code: def test_predict(model, X):
      y_hat = model.predict(X)
      assert_array_almost_equal(
          y_hat, [0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0], 4
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.bayes_classifier import BayesClassifier
  from pomegranate.distributions import Exponential
  from .distributions._utils import _test_initialization_raises_one_parameter
  from .distributions._utils import _test_initialization
  from .distributions._utils import _test_predictions
  from .distributions._utils import _test_efd_from_summaries
  from .distributions._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 14 for calling a global function with example usage: test_predict(model, X) without return types