code: def test_exception_on_divergence():
      no_users, no_items = (1000, 1000)
  
      train = sp.rand(no_users, no_items, format="csr", random_state=42)
  
      model = LightFM(learning_rate=10000000.0, loss="warp")
  
      with pytest.raises(ValueError):
          model.fit(train, epochs=10)
  
imports: import numpy
  import pytest
  import scipy.sparse
  from lightfm.lightfm import LightFM
label_desc: Use image node_id 12 for calling a global function with example usage: test_exception_on_divergence() without return types