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 <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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<div class="title">Convolutional.h</div> </div>
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<a href="Convolutional_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_CONVOLUTIONAL_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_CONVOLUTIONAL_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 <<a class="code" href="Layer_8h.html">OpenANN/layers/Layer.h</a>></span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#include <<a class="code" href="ActivationFunctions_8h.html">OpenANN/ActivationFunctions.h</a>></span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <<a class="code" href="Regularization_8h.html">OpenANN/Regularization.h</a>></span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="keyword">namespace </span>OpenANN</div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> {</div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div>
<div class="line"><a name="l00036"></a><span class="lineno"><a class="code" href="classOpenANN_1_1Convolutional.html"> 36</a></span> <span class="keyword">class </span><a class="code" href="classOpenANN_1_1Convolutional.html" title="Applies a learnable filter on a 2D or 3D input. ">Convolutional</a> : <span class="keyword">public</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="l00037"></a><span class="lineno"> 37</span> {</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordtype">int</span> I, fmin, inRows, inCols, fmout, kernelRows, kernelCols;</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">bool</span> bias;</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="namespaceOpenANN.html#a90e479eb54bb177043ce063427022968">ActivationFunction</a> act;</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">double</span> stdDev;</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  Eigen::MatrixXd* x;</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  std::vector<std::vector<Eigen::MatrixXd> > W;</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  std::vector<std::vector<Eigen::MatrixXd> > Wd;</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  Eigen::MatrixXd Wb;</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  Eigen::MatrixXd Wbd;</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  Eigen::MatrixXd a;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  Eigen::MatrixXd y;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  Eigen::MatrixXd yd;</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  Eigen::MatrixXd deltas;</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  Eigen::MatrixXd e;</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordtype">int</span> fmInSize, outRows, outCols, fmOutSize, maxRow, maxCol;</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="classOpenANN_1_1Regularization.html" title="Holds all information related to regularization terms in an error function. ">Regularization</a> regularization;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">public</span>:</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classOpenANN_1_1Convolutional.html#ad8cd849c758c7285dead58f34cd5c3e8">Convolutional</a>(<a class="code" href="classOpenANN_1_1OutputInfo.html" title="Provides information about the output of a layer. ">OutputInfo</a> <a class="code" href="namespaceutil.html#a69f48bb24702ab50b12a2245beebbffa">info</a>, <span class="keywordtype">int</span> featureMaps, <span class="keywordtype">int</span> kernelRows,</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordtype">int</span> kernelCols, <span class="keywordtype">bool</span> bias, <a class="code" href="namespaceOpenANN.html#a90e479eb54bb177043ce063427022968">ActivationFunction</a> act,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordtype">double</span> stdDev, <a class="code" href="classOpenANN_1_1Regularization.html" title="Holds all information related to regularization terms in an error function. ">Regularization</a> regularization);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</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_1Convolutional.html#aba9efd24e7a6885c37d040bd34abcfd5" title="Fill in the parameter pointers and parameter derivative pointers. ">initialize</a>(std::vector<double*>& parameterPointers,</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::vector<double*>& parameterDerivativePointers);</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_1Convolutional.html#a9d9fdc60217dbeca02755949cd7d33a8" title="Initialize the parameters. ">initializeParameters</a>();</div>
<div class="line"><a name="l00064"></a><span class="lineno"><a class="code" href="classOpenANN_1_1Convolutional.html#a630c9f07c680bb756a018535ceda5b4e"> 64</a></span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Convolutional.html#a630c9f07c680bb756a018535ceda5b4e" title="Generate internal parameters from externally visible parameters. ">updatedParameters</a>() {}</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Convolutional.html#a16ff4fcd64dc9765bfb0959a524e2e2a" title="Forward propagation in this layer. ">forwardPropagate</a>(Eigen::MatrixXd* x, Eigen::MatrixXd*& y,</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">bool</span> dropout, <span class="keywordtype">double</span>* <a class="code" href="namespaceutil.html#a06943c6087fb261249fd7eb484f39944">error</a> = 0);</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Convolutional.html#a3bfec235398b055034d4ef28b2e8db69" title="Backpropagation in this layer. ">backpropagate</a>(Eigen::MatrixXd* ein, Eigen::MatrixXd*& eout,</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordtype">bool</span> backpropToPrevious);</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">virtual</span> Eigen::MatrixXd& <a class="code" href="classOpenANN_1_1Convolutional.html#a82a27b31f46a5657c9969a83e5ee68e3" title="Output after last forward propagation. ">getOutput</a>();</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">virtual</span> Eigen::VectorXd <a class="code" href="classOpenANN_1_1Convolutional.html#a7e38e6f43eb2a94c62f0ec5af3de4420" title="Get the current values of parameters (weights, biases, ...). ">getParameters</a>();</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> };</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> } <span class="comment">// namespace OpenANN</span></div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="preprocessor">#endif // OPENANN_LAYERS_CONVOLUTIONAL_H_</span></div>
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