tf.contrib.rnn.CoupledInputForgetGateLSTMCell
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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

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tf.contrib.rnn.GridLSTMCell.zero_state()
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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

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tf.contrib.rnn.LSTMBlockCell.
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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

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tf.contrib.rnn.TimeFreqLSTMCell.
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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

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tf.contrib.rnn.LayerNormBasicLSTMCell.
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

tf.contrib.rnn.TimeFreqLSTMCell.output_size

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tf.contrib.rnn.CoupledInputForgetGateLSTMCell.zero_state()
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

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

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tf.contrib.rnn.GridLSTMCell.state_tuple_type
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

tf.contrib.rnn.GridLSTMCell.state_tuple_type

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tf.contrib.rnn.GRUBlockCell
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

class tf.contrib.rnn.GRUBlockCell Block GRU cell implementation. The implementation is based on:

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tf.contrib.rnn.CoupledInputForgetGateLSTMCell.
  • References/Big Data/TensorFlow/TensorFlow Python/RNN

tf.contrib.rnn.CoupledInputForgetGateLSTMCell.__init__(num_units, use_peepholes=False, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1

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