_predict1() without return types