tf.contrib.rnn.InputProjectionWrapper
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 )
Note: in many cases it may be more efficient to not use this wrapper, but instead concatenate the whole sequence of your inputs in time, do the projection on this batch-concatenated sequence, then split it.
Args | |
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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. |
Raises | |
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TypeError | if cell is not an RNNCell. |
Attributes | |
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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
get_initial_state( inputs=None, batch_size=None, dtype=None )
zero_state
zero_state( batch_size, dtype )
Return zero-filled state tensor(s).
Args | |
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batch_size | int, float, or unit Tensor representing the batch size. |
dtype | the data type to use for the state. |
Returns | |
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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 |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/rnn/InputProjectionWrapper