Merge changes from github.

Change: 149800363

1 files changed, 2 insertions, 2 deletions

diff --git a/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py b/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py
index 3d1589f27e..1202f961cc 100644
--- a/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py
+++ b/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py
@@ -1111,7 +1111,7 @@ def sequence_loss(logits,
     average_across_timesteps: If set, divide the returned cost by the total
       label weight.
     average_across_batch: If set, divide the returned cost by the batch size.
-    softmax_loss_function: Function (inputs-batch, labels-batch) -> loss-batch
+    softmax_loss_function: Function (labels-batch, inputs-batch) -> loss-batch
       to be used instead of the standard softmax (the default if this is None).
     name: Optional name for this operation, defaults to "sequence_loss".
 
@@ -1160,7 +1160,7 @@ def model_with_buckets(encoder_inputs,
     seq2seq: A sequence-to-sequence model function; it takes 2 input that
       agree with encoder_inputs and decoder_inputs, and returns a pair
       consisting of outputs and states (as, e.g., basic_rnn_seq2seq).
-    softmax_loss_function: Function (inputs-batch, labels-batch) -> loss-batch
+    softmax_loss_function: Function (labels-batch, inputs-batch) -> loss-batch
       to be used instead of the standard softmax (the default if this is None).
     per_example_loss: Boolean. If set, the returned loss will be a batch-sized
       tensor of losses for each sequence in the batch. If unset, it will be