diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.nn.rnn_cell.LSTMCell.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.nn.rnn_cell.LSTMCell.md
index eb17d56e862..042811ba248 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.nn.rnn_cell.LSTMCell.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.nn.rnn_cell.LSTMCell.md
@@ -19,7 +19,7 @@ The class uses optional peep-hole connections, optional cell clipping, and
an optional projection layer.
- - -
-#### `tf.nn.rnn_cell.LSTMCell.__init__(num_units, input_size=None, use_peepholes=False, cell_clip=None, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1, forget_bias=1.0, state_is_tuple=False, activation=tanh)` {#LSTMCell.__init__}
+#### `tf.nn.rnn_cell.LSTMCell.__init__(num_units, input_size=None, use_peepholes=False, cell_clip=None, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1, forget_bias=1.0, state_is_tuple=True, activation=tanh)` {#LSTMCell.__init__}
Initialize the parameters for an LSTM cell.
@@ -47,8 +47,8 @@ Initialize the parameters for an LSTM cell.
in order to reduce the scale of forgetting at the beginning of
the training.
* `state_is_tuple`: If True, accepted and returned states are 2-tuples of
- the `c_state` and `m_state`. By default (False), they are concatenated
- along the column axis. This default behavior will soon be deprecated.
+ the `c_state` and `m_state`. If False, they are concatenated
+ along the column axis. This latter behavior will soon be deprecated.
* `activation`: Activation function of the inner states.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.nn.rnn_cell.BasicLSTMCell.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.nn.rnn_cell.BasicLSTMCell.md
index 65c2c2b3454..27db9261173 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.nn.rnn_cell.BasicLSTMCell.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.nn.rnn_cell.BasicLSTMCell.md
@@ -11,7 +11,7 @@ use peep-hole connections: it is the basic baseline.
For advanced models, please use the full LSTMCell that follows.
- - -
-#### `tf.nn.rnn_cell.BasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, state_is_tuple=False, activation=tanh)` {#BasicLSTMCell.__init__}
+#### `tf.nn.rnn_cell.BasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, state_is_tuple=True, activation=tanh)` {#BasicLSTMCell.__init__}
Initialize the basic LSTM cell.
@@ -22,8 +22,8 @@ Initialize the basic LSTM cell.
* `forget_bias`: float, The bias added to forget gates (see above).
* `input_size`: Deprecated and unused.
* `state_is_tuple`: If True, accepted and returned states are 2-tuples of
- the `c_state` and `m_state`. By default (False), they are concatenated
- along the column axis. This default behavior will soon be deprecated.
+ the `c_state` and `m_state`. If False, they are concatenated
+ along the column axis. The latter behavior will soon be deprecated.
* `activation`: Activation function of the inner states.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.nn.rnn_cell.MultiRNNCell.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.nn.rnn_cell.MultiRNNCell.md
index f103e9dd6c2..ef5ed76657d 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.nn.rnn_cell.MultiRNNCell.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.nn.rnn_cell.MultiRNNCell.md
@@ -1,7 +1,7 @@
RNN cell composed sequentially of multiple simple cells.
- - -
-#### `tf.nn.rnn_cell.MultiRNNCell.__init__(cells, state_is_tuple=False)` {#MultiRNNCell.__init__}
+#### `tf.nn.rnn_cell.MultiRNNCell.__init__(cells, state_is_tuple=True)` {#MultiRNNCell.__init__}
Create a RNN cell composed sequentially of a number of RNNCells.
@@ -10,8 +10,9 @@ Create a RNN cell composed sequentially of a number of RNNCells.
* `cells`: list of RNNCells that will be composed in this order.
* `state_is_tuple`: If True, accepted and returned states are n-tuples, where
- `n = len(cells)`. By default (False), the states are all
- concatenated along the column axis.
+ `n = len(cells)`. If False, the states are all
+ concatenated along the column axis. This latter behavior will soon be
+ deprecated.
##### Raises:
diff --git a/tensorflow/g3doc/api_docs/python/rnn_cell.md b/tensorflow/g3doc/api_docs/python/rnn_cell.md
index 5fcbd27966a..8e956deb1ac 100644
--- a/tensorflow/g3doc/api_docs/python/rnn_cell.md
+++ b/tensorflow/g3doc/api_docs/python/rnn_cell.md
@@ -141,7 +141,7 @@ use peep-hole connections: it is the basic baseline.
For advanced models, please use the full LSTMCell that follows.
- - -
-#### `tf.nn.rnn_cell.BasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, state_is_tuple=False, activation=tanh)` {#BasicLSTMCell.__init__}
+#### `tf.nn.rnn_cell.BasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, state_is_tuple=True, activation=tanh)` {#BasicLSTMCell.__init__}
Initialize the basic LSTM cell.
@@ -152,8 +152,8 @@ Initialize the basic LSTM cell.
* `forget_bias`: float, The bias added to forget gates (see above).
* `input_size`: Deprecated and unused.
* `state_is_tuple`: If True, accepted and returned states are 2-tuples of
- the `c_state` and `m_state`. By default (False), they are concatenated
- along the column axis. This default behavior will soon be deprecated.
+ the `c_state` and `m_state`. If False, they are concatenated
+ along the column axis. The latter behavior will soon be deprecated.
* `activation`: Activation function of the inner states.
@@ -268,7 +268,7 @@ The class uses optional peep-hole connections, optional cell clipping, and
an optional projection layer.
- - -
-#### `tf.nn.rnn_cell.LSTMCell.__init__(num_units, input_size=None, use_peepholes=False, cell_clip=None, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1, forget_bias=1.0, state_is_tuple=False, activation=tanh)` {#LSTMCell.__init__}
+#### `tf.nn.rnn_cell.LSTMCell.__init__(num_units, input_size=None, use_peepholes=False, cell_clip=None, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1, forget_bias=1.0, state_is_tuple=True, activation=tanh)` {#LSTMCell.__init__}
Initialize the parameters for an LSTM cell.
@@ -296,8 +296,8 @@ Initialize the parameters for an LSTM cell.
in order to reduce the scale of forgetting at the beginning of
the training.
* `state_is_tuple`: If True, accepted and returned states are 2-tuples of
- the `c_state` and `m_state`. By default (False), they are concatenated
- along the column axis. This default behavior will soon be deprecated.
+ the `c_state` and `m_state`. If False, they are concatenated
+ along the column axis. This latter behavior will soon be deprecated.
* `activation`: Activation function of the inner states.
@@ -382,7 +382,7 @@ Alias for field number 1
RNN cell composed sequentially of multiple simple cells.
- - -
-#### `tf.nn.rnn_cell.MultiRNNCell.__init__(cells, state_is_tuple=False)` {#MultiRNNCell.__init__}
+#### `tf.nn.rnn_cell.MultiRNNCell.__init__(cells, state_is_tuple=True)` {#MultiRNNCell.__init__}
Create a RNN cell composed sequentially of a number of RNNCells.
@@ -391,8 +391,9 @@ Create a RNN cell composed sequentially of a number of RNNCells.
* `cells`: list of RNNCells that will be composed in this order.
* `state_is_tuple`: If True, accepted and returned states are n-tuples, where
- `n = len(cells)`. By default (False), the states are all
- concatenated along the column axis.
+ `n = len(cells)`. If False, the states are all
+ concatenated along the column axis. This latter behavior will soon be
+ deprecated.
##### Raises: