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https://github.com/VictorEijkhout/TheArtOfHPC_vol3_cppf08programming.git
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51 lines
1.5 KiB
C++
51 lines
1.5 KiB
C++
/****************************************************************
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****
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**** This file belongs with the course
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**** Introduction to Scientific Programming in C++/Fortran2003
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**** copyright 2020-2023 Victor Eijkhout eijkhout@tacc.utexas.edu
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****
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**** net.cxx : neural net tester
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****
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****************************************************************/
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#include <iostream>
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using std::cin;
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using std::cout;
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#include <vector>
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using std::vector;
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#include "ml.hpp"
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int main() {
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data_vector
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indata ( vector<float>{1,2,3,6,7,8,11,12,13,14,15,21,22,23,24,25,26} ),
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values ( vector<float>{0,0,0,0,0,0,01,01,01,01,01,00,00,00,00,00,00} ),
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outdata ( values.size() ),
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testdata( vector<float>{ -1.5,3.5,4.5,6.5,9.5, 11.5,12.5,15.5,16,5, 24.5,25.5,31,5 } ),
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testout ( testdata.size() )
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;
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auto net = network( {indata.size(),outdata.size() } );
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net.set_learning_rate(.05);
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cout << "Network with " << net.depth() << " layers" << '\n';
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cout << '\n';
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cout << "################" << '\n';
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cout << "Input data: " << indata.as_string() << '\n';
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cout << "values : " << values.as_string() << '\n';
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for (int step=0; step<10; ++step) {
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cout << "################ Step " << step << " ################" << '\n';
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net.apply(indata,outdata);
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auto c = net.cost(outdata,values);
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cout << "error: " << c << '\n';
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net.apply(testdata,testout);
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cout << "apply on test data: " << testout.as_string() << '\n';
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if (c<0) break;
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net.backpass(indata,outdata,values);
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}
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return 0;
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}
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