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|
The most basic RNN cell.
tf.compat.v1.nn.rnn_cell.BasicRNNCell(
num_units, activation=None, reuse=None, name=None, dtype=None, **kwargs
)
Note that this cell is not optimized for performance. Please use
tf.contrib.cudnn_rnn.CudnnRNNTanh for better performance on GPU.
Args | |
|---|---|
num_units
|
int, The number of units in the RNN cell. |
activation
|
Nonlinearity to use. Default: tanh. It could also be string
that is within Keras activation function names.
|
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.
|
name
|
String, the name of the layer. Layers with the same name will share weights, but to avoid mistakes we require reuse=True in such cases. |
dtype
|
Default dtype of the layer (default of None means use the type of
the first input). Required when build is called before call.
|
**kwargs
|
Dict, keyword named properties for common layer attributes, like
trainable etc when constructing the cell from configs of get_config().
|
Attributes | |
|---|---|
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 | |
|---|---|
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 |