Improve descriptions of go_backwards parameters. (#5966)

keras/backend/tensorflow_backend.py

@@ -2175,8 +2175,8 @@ def rnn(step_function, inputs, initial_states,
             (no time dimension),
             containing the initial values for the states used in
             the step function.
-        go_backwards: boolean. If True, do the iteration over
-            the time dimension in reverse order.
+        go_backwards: boolean. If True, do the iteration over the time
+            dimension in reverse order and return the reversed sequence.
         mask: binary tensor with shape `(samples, time, 1)`,
             with a zero for every element that is masked.
         constants: a list of constant values passed at each step.

keras/backend/theano_backend.py

@@ -1166,8 +1166,8 @@ def rnn(step_function, inputs, initial_states,
         initial_states: tensor with shape (samples, ...) (no time dimension),
             containing the initial values for the states used in
             the step function.
-        go_backwards: boolean. If True, do the iteration over
-            the time dimension in reverse order.
+        go_backwards: boolean. If True, do the iteration over the time
+            dimension in reverse order and return the reversed sequence.
         mask: binary tensor with shape (samples, time),
             with a zero for every element that is masked.
         constants: a list of constant values passed at each step.

keras/layers/recurrent.py

@@ -97,7 +97,8 @@ class Recurrent(Layer):
         return_sequences: Boolean. Whether to return the last output
             in the output sequence, or the full sequence.
         go_backwards: Boolean (default False).
-            If True, process the input sequence backwards.
+            If True, process the input sequence backwards and return the
+            reversed sequence.
         stateful: Boolean (default False). If True, the last state
             for each sample at index i in a batch will be used as initial
             state for the sample of index i in the following batch.