I upgraded versions, and models that use to work in the prior version are returning exceptions like the following:
Exception in thread "main" java.lang.IllegalStateException: Layer 0 returned null activations at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.ffToLayerActivationsInWs(MultiLayerNetwork.java:1154) at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:2781) at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:2739) at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:174) at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:61) at org.deeplearning4j.optimize.Solver.optimize(Solver.java:52) at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fitHelper(MultiLayerNetwork.java:1750) at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1671)
This is being thrown while trying to fit a DataSetIterator. My layer 0 is pretty simple with only one input feature:
.layer(0, new LSTM.Builder().activation(Activation.TANH).nIn(1).nOut(50).build())
Is there some new configuration that needs to be added with the latest version?
Additionally, I am attaching a snapshot of the debugger showing there is data going in.
I tried to follow this through as far as I could with the debugger and found that after line 157 in the LSTM class the downstream process expects a value for the fwdPassOutput but for some reason the LSTMHelper.activateHelper is returning a fwd that has all null attributes.