def test_pipeline_regression_creation(self):
input_names = self.scikit_data.feature_names
output_name = 'target'
p_regressor = PipelineRegressor(input_names, 'target')
p_regressor.add_model(self.scikit_spec)
self.assertIsNotNone(p_regressor.spec)
self.assertEqual(
len(p_regressor.spec.pipelineRegressor.pipeline.models), 1)
# Test the model class of the linear regressor model
spec = p_regressor.spec.pipelineRegressor.pipeline.models[0]
self.assertIsNotNone(spec.description)
# Test the interface class
self.assertEqual(spec.description.predictedFeatureName, 'target')
# Test the inputs and outputs
self.assertEqual(len(spec.description.output), 1)
self.assertEqual(spec.description.output[0].name, 'target')
self.assertEqual(spec.description.output[0].type.WhichOneof('Type'),
'doubleType')
for input_type in spec.description.input:
self.assertEqual(input_type.type.WhichOneof('Type'), 'doubleType')
self.assertEqual(sorted(input_names),
sorted(map(lambda x: x.name, spec.description.input)))
def test_pipeline_regressor_make_updatable(self):
builder = self.create_base_builder()
builder.spec.isUpdatable = False
training_input = [("input", datatypes.Array(3)), ("target", "Double")]
# fails due to missing sub-models
p_regressor = PipelineRegressor(self.input_features, self.output_names,
training_input)
with self.assertRaises(ValueError):
p_regressor.make_updatable()
self.assertEqual(p_regressor.spec.isUpdatable, False)
# fails due to sub-model being not updatable
p_regressor.add_model(builder.spec)
with self.assertRaises(ValueError):
p_regressor.make_updatable()
self.assertEqual(p_regressor.spec.isUpdatable, False)
builder.spec.isUpdatable = True
p_regressor.add_model(builder.spec)
self.assertEqual(p_regressor.spec.isUpdatable, False)
p_regressor.make_updatable()
self.assertEqual(p_regressor.spec.isUpdatable, True)
self.assertEqual(p_regressor.spec.description.trainingInput[0].name,
"input")
self.assertEqual(
p_regressor.spec.description.trainingInput[0].type.WhichOneof(
"Type"),
"multiArrayType",
)
self.assertEqual(p_regressor.spec.description.trainingInput[1].name,
"target")
self.assertEqual(
p_regressor.spec.description.trainingInput[1].type.WhichOneof(
"Type"),
"doubleType",
)
# fails since once updatable does not allow adding new models
with self.assertRaises(ValueError):
p_regressor.add_model(builder.spec)
self.assertEqual(p_regressor.spec.isUpdatable, True)