diff --git a/pytorch_lightning/metrics/functional/classification.py b/pytorch_lightning/metrics/functional/classification.py
index 854acc255cb5b..c8e1afe46f870 100644
--- a/pytorch_lightning/metrics/functional/classification.py
+++ b/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)
diff --git a/pytorch_lightning/metrics/functional/reduction.py b/pytorch_lightning/metrics/functional/reduction.py
index bc1425b71d507..c116b16d363a9 100644
--- a/pytorch_lightning/metrics/functional/reduction.py
+++ b/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)
\ No newline at end of file
+    return __cr(num=num, denom=denom, weights=weights, class_reduction=class_reduction)