docs

pytorch_lightning/metrics/functional/classification.py

@@ -84,8 +84,6 @@ def get_num_classes(
  return __gnc(pred,target, num_classes)
 
 
-
-
 def stat_scores(
  pred: torch.Tensor,
  target: torch.Tensor,
@@ -448,9 +446,15 @@ def roc(
  sample_weight: Optional[Sequence] = None,
  pos_label: int = 1.,
 ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """
+ Computes the Receiver Operating Characteristic (ROC). It assumes classifier is binary.
+
+ .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.roc.roc`
+ """
  rank_zero_warn(
- "This `multiclass_roc` was deprecated in v1.1.0 in favor of `pytorch_lightning.metrics.functional.roc.roc`."
- "It will be removed in v1.3.0", DeprecationWarning
+ "This `multiclass_roc` was deprecated in v1.1.0 in favor of"
+ " `from pytorch_lightning.metrics.functional.roc import roc`."
+ " It will be removed in v1.3.0", DeprecationWarning
  )
  return __roc(preds=pred, target=target, sample_weights=sample_weight, pos_label=pos_label)
 
@@ -465,16 +469,7 @@ def _roc(
  """
  Computes the Receiver Operating Characteristic (ROC). It assumes classifier is binary.
 
- .. warning:: Deprecated
-
- Args:
- pred: estimated probabilities
- target: ground-truth labels
- sample_weight: sample weights
- pos_label: the label for the positive class
-
- Return:
- false-positive rate (fpr), true-positive rate (tpr), thresholds
+ .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.roc.roc`
 
  Example:
 
@@ -490,8 +485,9 @@ def _roc(
 
  """
  rank_zero_warn(
- "This `multiclass_roc` was deprecated in v1.1.0 in favor of `pytorch_lightning.metrics.functional.roc.roc`."
- "It will be removed in v1.3.0", DeprecationWarning
+ "This `multiclass_roc` was deprecated in v1.1.0 in favor of"
+ " `from pytorch_lightning.metrics.functional.roc import roc`."
+ " It will be removed in v1.3.0", DeprecationWarning
  )
  fps, tps, thresholds = _binary_clf_curve(
  pred=pred, target=target, sample_weight=sample_weight, pos_label=pos_label
@@ -526,7 +522,7 @@ def multiclass_roc(
  """
  Computes the Receiver Operating Characteristic (ROC) for multiclass predictors.
 
- .. warning:: Deprecated
+ .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.roc.roc`
 
  Args:
  pred: estimated probabilities
@@ -869,6 +865,11 @@ def precision_recall_curve(
  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`."
@@ -884,6 +885,11 @@ def multiclass_precision_recall_curve(
  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`."
@@ -901,9 +907,14 @@ def average_precision(
  sample_weight: Optional[Sequence] = None,
  pos_label: int = 1.,
 ):
+ """
+ Compute average precision from prediction scores.
+
+ .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.average_precision.average_precision`
+ """
  rank_zero_warn(
  "This `average_precision` was deprecated in v1.1.0 in favor of"
- " `pytorch_lightning.metrics.functional.average_precision import precision_recall_curve`."
+ " `pytorch_lightning.metrics.functional.average_precision import average_precision`."
  " It will be removed in v1.3.0", DeprecationWarning
  )
  return __ap(preds=pred, target=target, sample_weights=sample_weight, pos_label=pos_label)

pytorch_lightning/metrics/functional/reduction.py

@@ -32,4 +32,4 @@ def class_reduce(num: torch.Tensor, denom: torch.Tensor, weights: torch.Tensor,
  " `pytorch_lightning.metrics.utils import class_reduce`."
  " It will be removed in v1.3.0", DeprecationWarning
  )
- return __cr(num=num, denom=denom, weights=weights, class_reduction=class_reduction)
+ return __cr(num=num, denom=denom, weights=weights, class_reduction=class_reduction)