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<a href="rnn_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#ifndef MLPACK_METHODS_ANN_RNN_HPP</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#define MLPACK_METHODS_ANN_RNN_HPP</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="prereqs_8hpp.html">mlpack/prereqs.hpp</a>&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="delete__visitor_8hpp.html">visitor/delete_visitor.hpp</a>&quot;</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="delta__visitor_8hpp.html">visitor/delta_visitor.hpp</a>&quot;</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="output__parameter__visitor_8hpp.html">visitor/output_parameter_visitor.hpp</a>&quot;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="reset__visitor_8hpp.html">visitor/reset_visitor.hpp</a>&quot;</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="weight__size__visitor_8hpp.html">visitor/weight_size_visitor.hpp</a>&quot;</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="layer__types_8hpp.html">mlpack/methods/ann/layer/layer_types.hpp</a>&gt;</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="ann_2init__rules_2random__init_8hpp.html">mlpack/methods/ann/init_rules/random_init.hpp</a>&gt;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="sgd_8hpp.html">mlpack/core/optimizers/sgd/sgd.hpp</a>&gt;</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacemlpack.html">mlpack</a> {</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="keyword">namespace </span>ann {</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="keyword">template</span>&lt;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keyword">typename</span> OutputLayerType = NegativeLogLikelihood&lt;&gt;,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keyword">typename</span> InitializationRuleType = RandomInitialization</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;&gt;</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html"> 40</a></span>&#160;<span class="keyword">class </span><a class="code" href="classmlpack_1_1ann_1_1RNN.html">RNN</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;{</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a7fe3f40e16983e49567690459958e63e"> 44</a></span>&#160; <span class="keyword">using</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html">NetworkType</a> = <a class="code" href="classmlpack_1_1ann_1_1RNN.html">RNN&lt;OutputLayerType, InitializationRuleType&gt;</a>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a8b2407c392dddfe13e890790d5ca9b17">RNN</a>(<span class="keyword">const</span> <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#abcc7132ff103b44854f75f4706e19bad">rho</a>,</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a40cf846d74a3fa9c530902ec8a6776eb">single</a> = <span class="keyword">false</span>,</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; OutputLayerType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4c86c4c8a443daeb1d19669260359f66">outputLayer</a> = OutputLayerType(),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; InitializationRuleType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a64a31f246a5f15b639eab5182cb0c9b3">initializeRule</a> = InitializationRuleType());</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a8b2407c392dddfe13e890790d5ca9b17">RNN</a>(<span class="keyword">const</span> arma::mat&amp; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#abb896f990996968bb7fed3d284e2b3e1">predictors</a>,</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keyword">const</span> arma::mat&amp; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4b33d09ea1a798f99311ca25d1ca2769">responses</a>,</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> rho,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a40cf846d74a3fa9c530902ec8a6776eb">single</a> = <span class="keyword">false</span>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; OutputLayerType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4c86c4c8a443daeb1d19669260359f66">outputLayer</a> = OutputLayerType(),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; InitializationRuleType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a64a31f246a5f15b639eab5182cb0c9b3">initializeRule</a> = InitializationRuleType());</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#af514c16592d13b87bec119f671e0b45b">~RNN</a>();</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keyword">template</span>&lt;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keyword">template</span>&lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>OptimizerType = <a class="code" href="classmlpack_1_1optimization_1_1SGD.html">mlpack::optimization::StandardSGD</a></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; &gt;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aa144efe7e1f98c2be93f39a79c4982f5">Train</a>(<span class="keyword">const</span> arma::mat&amp; predictors,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">const</span> arma::mat&amp; responses,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; OptimizerType&lt;NetworkType&gt;&amp; optimizer);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keyword">template</span>&lt;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keyword">template</span>&lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>OptimizerType = <a class="code" href="classmlpack_1_1optimization_1_1SGD.html">mlpack::optimization::StandardSGD</a></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; &gt;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aa144efe7e1f98c2be93f39a79c4982f5">Train</a>(<span class="keyword">const</span> arma::mat&amp; predictors, <span class="keyword">const</span> arma::mat&amp; responses);</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#adb34b68774a0dc10af834584ab9d3787">Predict</a>(arma::mat&amp; predictors, arma::mat&amp; responses);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordtype">double</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4998a414624de0d2985280d7abfaf3d9">Evaluate</a>(<span class="keyword">const</span> arma::mat&amp; <span class="comment">/* parameters */</span>,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> i,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a22697aa22257c189403910c69d9e4386">deterministic</a> = <span class="keyword">true</span>);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a5bc5a562cce79dd1fa377f0d6e1ac090">Gradient</a>(<span class="keyword">const</span> arma::mat&amp; parameters,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> i,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; arma::mat&amp; gradient);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <span class="comment">/*</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160;<span class="comment"> * Add a new module to the model.</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;<span class="comment"> * @param layer The Layer to be added to the model.</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <span class="keyword">template</span>&lt;<span class="keyword">typename</span> LayerType&gt;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a48d81c7b42355f9fe259bfe0a71525ed"> 168</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a48d81c7b42355f9fe259bfe0a71525ed">Add</a>(<span class="keyword">const</span> LayerType&amp; layer) { <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8">network</a>.push_back(<span class="keyword">new</span> LayerType(layer)); }</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="comment">/*</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;<span class="comment"> * Add a new module to the model.</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;<span class="comment"> * @param args The layer parameter.</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="keyword">template</span> &lt;<span class="keyword">class </span>LayerType, <span class="keyword">class</span>... Args&gt;</div><div class="line"><a name="l00176"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a4ca8786c54768027d3d957ac475a977a"> 176</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4ca8786c54768027d3d957ac475a977a">Add</a>(Args... args) { <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8">network</a>.push_back(<span class="keyword">new</span> LayerType(args...)); }</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <span class="comment">/*</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;<span class="comment"> * Add a new module to the model.</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160;<span class="comment"> * @param layer The Layer to be added to the model.</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00183"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#aecb5a6f994b1770f46465d6b75290a83"> 183</a></span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aecb5a6f994b1770f46465d6b75290a83">Add</a>(<a class="code" href="namespacemlpack_1_1ann.html#ab8d68f366a3cbbbc1f0f4990ec70c645">LayerTypes</a> layer) { <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8">network</a>.push_back(layer); }</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#ace974e0ffc8ce9afbf1cb66c30a77616"> 186</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#ace974e0ffc8ce9afbf1cb66c30a77616">NumFunctions</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4597b72b95e107847828d4283add180c">numFunctions</a>; }</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a481790a45dd3cf1441d08805de6e4e10"> 189</a></span>&#160; <span class="keyword">const</span> arma::mat&amp; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a481790a45dd3cf1441d08805de6e4e10">Parameters</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#acb2363276833b041e9cc04efe3e6da7a">parameter</a>; }</div><div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#aeaad2ebf3c00999459cd30351ea52d9c"> 191</a></span>&#160; arma::mat&amp; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aeaad2ebf3c00999459cd30351ea52d9c">Parameters</a>() { <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#acb2363276833b041e9cc04efe3e6da7a">parameter</a>; }</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <span class="keyword">template</span>&lt;<span class="keyword">typename</span> Archive&gt;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#abdfa2d68bb7c68c47a5223f0097eeb96">Serialize</a>(Archive&amp; ar, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <span class="comment">/* version */</span>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="comment">// Helper functions.</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160;<span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#ab908da54d633299a42b749b2ac3d4552">Forward</a>(arma::mat&amp;&amp; input);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a8d5cd6ac122a10f265b96c769e339b7b">Backward</a>();</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a5bc5a562cce79dd1fa377f0d6e1ac090">Gradient</a>();</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <span class="comment">/*</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160;<span class="comment"> * Predict the response of the given input sequence.</span></div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160;<span class="comment"> * @param predictors Input predictors.</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160;<span class="comment"> * @param responses Vector to put output prediction of a response into.</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#ae3c44882be75a13e4f53eee4131aba23">SinglePredict</a>(<span class="keyword">const</span> arma::mat&amp; predictors, arma::mat&amp; responses);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a215b8ed02c7c644aad17d57f7f6beb7c">ResetParameters</a>();</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a434a0fec69daad59ccfdf1dab95a71d4">ResetDeterministic</a>();</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aea2e221c136342d54c9bebdd9599219e">ResetGradients</a>(arma::mat&amp; gradient);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#abcc7132ff103b44854f75f4706e19bad"> 244</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#abcc7132ff103b44854f75f4706e19bad">rho</a>;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160;</div><div class="line"><a name="l00247"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a4c86c4c8a443daeb1d19669260359f66"> 247</a></span>&#160; OutputLayerType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4c86c4c8a443daeb1d19669260359f66">outputLayer</a>;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;</div><div class="line"><a name="l00251"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a64a31f246a5f15b639eab5182cb0c9b3"> 251</a></span>&#160; InitializationRuleType <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a64a31f246a5f15b639eab5182cb0c9b3">initializeRule</a>;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160;</div><div class="line"><a name="l00254"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a0b4965081bcc535dfea271f8918e8ff2"> 254</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a0b4965081bcc535dfea271f8918e8ff2">inputSize</a>;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160;</div><div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#ad5e15ca242906bbaa497490ae1f6e3b2"> 257</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#ad5e15ca242906bbaa497490ae1f6e3b2">outputSize</a>;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160;</div><div class="line"><a name="l00260"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a62f4a2851cf0f88aab7e13de375fcb16"> 260</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a62f4a2851cf0f88aab7e13de375fcb16">targetSize</a>;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160;</div><div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a8eaaf6b15ce560a7e31d00d94108a8d0"> 263</a></span>&#160; <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a8eaaf6b15ce560a7e31d00d94108a8d0">reset</a>;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160;</div><div class="line"><a name="l00266"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a40cf846d74a3fa9c530902ec8a6776eb"> 266</a></span>&#160; <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a40cf846d74a3fa9c530902ec8a6776eb">single</a>;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160;</div><div class="line"><a name="l00269"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8"> 269</a></span>&#160; std::vector&lt;LayerTypes&gt; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8">network</a>;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;</div><div class="line"><a name="l00272"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#abb896f990996968bb7fed3d284e2b3e1"> 272</a></span>&#160; arma::mat <a class="code" href="classmlpack_1_1ann_1_1RNN.html#abb896f990996968bb7fed3d284e2b3e1">predictors</a>;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160;</div><div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a4b33d09ea1a798f99311ca25d1ca2769"> 275</a></span>&#160; arma::mat <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4b33d09ea1a798f99311ca25d1ca2769">responses</a>;</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#acb2363276833b041e9cc04efe3e6da7a"> 278</a></span>&#160; arma::mat <a class="code" href="classmlpack_1_1ann_1_1RNN.html#acb2363276833b041e9cc04efe3e6da7a">parameter</a>;</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160;</div><div class="line"><a name="l00281"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a4597b72b95e107847828d4283add180c"> 281</a></span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a4597b72b95e107847828d4283add180c">numFunctions</a>;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160;</div><div class="line"><a name="l00284"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#acb5cefe5af510735a51c02d946fcfb58"> 284</a></span>&#160; arma::mat <a class="code" href="classmlpack_1_1ann_1_1RNN.html#acb5cefe5af510735a51c02d946fcfb58">error</a>;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160;</div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#adc9be34740bd9da29e7e648667f91094"> 287</a></span>&#160; arma::mat <a class="code" href="classmlpack_1_1ann_1_1RNN.html#adc9be34740bd9da29e7e648667f91094">currentInput</a>;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160;</div><div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a57a1993f3c0cefee06d106b9bd68025c"> 290</a></span>&#160; <a class="code" href="classmlpack_1_1ann_1_1DeltaVisitor.html">DeltaVisitor</a> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a57a1993f3c0cefee06d106b9bd68025c">deltaVisitor</a>;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160;</div><div class="line"><a name="l00293"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a0a3e30be54387448a4a678ee04e89472"> 293</a></span>&#160; <a class="code" href="classmlpack_1_1ann_1_1OutputParameterVisitor.html">OutputParameterVisitor</a> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a0a3e30be54387448a4a678ee04e89472">outputParameterVisitor</a>;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160;</div><div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a9e90e2c565468e9dcf33e305e04297fd"> 296</a></span>&#160; std::vector&lt;arma::mat&gt; <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a9e90e2c565468e9dcf33e305e04297fd">moduleOutputParameter</a>;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160;</div><div class="line"><a name="l00299"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a456c19be7024124922ee318e8aceb993"> 299</a></span>&#160; <a class="code" href="classmlpack_1_1ann_1_1WeightSizeVisitor.html">WeightSizeVisitor</a> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a456c19be7024124922ee318e8aceb993">weightSizeVisitor</a>;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160;</div><div class="line"><a name="l00302"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#aa2e5c1acffd87cb3cbd82ebcff16bb58"> 302</a></span>&#160; <a class="code" href="classmlpack_1_1ann_1_1ResetVisitor.html">ResetVisitor</a> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#aa2e5c1acffd87cb3cbd82ebcff16bb58">resetVisitor</a>;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160;</div><div class="line"><a name="l00305"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a1a1a8db8d4f76cb0995a49f524325060"> 305</a></span>&#160; <a class="code" href="classmlpack_1_1ann_1_1DeleteVisitor.html">DeleteVisitor</a> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a1a1a8db8d4f76cb0995a49f524325060">deleteVisitor</a>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160;</div><div class="line"><a name="l00308"></a><span class="lineno"><a class="line" href="classmlpack_1_1ann_1_1RNN.html#a22697aa22257c189403910c69d9e4386"> 308</a></span>&#160; <span class="keywordtype">bool</span> <a class="code" href="classmlpack_1_1ann_1_1RNN.html#a22697aa22257c189403910c69d9e4386">deterministic</a>;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160;}; <span class="comment">// class RNN</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160;} <span class="comment">// namespace ann</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160;} <span class="comment">// namespace mlpack</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160;<span class="comment">// Include implementation.</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160;<span class="preprocessor">#include &quot;rnn_impl.hpp&quot;</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160;<span class="preprocessor">#endif</span></div><div class="ttc" id="classmlpack_1_1ann_1_1DeleteVisitor_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1DeleteVisitor.html">mlpack::ann::DeleteVisitor</a></div><div class="ttdoc">DeleteVisitor executes the destructor of the instantiated object. </div><div class="ttdef"><b>Definition:</b> <a href="delete__visitor_8hpp_source.html#l00027">delete_visitor.hpp:27</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a1a1a8db8d4f76cb0995a49f524325060"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a1a1a8db8d4f76cb0995a49f524325060">mlpack::ann::RNN::deleteVisitor</a></div><div class="ttdeci">DeleteVisitor deleteVisitor</div><div class="ttdoc">Locally-stored delete visitor. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00305">rnn.hpp:305</a></div></div>
<div class="ttc" id="ann_2init__rules_2random__init_8hpp_html"><div class="ttname"><a href="ann_2init__rules_2random__init_8hpp.html">random_init.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4597b72b95e107847828d4283add180c"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4597b72b95e107847828d4283add180c">mlpack::ann::RNN::numFunctions</a></div><div class="ttdeci">size_t numFunctions</div><div class="ttdoc">The number of separable functions (the number of predictor points). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00281">rnn.hpp:281</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_abb896f990996968bb7fed3d284e2b3e1"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#abb896f990996968bb7fed3d284e2b3e1">mlpack::ann::RNN::predictors</a></div><div class="ttdeci">arma::mat predictors</div><div class="ttdoc">The matrix of data points (predictors). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00272">rnn.hpp:272</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_acb5cefe5af510735a51c02d946fcfb58"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#acb5cefe5af510735a51c02d946fcfb58">mlpack::ann::RNN::error</a></div><div class="ttdeci">arma::mat error</div><div class="ttdoc">The current error for the backward pass. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00284">rnn.hpp:284</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_af514c16592d13b87bec119f671e0b45b"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#af514c16592d13b87bec119f671e0b45b">mlpack::ann::RNN::~RNN</a></div><div class="ttdeci">~RNN()</div><div class="ttdoc">Destructor to release allocated memory. </div></div>
<div class="ttc" id="namespacemlpack_html"><div class="ttname"><a href="namespacemlpack.html">mlpack</a></div><div class="ttdoc">Linear algebra utility functions, generally performed on matrices or vectors. </div><div class="ttdef"><b>Definition:</b> <a href="binarize_8hpp_source.html#l00018">binarize.hpp:18</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a8eaaf6b15ce560a7e31d00d94108a8d0"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a8eaaf6b15ce560a7e31d00d94108a8d0">mlpack::ann::RNN::reset</a></div><div class="ttdeci">bool reset</div><div class="ttdoc">Indicator if we already trained the model. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00263">rnn.hpp:263</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a5bc5a562cce79dd1fa377f0d6e1ac090"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a5bc5a562cce79dd1fa377f0d6e1ac090">mlpack::ann::RNN::Gradient</a></div><div class="ttdeci">void Gradient()</div><div class="ttdoc">Iterate through all layer modules and update the the gradient using the layer defined optimizer...</div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a8b2407c392dddfe13e890790d5ca9b17"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a8b2407c392dddfe13e890790d5ca9b17">mlpack::ann::RNN::RNN</a></div><div class="ttdeci">RNN(const size_t rho, const bool single=false, OutputLayerType outputLayer=OutputLayerType(), InitializationRuleType initializeRule=InitializationRuleType())</div><div class="ttdoc">Create the RNN object with the given predictors and responses set (this is the set that is used to tr...</div></div>
<div class="ttc" id="reset__visitor_8hpp_html"><div class="ttname"><a href="reset__visitor_8hpp.html">reset_visitor.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_ab908da54d633299a42b749b2ac3d4552"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#ab908da54d633299a42b749b2ac3d4552">mlpack::ann::RNN::Forward</a></div><div class="ttdeci">void Forward(arma::mat &amp;&amp;input)</div><div class="ttdoc">The Forward algorithm (part of the Forward-Backward algorithm). </div></div>
<div class="ttc" id="prereqs_8hpp_html"><div class="ttname"><a href="prereqs_8hpp.html">prereqs.hpp</a></div><div class="ttdoc">The core includes that mlpack expects; standard C++ includes and Armadillo. </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a22697aa22257c189403910c69d9e4386"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a22697aa22257c189403910c69d9e4386">mlpack::ann::RNN::deterministic</a></div><div class="ttdeci">bool deterministic</div><div class="ttdoc">The current evaluation mode (training or testing). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00308">rnn.hpp:308</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_aeaad2ebf3c00999459cd30351ea52d9c"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#aeaad2ebf3c00999459cd30351ea52d9c">mlpack::ann::RNN::Parameters</a></div><div class="ttdeci">arma::mat &amp; Parameters()</div><div class="ttdoc">Modify the initial point for the optimization. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00191">rnn.hpp:191</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1WeightSizeVisitor_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1WeightSizeVisitor.html">mlpack::ann::WeightSizeVisitor</a></div><div class="ttdoc">WeightSizeVisitor returns the number of weights of the given module. </div><div class="ttdef"><b>Definition:</b> <a href="weight__size__visitor_8hpp_source.html#l00028">weight_size_visitor.hpp:28</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_aa2e5c1acffd87cb3cbd82ebcff16bb58"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#aa2e5c1acffd87cb3cbd82ebcff16bb58">mlpack::ann::RNN::resetVisitor</a></div><div class="ttdeci">ResetVisitor resetVisitor</div><div class="ttdoc">Locally-stored reset visitor. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00302">rnn.hpp:302</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_adc9be34740bd9da29e7e648667f91094"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#adc9be34740bd9da29e7e648667f91094">mlpack::ann::RNN::currentInput</a></div><div class="ttdeci">arma::mat currentInput</div><div class="ttdoc">THe current input of the forward/backward pass. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00287">rnn.hpp:287</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a0a3e30be54387448a4a678ee04e89472"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a0a3e30be54387448a4a678ee04e89472">mlpack::ann::RNN::outputParameterVisitor</a></div><div class="ttdeci">OutputParameterVisitor outputParameterVisitor</div><div class="ttdoc">Locally-stored output parameter visitor. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00293">rnn.hpp:293</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4c86c4c8a443daeb1d19669260359f66"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4c86c4c8a443daeb1d19669260359f66">mlpack::ann::RNN::outputLayer</a></div><div class="ttdeci">OutputLayerType outputLayer</div><div class="ttdoc">Instantiated outputlayer used to evaluate the network. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00247">rnn.hpp:247</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html">mlpack::ann::RNN</a></div><div class="ttdoc">Implementation of a standard recurrent neural network container. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00040">rnn.hpp:40</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a0b4965081bcc535dfea271f8918e8ff2"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a0b4965081bcc535dfea271f8918e8ff2">mlpack::ann::RNN::inputSize</a></div><div class="ttdeci">size_t inputSize</div><div class="ttdoc">The input size. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00254">rnn.hpp:254</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_aea2e221c136342d54c9bebdd9599219e"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#aea2e221c136342d54c9bebdd9599219e">mlpack::ann::RNN::ResetGradients</a></div><div class="ttdeci">void ResetGradients(arma::mat &amp;gradient)</div><div class="ttdoc">Reset the gradient for all modules that implement the Gradient function. </div></div>
<div class="ttc" id="delete__visitor_8hpp_html"><div class="ttname"><a href="delete__visitor_8hpp.html">delete_visitor.hpp</a></div></div>
<div class="ttc" id="sgd_8hpp_html"><div class="ttname"><a href="sgd_8hpp.html">sgd.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a62f4a2851cf0f88aab7e13de375fcb16"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a62f4a2851cf0f88aab7e13de375fcb16">mlpack::ann::RNN::targetSize</a></div><div class="ttdeci">size_t targetSize</div><div class="ttdoc">The target size. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00260">rnn.hpp:260</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4ca8786c54768027d3d957ac475a977a"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4ca8786c54768027d3d957ac475a977a">mlpack::ann::RNN::Add</a></div><div class="ttdeci">void Add(Args...args)</div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00176">rnn.hpp:176</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1ResetVisitor_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1ResetVisitor.html">mlpack::ann::ResetVisitor</a></div><div class="ttdoc">ResetVisitor executes the Reset() function. </div><div class="ttdef"><b>Definition:</b> <a href="reset__visitor_8hpp_source.html#l00027">reset_visitor.hpp:27</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_ace974e0ffc8ce9afbf1cb66c30a77616"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#ace974e0ffc8ce9afbf1cb66c30a77616">mlpack::ann::RNN::NumFunctions</a></div><div class="ttdeci">size_t NumFunctions() const </div><div class="ttdoc">Return the number of separable functions (the number of predictor points). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00186">rnn.hpp:186</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1OutputParameterVisitor_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1OutputParameterVisitor.html">mlpack::ann::OutputParameterVisitor</a></div><div class="ttdoc">OutputParameterVisitor exposes the output parameter of the given module. </div><div class="ttdef"><b>Definition:</b> <a href="output__parameter__visitor_8hpp_source.html#l00027">output_parameter_visitor.hpp:27</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_adb34b68774a0dc10af834584ab9d3787"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#adb34b68774a0dc10af834584ab9d3787">mlpack::ann::RNN::Predict</a></div><div class="ttdeci">void Predict(arma::mat &amp;predictors, arma::mat &amp;responses)</div><div class="ttdoc">Predict the responses to a given set of predictors. </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a434a0fec69daad59ccfdf1dab95a71d4"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a434a0fec69daad59ccfdf1dab95a71d4">mlpack::ann::RNN::ResetDeterministic</a></div><div class="ttdeci">void ResetDeterministic()</div><div class="ttdoc">Reset the module status by setting the current deterministic parameter for all modules that implement...</div></div>
<div class="ttc" id="delta__visitor_8hpp_html"><div class="ttname"><a href="delta__visitor_8hpp.html">delta_visitor.hpp</a></div></div>
<div class="ttc" id="namespacemlpack_1_1ann_html_ab8d68f366a3cbbbc1f0f4990ec70c645"><div class="ttname"><a href="namespacemlpack_1_1ann.html#ab8d68f366a3cbbbc1f0f4990ec70c645">mlpack::ann::LayerTypes</a></div><div class="ttdeci">boost::variant&lt; Add&lt; arma::mat, arma::mat &gt; *, AddMerge&lt; arma::mat, arma::mat &gt; *, BaseLayer&lt; LogisticFunction, arma::mat, arma::mat &gt; *, BaseLayer&lt; IdentityFunction, arma::mat, arma::mat &gt; *, BaseLayer&lt; TanhFunction, arma::mat, arma::mat &gt; *, BaseLayer&lt; RectifierFunction, arma::mat, arma::mat &gt; *, Concat&lt; arma::mat, arma::mat &gt; *, ConcatPerformance&lt; NegativeLogLikelihood&lt; arma::mat, arma::mat &gt;, arma::mat, arma::mat &gt; *, Constant&lt; arma::mat, arma::mat &gt; *, Convolution&lt; NaiveConvolution&lt; ValidConvolution &gt;, NaiveConvolution&lt; FullConvolution &gt;, NaiveConvolution&lt; ValidConvolution &gt;, arma::mat, arma::mat &gt; *, DropConnect&lt; arma::mat, arma::mat &gt; *, Dropout&lt; arma::mat, arma::mat &gt; *, Glimpse&lt; arma::mat, arma::mat &gt; *, HardTanH&lt; arma::mat, arma::mat &gt; *, Join&lt; arma::mat, arma::mat &gt; *, LeakyReLU&lt; arma::mat, arma::mat &gt; *, Linear&lt; arma::mat, arma::mat &gt; *, LinearNoBias&lt; arma::mat, arma::mat &gt; *, LogSoftMax&lt; arma::mat, arma::mat &gt; *, Lookup&lt; arma::mat, arma::mat &gt; *, LSTM&lt; arma::mat, arma::mat &gt; *, MaxPooling&lt; arma::mat, arma::mat &gt; *, MeanPooling&lt; arma::mat, arma::mat &gt; *, MeanSquaredError&lt; arma::mat, arma::mat &gt; *, MultiplyConstant&lt; arma::mat, arma::mat &gt; *, NegativeLogLikelihood&lt; arma::mat, arma::mat &gt; *, PReLU&lt; arma::mat, arma::mat &gt; *, Recurrent&lt; arma::mat, arma::mat &gt; *, RecurrentAttention&lt; arma::mat, arma::mat &gt; *, ReinforceNormal&lt; arma::mat, arma::mat &gt; *, Select&lt; arma::mat, arma::mat &gt; *, Sequential&lt; arma::mat, arma::mat &gt; *, VRClassReward&lt; arma::mat, arma::mat &gt; * &gt; LayerTypes</div><div class="ttdef"><b>Definition:</b> <a href="layer__types_8hpp_source.html#l00115">layer_types.hpp:115</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a8d5cd6ac122a10f265b96c769e339b7b"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a8d5cd6ac122a10f265b96c769e339b7b">mlpack::ann::RNN::Backward</a></div><div class="ttdeci">void Backward()</div><div class="ttdoc">The Backward algorithm (part of the Forward-Backward algorithm). </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4b33d09ea1a798f99311ca25d1ca2769"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4b33d09ea1a798f99311ca25d1ca2769">mlpack::ann::RNN::responses</a></div><div class="ttdeci">arma::mat responses</div><div class="ttdoc">The matrix of responses to the input data points. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00275">rnn.hpp:275</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_abdfa2d68bb7c68c47a5223f0097eeb96"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#abdfa2d68bb7c68c47a5223f0097eeb96">mlpack::ann::RNN::Serialize</a></div><div class="ttdeci">void Serialize(Archive &amp;ar, const unsigned int)</div><div class="ttdoc">Serialize the model. </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_aa144efe7e1f98c2be93f39a79c4982f5"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#aa144efe7e1f98c2be93f39a79c4982f5">mlpack::ann::RNN::Train</a></div><div class="ttdeci">void Train(const arma::mat &amp;predictors, const arma::mat &amp;responses, OptimizerType&lt; NetworkType &gt; &amp;optimizer)</div><div class="ttdoc">Train the recurrent neural network on the given input data using the given optimizer. </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a456c19be7024124922ee318e8aceb993"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a456c19be7024124922ee318e8aceb993">mlpack::ann::RNN::weightSizeVisitor</a></div><div class="ttdeci">WeightSizeVisitor weightSizeVisitor</div><div class="ttdoc">Locally-stored weight size visitor. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00299">rnn.hpp:299</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a9e90e2c565468e9dcf33e305e04297fd"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a9e90e2c565468e9dcf33e305e04297fd">mlpack::ann::RNN::moduleOutputParameter</a></div><div class="ttdeci">std::vector&lt; arma::mat &gt; moduleOutputParameter</div><div class="ttdoc">List of all module parameters for the backward pass (BBTT). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00296">rnn.hpp:296</a></div></div>
<div class="ttc" id="output__parameter__visitor_8hpp_html"><div class="ttname"><a href="output__parameter__visitor_8hpp.html">output_parameter_visitor.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a57a1993f3c0cefee06d106b9bd68025c"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a57a1993f3c0cefee06d106b9bd68025c">mlpack::ann::RNN::deltaVisitor</a></div><div class="ttdeci">DeltaVisitor deltaVisitor</div><div class="ttdoc">Locally-stored delta visitor. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00290">rnn.hpp:290</a></div></div>
<div class="ttc" id="classmlpack_1_1optimization_1_1SGD_html"><div class="ttname"><a href="classmlpack_1_1optimization_1_1SGD.html">mlpack::optimization::SGD</a></div><div class="ttdoc">Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum ...</div><div class="ttdef"><b>Definition:</b> <a href="sgd_8hpp_source.html#l00077">sgd.hpp:77</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_acb2363276833b041e9cc04efe3e6da7a"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#acb2363276833b041e9cc04efe3e6da7a">mlpack::ann::RNN::parameter</a></div><div class="ttdeci">arma::mat parameter</div><div class="ttdoc">Matrix of (trained) parameters. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00278">rnn.hpp:278</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1DeltaVisitor_html"><div class="ttname"><a href="classmlpack_1_1ann_1_1DeltaVisitor.html">mlpack::ann::DeltaVisitor</a></div><div class="ttdoc">DeltaVisitor exposes the delta parameter of the given module. </div><div class="ttdef"><b>Definition:</b> <a href="delta__visitor_8hpp_source.html#l00027">delta_visitor.hpp:27</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_ad5e15ca242906bbaa497490ae1f6e3b2"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#ad5e15ca242906bbaa497490ae1f6e3b2">mlpack::ann::RNN::outputSize</a></div><div class="ttdeci">size_t outputSize</div><div class="ttdoc">The output size. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00257">rnn.hpp:257</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_abcc7132ff103b44854f75f4706e19bad"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#abcc7132ff103b44854f75f4706e19bad">mlpack::ann::RNN::rho</a></div><div class="ttdeci">size_t rho</div><div class="ttdoc">Number of steps to backpropagate through time (BPTT). </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00244">rnn.hpp:244</a></div></div>
<div class="ttc" id="layer__types_8hpp_html"><div class="ttname"><a href="layer__types_8hpp.html">layer_types.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4049c23e47dfd069810fea73d6e93aa8"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4049c23e47dfd069810fea73d6e93aa8">mlpack::ann::RNN::network</a></div><div class="ttdeci">std::vector&lt; LayerTypes &gt; network</div><div class="ttdoc">Locally-stored model modules. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00269">rnn.hpp:269</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_ae3c44882be75a13e4f53eee4131aba23"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#ae3c44882be75a13e4f53eee4131aba23">mlpack::ann::RNN::SinglePredict</a></div><div class="ttdeci">void SinglePredict(const arma::mat &amp;predictors, arma::mat &amp;responses)</div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a4998a414624de0d2985280d7abfaf3d9"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a4998a414624de0d2985280d7abfaf3d9">mlpack::ann::RNN::Evaluate</a></div><div class="ttdeci">double Evaluate(const arma::mat &amp;, const size_t i, const bool deterministic=true)</div><div class="ttdoc">Evaluate the recurrent neural network with the given parameters. </div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a40cf846d74a3fa9c530902ec8a6776eb"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a40cf846d74a3fa9c530902ec8a6776eb">mlpack::ann::RNN::single</a></div><div class="ttdeci">bool single</div><div class="ttdoc">Only predict the last element of the input sequence. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00266">rnn.hpp:266</a></div></div>
<div class="ttc" id="weight__size__visitor_8hpp_html"><div class="ttname"><a href="weight__size__visitor_8hpp.html">weight_size_visitor.hpp</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a48d81c7b42355f9fe259bfe0a71525ed"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a48d81c7b42355f9fe259bfe0a71525ed">mlpack::ann::RNN::Add</a></div><div class="ttdeci">void Add(const LayerType &amp;layer)</div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00168">rnn.hpp:168</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a64a31f246a5f15b639eab5182cb0c9b3"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a64a31f246a5f15b639eab5182cb0c9b3">mlpack::ann::RNN::initializeRule</a></div><div class="ttdeci">InitializationRuleType initializeRule</div><div class="ttdoc">Instantiated InitializationRule object for initializing the network parameter. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00251">rnn.hpp:251</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a481790a45dd3cf1441d08805de6e4e10"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a481790a45dd3cf1441d08805de6e4e10">mlpack::ann::RNN::Parameters</a></div><div class="ttdeci">const arma::mat &amp; Parameters() const </div><div class="ttdoc">Return the initial point for the optimization. </div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00189">rnn.hpp:189</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_aecb5a6f994b1770f46465d6b75290a83"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#aecb5a6f994b1770f46465d6b75290a83">mlpack::ann::RNN::Add</a></div><div class="ttdeci">void Add(LayerTypes layer)</div><div class="ttdef"><b>Definition:</b> <a href="rnn_8hpp_source.html#l00183">rnn.hpp:183</a></div></div>
<div class="ttc" id="classmlpack_1_1ann_1_1RNN_html_a215b8ed02c7c644aad17d57f7f6beb7c"><div class="ttname"><a href="classmlpack_1_1ann_1_1RNN.html#a215b8ed02c7c644aad17d57f7f6beb7c">mlpack::ann::RNN::ResetParameters</a></div><div class="ttdeci">void ResetParameters()</div><div class="ttdoc">Reset the module infomration (weights/parameters). </div></div>
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