code: def X_custom():
      return pd.DataFrame(
          {
              # The weekday of "2018-01-02" is 1
              "time_name": pd.date_range(
                  "2018-01-02", periods=11, freq="D"
              ),
              "value_name": np.arange(11),
          }
      )
  
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 2 for calling a global function with example usage: X_custom() and returns: pd