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: