class tf.nn.rnn_cell.MultiRNNCell RNN cell composed sequentially of multiple simple cells.

tf.nn.rnn_cell.LSTMStateTuple.__repr__() Return a nicely formatted representation string

tf.nn.rnn_cell.LSTMStateTuple.__new__(_cls, c, h) Create new instance of LSTMStateTuple(c, h)

tf.nn.rnn_cell.LSTMStateTuple.__getstate__() Exclude the OrderedDict from pickling

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

tf.nn.rnn_cell.LSTMStateTuple.h Alias for field number 1

tf.nn.rnn_cell.LSTMStateTuple.dtype

tf.nn.rnn_cell.LSTMStateTuple.c Alias for field number 0

class tf.nn.rnn_cell.LSTMStateTuple Tuple used by LSTM Cells for state_size, zero_state, and output state. Stores two elements: (c, h), in that order. Only used when state_is_tuple=True.

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) Initialize the parameters for an LSTM cell. Args: num_units: int, The number of units in the LSTM cell input_size: Deprecated and unused. use_peepholes: bool, set True to enable diagonal/peephole connections. cell_clip: (optional) A float value, if provi