def get_empty_export_walkers(self) -> ExportedWalkers:
"""
Return a :class:`ExportedWalkers` with no walkers inside.
Used to initialize the algorithm.
"""
return ExportedWalkers(0)
def test_cross_fai_iteration(self, export_swarm):
walkers = ExportedWalkers(export_swarm.n_import)
local_ix, import_ix = export_swarm._get_merge_indexes(walkers)
compas_ix, will_clone = export_swarm._cross_fai_iteration(
local_ix=local_ix, import_ix=import_ix, walkers=walkers
)
assert len(compas_ix) == export_swarm.n_import
def reset(self, *args, **kwargs):
self.swarm.reset(*args, **kwargs)
self.param_server.best.update(
states=self.swarm.walkers.states.best_state,
id_walkers=self.swarm.walkers.states.best_id,
rewards=self.swarm.walkers.states.best_reward,
observs=self.swarm.walkers.states.best_obs,
)
self._exchange_next = ExportedWalkers(0)
def __init__(self,
swarm,
max_len: int = 20,
add_global_best: bool = True,
*args,
**kwargs):
super(ExportDummy, self).__init__(swarm=swarm, *args, **kwargs)
self.param_server = ParamServer(max_len=max_len,
add_global_best=add_global_best,
minimize=self.swarm.walkers.minimize)
self._exchange_next = ExportedWalkers(0)
def test_clone_to_imported(self, export_swarm):
walkers = ExportedWalkers(3)
walkers.rewards = tensor([999, 777, 333], dtype=dtype.float)
walkers.states = tensor([999, 777, 333], dtype=dtype.float)
walkers.id_walkers = tensor([999, 777, 333], dtype=dtype.float)
walkers.observs = tensor(
[[999, 999, 999, 999], [777, 777, 777, 777], [333, 333, 333, 333]],
dtype=dtype.float)
compas_ix = tensor([0, 1])
will_clone = tensor([True, False])
local_ix = tensor([0, 1])
import_ix = tensor([0, 1])
export_swarm._clone_to_imported(
compas_ix=compas_ix,
will_clone=will_clone,
local_ix=local_ix,
import_ix=import_ix,
walkers=walkers,
)
assert export_swarm.walkers.states.cum_rewards[0] == 999.0
assert export_swarm.walkers.env_states.states[0] == 999.0
assert (export_swarm.walkers.env_states.observs[0] == judo.ones(4) *
999).all()
def test_clone_to_imported(self, export_swarm):
walkers = ExportedWalkers(3)
walkers.rewards = numpy.array([999, 777, 333])
walkers.states = numpy.array([999, 777, 333])
walkers.id_walkers = numpy.array([999, 777, 333])
walkers.observs = numpy.array([[999, 999, 999, 999],
[777, 777, 777, 777],
[333, 333, 333, 333]])
compas_ix = numpy.array([0, 1])
will_clone = numpy.array([True, False])
local_ix = numpy.array([0, 1])
import_ix = numpy.array([0, 1])
export_swarm._clone_to_imported(
compas_ix=compas_ix,
will_clone=will_clone,
local_ix=local_ix,
import_ix=import_ix,
walkers=walkers,
)
assert export_swarm.walkers.states.cum_rewards[0] == 999
assert export_swarm.walkers.states.id_walkers[0] == 999
assert export_swarm.walkers.env_states.states[0] == 999
assert (export_swarm.walkers.env_states.observs[0] == numpy.ones(4) *
999).all()
def test_import_best(self, export_swarm):
walkers = ExportedWalkers(2)
walkers.rewards = numpy.array([999, 2])
walkers.states = numpy.array([0, 1])
walkers.id_walkers = numpy.array([10, 11])
walkers.observs = numpy.array([[0, 0, 0, 0], [2, 3, 1, 2]])
export_swarm.import_best(walkers)
assert export_swarm.best_reward == 999
assert export_swarm.walkers.states.best_state == walkers.states[0]
assert (export_swarm.walkers.states.best_obs == walkers.observs[0]).all()
assert export_swarm.walkers.states.best_id == walkers.id_walkers[0]
def test_import_best(self, export_swarm):
walkers = ExportedWalkers(2)
walkers.rewards = tensor([999.0, 2.0])
walkers.states = tensor([0.0, 1.0])
walkers.id_walkers = tensor([10.0, 11.0])
walkers.observs = tensor([[0, 0, 0, 0], [2, 3, 1, 2]],
dtype=dtype.float)
export_swarm.import_best(walkers)
assert export_swarm.best_reward == 999
assert export_swarm.walkers.states.best_state == walkers.states[0]
assert (
export_swarm.walkers.states.best_obs == walkers.observs[0]).all()
assert export_swarm.walkers.states.best_id == walkers.id_walkers[0]
def test_imported_best_is_better(self, export_swarm):
export_swarm.reset()
export_swarm.run_step()
walkers = ExportedWalkers(1)
walkers.rewards = tensor([1]) * numpy.inf
new_is_better = export_swarm._imported_best_is_better(walkers)
assert new_is_better, export_swarm.best_reward
walkers = ExportedWalkers(1)
export_swarm.walkers.minimize = True
walkers.rewards = tensor([1]) * numpy.NINF
new_is_better = export_swarm._imported_best_is_better(walkers)
assert new_is_better, export_swarm.best_reward
export_swarm.walkers.minimize = False
def test_imported_best_is_better(self, export_swarm):
export_swarm.reset()
export_swarm.run_step()
walkers = ExportedWalkers(1)
walkers.rewards = numpy.array([numpy.inf])
new_is_better = export_swarm._imported_best_is_better(walkers)
assert new_is_better, export_swarm.best_reward
walkers = ExportedWalkers(1)
export_swarm.walkers.minimize = True
walkers.rewards = numpy.array([-numpy.inf])
new_is_better = export_swarm._imported_best_is_better(walkers)
assert new_is_better, export_swarm.best_reward
export_swarm.walkers.minimize = False
def test_run_exchange_step(self, export_swarm):
export_swarm.reset()
walkers_0 = ExportedWalkers(0)
exported = export_swarm.run_exchange_step(walkers_0)
assert len(exported) == export_swarm.n_export
walkers = ExportedWalkers(3)
walkers.rewards = tensor([999, 777, 333], dtype=dtype.float)
walkers.states = tensor(
[[999, 999, 999, 999], [777, 777, 777, 777], [333, 333, 333, 333]],
dtype=dtype.float)
walkers.id_walkers = tensor([999, 777, 333], dtype=dtype.float)
walkers.observs = tensor(
[[999, 999, 999, 999], [777, 777, 777, 777], [333, 333, 333, 333]],
dtype=dtype.float)
export_swarm.reset()
exported = export_swarm.run_exchange_step(walkers)
assert len(exported) == export_swarm.n_export
assert export_swarm.best_reward == 999.0
def test_run_exchange_step(self, export_swarm):
export_swarm.reset()
walkers_0 = ExportedWalkers(0)
exported = export_swarm.run_exchange_step(walkers_0)
assert len(exported) == export_swarm.n_export
walkers = ExportedWalkers(3)
walkers.rewards = numpy.array([999, 777, 333])
walkers.states = numpy.array([[999, 999, 999,
999], [777, 777, 777, 777],
[333, 333, 333, 333]])
walkers.id_walkers = numpy.array([999, 777, 333])
walkers.observs = numpy.array([[999, 999, 999, 999],
[777, 777, 777, 777],
[333, 333, 333, 333]])
export_swarm.reset()
exported = export_swarm.run_exchange_step(walkers)
assert len(exported) == export_swarm.n_export
assert export_swarm.best_reward == 999
def test_get_merge_indexes(self, export_swarm):
walkers = ExportedWalkers(2)
local_ix, import_ix = export_swarm._get_merge_indexes(walkers)
assert len(local_ix) == len(import_ix)
assert len(local_ix) == export_swarm.n_import