def __init__(self, input_features, output_features, training_features=None):
        """
        Create a set of pipeline models given a set of model specs.  The final
        output model must be a regression model.

        Parameters
        ----------

        input_features: [list of 2-tuples]
            Name(s) of the input features, given as a list of `('name', datatype)`
            tuples.  The datatypes entry can be any of the data types defined in the
            :py:mod:`models.datatypes` module.

        output_features: [list of features]
            Name(s) of the output features, given as a list of
            `('name',datatype)` tuples.  The datatypes entry can be any of the
            data types defined in the :py:mod:`models.datatypes` module.  All features
            must be either defined in the inputs or be produced by one of the
            contained models.

        """
        spec = _proto.Model_pb2.Model()
        spec.specificationVersion = _SPECIFICATION_VERSION

        # Access this to declare it as a pipeline
        spec.pipelineRegressor
        spec = set_regressor_interface_params(
            spec, input_features, output_features, training_features
        )

        # Save as a member variable
        self.spec = spec

        Create a set of pipeline models given a set of model specs.  The final
        output model must be a regression model.

        Parameters
        ----------

        input_features: [list of 2-tuples]
            Name(s) of the input features, given as a list of `('name', datatype)`
            tuples.  The datatypes entry can be any of the data types defined in the
            :py:mod:`models.datatypes` module.

        output_features: [list of features]
            Name(s) of the output features, given as a list of
            `('name',datatype)` tuples.  The datatypes entry can be any of the
            data types defined in the :py:mod:`models.datatypes` module.  All features
            must be either defined in the inputs or be produced by one of the
            contained models.

        
coremltools/models/pipeline.py