def test__get_distance_single(self): """ Case where just a single item in each array """ # Arrange input_x = torch.tensor([[1, 8, 7]], dtype=torch.float) input_y = torch.tensor([[2, 3, 4]], dtype=torch.float) expected = torch.tensor([35]) sut = OnlineTripletLoss(.5) # Act actual = sut._get_distance(input_x, input_y) # Assert self.assertSequenceEqual(expected.cpu().numpy().round(2).tolist(), actual.cpu().numpy().round(2).tolist())
def test__get_distance_zero(self): """ Case where just a single item in each array that are the same """ # Arrange input_x = torch.tensor([[0, 0, 1]], dtype=torch.float) input_y = torch.tensor([[0, 0, 1]], dtype=torch.float) expected = torch.tensor([0]) sut = OnlineTripletLoss(.5) # Act actual = sut._get_distance(input_x, input_y) # Assert self.assertSequenceEqual(expected.cpu().numpy().tolist(), actual.cpu().numpy().tolist())