#NEWLINE# def test_batch_size_specialization( ) : #NEWLINE# #INDENT# m = 2 #NEWLINE# rng = np . random . RandomState ( [ 25 , 9 , 2012 ] ) #NEWLINE# X = np . zeros ( ( m , 1 ) ) #NEWLINE# dataset = DenseDesignMatrix ( X = X ) #NEWLINE# model = SoftmaxModel ( 1 ) #NEWLINE# learning_rate = 0.001 #NEWLINE# cost = DummyCost ( ) #NEWLINE# algorithm = SGD ( learning_rate , cost , batch_size = 1 , monitoring_batches = 1 , monitoring_dataset = dataset , termination_criterion = EpochCounter ( max_epochs = 1 ) , update_callbacks = None , set_batch_size = False ) #NEWLINE# train = Train ( dataset , rng , algorithm , save_path = None , save_freq = 0 , extensions = None ) #NEWLINE# train . main_loop ( )