deeplearning4j : How can I store/save a trained model on persistence level and load it back when an ad-hoc request comes to evaluate the deep learning model?
DataNormalization normalizer = new NormalizerStandardize();
normalizer.fit(trainingData); //Collect the statistics (mean/stdev) from the training data. This does not modify the input data
normalizer.transform(trainingData);
//run the model
MultiLayerNetwork model = new MultiLayerNetwork(conf);
model.init();
model.setListeners(new ScoreIterationListener(100));
for( int i=0; i<epochs; i++ ) {
model.fit(trainingData);
}
I need to store the trained model. How can I do this? With which Api?
//evaluate the model on the test set
Evaluation eval = new Evaluation(3);
INDArray output = model.output(testData.getFeatures());
eval.eval(testData.getLabels(), output);
log.info(eval.stats());