def test_new_cells_with_same_representation_only_best_returned_on_sample(
self):
worse_cell = total_cell.Cell(
representation_info=self.TestRepresentationInfo(0),
prioritizing_info=self.TestPrioritizingInfo(compare_value=0))
better_cell = total_cell.Cell(
representation_info=self.TestRepresentationInfo(0),
prioritizing_info=self.TestPrioritizingInfo(compare_value=100))
self.archive.update(worse_cell)
self.archive.update(better_cell)
sample = self.archive.sample(batch_size=1)
self.assertEqual(next(sample), better_cell)
def test_sample_cells_returns_values_according_to_utilities_as_softmax(
self):
probabilities = [0.1, 0.7, 0.2]
total_trials = 10**5
cells = [
total_cell.Cell(
representation_info=self.TestRepresentationInfo(i),
utility_info=self.TestUtilityInfo(
# Log for softmax (e^utility is used for scaling)
np.log(prob))) for i, prob in enumerate(probabilities)
]
for cell in cells:
self.archive.update(cell)
sampled_cells = self.archive.sample(batch_size=total_trials)
successes = [0] * len(probabilities)
for cell in sampled_cells:
successes[cell.representation_info.for_hashing] += 1
for desired_prob, success_count in zip(probabilities, successes):
got_prob = float(success_count) / total_trials
abs_difference = np.abs(got_prob - desired_prob)
max_difference = 9 * np.sqrt(desired_prob *
(1 - desired_prob) / total_trials)
# Probability of failing here is ~1e-15
# (if the implementation is valid).
self.assertLess(abs_difference, max_difference)
def setUp(self):
self.archive = in_memory_archive.InMemoryArchive()
self.cells_100_different = [
total_cell.Cell(
prioritizing_info=self.TestPrioritizingInfo(compare_value=i),
representation_info=self.TestRepresentationInfo(for_hashing=i),
utility_info=self.TestUtilityInfo(ret_utility=i))
for i in range(100)
]
def test_new_cell_gets_sampled_in_archive(self):
cell = total_cell.Cell()
self.archive.update(cell)
sampled_cells = self.archive.sample(batch_size=1)
self.assertEqual(next(sampled_cells), cell)
with self.assertRaises(
StopIteration,
msg='Expected that there is only one element in '
'the returned cells batch.'):
next(sampled_cells)
def test_same_representation_better_priority_utility_stays_same(self):
worse_cell = total_cell.Cell(
representation_info=self.TestRepresentationInfo(0),
prioritizing_info=self.TestPrioritizingInfo(compare_value=0),
utility_info=self.TestUtilityInfo(ret_utility=100))
better_cell = total_cell.Cell(
representation_info=self.TestRepresentationInfo(0),
prioritizing_info=self.TestPrioritizingInfo(compare_value=100),
utility_info=self.TestUtilityInfo(ret_utility=10))
self.archive.update(worse_cell)
self.archive.update(better_cell)
sample = next(self.archive.sample(batch_size=1))
self.assertEqual(
sample.utility_info.ret_utility,
100,
msg='Expected that when a cell is replaced with '
'a better one, utility for sampling stays the same.')