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The most basic RNN cell.
Inherits From: RNNCell
, Layer
, Layer
, Module
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.
Methods
apply
apply(
*args, **kwargs
)
get_initial_state
get_initial_state(
inputs=None, batch_size=None, dtype=None
)
get_losses_for
get_losses_for(
inputs
)
Retrieves losses relevant to a specific set of inputs.
Args | |
---|---|
inputs
|
Input tensor or list/tuple of input tensors. |
Returns | |
---|---|
List of loss tensors of the layer that depend on inputs .
|
get_updates_for
get_updates_for(
inputs
)
Retrieves updates relevant to a specific set of inputs.
Args | |
---|---|
inputs
|
Input tensor or list/tuple of input tensors. |
Returns | |
---|---|
List of update ops of the layer that depend on inputs .
|
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 |