def test_ill_opts(self):
pred = torch.ones((1, 3, 3, 3, 3), dtype=torch.float)
target = torch.ones((1, 3, 3, 3, 3), dtype=torch.float)
with self.assertRaisesRegex(ValueError, ""):
LocalNormalizedCrossCorrelationLoss(in_channels=3, kernel_type="unknown")(pred, target)
with self.assertRaisesRegex(ValueError, ""):
LocalNormalizedCrossCorrelationLoss(in_channels=3, kernel_type=None)(pred, target)
with self.assertRaisesRegex(ValueError, ""):
LocalNormalizedCrossCorrelationLoss(in_channels=3, kernel_size=4)(pred, target)
with self.assertRaisesRegex(ValueError, ""):
LocalNormalizedCrossCorrelationLoss(in_channels=3, reduction="unknown")(pred, target)
with self.assertRaisesRegex(ValueError, ""):
LocalNormalizedCrossCorrelationLoss(in_channels=3, reduction=None)(pred, target)
def test_ill_shape(self):
loss = LocalNormalizedCrossCorrelationLoss(in_channels=3, ndim=3)
# in_channel unmatch
with self.assertRaisesRegex(ValueError, ""):
loss.forward(torch.ones((1, 2, 3, 3, 3), dtype=torch.float), torch.ones((1, 2, 3, 3, 3), dtype=torch.float))
# ndim unmatch
with self.assertRaisesRegex(ValueError, ""):
loss.forward(torch.ones((1, 3, 3, 3), dtype=torch.float), torch.ones((1, 3, 3, 3), dtype=torch.float))
# pred, target shape unmatch
with self.assertRaisesRegex(ValueError, ""):
loss.forward(torch.ones((1, 3, 3, 3, 3), dtype=torch.float), torch.ones((1, 3, 4, 4, 4), dtype=torch.float))
def test_shape(self, input_param, input_data, expected_val):
result = LocalNormalizedCrossCorrelationLoss(**input_param).forward(
**input_data)
np.testing.assert_allclose(result.detach().cpu().numpy(),
expected_val,
rtol=1e-5)