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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">Input.h</div> </div>
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<a href="Input_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_INPUT_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_INPUT_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> </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_1Input.html"> 15</a></span> <span class="keyword">class </span><a class="code" href="classOpenANN_1_1Input.html" title="Input layer. ">Input</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="l00016"></a><span class="lineno"> 16</span> {</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keywordtype">int</span> J, dim1, dim2, dim3;</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  Eigen::MatrixXd* x;</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keyword">public</span>:</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="classOpenANN_1_1Input.html#a78f9f419385afdb445b1a310f9331c8a">Input</a>(<span class="keywordtype">int</span> dim1, <span class="keywordtype">int</span> dim2, <span class="keywordtype">int</span> dim3);</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</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_1Input.html#a711121cc67850306ae8ecc2f1fd0526d" title="Fill in the parameter pointers and parameter derivative pointers. ">initialize</a>(std::vector<double*>& parameterPointers,</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  std::vector<double*>& parameterDerivativePointers);</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Input.html#a0b06463f4e951e0c5567ac0bb52f2572" title="Initialize the parameters. ">initializeParameters</a>();</div>
<div class="line"><a name="l00025"></a><span class="lineno"><a class="code" href="classOpenANN_1_1Input.html#a15685c38a1feca41f14c85b60ec3b0da"> 25</a></span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Input.html#a15685c38a1feca41f14c85b60ec3b0da" title="Generate internal parameters from externally visible parameters. ">updatedParameters</a>() {}</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Input.html#a2753bca5b5a2ce9b94247ce43409c5f2" 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="l00027"></a><span class="lineno"> 27</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="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classOpenANN_1_1Input.html#a632664ca4b6b00435897088bea10e810" title="Backpropagation in this layer. ">backpropagate</a>(Eigen::MatrixXd* ein, Eigen::MatrixXd*& eout,</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordtype">bool</span> backpropToPrevious);</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">virtual</span> Eigen::MatrixXd& <a class="code" href="classOpenANN_1_1Input.html#adb4f198152ea276486317c3901bb9e36" title="Output after last forward propagation. ">getOutput</a>();</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">virtual</span> Eigen::VectorXd <a class="code" href="classOpenANN_1_1Input.html#a42ffc1dbfb724b8641b75286cd64a702" title="Get the current values of parameters (weights, biases, ...). ">getParameters</a>();</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> };</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> } <span class="comment">// namespace OpenANN</span></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="preprocessor">#endif // OPENANN_LAYERS_INPUT_H_</span></div>
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