class_docstr: Wrapper class for scikit-learn regression models.
docstr: Compute the MSE loss of the regressor for predictions `pred`.
  
  :param pred: Model predictions.
  :param y: Target values.
  :return: Loss values.
docstr_tok: ["Compute","the","MSE","loss","of","the","regressor","for","predictions","`","pred","`",".",":","param","pred",":","Model","predictions",".",":","param","y",":","Target","values",".",":","return",":","Loss","values","."]
code: def compute_loss_from_predictions(
      self, pred: np.ndarray, y: np.ndarray, **kwargs
  ) -> np.ndarray:
      """
      Compute the MSE loss of the regressor for predictions `pred`.
  
      :param pred: Model predictions.
      :param y: Target values.
      :return: Loss values.
      """
  
      return (y - pred) ** 2
  
imports: import logging
  import os
  import pickle
  from copy import deepcopy
  from typing import List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.estimators.scikitlearn import ScikitlearnEstimator
  from art.estimators.regression.regressor import RegressorMixin
  from art import config
label_desc: Use image node_id 9 for calling the ScikitlearnRegressor obj's underlying member method code with example usage: obj.compute_loss_from_predictions(pred, y) and returns: unknown