1 files changed, 7 insertions, 6 deletions
diff --git a/tensorflow/contrib/losses/python/losses/loss_ops.py b/tensorflow/contrib/losses/python/losses/loss_ops.py
index f6d3601c7d..1d2477b8b7 100644
--- a/tensorflow/contrib/losses/python/losses/loss_ops.py
+++ b/tensorflow/contrib/losses/python/losses/loss_ops.py
@@ -301,7 +301,7 @@ def absolute_difference(predictions, labels=None, weights=1.0, scope=None):
 
 @deprecated("2016-12-30",
             "Use tf.losses.sigmoid_cross_entropy instead. Note that the order "
-            "of the predictions and labels arguments was changed.")
+            "of the predictions and labels arguments has been changed.")
 def sigmoid_cross_entropy(
     logits, multi_class_labels, weights=1.0, label_smoothing=0, scope=None):
   """Creates a cross-entropy loss using tf.nn.sigmoid_cross_entropy_with_logits.
@@ -436,7 +436,7 @@ def sparse_softmax_cross_entropy(logits, labels, weights=1.0, scope=None):
 
 @deprecated("2016-12-30",
             "Use tf.losses.log_loss instead. Note that the order of the "
-            "predictions and labels arguments was changed.")
+            "predictions and labels arguments has been changed.")
 def log_loss(predictions, labels=None, weights=1.0, epsilon=1e-7, scope=None):
   """Adds a Log Loss term to the training procedure.
 
@@ -477,7 +477,8 @@ def log_loss(predictions, labels=None, weights=1.0, epsilon=1e-7, scope=None):
 
 @deprecated("2016-12-30",
             "Use tf.losses.hinge_loss instead. Note that the order of the "
-            "predictions and labels arguments were changed.")
+            "logits and labels arguments has been changed, and to stay "
+            "unweighted, reduction=Reduction.NONE")
 def hinge_loss(logits, labels=None, scope=None):
   """Method that returns the loss tensor for hinge loss.
 
@@ -488,8 +489,8 @@ def hinge_loss(logits, labels=None, scope=None):
     scope: The scope for the operations performed in computing the loss.
 
   Returns:
-    A `Tensor` of same shape as `logits` and `labels` representing the loss
-      values across the batch.
+    An unweighted `Tensor` of same shape as `logits` and `labels` representing the
+      loss values across the batch.
 
   Raises:
     ValueError: If the shapes of `logits` and `labels` don't match.
@@ -541,7 +542,7 @@ def mean_squared_error(predictions, labels=None, weights=1.0, scope=None):
 
 @deprecated("2016-12-30",
             "Use tf.losses.mean_pairwise_squared_error instead. Note that the "
-            "order of the predictions and labels arguments was changed.")
+            "order of the predictions and labels arguments has been changed.")
 def mean_pairwise_squared_error(
     predictions, labels=None, weights=1.0, scope=None):
   """Adds a pairwise-errors-squared loss to the training procedure.