def testPartiallySpecifiedTestSet(self): """Check that partially specified test set raises an error.""" num_counties = 3 test_size = 5 dataset = _test_dataset( train_size=20, test_size=test_size, num_counties=num_counties) del dataset['test_county'] with self.assertRaisesRegex(ValueError, 'all be specified'): radon_contextual_effects.RadonContextualEffects(**dataset)
def testCreateDataset(self, test_size): """Checks that creating a dataset works.""" train_size = 30 num_counties = 3 model = radon_contextual_effects.RadonContextualEffects( **_test_dataset(train_size, test_size, num_counties)) model2 = radon_contextual_effects.RadonContextualEffects( **model._sample_dataset(tfp_test_util.test_seed())) self.validate_log_prob_and_transforms( model2, sample_transformation_shapes=dict( identity={ 'county_effect_mean': [], 'county_effect_scale': [], 'county_effect': [num_counties], 'weight': [3], 'log_radon_scale': [] }, test_nll=[], per_example_test_nll=[test_size]))
def testBasic(self, test_size): """Checks that unconstrained parameters yield finite joint densities.""" num_counties = 3 train_size = 20 model = radon_contextual_effects.RadonContextualEffects( **_test_dataset(train_size, test_size, num_counties)) self.validate_log_prob_and_transforms( model, sample_transformation_shapes=dict( identity={ 'county_effect_mean': [], 'county_effect_scale': [], 'county_effect': [num_counties], 'weight': [3], 'log_radon_scale': [] }, test_nll=[], per_example_test_nll=[test_size]))
def testInvalidPriorScaleRaises(self): with self.assertRaisesRegex(ValueError, 'not a valid value'): radon_contextual_effects.RadonContextualEffects( prior_scale='invalid_input', **_test_dataset(train_size=20))