qhjqhj00 signalnoiseratio
Metric
SignalNoiseRatiofromtorchmetrics(torchmetrics.SignalNoiseRatio)
When to invoke this skill
The user has predictions + ground truth and asks to evaluate with SignalNoiseRatio, or
mentions torchmetrics.SignalNoiseRatio directly, or wants the standard torchmetrics implementation.
Reference signature
from torchmetrics import SignalNoiseRatio
# _SignalNoiseRatio(zero_mean: bool = False, **kwargs: Any) -> None
Library docstring
Wrapper for deprecated import.
>>> from torch import tensor
>>> target = tensor([3.0, -0.5, 2.0, 7.0])
>>> preds = tensor([2.5, 0.0, 2.0, 8.0])
>>> snr = _SignalNoiseRatio()
>>> snr(preds, target)
tensor(16.1805)
Quick recipe
import torchmetrics as _m
score = _m.SignalNoiseRatio(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).