def test_simple_shapley_sampling_boolean(self) -> None:
net = BasicModelBoolInput()
inp = torch.tensor([[True, False, True]])
self._shapley_test_assert(
net,
inp,
[35.0, 35.0, 35.0],
feature_mask=torch.tensor([[0, 0, 1]]),
perturbations_per_eval=(1, 2, 3),
)
def test_simple_ablation_boolean(self) -> None:
ablation_algo = FeatureAblation(BasicModelBoolInput())
inp = torch.tensor([[True, False, True]])
self._ablation_test_assert(
ablation_algo,
inp,
[[40.0, 40.0, 40.0]],
feature_mask=torch.tensor([[0, 0, 1]]),
perturbations_per_eval=(1, 2, 3),
)
def test_simple_lime_boolean(self) -> None:
net = BasicModelBoolInput()
inp = torch.tensor([[True, False, True]])
self._lime_test_assert(
net,
inp,
[31.42, 31.42, 30.90],
feature_mask=torch.tensor([[0, 0, 1]]),
perturbations_per_eval=(1, 2, 3),
test_generator=True,
)
def test_simple_lime_boolean_with_baselines(self) -> None:
net = BasicModelBoolInput()
inp = torch.tensor([[True, False, True]])
self._lime_test_assert(
net,
inp,
[-36.0, -36.0, 0.0],
feature_mask=torch.tensor([[0, 0, 1]]),
baselines=True,
perturbations_per_eval=(1, 2, 3),
test_generator=True,
)