code: def test_predict_proba_cycle(model2, X_masked):
      y_hat = model2.predict_proba(X_masked)
  
      assert_array_almost_equal(
          y_hat[0],
          [
              [0.3368, 0.6632],
              [1.0000, 0.0000],
              [0.3673, 0.6327],
              [0.0000, 1.0000],
              [0.1031, 0.8969],
              [1.0000, 0.0000],
              [0.3673, 0.6327],
              [0.0000, 1.0000],
              [0.0000, 1.0000],
              [1.0000, 0.0000],
              [1.0000, 0.0000],
          ],
          4,
      )
  
      assert_array_almost_equal(
          y_hat[1],
          [
              [0.0000, 0.0000, 1.0000],
              [1.0000, 0.0000, 0.0000],
              [0.5408, 0.2704, 0.1888],
              [0.0000, 0.0000, 1.0000],
              [0.0000, 1.0000, 0.0000],
              [0.0000, 1.0000, 0.0000],
              [0.5408, 0.2704, 0.1888],
              [0.2381, 0.4762, 0.2857],
              [0.0000, 1.0000, 0.0000],
              [0.0000, 0.0000, 1.0000],
              [0.5388, 0.2371, 0.2241],
          ],
          4,
      )
  
      assert_array_almost_equal(
          y_hat[2],
          [
              [1.0000, 0.0000],
              [0.4474, 0.5526],
              [0.4287, 0.5713],
              [0.0000, 1.0000],
              [0.4110, 0.5890],
              [1.0000, 0.0000],
              [0.4287, 0.5713],
              [0.0000, 1.0000],
              [1.0000, 0.0000],
              [0.0000, 1.0000],
              [1.0000, 0.0000],
          ],
          4,
      )
  
      assert_array_almost_equal(
          y_hat[3],
          [
              [1.0000, 0.0000],
              [0.7916, 0.2084],
              [1.0000, 0.0000],
              [0.0000, 1.0000],
              [0.2031, 0.7969],
              [0.7273, 0.2727],
              [1.0000, 0.0000],
              [0.0000, 1.0000],
              [0.1429, 0.8571],
              [1.0000, 0.0000],
              [0.6897, 0.3103],
          ],
          4,
      )
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.factor_graph import FactorGraph
  from pomegranate.distributions import Exponential
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import JointCategorical
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 22 for calling a global function with example usage: test_predict_proba_cycle(model2, X_masked) without return types