text: """Checks if RMSE of Model Prediction is as low as expected."""
  
  import pandas as pd
  from lifetimes import BetaGeoFitter
  from sklearn.metrics import mean_squared_error
  
  import pytest
  
  @pytest.fixture
  def load_data_and_model():
      """Loads Customer Lifetime Estimator Model"""
      model = BetaGeoFitter(penalizer_coef=0.0)
      model.load_model("../models/calibration_model.pkl")
      summary_cal_holdout = pd.read_csv("../datasets/summary_cal_holdout.csv")
      return model, summary_cal_holdout
  
  def test_model_rmse(load_data_and_model):
      """Test RMSE of Predicted Frequency vs Holdout Frequency"""
      data = load_data_and_model[1]
      model = load_data_and_model[0]
      predictions = model.predict(t=243,
                                  frequency=data["frequency_cal"],
                                  recency=data["recency_cal"],
                                  T=data["T_cal"])
      rmse = mean_squared_error(data["frequency_holdout"],
                                predictions,
                                squared=False)
      assert rmse < 0.15, "RMSE is greater than 0.15"
  