tf.contrib.rnn.InputProjectionWrapper

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Operator adding an input projection to the given cell.

Inherits From: RNNCell

tf.contrib.rnn.InputProjectionWrapper(
    cell, num_proj, activation=None, input_size=None, reuse=None
)

cell an RNNCell, a projection of inputs is added before it.
num_proj Python integer. The dimension to project to.
activation (optional) an optional activation function.
input_size Deprecated and unused.
reuse (optional) Python boolean describing whether to reuse variables in an existing scope. If not True, and the existing scope already has the given variables, an error is raised.

TypeError if cell is not an RNNCell.

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

get_initial_state

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get_initial_state(
    inputs=None, batch_size=None, dtype=None
)

zero_state

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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.