code: def mse_obj(y_pred, dtrain):
      y_true = dtrain.get_label()
      grad = y_pred - y_true
      hess = np.ones(len(grad))
      return grad, hess
  
imports: import pickle
  from functools import lru_cache
  from inspect import getfullargspec
  import cloudpickle
  import joblib
  import numpy
  import sklearn.datasets
  from sklearn.utils import check_random_state
  import lightgbm
label_desc: Use image node_id 8 for calling a global function with example usage: mse_obj(y_pred, dtrain) and returns: grad,  hess