lilalinux

		net.rnnClearPreviousState();
		trainDataIter.reset();
		
		INDArray pred = null;
		List<INDArray> predictionsTrain = new ArrayList<>();
		while (trainDataIter.hasNext()) {
			DataSet t = trainDataIter.next();
			INDArray featureMatrix = t.getFeatureMatrix(); // [miniBatchSize,inputSize,inputTimeSeriesLength], 5000x2x20 -> [3,5000,2,20,1,100000,5000,0,-1,99]
			INDArray predictionMiniBatch = net.rnnTimeStep(featureMatrix);
			normalizer.revertLabels(predictionMiniBatch);