Neuro/Neuro.cpp

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#include <iostream>
#include <exception>
#include <algorithm>
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#include <assert.h>
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#include "Net.h"
const double pi = std::acos(-1);
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int main()
{
try
{
std::cout << "Neuro running" << std::endl;
Net myNet({ 2, 3, 1 });
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size_t batchSize = 5000;
size_t batchIndex = 0;
double batchMaxError = 0.0;
double batchMeanError = 0.0;
size_t numIterations = 1000000;
for (size_t iteration = 0; iteration < numIterations; ++iteration)
{
std::vector<double> inputValues =
{
std::rand() / (double)RAND_MAX,
std::rand() / (double)RAND_MAX
};
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std::vector<double> targetValues =
{
(inputValues[0] + inputValues[1]) / 2.0
};
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myNet.feedForward(inputValues);
std::vector<double> outputValues = myNet.getOutput();
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double error = outputValues[0] - targetValues[0];
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batchMeanError += error;
batchMaxError = std::max<double>(batchMaxError, error);
if (batchIndex++ == batchSize)
{
std::cout << "Batch error (" << batchSize << " iterations, max/mean): ";
std::cout << std::abs(batchMaxError);
std::cout << " / ";
std::cout << std::abs(batchMeanError / batchSize);
std::cout << std::endl;
batchIndex = 0;
batchMaxError = 0.0;
batchMeanError = 0.0;
}
myNet.backProp(targetValues);
}
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}
catch (std::exception &ex)
{
std::cerr << "Error: " << ex.what() << std::endl;
return 1;
}
return 0;
}