def test_compute():
acc = TopKCategoricalAccuracy(2)
y_pred = torch.FloatTensor([[0.2, 0.4, 0.6, 0.8], [0.8, 0.6, 0.4, 0.2]])
y = torch.ones(2).type(torch.LongTensor)
acc.update((y_pred, y))
assert acc.compute() == 0.5
acc.reset()
y_pred = torch.FloatTensor([[0.4, 0.8, 0.2, 0.6], [0.8, 0.6, 0.4, 0.2]])
y = torch.ones(2).type(torch.LongTensor)
acc.update((y_pred, y))
assert acc.compute() == 1.0
def test_compute():
acc = TopKCategoricalAccuracy(2)
y_pred = torch.FloatTensor([[0.2, 0.4, 0.6, 0.8], [0.8, 0.6, 0.4, 0.2]])
y = torch.ones(2).long()
acc.update((y_pred, y))
assert isinstance(acc.compute(), float)
assert acc.compute() == 0.5
acc.reset()
y_pred = torch.FloatTensor([[0.4, 0.8, 0.2, 0.6], [0.8, 0.6, 0.4, 0.2]])
y = torch.ones(2).long()
acc.update((y_pred, y))
assert isinstance(acc.compute(), float)
assert acc.compute() == 1.0