code: def rmse(y, p):
      """Root Mean Squared Error (RMSE).
      Args:
          y (numpy.array): target
          p (numpy.array): prediction
  
      Returns:
          e (numpy.float64): RMSE
      """
  
      # check and get number of samples
      assert y.shape == p.shape
  
      return np.sqrt(mse(y, p))
  
file_path: causalml/causalml/metrics/regression.py
imports: import logging
  import numpy
  from sklearn.metrics import mean_squared_error
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import r2_score
  from .const import EPS
label_desc: Use image node_id 4 for calling a global function with example usage: rmse(y, p) and returns: np