def precision_recall_curve(
pred: torch.Tensor,
target: torch.Tensor,
sample_weight: Optional[Sequence] = None,
pos_label: int = 1.,
):
"""
Computes precision-recall pairs for different thresholds.
.. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.precision_recall_curve.precision_recall_curve`
"""
rank_zero_warn(
"This `precision_recall_curve` was deprecated in v1.1.0 in favor of"
" `from pytorch_lightning.metrics.functional.precision_recall_curve import precision_recall_curve`."
" It will be removed in v1.3.0", DeprecationWarning)
return __prc(preds=pred,
target=target,
sample_weights=sample_weight,
pos_label=pos_label)
def multiclass_precision_recall_curve(
pred: torch.Tensor,
target: torch.Tensor,
sample_weight: Optional[Sequence] = None,
num_classes: Optional[int] = None,
):
"""
Computes precision-recall pairs for different thresholds given a multiclass scores.
.. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.precision_recall_curve.precision_recall_curve`
"""
rank_zero_warn(
"This `multiclass_precision_recall_curve` was deprecated in v1.1.0 in favor of"
" `from pytorch_lightning.metrics.functional.precision_recall_curve import precision_recall_curve`."
" It will be removed in v1.3.0", DeprecationWarning)
if num_classes is None:
num_classes = get_num_classes(pred, target, num_classes)
return __prc(preds=pred,
target=target,
sample_weights=sample_weight,
num_classes=num_classes)