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())