code: def test_state_reset():
      model = LightFM(random_state=SEED)
  
      model.fit(train, epochs=1)
  
      assert np.mean(model.user_embedding_gradients) > 1.0
  
      model.fit(train, epochs=0)
      assert np.all(model.user_embedding_gradients == 1.0)
  
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 25 for calling a global function with example usage: test_state_reset() without return types