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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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<div id="projectname">OpenANN
 <span id="projectnumber">1.1.0</span>
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<div id="projectbrief">An open source library for artificial neural networks.</div>
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<li class="navelem"><a class="el" href="dir_f128aa1447a98eefc0df3f91bf5f583f.html">OpenANN</a></li><li class="navelem"><a class="el" href="dir_d112c915dc1bb28e462e6df73abab22a.html">layers</a></li> </ul>
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<div class="title">Layer.h</div> </div>
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<a href="Layer_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#ifndef OPENANN_LAYERS_LAYER_H_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor"></span><span class="preprocessor">#define OPENANN_LAYERS_LAYER_H_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="preprocessor"></span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="preprocessor">#include <Eigen/Core></span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#include <vector></span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="keyword">namespace </span>OpenANN</div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> {</div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div>
<div class="line"><a name="l00015"></a><span class="lineno"><a class="code" href="classOpenANN_1_1OutputInfo.html"> 15</a></span> <span class="keyword">class </span><a class="code" href="classOpenANN_1_1OutputInfo.html" title="Provides information about the output of a layer. ">OutputInfo</a></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">public</span>:</div>
<div class="line"><a name="l00019"></a><span class="lineno"><a class="code" href="classOpenANN_1_1OutputInfo.html#a754883365abe65167f2b6e6de63640c0"> 19</a></span>  std::vector<int> <a class="code" href="classOpenANN_1_1OutputInfo.html#a754883365abe65167f2b6e6de63640c0" title="The dimensions of the output. There can be 1-3 dimensions. ">dimensions</a>;</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordtype">int</span> <a class="code" href="classOpenANN_1_1OutputInfo.html#a368013a4ab64685964353c2035a66488" title="Get number of outputs. ">outputs</a>();</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> };</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div>
<div class="line"><a name="l00034"></a><span class="lineno"><a class="code" href="classOpenANN_1_1Layer.html"> 34</a></span> <span class="keyword">class </span><a class="code" href="classOpenANN_1_1Layer.html" title="Interface that has to be implemented by all layers of a neural network that can be trained with backp...">Layer</a></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">public</span>:</div>
<div class="line"><a name="l00037"></a><span class="lineno"><a class="code" href="classOpenANN_1_1Layer.html#a459798712b12ef380e3e21f4a74e9511"> 37</a></span>  <span class="keyword">virtual</span> <a class="code" href="classOpenANN_1_1Layer.html#a459798712b12ef380e3e21f4a74e9511">~Layer</a>() {}</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">virtual</span> <a class="code" href="classOpenANN_1_1OutputInfo.html" title="Provides information about the output of a layer. ">OutputInfo</a> <a class="code" href="classOpenANN_1_1Layer.html#a5cffa0affbc947bd9f2d9385d5129300" title="Fill in the parameter pointers and parameter derivative pointers. ">initialize</a>(std::vector<double*>& parameterPointers,</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  std::vector<double*>& parameterDerivativePointers) = 0;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Layer.html#a2087cdd9b556cb33cd8eab7c4d96e80a" title="Initialize the parameters. ">initializeParameters</a>() = 0;</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Layer.html#a85a5811885b48561049ceaf9b3cbda5b" title="Generate internal parameters from externally visible parameters. ">updatedParameters</a>() = 0;</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Layer.html#a84ab804bbd899c298b0e6f1e459f9033" title="Forward propagation in this layer. ">forwardPropagate</a>(Eigen::MatrixXd* x, Eigen::MatrixXd*& <a class="code" href="namespacexor.html#ac10c3225dba7d99e545014d575bd3af4">y</a>,</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">bool</span> dropout, <span class="keywordtype">double</span>* <a class="code" href="namespaceutil.html#a06943c6087fb261249fd7eb484f39944">error</a> = 0) = 0;</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Layer.html#ae0cff4ccaffcfd46eb5752bf74fb865a" title="Backpropagation in this layer. ">backpropagate</a>(Eigen::MatrixXd* ein, Eigen::MatrixXd*& eout,</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordtype">bool</span> backpropToPrevious) = 0;</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">virtual</span> Eigen::MatrixXd& <a class="code" href="classOpenANN_1_1Layer.html#abb14de9d8e30f242f919e59d7f034c42" title="Output after last forward propagation. ">getOutput</a>() = 0;</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">virtual</span> Eigen::VectorXd <a class="code" href="classOpenANN_1_1Layer.html#a1690d4c0d721f67a060e713b5f4ef32c" title="Get the current values of parameters (weights, biases, ...). ">getParameters</a>() = 0;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> };</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> } <span class="comment">// namespace OpenANN</span></div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#endif // OPENANN_LAYERS_LAYER_H_</span></div>
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