def test_validation(self):
# model
cnn_model = CharacterLevelCnnModel(label_mapping=self.label_mapping)
cnn_model._construct_model()
# data for model
cv_data_gen = [[
np.array([['test']]), # x_data
np.zeros((1, 3400, max(self.label_mapping.values()) + 1))
]
# y_data
]
# validation
cnn_model._validate_training(cv_data_gen,
batch_size_test=32,
verbose_log=True,
verbose_keras=False)
def test_validation_evaluate_and_classification_report(self, *mocks):
cnn_model = CharacterLevelCnnModel(self.label_mapping)
cnn_model._construct_model()
# validation data
val_gen = [[
np.array([['123 fake st']]),
np.zeros((1, 3400, max(self.label_mapping.values()) + 1))
]]
val_gen[0][1][:, :11, self.label_mapping['ADDRESS']] = 1
f1, f1_report = cnn_model._validate_training(val_gen, 32, True, True)
self.assertIsNotNone(f1)
self.assertIsNotNone(f1_report)
self.assertEqual(11, f1_report['ADDRESS']['support'])
