Predictor summaries are not refreshed after refitting

[pieths]

If a predictor is re-fit after retrieving a summary then the next time a summary is requested, it will return the old cached value. See the following unit tests for more details. Note, these currently fail because in both cases summary1 is equal to summary2.

def test_pipeline_summary_is_refreshed_after_refitting(self):
    predictor = OrdinaryLeastSquaresRegressor(normalize='No', l2_weight=0)
    pipeline = Pipeline([predictor])

    pipeline.fit([0,1,2,3], [1,2,3,4])
    summary1 = pipeline.summary()

    pipeline.fit([0,1,2,3], [2,5,8,11])
    summary2 = pipeline.summary()

    self.assertFalse(summary1.equals(summary2))

def test_predictor_summary_is_refreshed_after_refitting(self):
    predictor = OrdinaryLeastSquaresRegressor(normalize='No', l2_weight=0)

    predictor.fit([0,1,2,3], [1,2,3,4])
    summary1 = predictor.summary()

    predictor.fit([0,1,2,3], [2,5,8,11])
    summary2 = predictor.summary()

    self.assertFalse(summary1.equals(summary2))

Is running fit(...) more than once on a single instance of a predictor a supported scenario?