def test_auc(x, y, expected, unsqueeze_x, unsqueeze_y):
x = tensor(x)
y = tensor(y)
if unsqueeze_x:
x = x.unsqueeze(-1)
if unsqueeze_y:
y = y.unsqueeze(-1)
# Test Area Under Curve (AUC) computation
assert auc(x, y, reorder=True) == expected
def compute(self) -> torch.Tensor:
preds, targets = self._get_preds_and_targets()
if torch.unique(targets).numel() == 1:
return torch.tensor(np.nan)
prec, recall, _ = precision_recall_curve(preds, targets)
return auc(recall, prec) # type: ignore
def test_auc(x, y, expected):
# Test Area Under Curve (AUC) computation
assert auc(tensor(x), tensor(y), reorder=True) == expected
def test_auc(x, y, expected):
# Test Area Under Curve (AUC) computation
assert auc(torch.tensor(x), torch.tensor(y)) == expected