Java Deep Learning Cookbook

How to do it...

1. Detach the INDArray data to use it across workspaces:

INDArray array = Nd4j.rand(6, 6); INDArray mean = array.mean(1); INDArray result = mean.detach();

2. Remove all workspaces that were created during training/evaluation in case they are running short of RAM:

Nd4j.getWorkspaceManager().destroyAllWorkspacesForCurrentThread();

3. Leverage an array instance from another workspace in the current workspace by calling leverageTo():

LayerWorkspaceMgr.leverageTo(ArrayType.ACTIVATIONS, myArray);

4. Track the time spent on every iteration during training using PerformanceListener:

model.setListeners(new PerformanceListener(frequency,reportScore)); 

5. Add the following Maven dependency for cuDNN support:

<dependency> <groupId>org.deeplearning4j</groupId> ...