code: def rse(pred, ground_truth):
      """
      Desc:
          Root square error
      Args:
          pred:
          ground_truth: ground truth vector
      Returns:
          RSE value
      """
      _rse = 0.0
      if len(pred) > 0 and len(ground_truth) > 0:
          _rse = np.sqrt(np.sum((ground_truth - pred) ** 2)) / np.sqrt(
              np.sum((ground_truth - ground_truth.mean()) ** 2)
          )
      return _rse
  
file_path: PGL/examples/kddcup2022/wpf_baseline/metrics.py
imports: import pandas
  import time
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: rse(pred, ground_truth) and returns: _rse