tf.nn.rnn_cell.RNNCell.output_size Integer or TensorShape: size of outputs produced by this cell.

tf.nn.rnn_cell.RNNCell.__call__(inputs, state, scope=None) Run this RNN cell on inputs, starting from the given state.

tf.nn.rnn_cell.GRUCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s). Args:

tf.nn.rnn_cell.DropoutWrapper.__init__(cell, input_keep_prob=1.0, output_keep_prob=1.0, seed=None) Create a cell with added input

tf.nn.rnn_cell.DropoutWrapper.__call__(inputs, state, scope=None) Run the cell with the declared dropouts.

tf.nn.rnn_cell.LSTMStateTuple.__getnewargs__() Return self as a plain tuple. Used by copy and pickle.

class tf.nn.rnn_cell.RNNCell Abstract object representing an RNN cell. The definition of cell

tf.nn.rnn_cell.InputProjectionWrapper.__call__(inputs, state, scope=None) Run the input projection and then the cell.

class tf.nn.rnn_cell.EmbeddingWrapper Operator adding input embedding to the given cell. Note:

tf.nn.rnn_cell.EmbeddingWrapper.output_size