C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

spat_stoch_pool2d_layer_dense_batch.cpp

/* file: spat_stoch_pool2d_layer_dense_batch.cpp */
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/*
! Content:
! C++ example of neural network forward and backward two-dimensional spatial pyramid stochastic pooling layers usage.
!
!******************************************************************************/
#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::algorithms::neural_networks;
using namespace daal::data_management;
using namespace daal::services;
static const size_t nDim = 4;
static const size_t dims[] = {2, 3, 2, 4};
static float dataArray[2][3][2][4] = {{{{ 1, 2, 3, 4},
{ 5, 6, 7, 8}},
{{ 9, 10, 11, 12},
{13, 14, 15, 16}},
{{17, 18, 19, 20},
{21, 22, 23, 24}}},
{{{ 10, 20, 30, 40},
{ 50, 60, 70, 80}},
{{ 90, 100, 110, 120},
{130, 140, 150, 160}},
{{170, 180, 190, 200},
{210, 220, 230, 240}}}};
int main(int argc, char *argv[])
{
TensorPtr data(new HomogenTensor<>(nDim, dims, (float *)dataArray));
printTensor(data, "Forward two-dimensional spatial pyramid stochastic pooling layer input (first 10 rows):", 10);
/* Create an algorithm to compute forward two-dimensional spatial pyramid stochastic pooling layer results using default method */
spatial_stochastic_pooling2d::forward::Batch<> forwardLayer(2, nDim);
forwardLayer.input.set(forward::data, data);
/* Compute forward two-dimensional spatial pyramid stochastic pooling layer results */
forwardLayer.compute();
/* Get the computed forward two-dimensional spatial pyramid stochastic pooling layer results */
spatial_stochastic_pooling2d::forward::ResultPtr forwardResult = forwardLayer.getResult();
printTensor(forwardResult->get(forward::value), "Forward two-dimensional spatial pyramid stochastic pooling layer result (first 5 rows):", 5);
printTensor(forwardResult->get(spatial_stochastic_pooling2d::auxSelectedIndices),
"Forward two-dimensional spatial pyramid stochastic pooling layer selected indices (first 10 rows):", 10);
/* Create an algorithm to compute backward two-dimensional spatial pyramid stochastic pooling layer results using default method */
spatial_stochastic_pooling2d::backward::Batch<> backwardLayer(2, nDim);
backwardLayer.input.set(backward::inputGradient, forwardResult->get(forward::value));
backwardLayer.input.set(backward::inputFromForward, forwardResult->get(forward::resultForBackward));
/* Compute backward two-dimensional spatial pyramid stochastic pooling layer results */
backwardLayer.compute();
/* Get the computed backward two-dimensional spatial pyramid stochastic pooling layer results */
backward::ResultPtr backwardResult = backwardLayer.getResult();
printTensor(backwardResult->get(backward::gradient),
"Backward two-dimensional spatial pyramid stochastic pooling layer result (first 10 rows):", 10);
return 0;
}

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