Comments (1)
I've already solved it, using the write/readCSV of the MatrixUtils class, here is the code if someone needs it, just put into the NeuralNetwork class the following methods:
/**
* Loads NN from file, with parameters supplied in myParms
* note: doesn't check matrices match sizes!
* it's up to the developer to specify them properly when invoking the NN constructor
*/
public void loadNN(String filename){
mySoftmax = myParams.numClasses > 1;
myNumOutputs = myParams.numClasses;
// Add null params for layer 0, which is just the input and last layer, which is just output.
myLayerParams = new NNParams.NNLayerParams[myParams.hiddenLayerParams.length+2];
System.arraycopy(myParams.hiddenLayerParams, 0, myLayerParams, 1, myParams.hiddenLayerParams.length);
myLayerParams[myLayerParams.length-1] = new NNParams.NNLayerParams(myNumOutputs);
myParams.numThreads = myParams.numThreads > 0 ? myParams.numThreads : Runtime.getRuntime().availableProcessors();
myExecutorService = Executors.newFixedThreadPool(myParams.numThreads);
int numLayers = myLayerParams.length;
initThetas();
for (int layer = 1; layer < numLayers; layer++)
try{
myThetas[layer]=MatrixUtils.readCSV(filename+"_l"+layer+".csv",',', 0);
}catch(Exception e) {System.out.println(e.toString());}
}
from neuralnetwork.
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from neuralnetwork.