1 files changed, 11 insertions, 10 deletions
diff --git a/tensorflow/contrib/crf/python/ops/crf.py b/tensorflow/contrib/crf/python/ops/crf.py
index 7166e38b28..c8adb0369b 100644
--- a/tensorflow/contrib/crf/python/ops/crf.py
+++ b/tensorflow/contrib/crf/python/ops/crf.py
@@ -360,8 +360,8 @@ class CrfDecodeForwardRnnCell(rnn_cell.RNNCell):
       scope: Unused variable scope of this cell.
 
     Returns:
-      backpointers: [batch_size, num_tags], containing backpointers.
-      new_state: [batch_size, num_tags], containing new score values.
+      backpointers: A [batch_size, num_tags] matrix of backpointers.
+      new_state: A [batch_size, num_tags] matrix of new score values.
     """
     # For simplicity, in shape comments, denote:
     # 'batch_size' by 'B', 'max_seq_len' by 'T' , 'num_tags' by 'O' (output).
@@ -385,7 +385,7 @@ class CrfDecodeBackwardRnnCell(rnn_cell.RNNCell):
     """Initialize the CrfDecodeBackwardRnnCell.
 
     Args:
-      num_tags
+      num_tags: An integer.
     """
     self._num_tags = num_tags
 
@@ -401,8 +401,9 @@ class CrfDecodeBackwardRnnCell(rnn_cell.RNNCell):
     """Build the CrfDecodeBackwardRnnCell.
 
     Args:
-      inputs: [batch_size, num_tags], backpointer of next step (in time order).
-      state: [batch_size, 1], next position's tag index.
+      inputs: A [batch_size, num_tags] matrix of
+            backpointer of next step (in time order).
+      state: A [batch_size, 1] matrix of tag index of next step.
       scope: Unused variable scope of this cell.
 
     Returns:
@@ -426,16 +427,16 @@ def crf_decode(potentials, transition_params, sequence_length):
   This is a function for tensor.
 
   Args:
-    potentials: A [batch_size, max_seq_len, num_tags] tensor, matrix of
+    potentials: A [batch_size, max_seq_len, num_tags] tensor of
               unary potentials.
-    transition_params: A [num_tags, num_tags] tensor, matrix of
+    transition_params: A [num_tags, num_tags] matrix of
               binary potentials.
-    sequence_length: A [batch_size] tensor, containing sequence lengths.
+    sequence_length: A [batch_size] vector of true sequence lengths.
 
   Returns:
-    decode_tags: A [batch_size, max_seq_len] tensor, with dtype tf.int32.
+    decode_tags: A [batch_size, max_seq_len] matrix, with dtype `tf.int32`.
                 Contains the highest scoring tag indicies.
-    best_score: A [batch_size] tensor, containing the score of decode_tags.
+    best_score: A [batch_size] vector, containing the score of `decode_tags`.
   """
   # For simplicity, in shape comments, denote:
   # 'batch_size' by 'B', 'max_seq_len' by 'T' , 'num_tags' by 'O' (output).