tf.nn.rnn_cell.RNNCell

class tf.nn.rnn_cell.RNNCell

Abstract object representing an RNN cell.

The definition of cell in this package differs from the definition used in the literature. In the literature, cell refers to an object with a single scalar output. The definition in this package refers to a horizontal array of such units.

An RNN cell, in the most abstract setting, is anything that has a state and performs some operation that takes a matrix of inputs. This operation results in an output matrix with self.output_size columns. If self.state_size is an integer, this operation also results in a new state matrix with self.state_size columns. If self.state_size is a tuple of integers, then it results in a tuple of len(state_size) state matrices, each with a column size corresponding to values in state_size.

This module provides a number of basic commonly used RNN cells, such as LSTM (Long Short Term Memory) or GRU (Gated Recurrent Unit), and a number of operators that allow add dropouts, projections, or embeddings for inputs. Constructing multi-layer cells is supported by the class MultiRNNCell, or by calling the rnn ops several times. Every RNNCell must have the properties below and and implement __call__ with the following signature.