def test_compute_feats_cuda() -> None:
try:
dataset = TestDataset()
loader = torch.utils.data.DataLoader(
dataset,
batch_size=3,
num_workers=2,
)
metric = MSID()
model = InceptionV3()
metric.compute_feats(loader, model, device='cuda')
except Exception as e:
pytest.fail(f"Unexpected error occurred: {e}")
def test_compute_msid_works_for_different_number_of_images_in_stack(
features_target_normal: torch.Tensor) -> None:
features_prediction_normal = torch.rand(1001, 20)
metric = MSID()
try:
metric(features_target_normal, features_prediction_normal)
except Exception as e:
pytest.fail(f"Unexpected error occurred: {e}")
def test_msid_is_smaller_for_equal_tensors(features_y_normal,
features_x_normal,
features_x_constant) -> None:
metric = MSID()
measure = metric(features_y_normal, features_x_normal)
measure_constant = metric(features_y_normal, features_x_normal)
assert measure <= measure_constant, \
f'MSID should be smaller for samples from the same distribution, got {measure} and {measure_constant}'
def test_forward(
features_target_normal: torch.Tensor,
features_prediction_normal: torch.Tensor,
) -> None:
try:
metric = MSID()
metric(features_target_normal, features_prediction_normal)
except Exception as e:
pytest.fail(f"Unexpected error occurred: {e}")
def test_forward(
features_y_normal,
features_x_normal,
) -> None:
try:
metric = MSID()
metric(features_y_normal, features_x_normal)
except Exception as e:
pytest.fail(f"Unexpected error occurred: {e}")
def test_msid_is_smaller_for_equal_tensors(
features_target_normal: torch.Tensor,
features_prediction_normal: torch.Tensor,
features_prediction_constant: torch.Tensor) -> None:
metric = MSID()
measure = metric(features_target_normal, features_prediction_normal)
measure_constant = metric(features_target_normal,
features_prediction_normal)
assert measure <= measure_constant, \
f'MSID should be smaller for samples from the same distribution, got {measure} and {measure_constant}'
def test_initialization() -> None:
try:
MSID()
except Exception as e:
pytest.fail(f"Unexpected error occurred: {e}")
def test_fails_for_different_dimensions(
features_target_normal: torch.Tensor) -> None:
features_prediction_normal = torch.rand(1000, 21)
metric = MSID()
with pytest.raises(AssertionError):
metric(features_target_normal, features_prediction_normal)
def test_fails_for_different_dimensions(features_y_normal) -> None:
features_x_normal = torch.rand(1000, 21)
metric = MSID()
with pytest.raises(AssertionError):
metric(features_y_normal, features_x_normal)
