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Class CrfDecodeForwardRnnCell
Computes the forward decoding in a linear-chain CRF.
Inherits From: RNNCell
__init__
__init__(transition_params)
Initialize the CrfDecodeForwardRnnCell.
Args:
transition_params: A [num_tags, num_tags] matrix of binary potentials. This matrix is expanded into a [1, num_tags, num_tags] in preparation for the broadcast summation occurring within the cell.
Properties
graph
DEPRECATED FUNCTION
output_size
Integer or TensorShape: size of outputs produced by this cell.
scope_name
state_size
size(s) of state(s) used by this cell.
It can be represented by an Integer, a TensorShape or a tuple of Integers or TensorShapes.
Methods
tf.contrib.crf.CrfDecodeForwardRnnCell.get_initial_state
get_initial_state(
inputs=None,
batch_size=None,
dtype=None
)
tf.contrib.crf.CrfDecodeForwardRnnCell.zero_state
zero_state(
batch_size,
dtype
)
Return zero-filled state tensor(s).
Args:
batch_size: int, float, or unit Tensor representing the batch size.dtype: the data type to use for the state.
Returns:
If state_size is an int or TensorShape, then the return value is a
N-D tensor of shape [batch_size, state_size] filled with zeros.
If state_size is a nested list or tuple, then the return value is
a nested list or tuple (of the same structure) of 2-D tensors with
the shapes [batch_size, s] for each s in state_size.