code: def mse(pred, gt):
      """
      Desc:
          Mean Square Error
      Args:
          pred:
          gt: ground truth vector
      Returns:
          MSE value
      """
      _mse = 0.0
      if len(pred) > 0 and len(gt) > 0:
          _mse = np.mean((pred - gt) ** 2)
      return _mse
  
file_path: PGL/examples/kddcup2022/wpf_baseline/metrics.py
imports: import pandas
  import time
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: mse(pred, gt) and returns: _mse