def make_configs(self):
configurator = Configurator('grid')
configurator.fixed('cuda', True)
configurator.grid('network.type', ['VAE', 'ConvVAE'])
configurator.fixed('network.z_dim', 8)
configurator.fixed('train.num_epoch', 100)
configurator.fixed('train.batch_size', 128)
configurator.fixed('eval.batch_size', 128)
configurator.fixed('log.interval', 100)
configurator.fixed('log.dir', 'logs')
list_config = configurator.make_configs()
return list_config
def make_configs(self):
configurator = Configurator('grid')
configurator.fixed('log.dir', 'some path')
configurator.grid('network.lr', [0.1, 0.01, 0.05])
configurator.grid('network.layers', [16, 32])
configurator.grid('env.id', ['CartPole-v1', 'Ant-v2', 'HalfCheetah-v2'])
configs = configurator.make_configs()
return configs
def test_configurator():
# Construction invalidity check
with pytest.raises(AssertionError):
Configurator(search_mode='n')
with pytest.raises(AssertionError):
Configurator(search_mode='random', num_sample=None)
# Create a configurator
# Grid search
configurator = Configurator(search_mode='grid')
assert len(configurator.items) == 0
with pytest.raises(AssertionError):
configurator.fixed('seeds', [1, 2, 3])
configurator.fixed('log.dir', 'some path')
assert len(configurator.items) == 1
assert isinstance(configurator.items['log.dir'], list)
assert configurator.items['log.dir'][0] == 'some path'
with pytest.raises(AssertionError):
configurator.fixed('log.dir', 'second')
with pytest.raises(AssertionError):
configurator.grid('log.T', 'must be list, not string')
configurator.grid('network.lr', [1e-2, 5e-3, 1e-4, 5e-4])
configurator.grid('network.layers', [1, 2, 3])
configurator.grid('env.id', ['CartPole-v1', 'Ant-v2'])
configs = configurator.make_configs()
assert len(configs) == 24
# order-preserving check
assert all([list(c.keys()) == ['ID', 'log.dir', 'network.lr', 'network.layers', 'env.id'] for c in configs])
assert all([c['log.dir'] == 'some path' for c in configs])
assert all([c['network.lr'] in [1e-2, 5e-3, 1e-4, 5e-4] for c in configs])
assert all([c['network.layers'] in [1, 2, 3] for c in configs])
assert all([c['env.id'] in ['CartPole-v1', 'Ant-v2'] for c in configs])
# Grid search does not allow methods for random search
with pytest.raises(AssertionError):
configurator.categorical('one', [1, 2])
with pytest.raises(AssertionError):
configurator.uniform('two', 1, 3)
with pytest.raises(AssertionError):
configurator.discrete_uniform('three', 5, 10)
with pytest.raises(AssertionError):
configurator.log_uniform('four', 0.0001, 0.1)
Configurator.print_config(configs[20])
config_dataframe = Configurator.to_dataframe(configs)
config_dataframe = Configurator.dataframe_subset(config_dataframe, 'network.lr', [0.01, 0.005])
config_dataframe = Configurator.dataframe_groupview(config_dataframe, ['env.id', 'network.lr'])
del configurator
del configs
del config_dataframe
# Random search
configurator = Configurator('random', num_sample=20)
assert len(configurator.items) == 0
with pytest.raises(AssertionError):
configurator.fixed('seeds', [1, 2, 3])
with pytest.raises(AssertionError):
configurator.categorical('seeds', [1, 2])
with pytest.raises(AssertionError):
configurator.uniform('seeds', 1, 3)
with pytest.raises(AssertionError):
configurator.discrete_uniform('seeds', 5, 10)
with pytest.raises(AssertionError):
configurator.log_uniform('seeds', 0.0001, 0.1)
with pytest.raises(AssertionError):
configurator.grid('network.layers', [1, 2, 3])
configurator.fixed('log.dir', 'some path')
assert len(configurator.items) == 1
assert isinstance(configurator.items['log.dir'], typing.Generator)
assert next(configurator.items['log.dir']) == 'some path'
with pytest.raises(AssertionError):
configurator.fixed('log.dir', 'second')
configurator.categorical('network.layers', [1, 2, 3])
with pytest.raises(AssertionError):
configurator.categorical('network.layers2', 12) # must be list
assert isinstance(configurator.items['network.layers'], typing.Generator)
configurator.uniform('entropy_coef', 0.1, 2.0)
configurator.discrete_uniform('train.N', 1, 100)
configurator.log_uniform('network.lr', 1e-7, 1e-1)
assert len(configurator.items) == 5
configs = configurator.make_configs()
assert len(configs[0]) == 1+5
assert len(configs) == 20
# order-preserving check
l = ['ID', 'log.dir', 'network.layers', 'entropy_coef', 'train.N', 'network.lr']
assert all([list(c.keys()) == l for c in configs])
assert all([c['log.dir'] == 'some path' for c in configs])
assert all([c['network.layers'] in [1, 2, 3] for c in configs])
assert all([c['entropy_coef'] >= 0.1 and c['entropy_coef'] <= 2.0 for c in configs])
assert all([isinstance(c['train.N'], int) for c in configs])
assert all([c['train.N'] >= 1 and c['train.N'] <= 100 for c in configs])
assert all([isinstance(c['network.lr'], float) for c in configs])
assert all([c['network.lr'] >= 1e-7 and c['network.lr'] <= 1e-1 for c in configs])
Configurator.print_config(configs[11])
config_dataframe = Configurator.to_dataframe(configs)
config_dataframe = Configurator.dataframe_subset(config_dataframe, 'network.layers', [1, 2])
config_dataframe = Configurator.dataframe_groupview(config_dataframe, ['network.layers', 'log.dir'])
config_dataframe