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Documentation for 895ae31cd7
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@@ -107,10 +107,10 @@ Collaboration diagram for machine_learning::neural_network::layers::DenseLayer:<
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
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Public Member Functions</h2></td></tr>
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<tr class="memitem:a51c2b942ecf10625780c6bb9d5c50ff1"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a51c2b942ecf10625780c6bb9d5c50ff1">DenseLayer</a> (const int &neurons, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/basic_string.html">std::string</a> &activation, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/pair.html">std::pair</a>< size_t, size_t > &kernal_shape, const bool &random_kernal)</td></tr>
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<tr class="separator:a51c2b942ecf10625780c6bb9d5c50ff1"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a04b8e21316458436c8851959928c3964"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a04b8e21316458436c8851959928c3964">DenseLayer</a> (const int &neurons, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/basic_string.html">std::string</a> &activation, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>< <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>< double >> &kernal)</td></tr>
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<tr class="separator:a04b8e21316458436c8851959928c3964"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a11046825be0b6dbb73fbe834aa49200e"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a11046825be0b6dbb73fbe834aa49200e">DenseLayer</a> (const int &neurons, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/basic_string.html">std::string</a> &activation, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/pair.html">std::pair</a>< size_t, size_t > &kernel_shape, const bool &random_kernel)</td></tr>
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<tr class="separator:a11046825be0b6dbb73fbe834aa49200e"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a35ab6f1b2840f89a858ca36b78739b69"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a35ab6f1b2840f89a858ca36b78739b69">DenseLayer</a> (const int &neurons, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/basic_string.html">std::string</a> &activation, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>< <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>< double >> &kernel)</td></tr>
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<tr class="separator:a35ab6f1b2840f89a858ca36b78739b69"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a2871146feaaa453558239df67b21e0d2"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a2871146feaaa453558239df67b21e0d2">DenseLayer</a> (const <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> &layer)=default</td></tr>
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<tr class="separator:a2871146feaaa453558239df67b21e0d2"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ac9cda9453c4a0caf5bae7f9213b019a0"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#ac9cda9453c4a0caf5bae7f9213b019a0">~DenseLayer</a> ()=default</td></tr>
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@@ -136,15 +136,15 @@ int </td><td class="memItemRight" valign="bottom"><b>neurons</b></td></tr>
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<tr class="memitem:a891264e2eb1357b2b3282e5532250869"><td class="memItemLeft" align="right" valign="top"><a id="a891264e2eb1357b2b3282e5532250869"></a>
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<a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/basic_string.html">std::string</a> </td><td class="memItemRight" valign="bottom"><b>activation</b></td></tr>
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<tr class="separator:a891264e2eb1357b2b3282e5532250869"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a2e3fb82813c0fb305d6330867dd42ac8"><td class="memItemLeft" align="right" valign="top"><a id="a2e3fb82813c0fb305d6330867dd42ac8"></a>
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<a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>< <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>< double > > </td><td class="memItemRight" valign="bottom"><b>kernal</b></td></tr>
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<tr class="separator:a2e3fb82813c0fb305d6330867dd42ac8"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a494d39f6c367071d1fd31b3c1caf1a7d"><td class="memItemLeft" align="right" valign="top"><a id="a494d39f6c367071d1fd31b3c1caf1a7d"></a>
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<a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>< <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>< double > > </td><td class="memItemRight" valign="bottom"><b>kernel</b></td></tr>
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<tr class="separator:a494d39f6c367071d1fd31b3c1caf1a7d"><td class="memSeparator" colspan="2"> </td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<div class="textblock"><p><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">neural_network::layers::DenseLayer</a> class is used to store all necessary information about the layers (i.e. neurons, activation and kernal). This class is used by <a class="el" href="../../d4/df4/classmachine__learning_1_1neural__network_1_1_neural_network.html">NeuralNetwork</a> class to store layers. </p>
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<div class="textblock"><p><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">neural_network::layers::DenseLayer</a> class is used to store all necessary information about the layers (i.e. neurons, activation and kernel). This class is used by <a class="el" href="../../d4/df4/classmachine__learning_1_1neural__network_1_1_neural_network.html">NeuralNetwork</a> class to store layers. </p>
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</div><h2 class="groupheader">Constructor & Destructor Documentation</h2>
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<a id="a51c2b942ecf10625780c6bb9d5c50ff1"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a51c2b942ecf10625780c6bb9d5c50ff1">◆ </a></span>DenseLayer() <span class="overload">[1/4]</span></h2>
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<a id="a11046825be0b6dbb73fbe834aa49200e"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a11046825be0b6dbb73fbe834aa49200e">◆ </a></span>DenseLayer() <span class="overload">[1/4]</span></h2>
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<div class="memitem">
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<div class="memproto">
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@@ -168,13 +168,13 @@ int </td><td class="memItemRight" valign="bottom"><b>neurons</b></td></tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/pair.html">std::pair</a>< size_t, size_t > & </td>
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<td class="paramname"><em>kernal_shape</em>, </td>
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<td class="paramname"><em>kernel_shape</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const bool & </td>
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<td class="paramname"><em>random_kernal</em> </td>
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<td class="paramname"><em>random_kernel</em> </td>
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</tr>
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<tr>
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<td></td>
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@@ -192,8 +192,8 @@ int </td><td class="memItemRight" valign="bottom"><b>neurons</b></td></tr>
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<table class="params">
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<tr><td class="paramname">neurons</td><td>number of neurons </td></tr>
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<tr><td class="paramname">activation</td><td>activation function for layer </td></tr>
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<tr><td class="paramname">kernal_shape</td><td>shape of kernal </td></tr>
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<tr><td class="paramname">random_kernal</td><td>flag for whether to intialize kernal randomly </td></tr>
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<tr><td class="paramname">kernel_shape</td><td>shape of kernel </td></tr>
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<tr><td class="paramname">random_kernel</td><td>flag for whether to intialize kernel randomly </td></tr>
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</table>
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</dd>
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</dl>
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@@ -224,24 +224,24 @@ int </td><td class="memItemRight" valign="bottom"><b>neurons</b></td></tr>
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<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  }</div>
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<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  this->activation = activation; <span class="comment">// Setting activation name</span></div>
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<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  this->neurons = neurons; <span class="comment">// Setting number of neurons</span></div>
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<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// Initialize kernal according to flag</span></div>
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<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">if</span> (random_kernal) {</div>
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<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="../../d8/d77/namespacemachine__learning.html#a73ee7ed3546ab9e8792a92336d0d14ab">uniform_random_initialization</a>(kernal, kernal_shape, -1.0, 1.0);</div>
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<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// Initialize kernel according to flag</span></div>
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<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">if</span> (random_kernel) {</div>
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<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="../../d8/d77/namespacemachine__learning.html#a73ee7ed3546ab9e8792a92336d0d14ab">uniform_random_initialization</a>(kernel, kernel_shape, -1.0, 1.0);</div>
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<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="../../d8/d77/namespacemachine__learning.html#abf136b863d804899647f46eeb2e1392b">unit_matrix_initialization</a>(kernal, kernal_shape);</div>
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<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="../../d8/d77/namespacemachine__learning.html#abf136b863d804899647f46eeb2e1392b">unit_matrix_initialization</a>(kernel, kernel_shape);</div>
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<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  }</div>
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<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  }</div>
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</div><!-- fragment --><div class="dynheader">
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<div class="dyncontent">
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<div class="center"><iframe scrolling="no" frameborder="0" src="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer_a51c2b942ecf10625780c6bb9d5c50ff1_cgraph.svg" width="616" height="220"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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<div class="center"><iframe scrolling="no" frameborder="0" src="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer_a11046825be0b6dbb73fbe834aa49200e_cgraph.svg" width="616" height="220"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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<a id="a04b8e21316458436c8851959928c3964"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a04b8e21316458436c8851959928c3964">◆ </a></span>DenseLayer() <span class="overload">[2/4]</span></h2>
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<a id="a35ab6f1b2840f89a858ca36b78739b69"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a35ab6f1b2840f89a858ca36b78739b69">◆ </a></span>DenseLayer() <span class="overload">[2/4]</span></h2>
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@@ -265,7 +265,7 @@ Here is the call graph for this function:</div>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>< <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>< double >> & </td>
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<td class="paramname"><em>kernal</em> </td>
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<td class="paramname"><em>kernel</em> </td>
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</tr>
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<tr>
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<td></td>
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@@ -283,7 +283,7 @@ Here is the call graph for this function:</div>
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<table class="params">
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<tr><td class="paramname">neurons</td><td>number of neurons </td></tr>
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<tr><td class="paramname">activation</td><td>activation function for layer </td></tr>
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<tr><td class="paramname">kernal</td><td>values of kernal (useful in loading model) </td></tr>
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<tr><td class="paramname">kernel</td><td>values of kernel (useful in loading model) </td></tr>
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</table>
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</dd>
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</dl>
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@@ -314,12 +314,12 @@ Here is the call graph for this function:</div>
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<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  }</div>
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<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  this->activation = activation; <span class="comment">// Setting activation name</span></div>
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<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  this->neurons = neurons; <span class="comment">// Setting number of neurons</span></div>
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<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  this->kernal = kernal; <span class="comment">// Setting supplied kernal values</span></div>
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<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  this->kernel = kernel; <span class="comment">// Setting supplied kernel values</span></div>
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<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  }</div>
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</div><!-- fragment --><div class="dynheader">
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<div class="dyncontent">
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<div class="center"><iframe scrolling="no" frameborder="0" src="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer_a04b8e21316458436c8851959928c3964_cgraph.svg" width="327" height="88"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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<div class="center"><iframe scrolling="no" frameborder="0" src="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer_a35ab6f1b2840f89a858ca36b78739b69_cgraph.svg" width="327" height="88"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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</div>
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@@ -1,7 +1,7 @@
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var classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer =
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[
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a51c2b942ecf10625780c6bb9d5c50ff1", null ],
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a04b8e21316458436c8851959928c3964", null ],
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a11046825be0b6dbb73fbe834aa49200e", null ],
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a35ab6f1b2840f89a858ca36b78739b69", null ],
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a2871146feaaa453558239df67b21e0d2", null ],
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[ "~DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#ac9cda9453c4a0caf5bae7f9213b019a0", null ],
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[ "DenseLayer", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a6c859e3737aa88b29854df0347b29f4e", null ],
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@@ -10,6 +10,6 @@ var classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer =
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[ "activation", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a891264e2eb1357b2b3282e5532250869", null ],
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[ "activation_function", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a8e4c57922478ccc2b7c6277c05608714", null ],
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[ "dactivation_function", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#acc6cfdcc9d6e5170340abae63234a442", null ],
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[ "kernal", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a2e3fb82813c0fb305d6330867dd42ac8", null ],
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[ "kernel", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a494d39f6c367071d1fd31b3c1caf1a7d", null ],
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[ "neurons", "dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#ace9c37dd1322d3745de9713c90df8003", null ]
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];
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