Created
May 9, 2016 16:12
-
-
Save tmsimont/8c08e821b5cbb813b71d532d782de1d9 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| ListBuilder listBuilder = builder.list(2); | |
| GravesLSTM.Builder hiddenLayerBuilder = new GravesLSTM.Builder(); | |
| hiddenLayerBuilder.nIn(100); | |
| hiddenLayerBuilder.nOut(100); | |
| hiddenLayerBuilder.activation("tanh"); | |
| listBuilder.layer(0, hiddenLayerBuilder.build()); | |
| RnnOutputLayer.Builder outputLayerBuilder = new RnnOutputLayer.Builder(LossFunction.MCXENT); | |
| outputLayerBuilder.activation("softmax"); | |
| outputLayerBuilder.nIn(100); | |
| outputLayerBuilder.nOut(100); | |
| listBuilder.layer(1, outputLayerBuilder.build()); | |
| listBuilder.pretrain(false); | |
| listBuilder.backprop(true); | |
| MultiLayerConfiguration conf = listBuilder.build(); | |
| MultiLayerNetwork net = new MultiLayerNetwork(conf); | |
| net.init(); | |
| // some time later... | |
| net.rnnTimeStep(input); |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
How can I swap out RnnOutputLayer.Builder with a custom class type and have it relate to a custom Layer Model without re-writing the factory code here: https://github.com/deeplearning4j/deeplearning4j/blob/b1ffaddb67b6cf89ee97d40db931dd95f6cab742/deeplearning4j-core/src/main/java/org/deeplearning4j/nn/layers/factory/DefaultLayerFactory.java#L69