tf.contrib.rnn.LayerNormBasicLSTMCell.

tf.contrib.rnn.LayerNormBasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, activation=tanh, layer_norm=True, norm_gain=1.0, norm_shift=0.0, dropout_keep_prob=1

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tf.contrib.rnn.TimeFreqLSTMCell.output_size

tf.contrib.rnn.TimeFreqLSTMCell.output_size

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tf.contrib.rnn.CoupledInputForgetGateLSTMCell

class tf.contrib.rnn.CoupledInputForgetGateLSTMCell Long short-term memory unit (LSTM) recurrent network cell.

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tf.contrib.rnn.TimeFreqLSTMCell.

tf.contrib.rnn.TimeFreqLSTMCell.__call__(inputs, state, scope=None) Run one step of LSTM. Args:

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tf.contrib.rnn.GridLSTMCell.zero_state()

tf.contrib.rnn.GridLSTMCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s). Args:

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tf.contrib.rnn.CoupledInputForgetGateLSTMCell.zero_state()

tf.contrib.rnn.CoupledInputForgetGateLSTMCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s).

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tf.contrib.rnn.LSTMBlockCell.

tf.contrib.rnn.LSTMBlockCell.__call__(x, states_prev, scope=None) Long short-term memory cell (LSTM).

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tf.contrib.rnn.GridLSTMCell.state_tuple_type

tf.contrib.rnn.GridLSTMCell.state_tuple_type

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tf.contrib.rnn.LSTMBlockCell.

tf.contrib.rnn.LSTMBlockCell.__init__(num_units, forget_bias=1.0, use_peephole=False) Initialize the basic LSTM cell.

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tf.contrib.rnn.GridLSTMCell.

tf.contrib.rnn.GridLSTMCell.__init__(num_units, use_peepholes=False, share_time_frequency_weights=False, cell_clip=None, initializer=None, num_unit_shards=1, forget_bias=1

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