def test_multi_normal_serialization_deserialization():
h1 = hp.MultiNormalContinuousHyperParameter('h1', 0.0, 1.0, sample_count=5)
config = h1.get_config()
assert 'name' in config
assert 'mean' in config
assert 'std' in config
assert 'sample_count' in config
mean, std = config['mean'], config['std']
assert mean == 0.0
assert std == 1.0
assert config['sample_count'] == 5
h2 = hp.MultiNormalContinuousHyperParameter.load_from_config(config)
config = h2.get_config()
assert 'name' in config
assert 'mean' in config
assert 'std' in config
assert 'sample_count' in config
mean, std = config['mean'], config['std']
assert mean == 0.0
assert std == 1.0
assert config['sample_count'] == 5
def test_continuous_multi_normal_encode_decode():
h1 = hp.MultiNormalContinuousHyperParameter('h1', 0.0, 1.0, sample_count=3)
sample = h1.sample()
encoded = h1.encode(sample)
assert encoded == sample
decoded = h1.decode(encoded)
assert decoded == sample
def test_continuous_multi_normal():
h1 = hp.MultiNormalContinuousHyperParameter('h1', 0.0, 1.0, sample_count=5)
assert h1.name == 'h1'
assert h1.num_choices == 0
assert h1.mean == 0.0
assert h1.std == 1.0
assert repr(h1)
assert h1.sample_count == 5
def test_continuous_normal_sample():
h1 = hp.MultiNormalContinuousHyperParameter('h1',
0.0,
1.0,
sample_count=1000)
sample = [h1.sample() for _ in range(10)]
mean = np.mean(sample)
std = np.std(sample)
assert np.allclose(mean, 0.0, atol=0.025)
assert np.allclose(std, 1.0, atol=0.025)
def test_continuous_multi_normal_no_values():
with pytest.raises(ValueError):
hp.MultiNormalContinuousHyperParameter(None, 0, 1)
with pytest.raises(ValueError):
hp.MultiNormalContinuousHyperParameter('h1', None, None)
