code: def smape(y, p):
      """Symmetric Mean Absolute Percentage Error (sMAPE).
      Args:
          y (numpy.array): target
          p (numpy.array): prediction
  
      Returns:
          e (numpy.float64): sMAPE
      """
      return 2.0 * np.mean(np.abs(y - p) / (np.abs(y) + np.abs(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 3 for calling a global function with example usage: smape(y, p) and returns: unknown