code: def test_rbm_sampling(self):
      data = self.data
  
      rbm = algorithms.RBM(n_visible=4, n_hidden=1)
      rbm.train(data, epochs=500)
  
      proba_sample = rbm.hidden_to_visible(rbm.visible_to_hidden(data))
      proba_sample = proba_sample.round().astype(int)
  
      np.testing.assert_array_equal(
          proba_sample.round(),
          np.array(
              [
                  [1, 0, 1, 0],
                  [1, 0, 1, 0],
                  [1, 0, 1, 0],  # fixed sample
                  [1, 0, 1, 0],
                  [0, 1, 0, 1],
                  [0, 1, 0, 1],  # fixed sample
                  [0, 1, 0, 1],
                  [0, 1, 0, 1],
                  [0, 1, 0, 1],
                  [0, 1, 0, 1],
              ]
          ),
      )
  
      sampled_data = rbm.gibbs_sampling(data, n_iter=1)
      self.assertNotEqual(0, np.abs(sampled_data - self.data).sum())
  
file_path: neupy/tests/algorithms/rbm/test_rbm.py
imports: import pickle
  import numpy
  from neupy import algorithms
  from neupy.utils import asfloat
  from base import BaseTestCase
label_desc: Use image node_id 6 for calling the BernoulliRBMTestCase obj's underlying member method code with example usage: obj.test_rbm_sampling() without return types