code: def mae(pred, gt):
      """
      Desc:
          Mean Absolute Error
      Args:
          pred:
          gt: ground truth vector
      Returns:
          MAE value
      """
      _mae = 0.0
      if len(pred) > 0 and len(gt) > 0:
          _mae = np.mean(np.abs(pred - gt))
      return _mae
  
file_path: PGL/examples/kddcup2022/wpf_baseline/metrics.py
imports: import pandas
  import time
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: mae(pred, gt) and returns: _mae