def test_it_reassings_properties(self, Services: MagicMock): PM = PropertiesManager() PM.classifier = 'is_cancer' Services.getService.side_effect = lambda Key, __: PM if Key == 'properties' else MagicMock( ) Pipe = Pipeline.Factory.getInstance() Pipe.pipe(MagicMock(), MagicMock(), MagicMock(), MagicMock(), {'classifier': 'doid'}) self.assertEqual('doid', PM.classifier)
def test_it_returns_normalized_multi_classified_data( self ): Model = MagicMock( spec = Sequential ) ToPredict = MagicMock() PM = PropertiesManager() PM[ "training" ][ "epochs" ] = 1 PM[ "training" ][ "batch_size" ] = 2 PM[ "training" ][ "workers" ] = 1 PM.classifier = 'doid' X = InputData( MagicMock(), MagicMock(), MagicMock() ) Y = InputData( NP.zeros( ( 4, 4 ) ), MagicMock(), MagicMock() ) Model.predict.return_value = NP.array( [ [ -0.00716622, 23 ], [ -23, -98.98867947 ], [ -42, 12 ] ] ) self.__Loader.return_value = Model FFN = ModelBaseSpec.StubbedFFN( PM, Model ) FFN.train( X, Y ) arrayEqual( FFN.predict( ToPredict ), NP.array( [ 1, 0, 1 ] ) )