def test_bad_hyperparams(self):
sealed = dlc.HyperParams(
(dlc.ParamDesc('model_name', 'Name of Model', None, 'im2latex'),
dlc.ParamDesc('layer_type', 'Type of layers to be created',
['CNN', 'MLP', 'LSTM', 'RNN']),
dlc.ParamDesc('num_layers', 'Number of layers to create',
list(range(1, 11))),
dlc.ParamDesc('unset', 'Unset property', list(range(1, 11))),
dlc.ParamDesc('none', 'None property', (None, ), None))).seal()
frozen = dlc.HyperParams(sealed, {'num_layers': 10}).freeze()
self.assertRaises(KeyError, setattr, sealed, "x", "MyNeuralNetwork")
self.assertRaises(KeyError, self.dictSet, sealed, "x",
"MyNeuralNetwork")
self.assertRaises(KeyError, setattr, frozen, "name", "MyNeuralNetwork")
self.assertRaises(KeyError, self.dictSet, frozen, "name",
"MyNeuralNetwork")
self.assertRaises(ValueError, setattr, sealed, "layer_type", "SVM")
self.assertRaises(ValueError, self.dictSet, sealed, "layer_type",
"SVM")
self.assertRaises(KeyError, getattr, sealed, "x")
self.assertRaises(KeyError, self.dictGet, sealed, "x")
self.assertRaises(KeyError, getattr, frozen, 'layer_type')
self.assertRaises(KeyError, getattr, sealed, 'layer_type')
def test_good_params(self):
sealed = dlc.Params(
(dlc.ParamDesc('model_name', 'Name of Model', None, 'im2latex'),
dlc.ParamDesc('layer_type', 'Type of layers to be created',
['CNN', 'MLP', 'LSTM', 'RNN'], 'LSTM'),
dlc.ParamDesc('num_layers', 'Number of layers to create',
range(1, 11)),
dlc.ParamDesc('unset', 'Unset property', range(1, 11)))).seal()
frozen = dlc.Params(sealed, {'num_layers': 10}).freeze()
sealed.layer_type = 'MLP'
self.assertEqual(sealed.layer_type, 'MLP')
self.assertEqual(sealed['layer_type'], 'MLP')
sealed['layer_type'] = 'CNN'
self.assertEqual(sealed.layer_type, 'CNN')
self.assertEqual(sealed['layer_type'], 'CNN')
self.assertEqual(frozen.model_name, 'im2latex')
self.assertEqual(frozen.layer_type, 'LSTM')
self.assertEqual(frozen['num_layers'], 10)
self.assertEqual(frozen.num_layers, 10)
def test_good_hyperparams(self):
sealed = dlc.HyperParams(
(dlc.ParamDesc('model_name', 'Name of Model', None, 'im2latex'),
dlc.ParamDesc('layer_type', 'Type of layers to be created',
['CNN', 'MLP', 'LSTM', 'RNN'], 'MLP'),
dlc.ParamDesc('num_layers', 'Number of layers to create',
list(range(1, 11))),
dlc.ParamDesc('unset', 'Unset property', list(range(1, 11))),
dlc.ParamDesc('none', 'None property', (None, ), None))).seal()
frozen = dlc.HyperParams(sealed, {'num_layers': 10}).freeze()
self.assertRaises(dlc.OneValError, setattr, sealed, "model_name",
"xyz")
self.assertRaises(dlc.OneValError, setattr, sealed, "layer_type",
"xyz")
self.assertEqual(sealed.layer_type, 'MLP')
self.assertEqual(sealed['layer_type'], 'MLP')
self.assertEqual(frozen.model_name, 'im2latex')
self.assertEqual(frozen['num_layers'], 10)
self.assertEqual(frozen.num_layers, 10)
self.assertEqual(frozen.none, None)
self.assertEqual(frozen['none'], None)
self.assertEqual(sealed.none, None)
self.assertEqual(sealed['none'], None)