input: Write a python function to calculate Root Mean Squared Error (RMSE) given the true and predicted values.
  assert calculate_rmse([3, -0.5, 2, 7], [2.5, 0.0, 2, 8]) == 0.6123724356957945
  assert calculate_rmse([1, 2, 3], [1, 2, 3]) == 0.0
  assert calculate_rmse([1, 2, 3], [2, 3, 4]) == 1.0
output: def calculate_rmse(true_values, predicted_values):
      import math
      n = len(true_values)
      mse = sum((true - pred) ** 2 for true, pred in zip(true_values, predicted_values)) / n
      rmse = math.sqrt(mse)
      return rmse