an RNNCell, a projection to output_size is added to it.
input_keep_prob
unit Tensor or float between 0 and 1, input keep
probability; if it is constant and 1, no input dropout will be added.
output_keep_prob
unit Tensor or float between 0 and 1, output keep
probability; if it is constant and 1, no output dropout will be added.
state_keep_prob
unit Tensor or float between 0 and 1, output keep
probability; if it is constant and 1, no output dropout will be added.
State dropout is performed on the outgoing states of the cell. Note
the state components to which dropout is applied when state_keep_prob
is in (0, 1) are also determined by the argument
dropout_state_filter_visitor (e.g. by default dropout is never applied
to the c component of an LSTMStateTuple).
variational_recurrent
Python bool. If True, then the same dropout
pattern is applied across all time steps per run call. If this parameter
is set, input_sizemust be provided.
input_size
(optional) (possibly nested tuple of) TensorShape objects
containing the depth(s) of the input tensors expected to be passed in to
the DropoutWrapper. Required and used iffvariational_recurrent
= True and input_keep_prob < 1.
dtype
(optional) The dtype of the input, state, and output tensors.
Required and used iffvariational_recurrent = True.
seed
(optional) integer, the randomness seed.
dropout_state_filter_visitor
(optional), default: (see below). Function
that takes any hierarchical level of the state and returns a scalar or
depth=1 structure of Python booleans describing which terms in the state
should be dropped out. In addition, if the function returns True,
dropout is applied across this sublevel. If the function returns
False, dropout is not applied across this entire sublevel.
Default behavior: perform dropout on all terms except the memory (c)
state of LSTMCellState objects, and don't try to apply dropout to
TensorArray objects: def dropout_state_filter_visitor(s):
if isinstance(s, LSTMCellState): # Never perform dropout on the c
state. return LSTMCellState(c=False, h=True)
elif isinstance(s, TensorArray): return False return True
**kwargs
dict of keyword arguments for base layer.
Raises
TypeError
if cell is not an RNNCell, or keep_state_fn is provided
but not callable.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[]]
View source on GitHub