Class AttentionWrapperState
Defined in tensorflow/contrib/seq2seq/python/ops/attention_wrapper.py
.
namedtuple
storing the state of a AttentionWrapper
.
Contains:
cell_state
: The state of the wrappedRNNCell
at the previous time step.attention
: The attention emitted at the previous time step.time
: int32 scalar containing the current time step.alignments
: A single or tuple ofTensor
(s) containing the alignments emitted at the previous time step for each attention mechanism.alignment_history
: (if enabled) a single or tuple ofTensorArray
(s) containing alignment matrices from all time steps for each attention mechanism. Callstack()
on each to convert to aTensor
.attention_state
: A single or tuple of nested objects containing attention mechanism state for each attention mechanism. The objects may contain Tensors or TensorArrays.
__new__
__new__(
_cls,
cell_state,
attention,
time,
alignments,
alignment_history,
attention_state
)
Create new instance of AttentionWrapperState(cell_state, attention, time, alignments, alignment_history, attention_state)
Properties
cell_state
attention
time
alignments
alignment_history
attention_state
Methods
tf.contrib.seq2seq.AttentionWrapperState.clone
clone(**kwargs)
Clone this object, overriding components provided by kwargs.
The new state fields' shape must match original state fields' shape. This will be validated, and original fields' shape will be propagated to new fields.
Example:
initial_state = attention_wrapper.zero_state(dtype=..., batch_size=...)
initial_state = initial_state.clone(cell_state=encoder_state)
Args:
**kwargs
: Any properties of the state object to replace in the returnedAttentionWrapperState
.
Returns:
A new AttentionWrapperState
whose properties are the same as
this one, except any overridden properties as provided in kwargs
.