package com.intel.daal.examples.neural_networks;
import com.intel.daal.algorithms.neural_networks.layers.eltwise_sum.*;
import com.intel.daal.algorithms.neural_networks.layers.ForwardResultId;
import com.intel.daal.algorithms.neural_networks.layers.ForwardResultLayerDataId;
import com.intel.daal.algorithms.neural_networks.layers.ForwardInputLayerDataId;
import com.intel.daal.algorithms.neural_networks.layers.BackwardResultLayerDataId;
import com.intel.daal.algorithms.neural_networks.layers.BackwardInputId;
import com.intel.daal.algorithms.neural_networks.layers.BackwardInputLayerDataId;
import com.intel.daal.data_management.data.Tensor;
import com.intel.daal.data_management.data.HomogenTensor;
import com.intel.daal.data_management.data.KeyValueDataCollection;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
class EltwiseSumLayerDenseBatch {
private static DaalContext context = new DaalContext();
private static final String datasetFileName = "../data/batch/layer.csv";
private static final long nInputs = 3;
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
EltwiseSumForwardBatch forwardLayer = new EltwiseSumForwardBatch(context, Float.class, EltwiseSumMethod.defaultDense);
for (int i = 0; i < nInputs; i++) {
Tensor data = Service.readTensorFromCSV(context, datasetFileName);
forwardLayer.input.set(ForwardInputLayerDataId.inputLayerData, data, i);
}
EltwiseSumForwardResult forwardResult = forwardLayer.compute();
Service.printTensor("Forward element-wise sum layer result (first 5 rows):",
forwardResult.get(ForwardResultId.value), 5, 0);
Service.printNumericTable("Forward element-wise sum layer number of inputs (number of coefficients)",
forwardResult.get(EltwiseSumLayerDataNumericTableId.auxNumberOfCoefficients), 1, 0);
EltwiseSumBackwardBatch backwardLayer = new EltwiseSumBackwardBatch(context, Float.class, EltwiseSumMethod.defaultDense);
Tensor inputGradient = Service.readTensorFromCSV(context, datasetFileName);
backwardLayer.input.set(BackwardInputId.inputGradient, inputGradient);
backwardLayer.input.set(BackwardInputLayerDataId.inputFromForward, forwardResult.get(ForwardResultLayerDataId.resultForBackward));
EltwiseSumBackwardResult backwardResult = backwardLayer.compute();
for (int i = 0; i < nInputs; i++) {
Service.printTensor("Backward element-wise sum layer backward result (first 5 rows):",
backwardResult.get(BackwardResultLayerDataId.resultLayerData, i), 5, 0);
}
context.dispose();
}
}