Documentation. Precision — PyTorch-Metrics 0.10.2 documentation

```
from torchmetrics import Precision
from torchmetrics.classification import BinaryPrecision
preds = torch.tensor([0, 0, 0, 0])
target = torch.tensor([0, 0, 0, 0])
general_precision = Precision(num_classes=2)
bin_precision = BinaryPrecision()
# both should be same?
general_precision(preds, target)
# (tensor(1.)
bin_precision(preds, target)
# tensor(0.))
```

From equation, and from `preds`

and `target`

, as there are now `True Positive`

, the numerator becomes `0`

and so the answer should be `0`

. But in general precision, how does it calcuate this?

[ Same goes to (`F1Score - BinaryF1Score`

, `BinaryRecall, Recall`

). ]