code: def test_rbm_batch_size(self):
      data = self.data
      batch_size = 7
  
      self.assertNotEqual(len(data) % batch_size, 0)
  
      rbm = algorithms.RBM(
          n_visible=4, n_hidden=1, step=0.1, batch_size=batch_size
      )
      # Check if it's possilbe to train RBM in case if
      # we cannot divide dataset into full mini-batches
      rbm.train(data, epochs=2)
  
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 5 for calling the BernoulliRBMTestCase obj's underlying member method code with example usage: obj.test_rbm_batch_size() without return types