Update generated Python Op docs.

Change: 146748564

2 files changed, 22 insertions, 4 deletions

diff --git a/tensorflow/g3doc/api_docs/python/contrib.training.md b/tensorflow/g3doc/api_docs/python/contrib.training.md
index 8b8847d41d..1804d5339b 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.training.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.training.md
@@ -15,7 +15,7 @@ like to store state in the forward direction across segments of an example.
 
 - - -
 
-### `tf.contrib.training.batch_sequences_with_states(input_key, input_sequences, input_context, input_length, initial_states, num_unroll, batch_size, num_threads=3, capacity=1000, allow_small_batch=True, pad=True, name=None)` {#batch_sequences_with_states}
+### `tf.contrib.training.batch_sequences_with_states(input_key, input_sequences, input_context, input_length, initial_states, num_unroll, batch_size, num_threads=3, capacity=1000, allow_small_batch=True, pad=True, make_keys_unique=False, make_keys_unique_seed=None, name=None)` {#batch_sequences_with_states}
 
 Creates batches of segments of sequential input.
 
@@ -103,7 +103,11 @@ while True:
     input example.  This is used to keep track of the split minibatch elements
     of this input.  Batched keys of the current iteration are made
     accessible via the `key` property.  The shape of `input_key` (scalar) must
-    be fully specified.
+    be fully specified.  Consider setting `make_keys_unique` to True when
+    iterating over the same input multiple times.
+
+    **Note**: if `make_keys_unique=False` then `input_key`s must be unique.
+
 *  <b>`input_sequences`</b>: A dict mapping string names to `Tensor` values.  The values
     must all have matching first dimension, called `value_length`. They may
     vary from input to input. The remainder of the shape (other than the first
@@ -158,6 +162,11 @@ while True:
     `num_unroll`. In that case `input_length` may be `None` and is assumed to
     be the length of first dimension of values in `input_sequences`
     (i.e. `value_length`).
+*  <b>`make_keys_unique`</b>: Whether to append a random integer to the `input_key` in
+    an effort to make it unique. The seed can be set via
+    `make_keys_unique_seed`.
+*  <b>`make_keys_unique_seed`</b>: If `make_keys_unique=True` this fixes the seed with
+    which a random postfix is generated.
 *  <b>`name`</b>: An op name string (optional).
 
 ##### Returns:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.training.batch_sequences_with_states.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.training.batch_sequences_with_states.md
index a59080eb30..63c3a47229 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.training.batch_sequences_with_states.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.training.batch_sequences_with_states.md
@@ -1,4 +1,4 @@
-### `tf.contrib.training.batch_sequences_with_states(input_key, input_sequences, input_context, input_length, initial_states, num_unroll, batch_size, num_threads=3, capacity=1000, allow_small_batch=True, pad=True, name=None)` {#batch_sequences_with_states}
+### `tf.contrib.training.batch_sequences_with_states(input_key, input_sequences, input_context, input_length, initial_states, num_unroll, batch_size, num_threads=3, capacity=1000, allow_small_batch=True, pad=True, make_keys_unique=False, make_keys_unique_seed=None, name=None)` {#batch_sequences_with_states}
 
 Creates batches of segments of sequential input.
 
@@ -86,7 +86,11 @@ while True:
     input example.  This is used to keep track of the split minibatch elements
     of this input.  Batched keys of the current iteration are made
     accessible via the `key` property.  The shape of `input_key` (scalar) must
-    be fully specified.
+    be fully specified.  Consider setting `make_keys_unique` to True when
+    iterating over the same input multiple times.
+
+    **Note**: if `make_keys_unique=False` then `input_key`s must be unique.
+
 *  <b>`input_sequences`</b>: A dict mapping string names to `Tensor` values.  The values
     must all have matching first dimension, called `value_length`. They may
     vary from input to input. The remainder of the shape (other than the first
@@ -141,6 +145,11 @@ while True:
     `num_unroll`. In that case `input_length` may be `None` and is assumed to
     be the length of first dimension of values in `input_sequences`
     (i.e. `value_length`).
+*  <b>`make_keys_unique`</b>: Whether to append a random integer to the `input_key` in
+    an effort to make it unique. The seed can be set via
+    `make_keys_unique_seed`.
+*  <b>`make_keys_unique_seed`</b>: If `make_keys_unique=True` this fixes the seed with
+    which a random postfix is generated.
 *  <b>`name`</b>: An op name string (optional).
 
 ##### Returns: