code: def _get_feature_matrices(interactions):
      no_users, no_items = interactions.shape
  
      user_features = sp.identity(no_users, dtype=np.int32).tocsr()
      item_features = sp.identity(no_items, dtype=np.int32).tocsr()
  
      return (user_features.tocsr(), item_features.tocsr())
  
imports: import pickle
  import numpy
  import scipy.sparse
  from scipy import stats
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import KFold, RandomizedSearchCV
  from lightfm.lightfm import LightFM
  from lightfm.datasets import fetch_movielens
  from lightfm.evaluation import auc_score, precision_at_k
label_desc: Use image node_id 2 for calling a global function with example usage: _get_feature_matrices(interactions) and returns: user_features,  item_features