qhjqhj00 totalvariation
Metric
TotalVariationfromtorchmetrics(torchmetrics.TotalVariation)
When to invoke this skill
The user has predictions + ground truth and asks to evaluate with TotalVariation, or
mentions torchmetrics.TotalVariation directly, or wants the standard torchmetrics implementation.
Reference signature
from torchmetrics import TotalVariation
# _TotalVariation(reduction: Literal['mean', 'sum', 'none', None] = 'sum', **kwargs: Any) -> None
Library docstring
Wrapper for deprecated import.
>>> from torch import rand
>>> tv = _TotalVariation()
>>> img = rand(5, 3, 28, 28)
>>> tv(img)
tensor(7546.8018)
Quick recipe
import torchmetrics as _m
score = _m.TotalVariation(y_true, y_pred)
Don'ts
- Don't reimplement when the library version handles edge cases (NaN, ties, empty inputs) better than a hand-rolled formula.
- Always check the library version's argument order — sklearn is
(y_true, y_pred)while torchmetrics is(preds, target).