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<div class="title">machine_learning::neural_network::layers::DenseLayer Class Reference</div> </div>
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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="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="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="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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<tr class="memitem:a8809e6df990f37c85c06474dd955cb2b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html#a8809e6df990f37c85c06474dd955cb2b">operator=</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="memitem:a6c859e3737aa88b29854df0347b29f4e"><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#a6c859e3737aa88b29854df0347b29f4e">DenseLayer</a> (<a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> &&)=default</td></tr>
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<tr class="memitem:a8e4c57922478ccc2b7c6277c05608714"><td class="memItemLeft" align="right" valign="top"><a id="a8e4c57922478ccc2b7c6277c05608714"></a>
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double(* </td><td class="memItemRight" valign="bottom"><b>activation_function</b> )(const double &)</td></tr>
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double(* </td><td class="memItemRight" valign="bottom"><b>dactivation_function</b> )(const double &)</td></tr>
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int </td><td class="memItemRight" valign="bottom"><b>neurons</b></td></tr>
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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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<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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<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><h2 class="groupheader">Constructor & Destructor Documentation</h2>
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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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<td class="memname">machine_learning::neural_network::layers::DenseLayer::DenseLayer </td>
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<td>(</td>
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<p>Constructor for <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">neural_network::layers::DenseLayer</a> class </p><dl class="params"><dt>Parameters</dt><dd>
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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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<div class="fragment"><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div>
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<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// Choosing activation (and it's derivative)</span></div>
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<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span> (activation == <span class="stringliteral">"sigmoid"</span>) {</div>
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<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  activation_function = neural_network::activations::sigmoid;</div>
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<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  dactivation_function = neural_network::activations::sigmoid;</div>
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<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div>
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<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"relu"</span>) {</div>
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<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  activation_function = neural_network::activations::relu;</div>
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<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  dactivation_function = neural_network::activations::drelu;</div>
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<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  }</div>
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<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"tanh"</span>) {</div>
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<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  activation_function = neural_network::activations::tanh;</div>
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<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  dactivation_function = neural_network::activations::dtanh;</div>
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<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  }</div>
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<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"none"</span>) {</div>
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<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// Set identity function in casse of none is supplied</span></div>
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<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  activation_function = neural_network::util_functions::identity_function;</div>
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<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  dactivation_function = neural_network::util_functions::identity_function;</div>
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<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  }</div>
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<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="comment">// If supplied activation is invalid</span></div>
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<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << <span class="stringliteral">"ERROR: Invalid argument for layer -> constructor -> activation, "</span>;</div>
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<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << <span class="stringliteral">"Expected from {none, sigmoid, relu, tanh} got "</span>;</div>
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<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << activation << <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
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<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a>(EXIT_FAILURE);</div>
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<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div>
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<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">this</span> -> activation = activation; <span class="comment">// Setting activation name</span></div>
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<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">this</span> -> neurons = neurons; <span class="comment">// Setting number of neurons</span></div>
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<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Initialize kernal according to flag</span></div>
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<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">if</span>(random_kernal) {</div>
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<div class="line"><a name="l00183"></a><span class="lineno"> 183</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="l00184"></a><span class="lineno"> 184</span>  }</div>
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<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00186"></a><span class="lineno"> 186</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="l00187"></a><span class="lineno"> 187</span>  }</div>
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<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  }</div>
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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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<h2 class="memtitle"><span class="permalink"><a href="#a04b8e21316458436c8851959928c3964">◆ </a></span>DenseLayer() <span class="overload">[2/4]</span></h2>
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<td class="memname">machine_learning::neural_network::layers::DenseLayer::DenseLayer </td>
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<td>(</td>
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<td class="paramtype">const int & </td>
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<td class="paramname"><em>neurons</em>, </td>
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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/string/basic_string.html">std::string</a> & </td>
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<td class="paramname"><em>activation</em>, </td>
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<td class="paramkey"></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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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</div><div class="memdoc">
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<p>Constructor for <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">neural_network::layers::DenseLayer</a> class </p><dl class="params"><dt>Parameters</dt><dd>
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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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</table>
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</dl>
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<div class="fragment"><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  {</div>
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<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// Choosing activation (and it's derivative)</span></div>
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<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">if</span> (activation == <span class="stringliteral">"sigmoid"</span>) {</div>
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<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  activation_function = neural_network::activations::sigmoid;</div>
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<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  dactivation_function = neural_network::activations::sigmoid;</div>
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<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  }</div>
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<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"relu"</span>) {</div>
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<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  activation_function = neural_network::activations::relu;</div>
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<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  dactivation_function = neural_network::activations::drelu;</div>
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<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div>
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<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"tanh"</span>) {</div>
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<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  activation_function = neural_network::activations::tanh;</div>
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<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  dactivation_function = neural_network::activations::dtanh;</div>
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<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div>
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<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (activation == <span class="stringliteral">"none"</span>) {</div>
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<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// Set identity function in casse of none is supplied</span></div>
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<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  activation_function = neural_network::util_functions::identity_function;</div>
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<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  dactivation_function = neural_network::util_functions::identity_function;</div>
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<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div>
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<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="comment">// If supplied activation is invalid</span></div>
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<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << <span class="stringliteral">"ERROR: Invalid argument for layer -> constructor -> activation, "</span>;</div>
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<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << <span class="stringliteral">"Expected from {none, sigmoid, relu, tanh} got "</span>;</div>
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<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> << activation << <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
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<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a>(EXIT_FAILURE);</div>
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<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  }</div>
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<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keyword">this</span> -> activation = activation; <span class="comment">// Setting activation name</span></div>
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<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keyword">this</span> -> neurons = neurons; <span class="comment">// Setting number of neurons</span></div>
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<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">this</span> -> kernal = kernal; <span class="comment">// Setting supplied kernal values </span></div>
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<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div>
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</div><!-- fragment --><div class="dynheader">
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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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<h2 class="memtitle"><span class="permalink"><a href="#a2871146feaaa453558239df67b21e0d2">◆ </a></span>DenseLayer() <span class="overload">[3/4]</span></h2>
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<td class="memname">machine_learning::neural_network::layers::DenseLayer::DenseLayer </td>
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<td>(</td>
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<td class="paramtype">const <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> & </td>
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<td class="paramname"><em>layer</em></td><td>)</td>
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<p>Copy Constructor for class <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a>.</p>
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<a id="ac9cda9453c4a0caf5bae7f9213b019a0"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#ac9cda9453c4a0caf5bae7f9213b019a0">◆ </a></span>~DenseLayer()</h2>
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<td class="memname">machine_learning::neural_network::layers::DenseLayer::~DenseLayer </td>
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<p>Destructor for class <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a>. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a6c859e3737aa88b29854df0347b29f4e">◆ </a></span>DenseLayer() <span class="overload">[4/4]</span></h2>
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<td class="memname">machine_learning::neural_network::layers::DenseLayer::DenseLayer </td>
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<td class="paramtype"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> && </td>
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<p>Move constructor for class <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> </p>
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<h2 class="groupheader">Member Function Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a8809e6df990f37c85c06474dd955cb2b">◆ </a></span>operator=() <span class="overload">[1/2]</span></h2>
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<td class="memname"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a>& machine_learning::neural_network::layers::DenseLayer::operator= </td>
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<td class="paramtype">const <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> & </td>
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<p>Copy assignment operator for class <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a6385ad4d8186b8a74b17e4a8dc41da11">◆ </a></span>operator=() <span class="overload">[2/2]</span></h2>
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<td class="memname"><a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a>& machine_learning::neural_network::layers::DenseLayer::operator= </td>
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<p>Move assignment operator for class <a class="el" href="../../dc/d93/classmachine__learning_1_1neural__network_1_1layers_1_1_dense_layer.html">DenseLayer</a> </p>
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<hr/>The documentation for this class was generated from the following file:<ul>
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<div class="ttc" id="anamespacemachine__learning_html_abf136b863d804899647f46eeb2e1392b"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#abf136b863d804899647f46eeb2e1392b">machine_learning::unit_matrix_initialization</a></div><div class="ttdeci">void unit_matrix_initialization(std::vector< std::valarray< T >> &A, const std::pair< size_t, size_t > &shape)</div><div class="ttdef"><b>Definition:</b> vector_ops.hpp:189</div></div>
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<div class="ttc" id="abasic_ostream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a></div></div>
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