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 ] )
)
