def test_convolutional_network():
 skip.skip_if_no_data()
 yaml_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
 save_path = os.path.dirname(os.path.realpath(__file__))
 save_path.replace('\\', '\\\\')
 yaml = open('{0}/conv.yaml'.format(yaml_file_path), 'r').read()
 hyper_params = {'train_stop': 50, 'valid_stop': 50050, 'test_stop': 50, 'batch_size': 50, 'output_channels_h2': 4, 'output_channels_h3': 4, 'max_epochs': 1, 'save_path': save_path}
 yaml = (yaml % hyper_params)
 train = yaml_parse.load(yaml)
 train.main_loop()
 try:
  os.remove('{}/convolutional_network_best.pkl'.format(save_path))
 except OSError:
  pass

def test_convolutional_network ( ) : skip . skip_if_no_data ( ) yaml_file_path = os . path . abspath ( os . path . join ( os . path . dirname ( __file__ ) , '..' ) ) save_path = os . path . dirname ( os . path . realpath ( __file__ ) ) save_path . replace ( '\\' , '\\\\' ) yaml = open ( '{0}/conv.yaml' . format ( yaml_file_path ) , 'r' ) . read ( ) hyper_params = { 'train_stop' : 50 , 'valid_stop' : 50050 , 'test_stop' : 50 , 'batch_size' : 50 , 'output_channels_h2' : 4 , 'output_channels_h3' : 4 , 'max_epochs' : 1 , 'save_path' : save_path } yaml = ( yaml % hyper_params ) train = yaml_parse . load ( yaml ) train . main_loop ( ) try : os . remove ( '{}/convolutional_network_best.pkl' . format ( save_path ) ) except OSError : pass
test smaller version of convolutional_network .