#include "daal.h"
#include "service.h"
using namespace std;
using namespace daal;
using namespace daal::algorithms;
using namespace daal::algorithms::neural_networks::layers;
using namespace daal::data_management;
using namespace daal::services;
string datasetName = "../data/batch/logistic_cross_entropy_layer.csv";
string datasetGroundTruthName = "../data/batch/logistic_cross_entropy_layer_ground_truth.csv";
int main()
{
TensorPtr tensorData = readTensorFromCSV(datasetName);
TensorPtr groundTruth = readTensorFromCSV(datasetGroundTruthName);
loss::logistic_cross::forward::Batch<> logisticCrossEntropyLayerForward;
logisticCrossEntropyLayerForward.input.set(forward::data, tensorData);
logisticCrossEntropyLayerForward.input.set(loss::forward::groundTruth, groundTruth);
logisticCrossEntropyLayerForward.compute();
loss::logistic_cross::forward::ResultPtr forwardResult = logisticCrossEntropyLayerForward.getResult();
printTensor(forwardResult->get(forward::value), "Forward logistic cross-entropy layer result (first 5 rows):", 5);
printTensor(forwardResult->get(loss::logistic_cross::auxGroundTruth), "Logistic Cross-Entropy layer ground truth (first 5 rows):", 5);
loss::logistic_cross::backward::Batch<> logisticCrossEntropyLayerBackward;
logisticCrossEntropyLayerBackward.input.set(backward::inputFromForward, forwardResult->get(forward::resultForBackward));
logisticCrossEntropyLayerBackward.compute();
backward::ResultPtr backwardResult = logisticCrossEntropyLayerBackward.getResult();
printTensor(backwardResult->get(backward::gradient), "Backward logistic cross-entropy layer result (first 5 rows):", 5);
return 0;
}