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))