code: def test_bam_predict_different_inputs(self):
      bamnet = algorithms.DiscreteBAM()
  
      data = np.array([[1, 0, 0, 1]])
      target = np.array([[1, 0]])
  
      bamnet.train(data, target)
      test_vectors = vectors_for_testing(
          data.reshape(data.size), is_feature1d=False
      )
  
      for test_vector in test_vectors:
          np.testing.assert_array_almost_equal(
              bamnet.predict(test_vector)[1], target
          )
  
file_path: neupy/tests/algorithms/memory/test_bam.py
imports: import pickle
  import numpy
  from neupy import algorithms
  from neupy.exceptions import NotTrained
  from algorithms.memory.data import zero, one, half_one, half_zero
  from base import BaseTestCase
  from helpers import vectors_for_testing
label_desc: Use image node_id 10 for calling the BAMTestCase obj's underlying member method code with example usage: obj.test_bam_predict_different_inputs() without return types