code: def params_multiple_regressors():
      add_regressor_dict = {
          "regressor1": {
              "prior_scale": 10,
              "standardize": True,
              "mode": "additive",
          },
          "regressor2": {
              "prior_scale": 15,
              "standardize": False,
              "mode": "additive",
          },
          "regressor3": {},
      }
      return {"add_regressor_dict": add_regressor_dict}
  
imports: import sys
  import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  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 EvaluationMetricEnum
  from greykite.common.evaluation import calc_pred_err
  from greykite.common.python_utils import assert_equal
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.common.testing_utils import generate_df_with_reg_for_tests
  from greykite.sklearn.estimator.prophet_estimator import ProphetEstimator
label_desc: Use image node_id 2 for calling a global function with example usage: params_multiple_regressors() and returns: dict