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<html><head><meta http-equiv="Content-Type" content="text/html;charset=UTF-8">
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<title>Neural++: examples/doAdd.cpp</title>
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<li><a href="index.html"><span>Main Page</span></a></li>
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<div class="contents">
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<h1>examples/doAdd.cpp</h1>Show how to use a network already trained and saved to a binary file. In this case, a network trained to simply perform sums between two real numbers, that should have already been created using learnAdd.<p>
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<div class="fragment"><pre class="fragment">
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<span class="preprocessor">#include <iostream></span>
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<span class="preprocessor">#include <<a class="code" href="neural_09_09_8hpp.html">neural++.hpp</a>></span>
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<span class="keyword">using namespace </span>std;
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<span class="keyword">using namespace </span>neuralpp;
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<span class="preprocessor">#define NETFILE "adder.net"</span>
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<span class="preprocessor"></span>
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<span class="keywordtype">int</span> main() {
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<span class="keywordtype">double</span> a,b;
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<a name="_a0"></a><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&#39;s class.">NeuralNet</a> net;
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<span class="comment">// Load the pre-trained network from "adder.net" file</span>
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<span class="keywordflow">try</span> {
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net = <a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&#39;s class.">NeuralNet</a>(NETFILE);
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}
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<span class="keywordflow">catch</span> (<a name="_a1"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html" title="Exception thrown when doing an attempt to load a network from an invalid file.">NetworkFileNotFoundException</a> e) {
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cerr << <span class="stringliteral">"Fatal error while opening "</span> << NETFILE << <span class="stringliteral">": "</span> << e.<a name="a2"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">what</a>();
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<span class="keywordflow">return</span> 1;
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}
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cout << <span class="stringliteral">"First number to add: "</span>;
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cin >> a;
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cout << <span class="stringliteral">"Second number to add: "</span>;
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cin >> b;
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vector<double> v;
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v.push_back(a);
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v.push_back(b);
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<span class="comment">// Set the numbers just read as input values, propagate those values, and get</span>
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<span class="comment">// the output</span>
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net.<a name="a3"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17" title="It sets the input for the network.">setInput</a>(v);
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net.<a name="a4"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890" title="It propagates values through the network.">propagate</a>();
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cout << <span class="stringliteral">"Neural net output: "</span> << net.<a name="a5"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810" title="It gets the output of the network (note: the layer output should contain an only...">getOutput</a>() << endl;
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<span class="keywordflow">return</span> 0;
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}
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</pre></div> </div>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by
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<a href="http://www.doxygen.org/index.html">
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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