text: import numpy as np
  
  
  def mae(y_true, y_pred):
      """
      Simple mean absolute error calculations
  
      Args:
          y_true: (numpy array) ground truth
          y_pred: (numpy array) predicted values
      Returns:
           (float) mean absolute error
      """
      return np.mean(np.abs(y_true - y_pred))
  
  
  def accuracy(y_true, y_pred):
      """
      Simple accuracy calculation
  
      Args:
          y_true: numpy array of 0 and 1's
          y_pred: numpy array of predict sigmoid
      Returns:
          (float) accuracy
      """
      y_pred = y_pred > 0.5
      return np.sum(y_true == y_pred) / len(y_pred)
  