Hi if anyone could help
I created custom layers to use for my project but I keep getting the following errors
Cannot perform forward pass in layer MessagePassingImplementation: layer input field is not set
this is my conf
private static MultiLayerNetwork mpnn(Protein p, long sampledFeatures) {
int seed = 123;
double learningRate = 0.5;
int out = 2; // binary
//Configure the layer with custom GCN and Readout layers
MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
.seed(seed)
// .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
.updater(new Nesterovs(learningRate, 0.5))
.list()
.layer(new MessagePassingLayer.Builder()
.messageActivationFunction(Activation.SIGMOID)
.updateActivationFunction(Activation.SIGMOID)
.adjacencyMatrix(p.getAdjacencyMatrix())
.nIn(p.getFeatureMatrix().columns())
.nOut(p.getFeatureMatrix().columns())
.build())
.layer(new ReadoutLayer.Builder().readActivationFunction(Activation.SIGMOID)
.nIn(p.getFeatureMatrix().columns())
.nOut(p.getFeatureMatrix().columns())
.build())
.layer(new DenseLayer.Builder()
.nIn(p.getFeatureMatrix().columns())
.nOut(sampledFeatures)
.weightInit(WeightInit.XAVIER)
.activation(Activation.RELU)
.build()) //Configuring Layers
.layer(new OutputLayer.Builder(LossFunctions.LossFunction.MCXENT)
.weightInit(WeightInit.XAVIER)
.activation(Activation.SOFTMAX)
.nIn(sampledFeatures)
.nOut(2)
.build())
.build();
return new MultiLayerNetwork(conf);
thanks