code: def test_bias_item_predict():
      algo = Bias(users=False)
      algo.fit(simple_df)
      p = algo.predict_for_user(10, [1, 2, 3])
  
      assert len(p) == 3
      assert p.values == approx(
          (algo.item_offsets_ + algo.mean_).values
      )
  
imports: from lenskit.algorithms.bias import Bias
  from lenskit import util
  import logging
  import pickle
  import binpickle
  import pandas
  import numpy
  from pytest import approx, raises, mark
  from lenskit.util.test import ml_test
label_desc: Use image node_id 9 for calling a global function with example usage: test_bias_item_predict() without return types