#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/layer.csv";
const size_t nOutputs = 3;
const size_t nInputs = 3;
int main(int argc, char *argv[])
{
checkArguments(argc, argv, 1, &datasetName);
TensorPtr tensorData = readTensorFromCSV(datasetName);
split::forward::Batch<> splitLayerForward;
splitLayerForward.parameter.nOutputs = nOutputs;
splitLayerForward.parameter.nInputs = nInputs;
splitLayerForward.input.set(forward::data, tensorData);
printTensor(tensorData, "Split layer input (first 5 rows):", 5);
splitLayerForward.compute();
split::forward::ResultPtr forwardResult = splitLayerForward.getResult();
for(size_t i = 0; i < nOutputs; i++)
{
printTensor(forwardResult->get(split::forward::valueCollection, i), "Forward split layer result (first 5 rows):", 5);
}
split::backward::Batch<> splitLayerBackward;
splitLayerBackward.parameter.nOutputs = nOutputs;
splitLayerBackward.parameter.nInputs = nInputs;
splitLayerBackward.input.set(split::backward::inputGradientCollection, forwardResult->get(split::forward::valueCollection));
splitLayerBackward.compute();
backward::ResultPtr backwardResult = splitLayerBackward.getResult();
printTensor(backwardResult->get(backward::gradient), "Backward split layer result (first 5 rows):", 5);
return 0;
}