See: Description
| Class | Description |
|---|---|
| GRU |
GRU is an abstract implementation of recurrent neural networks which applies GRU (Gated
Recurrent Unit) recurrent layer to input. |
| GRU.Builder | |
| LSTM |
LSTM is an implementation of recurrent neural networks which applies Long Short-Term
Memory recurrent layer to input. |
| LSTM.Builder | |
| RecurrentBlock |
RecurrentBlock is an abstract implementation of recurrent neural networks. |
| RecurrentBlock.BaseBuilder<T extends RecurrentBlock.BaseBuilder> |
The Builder to construct a
RecurrentBlock type of Block. |
| RNN |
RNN is an implementation of recurrent neural networks which applies a single-gate
recurrent layer to input. |
| RNN.Builder |
| Enum | Description |
|---|---|
| RNN.Activation |
An enum that enumerates the type of activation.
|
RecurrentBlock