code: def test_learning_process(self):
      hn = algorithms.HebbRule(
          n_inputs=2,
          n_outputs=1,
          n_unconditioned=1,
          step=1,
          verbose=False,
      )
      hn.train(X, epochs=2)
  
      test_data = np.array(
          [
              [0, 0],
              [0, 1],
              [1, 0],
              [1, 1],
          ]
      )
      np.testing.assert_array_equal(
          hn.predict(test_data), np.array([[0, 1, 1, 1]]).T
      )
  
file_path: neupy/tests/algorithms/associative/test_hebb.py
imports: import numpy
  from neupy import algorithms
  from base import BaseTestCase
label_desc: Use image node_id 3 for calling the HebbRuleTestCase obj's underlying member method code with example usage: obj.test_learning_process() without return types