def test_validate(self):
''' test validation '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality',
'instances' : self.train_insts,
'test_instances': self.test_insts})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Test basic usage
rh = validator.validate(config_mode='def', instance_mode='test',
repetitions=3)
self.assertEqual(len(rh.get_all_configs()), 1)
self.assertEqual(len(rh.get_runs_for_config(rh.get_all_configs()[0])), 9)
rh = validator.validate(config_mode='inc', instance_mode='train+test')
self.assertEqual(len(rh.get_all_configs()), 1)
self.assertEqual(len(rh.get_runs_for_config(rh.get_all_configs()[0])), 6)
rh = validator.validate(config_mode='wallclock_time', instance_mode='train')
self.assertEqual(len(rh.get_all_configs()), 7)
self.assertEqual(sum([len(rh.get_runs_for_config(c)) for c in
rh.get_all_configs()]), 21)
# Test with backend multiprocessing
rh = validator.validate(config_mode='def', instance_mode='test',
repetitions=3, backend='multiprocessing')
self.assertEqual(len(rh.get_all_configs()), 1)
self.assertEqual(len(rh.get_runs_for_config(rh.get_all_configs()[0])), 9)
def test_passed_runhistory(self):
''' test if passed runhistory is in resulting runhistory '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality',
'instances' : self.train_insts,
'test_instances': self.test_insts})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Add a few runs and check, if they are correctly processed
old_configs = [entry["incumbent"] for entry in self.trajectory]
old_rh = RunHistory(average_cost)
seeds = [127 for i in range(int(len(old_configs)/2))]
seeds[-1] = 126 # Test instance_seed-structure in validation
for config in old_configs[:int(len(old_configs)/2)]:
old_rh.add(config, 1, 1, StatusType.SUCCESS, instance_id='0',
seed=seeds[old_configs.index(config)])
configs = validator._get_configs('all')
insts = validator._get_instances('train')
runs_w_rh = validator.get_runs(configs, insts, repetitions=2,
runhistory=old_rh)
runs_wo_rh = validator.get_runs(configs, insts, repetitions=2)
self.assertEqual(len(runs_w_rh[0]), len(runs_wo_rh[0]) - 4)
self.assertEqual(len(runs_w_rh[1].data), 4)
self.assertEqual(len(runs_wo_rh[1].data), 0)
def test_inst_no_feat(self):
''' test if scenarios are treated correctly if no features are
specified.'''
scen = Scenario(self.scen_fn,
cmd_options={
'run_obj': 'quality',
'train_insts': self.train_insts,
'test_insts': self.test_insts
})
self.assertTrue(scen.feature_array is None)
self.assertEqual(len(scen.feature_dict), 0)
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Add a few runs and check, if they are correctly processed
old_configs = [entry["incumbent"] for entry in self.trajectory]
old_rh = RunHistory()
for config in old_configs[:int(len(old_configs) / 2)]:
old_rh.add(config,
1,
1,
StatusType.SUCCESS,
instance_id='0',
seed=127)
rh = validator.validate_epm('all', 'train+test', 1, old_rh)
self.assertEqual(len(old_rh.get_all_configs()), 4)
self.assertEqual(len(rh.get_all_configs()), 10)
def test_passed_runhistory_deterministic(self):
''' test if passed runhistory is in resulting runhistory '''
scen = Scenario(self.scen_fn,
cmd_options={
'run_obj': 'quality',
'train_insts': self.train_insts,
'deterministic': True
})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Add a few runs and check, if they are correctly processed
old_configs = [entry["incumbent"] for entry in self.trajectory]
old_rh = RunHistory()
for config in old_configs[:int(len(old_configs) / 2)]:
old_rh.add(config, 1, 1, StatusType.SUCCESS, instance_id='0')
configs = validator._get_configs('all')
insts = validator._get_instances('train')
runs_w_rh = validator._get_runs(configs,
insts,
repetitions=2,
runhistory=old_rh)
runs_wo_rh = validator._get_runs(configs, insts, repetitions=2)
self.assertEqual(len(runs_w_rh[0]), len(runs_wo_rh[0]) - 4)
self.assertEqual(len(runs_w_rh[1].data), 4)
self.assertEqual(len(runs_wo_rh[1].data), 0)
def test_validate_deterministic(self):
''' deterministic ta '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality',
'instances' : self.train_insts,
'deterministic': True})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
rh = validator.validate(config_mode='def+inc',
instance_mode='train', repetitions=3)
self.assertEqual(len(rh.get_all_configs()), 2)
self.assertEqual(sum([len(rh.get_runs_for_config(c)) for c in
rh.get_all_configs()]), 6)
def test_get_runs(self):
''' test if the runs are generated as expected '''
scen = Scenario(self.scen_fn,
cmd_options={'run_obj': 'quality',
'train_insts': self.train_insts,
'test_insts': self.test_insts})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Get multiple configs
self.maxDiff = None
expected = [_Run(config='config1', inst='3', seed=1608637542, inst_specs='three'),
_Run(config='config2', inst='3', seed=1608637542, inst_specs='three'),
_Run(config='config1', inst='3', seed=1273642419, inst_specs='three'),
_Run(config='config2', inst='3', seed=1273642419, inst_specs='three'),
_Run(config='config1', inst='4', seed=1935803228, inst_specs='four'),
_Run(config='config2', inst='4', seed=1935803228, inst_specs='four'),
_Run(config='config1', inst='4', seed=787846414, inst_specs='four'),
_Run(config='config2', inst='4', seed=787846414, inst_specs='four'),
_Run(config='config1', inst='5', seed=996406378, inst_specs='five'),
_Run(config='config2', inst='5', seed=996406378, inst_specs='five'),
_Run(config='config1', inst='5', seed=1201263687, inst_specs='five'),
_Run(config='config2', inst='5', seed=1201263687, inst_specs='five')]
runs = validator._get_runs(['config1', 'config2'], scen.test_insts, repetitions=2)
self.assertEqual(runs[0], expected)
# Only train
expected = [_Run(config='config1', inst='0', seed=423734972, inst_specs='null'),
_Run(config='config1', inst='0', seed=415968276, inst_specs='null'),
_Run(config='config1', inst='1', seed=670094950, inst_specs='one'),
_Run(config='config1', inst='1', seed=1914837113, inst_specs='one'),
_Run(config='config1', inst='2', seed=669991378, inst_specs='two'),
_Run(config='config1', inst='2', seed=429389014, inst_specs='two')]
runs = validator._get_runs(['config1'], scen.train_insts, repetitions=2)
self.assertEqual(runs[0], expected)
# Test and train
expected = [_Run(config='config1', inst='0', seed=249467210, inst_specs='null'),
_Run(config='config1', inst='1', seed=1972458954, inst_specs='one'),
_Run(config='config1', inst='2', seed=1572714583, inst_specs='two'),
_Run(config='config1', inst='3', seed=1433267572, inst_specs='three'),
_Run(config='config1', inst='4', seed=434285667, inst_specs='four'),
_Run(config='config1', inst='5', seed=613608295, inst_specs='five')]
insts = self.train_insts
insts.extend(self.test_insts)
runs = validator._get_runs(['config1'], insts, repetitions=1)
self.assertEqual(runs[0], expected)
def test_get_runs(self):
''' test if the runs are generated as expected '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality',
'instances' : self.train_insts,
'test_instances': self.test_insts})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Get multiple configs
expected = [Run(inst_specs='three', seed=1608637542, inst='3', config='config1'),
Run(inst_specs='three', seed=1608637542, inst='3', config='config2'),
Run(inst_specs='three', seed=1935803228, inst='3', config='config1'),
Run(inst_specs='three', seed=1935803228, inst='3', config='config2'),
Run(inst_specs='four', seed=996406378, inst='4', config='config1'),
Run(inst_specs='four', seed=996406378, inst='4', config='config2'),
Run(inst_specs='four', seed=423734972, inst='4', config='config1'),
Run(inst_specs='four', seed=423734972, inst='4', config='config2'),
Run(inst_specs='five', seed=670094950, inst='5', config='config1'),
Run(inst_specs='five', seed=670094950, inst='5', config='config2'),
Run(inst_specs='five', seed=669991378, inst='5', config='config1'),
Run(inst_specs='five', seed=669991378, inst='5', config='config2')]
runs = validator.get_runs(['config1', 'config2'], scen.test_insts, repetitions=2)
self.assertEqual(runs[0], expected)
# Only train
expected = [Run(inst_specs='null', seed=249467210, inst='0', config='config1'),
Run(inst_specs='null', seed=1572714583, inst='0', config='config1'),
Run(inst_specs='one', seed=434285667, inst='1', config='config1'),
Run(inst_specs='one', seed=893664919, inst='1', config='config1'),
Run(inst_specs='two', seed=88409749, inst='2', config='config1'),
Run(inst_specs='two', seed=2018247425, inst='2', config='config1')]
runs = validator.get_runs(['config1'], scen.train_insts, repetitions=2)
self.assertEqual(runs[0], expected)
# Test and train
expected = [Run(inst='0', seed=1427830251, config='config1', inst_specs='null' ),
Run(inst='1', seed=911989541, config='config1', inst_specs='one' ),
Run(inst='2', seed=780932287, config='config1', inst_specs='two' ),
Run(inst='3', seed=787716372, config='config1', inst_specs='three'),
Run(inst='4', seed=1306710475, config='config1', inst_specs='four' ),
Run(inst='5', seed=106328085, config='config1', inst_specs='five' )]
insts = self.train_insts
insts.extend(self.test_insts)
runs = validator.get_runs(['config1'], insts, repetitions=1)
self.assertEqual(runs[0], expected)
def test_validate_epm(self):
''' test using epm to validate '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality',
'instances' : self.train_insts,
'test_instances': self.test_insts,
'features': self.feature_dict})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Add a few runs and check, if they are correctly processed
old_configs = [entry["incumbent"] for entry in self.trajectory]
old_rh = RunHistory(average_cost)
for config in old_configs[:int(len(old_configs)/2)]:
old_rh.add(config, 1, 1, StatusType.SUCCESS, instance_id='0',
seed=127)
validator.validate_epm('all', 'train', 1, old_rh)
def test_passed_runhistory_no_insts(self):
''' test passed runhistory, without instances '''
scen = Scenario(self.scen_fn,
cmd_args={'run_obj':'quality'})
scen.instance_specific = self.inst_specs
validator = Validator(scen, self.trajectory, self.rng)
# Add a few runs and check, if they are correctly processed
old_configs = [entry["incumbent"] for entry in self.trajectory]
old_rh = RunHistory(average_cost)
for config in old_configs[:int(len(old_configs)/2)]:
old_rh.add(config, 1, 1, StatusType.SUCCESS, seed=127)
configs = validator._get_configs('all')
insts = validator._get_instances('train')
runs_w_rh = validator.get_runs(configs, insts, repetitions=2,
runhistory=old_rh)
runs_wo_rh = validator.get_runs(configs, insts, repetitions=2)
self.assertEqual(len(runs_w_rh[0]), len(runs_wo_rh[0]) - 4)
self.assertEqual(len(runs_w_rh[1].data), 4)
self.assertEqual(len(runs_wo_rh[1].data), 0)
