code: def test_sparse_input_for_predict(csr_container):
      # Test to make sure sparse inputs are accepted for predict
      # (non-regression test for issue #20049)
      af = AffinityPropagation(affinity="euclidean", random_state=42)
      af.fit(X)
      labels = af.predict(csr_container((2, 2)))
      assert_array_equal(labels, (2, 2))
  
imports: import warnings
  import numpy
  import pytest
  from sklearn.cluster import AffinityPropagation, affinity_propagation
  from sklearn.cluster._affinity_propagation import _equal_similarities_and_preferences
  from sklearn.datasets import make_blobs
  from sklearn.exceptions import ConvergenceWarning, NotFittedError
  from sklearn.metrics import euclidean_distances
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 16 for calling a global function with example usage: test_sparse_input_for_predict(csr_container) without return types