def test_Linear():
linear = hp_module.Linear(
'linear', min_value=0.5, max_value=9.5, resolution=0.1, default=9.)
linear = hp_module.Linear.from_config(linear.get_config())
assert linear.default == 9.
assert 0.5 <= linear.random_sample() < 9.5
assert isinstance(linear.random_sample(), float)
assert linear.random_sample(123) == linear.random_sample(123)
# No default
linear = hp_module.Linear(
'linear', min_value=0.5, max_value=9.5, resolution=0.1)
assert linear.default == 0.5
def test_bayesian_oracle_with_zero_y(tmp_dir):
hp_list = [hp_module.Choice('a', [1, 2], default=1),
hp_module.Range('b', 3, 10, default=3),
hp_module.Linear('c', 0, 1, 0.1, default=0),
hp_module.Fixed('d', 7),
hp_module.Choice('e', [9, 0], default=9)]
oracle = bo_module.BayesianOptimizationOracle()
for i in range(100):
oracle.populate_space(str(i), hp_list)
oracle.result(str(i), 0)
def test_save_before_result(tmp_dir):
hp_list = [
hp_module.Choice('a', [1, 2], default=1),
hp_module.Range('b', 3, 10, default=3),
hp_module.Linear('c', 0, 1, 0.1, default=0),
hp_module.Fixed('d', 7),
hp_module.Choice('e', [9, 0], default=9)
]
oracle = bo_module.BayesianOptimizationOracle()
oracle.populate_space(str(1), hp_list)
oracle.save(os.path.join(tmp_dir, 'temp_oracle'))
oracle.result(str(1), 0)
def test_bayesian_dynamic_space(tmp_dir):
hp_list = [hp_module.Choice('a', [1, 2], default=1)]
oracle = bo_module.BayesianOptimizationOracle()
for i in range(10):
oracle.populate_space(str(i), hp_list)
oracle.result(str(i), i)
hp_list.append(hp_module.Range('b', 3, 10, default=3))
assert 'b' in oracle.populate_space('1_0', hp_list)['values']
hp_list.append(hp_module.Linear('c', 0, 1, 0.1, default=0))
assert 'c' in oracle.populate_space('1_1', hp_list)['values']
hp_list.append(hp_module.Fixed('d', 7))
assert 'd' in oracle.populate_space('1_2', hp_list)['values']
hp_list.append(hp_module.Choice('e', [9, 0], default=9))
assert 'e' in oracle.populate_space('1_3', hp_list)['values']