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RNN Cells and additional RNN operations.
Classes
class AttentionCellWrapper: Basic attention cell wrapper.
class BasicLSTMCell: DEPRECATED: Please use tf.compat.v1.nn.rnn_cell.LSTMCell instead.
class BasicRNNCell: The most basic RNN cell.
class BidirectionalGridLSTMCell: Bidirectional GridLstm cell.
class CompiledWrapper: Wraps step execution in an XLA JIT scope.
class Conv1DLSTMCell: 1D Convolutional LSTM recurrent network cell.
class Conv2DLSTMCell: 2D Convolutional LSTM recurrent network cell.
class Conv3DLSTMCell: 3D Convolutional LSTM recurrent network cell.
class ConvLSTMCell: Convolutional LSTM recurrent network cell.
class CoupledInputForgetGateLSTMCell: Long short-term memory unit (LSTM) recurrent network cell.
class DeviceWrapper: Operator that ensures an RNNCell runs on a particular device.
class DropoutWrapper: Operator adding dropout to inputs and outputs of the given cell.
class EmbeddingWrapper: Operator adding input embedding to the given cell.
class FusedRNNCell: Abstract object representing a fused RNN cell.
class FusedRNNCellAdaptor: This is an adaptor for RNNCell classes to be used with FusedRNNCell.
class GLSTMCell: Group LSTM cell (G-LSTM).
class GRUBlockCell: Block GRU cell implementation.
class GRUBlockCellV2: Temporary GRUBlockCell impl with a different variable naming scheme.
class GRUCell: Gated Recurrent Unit cell (cf.
class GridLSTMCell: Grid Long short-term memory unit (LSTM) recurrent network cell.
class HighwayWrapper: RNNCell wrapper that adds highway connection on cell input and output.
class IndRNNCell: Independently Recurrent Neural Network (IndRNN) cell
class IndyGRUCell: Independently Gated Recurrent Unit cell.
class IndyLSTMCell: Basic IndyLSTM recurrent network cell.
class InputProjectionWrapper: Operator adding an input projection to the given cell.
class IntersectionRNNCell: Intersection Recurrent Neural Network (+RNN) cell.
class LSTMBlockCell: Basic LSTM recurrent network cell.
class LSTMBlockFusedCell: FusedRNNCell implementation of LSTM.
class LSTMBlockWrapper: This is a helper class that provides housekeeping for LSTM cells.
class LSTMCell: Long short-term memory unit (LSTM) recurrent network cell.
class LSTMStateTuple: Tuple used by LSTM Cells for state_size, zero_state, and output state.
class LayerNormBasicLSTMCell: LSTM unit with layer normalization and recurrent dropout.
class LayerRNNCell: Subclass of RNNCells that act like proper tf.Layer objects.
class MultiRNNCell: RNN cell composed sequentially of multiple simple cells.
class NASCell: Neural Architecture Search (NAS) recurrent network cell.
class OutputProjectionWrapper: Operator adding an output projection to the given cell.
class PhasedLSTMCell: Phased LSTM recurrent network cell.
class RNNCell: Abstract object representing an RNN cell.
class ResidualWrapper: RNNCell wrapper that ensures cell inputs are added to the outputs.
class SRUCell: SRU, Simple Recurrent Unit.
class TimeFreqLSTMCell: Time-Frequency Long short-term memory unit (LSTM) recurrent network cell.
class TimeReversedFusedRNN: This is an adaptor to time-reverse a FusedRNNCell.
class UGRNNCell: Update Gate Recurrent Neural Network (UGRNN) cell.
Functions
best_effort_input_batch_size(...): Get static input batch size if available, with fallback to the dynamic one.
stack_bidirectional_dynamic_rnn(...): Creates a dynamic bidirectional recurrent neural network.
stack_bidirectional_rnn(...): Creates a bidirectional recurrent neural network.
static_bidirectional_rnn(...): Creates a bidirectional recurrent neural network. (deprecated)
static_rnn(...): Creates a recurrent neural network specified by RNNCell cell. (deprecated)
static_state_saving_rnn(...): RNN that accepts a state saver for time-truncated RNN calculation. (deprecated)
transpose_batch_time(...): Transposes the batch and time dimensions of a Tensor.