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<div id="projectbrief">Bayesian Network Classifiers using libtorch from scratch</div>
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<div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno"> 1</span><span class="comment">// ***************************************************************</span></div>
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<div class="line"><a id="l00002" name="l00002"></a><span class="lineno"> 2</span><span class="comment">// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez</span></div>
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<div class="line"><a id="l00003" name="l00003"></a><span class="lineno"> 3</span><span class="comment">// SPDX-FileType: SOURCE</span></div>
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<div class="line"><a id="l00004" name="l00004"></a><span class="lineno"> 4</span><span class="comment">// SPDX-License-Identifier: MIT</span></div>
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<div class="line"><a id="l00005" name="l00005"></a><span class="lineno"> 5</span><span class="comment">// ***************************************************************</span></div>
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<div class="line"><a id="l00006" name="l00006"></a><span class="lineno"> 6</span> </div>
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<div class="line"><a id="l00007" name="l00007"></a><span class="lineno"> 7</span><span class="preprocessor">#include "Node.h"</span></div>
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<div class="line"><a id="l00008" name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a id="l00009" name="l00009"></a><span class="lineno"> 9</span><span class="keyword">namespace </span>bayesnet {</div>
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<div class="line"><a id="l00010" name="l00010"></a><span class="lineno"> 10</span> </div>
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<div class="line"><a id="l00011" name="l00011"></a><span class="lineno"> 11</span> Node::Node(<span class="keyword">const</span> std::string& name)</div>
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<div class="line"><a id="l00012" name="l00012"></a><span class="lineno"> 12</span> : name(name)</div>
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<div class="line"><a id="l00013" name="l00013"></a><span class="lineno"> 13</span> {</div>
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<div class="line"><a id="l00014" name="l00014"></a><span class="lineno"> 14</span> }</div>
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<div class="line"><a id="l00015" name="l00015"></a><span class="lineno"> 15</span> <span class="keywordtype">void</span> Node::clear()</div>
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<div class="line"><a id="l00016" name="l00016"></a><span class="lineno"> 16</span> {</div>
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<div class="line"><a id="l00017" name="l00017"></a><span class="lineno"> 17</span> parents.clear();</div>
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<div class="line"><a id="l00018" name="l00018"></a><span class="lineno"> 18</span> children.clear();</div>
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<div class="line"><a id="l00019" name="l00019"></a><span class="lineno"> 19</span> cpTable = torch::Tensor();</div>
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<div class="line"><a id="l00020" name="l00020"></a><span class="lineno"> 20</span> dimensions.clear();</div>
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<div class="line"><a id="l00021" name="l00021"></a><span class="lineno"> 21</span> numStates = 0;</div>
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<div class="line"><a id="l00022" name="l00022"></a><span class="lineno"> 22</span> }</div>
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<div class="line"><a id="l00023" name="l00023"></a><span class="lineno"> 23</span> std::string Node::getName()<span class="keyword"> const</span></div>
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<div class="line"><a id="l00024" name="l00024"></a><span class="lineno"> 24</span><span class="keyword"> </span>{</div>
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<div class="line"><a id="l00025" name="l00025"></a><span class="lineno"> 25</span> <span class="keywordflow">return</span> name;</div>
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<div class="line"><a id="l00026" name="l00026"></a><span class="lineno"> 26</span> }</div>
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<div class="line"><a id="l00027" name="l00027"></a><span class="lineno"> 27</span> <span class="keywordtype">void</span> Node::addParent(Node* parent)</div>
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<div class="line"><a id="l00028" name="l00028"></a><span class="lineno"> 28</span> {</div>
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<div class="line"><a id="l00029" name="l00029"></a><span class="lineno"> 29</span> parents.push_back(parent);</div>
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<div class="line"><a id="l00030" name="l00030"></a><span class="lineno"> 30</span> }</div>
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<div class="line"><a id="l00031" name="l00031"></a><span class="lineno"> 31</span> <span class="keywordtype">void</span> Node::removeParent(Node* parent)</div>
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<div class="line"><a id="l00032" name="l00032"></a><span class="lineno"> 32</span> {</div>
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<div class="line"><a id="l00033" name="l00033"></a><span class="lineno"> 33</span> parents.erase(std::remove(parents.begin(), parents.end(), parent), parents.end());</div>
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<div class="line"><a id="l00034" name="l00034"></a><span class="lineno"> 34</span> }</div>
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<div class="line"><a id="l00035" name="l00035"></a><span class="lineno"> 35</span> <span class="keywordtype">void</span> Node::removeChild(Node* child)</div>
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<div class="line"><a id="l00036" name="l00036"></a><span class="lineno"> 36</span> {</div>
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<div class="line"><a id="l00037" name="l00037"></a><span class="lineno"> 37</span> children.erase(std::remove(children.begin(), children.end(), child), children.end());</div>
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<div class="line"><a id="l00038" name="l00038"></a><span class="lineno"> 38</span> }</div>
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<div class="line"><a id="l00039" name="l00039"></a><span class="lineno"> 39</span> <span class="keywordtype">void</span> Node::addChild(Node* child)</div>
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<div class="line"><a id="l00040" name="l00040"></a><span class="lineno"> 40</span> {</div>
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<div class="line"><a id="l00041" name="l00041"></a><span class="lineno"> 41</span> children.push_back(child);</div>
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<div class="line"><a id="l00042" name="l00042"></a><span class="lineno"> 42</span> }</div>
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<div class="line"><a id="l00043" name="l00043"></a><span class="lineno"> 43</span> std::vector<Node*>& Node::getParents()</div>
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<div class="line"><a id="l00044" name="l00044"></a><span class="lineno"> 44</span> {</div>
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<div class="line"><a id="l00045" name="l00045"></a><span class="lineno"> 45</span> <span class="keywordflow">return</span> parents;</div>
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<div class="line"><a id="l00046" name="l00046"></a><span class="lineno"> 46</span> }</div>
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<div class="line"><a id="l00047" name="l00047"></a><span class="lineno"> 47</span> std::vector<Node*>& Node::getChildren()</div>
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<div class="line"><a id="l00048" name="l00048"></a><span class="lineno"> 48</span> {</div>
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<div class="line"><a id="l00049" name="l00049"></a><span class="lineno"> 49</span> <span class="keywordflow">return</span> children;</div>
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<div class="line"><a id="l00050" name="l00050"></a><span class="lineno"> 50</span> }</div>
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<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"> 51</span> <span class="keywordtype">int</span> Node::getNumStates()<span class="keyword"> const</span></div>
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<div class="line"><a id="l00052" name="l00052"></a><span class="lineno"> 52</span><span class="keyword"> </span>{</div>
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<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"> 53</span> <span class="keywordflow">return</span> numStates;</div>
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<div class="line"><a id="l00054" name="l00054"></a><span class="lineno"> 54</span> }</div>
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<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"> 55</span> <span class="keywordtype">void</span> Node::setNumStates(<span class="keywordtype">int</span> numStates)</div>
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<div class="line"><a id="l00056" name="l00056"></a><span class="lineno"> 56</span> {</div>
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<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"> 57</span> this->numStates = numStates;</div>
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<div class="line"><a id="l00058" name="l00058"></a><span class="lineno"> 58</span> }</div>
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<div class="line"><a id="l00059" name="l00059"></a><span class="lineno"> 59</span> torch::Tensor& Node::getCPT()</div>
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<div class="line"><a id="l00060" name="l00060"></a><span class="lineno"> 60</span> {</div>
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<div class="line"><a id="l00061" name="l00061"></a><span class="lineno"> 61</span> <span class="keywordflow">return</span> cpTable;</div>
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<div class="line"><a id="l00062" name="l00062"></a><span class="lineno"> 62</span> }</div>
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<div class="line"><a id="l00063" name="l00063"></a><span class="lineno"> 63</span> <span class="comment">/*</span></div>
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<div class="line"><a id="l00064" name="l00064"></a><span class="lineno"> 64</span><span class="comment"> The MinFill criterion is a heuristic for variable elimination.</span></div>
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<div class="line"><a id="l00065" name="l00065"></a><span class="lineno"> 65</span><span class="comment"> The variable that minimizes the number of edges that need to be added to the graph to make it triangulated.</span></div>
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<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"> 66</span><span class="comment"> This is done by counting the number of edges that need to be added to the graph if the variable is eliminated.</span></div>
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<div class="line"><a id="l00067" name="l00067"></a><span class="lineno"> 67</span><span class="comment"> The variable with the minimum number of edges is chosen.</span></div>
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<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"> 68</span><span class="comment"> Here this is done computing the length of the combinations of the node neighbors taken 2 by 2.</span></div>
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<div class="line"><a id="l00069" name="l00069"></a><span class="lineno"> 69</span><span class="comment"> */</span></div>
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<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"> 70</span> <span class="keywordtype">unsigned</span> Node::minFill()</div>
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<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"> 71</span> {</div>
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<div class="line"><a id="l00072" name="l00072"></a><span class="lineno"> 72</span> std::unordered_set<std::string> neighbors;</div>
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<div class="line"><a id="l00073" name="l00073"></a><span class="lineno"> 73</span> <span class="keywordflow">for</span> (<span class="keyword">auto</span> child : children) {</div>
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<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"> 74</span> neighbors.emplace(child->getName());</div>
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<div class="line"><a id="l00075" name="l00075"></a><span class="lineno"> 75</span> }</div>
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<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"> 76</span> <span class="keywordflow">for</span> (<span class="keyword">auto</span> parent : parents) {</div>
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<div class="line"><a id="l00077" name="l00077"></a><span class="lineno"> 77</span> neighbors.emplace(parent->getName());</div>
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<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"> 78</span> }</div>
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<div class="line"><a id="l00079" name="l00079"></a><span class="lineno"> 79</span> <span class="keyword">auto</span> source = std::vector<std::string>(neighbors.begin(), neighbors.end());</div>
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<div class="line"><a id="l00080" name="l00080"></a><span class="lineno"> 80</span> <span class="keywordflow">return</span> combinations(source).size();</div>
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<div class="line"><a id="l00081" name="l00081"></a><span class="lineno"> 81</span> }</div>
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<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"> 82</span> std::vector<std::pair<std::string, std::string>> Node::combinations(<span class="keyword">const</span> std::vector<std::string>& source)</div>
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<div class="line"><a id="l00083" name="l00083"></a><span class="lineno"> 83</span> {</div>
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<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"> 84</span> std::vector<std::pair<std::string, std::string>> result;</div>
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<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"> 85</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < source.size(); ++i) {</div>
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<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"> 86</span> std::string temp = source[i];</div>
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<div class="line"><a id="l00087" name="l00087"></a><span class="lineno"> 87</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = i + 1; j < source.size(); ++j) {</div>
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<div class="line"><a id="l00088" name="l00088"></a><span class="lineno"> 88</span> result.push_back({ temp, source[j] });</div>
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<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"> 89</span> }</div>
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<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"> 90</span> }</div>
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<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"> 91</span> <span class="keywordflow">return</span> result;</div>
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<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"> 92</span> }</div>
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<div class="line"><a id="l00093" name="l00093"></a><span class="lineno"> 93</span> <span class="keywordtype">void</span> Node::computeCPT(<span class="keyword">const</span> torch::Tensor& dataset, <span class="keyword">const</span> std::vector<std::string>& features, <span class="keyword">const</span> <span class="keywordtype">double</span> laplaceSmoothing, <span class="keyword">const</span> torch::Tensor& weights)</div>
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<div class="line"><a id="l00094" name="l00094"></a><span class="lineno"> 94</span> {</div>
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<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"> 95</span> dimensions.clear();</div>
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<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"> 96</span> <span class="comment">// Get dimensions of the CPT</span></div>
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<div class="line"><a id="l00097" name="l00097"></a><span class="lineno"> 97</span> dimensions.push_back(numStates);</div>
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<div class="line"><a id="l00098" name="l00098"></a><span class="lineno"> 98</span> transform(parents.begin(), parents.end(), back_inserter(dimensions), [](<span class="keyword">const</span> <span class="keyword">auto</span>& parent) { <span class="keywordflow">return</span> parent->getNumStates(); });</div>
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<div class="line"><a id="l00099" name="l00099"></a><span class="lineno"> 99</span> <span class="comment">// Create a tensor of zeros with the dimensions of the CPT</span></div>
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<div class="line"><a id="l00100" name="l00100"></a><span class="lineno"> 100</span> cpTable = torch::zeros(dimensions, torch::kFloat) + laplaceSmoothing;</div>
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<div class="line"><a id="l00101" name="l00101"></a><span class="lineno"> 101</span> <span class="comment">// Fill table with counts</span></div>
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<div class="line"><a id="l00102" name="l00102"></a><span class="lineno"> 102</span> <span class="keyword">auto</span> pos = find(features.begin(), features.end(), name);</div>
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<div class="line"><a id="l00103" name="l00103"></a><span class="lineno"> 103</span> <span class="keywordflow">if</span> (pos == features.end()) {</div>
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<div class="line"><a id="l00104" name="l00104"></a><span class="lineno"> 104</span> <span class="keywordflow">throw</span> std::logic_error(<span class="stringliteral">"Feature "</span> + name + <span class="stringliteral">" not found in dataset"</span>);</div>
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<div class="line"><a id="l00105" name="l00105"></a><span class="lineno"> 105</span> }</div>
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<div class="line"><a id="l00106" name="l00106"></a><span class="lineno"> 106</span> <span class="keywordtype">int</span> name_index = pos - features.begin();</div>
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<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"> 107</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> n_sample = 0; n_sample < dataset.size(1); ++n_sample) {</div>
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<div class="line"><a id="l00108" name="l00108"></a><span class="lineno"> 108</span> c10::List<c10::optional<at::Tensor>> coordinates;</div>
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<div class="line"><a id="l00109" name="l00109"></a><span class="lineno"> 109</span> coordinates.push_back(dataset.index({ name_index, n_sample }));</div>
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<div class="line"><a id="l00110" name="l00110"></a><span class="lineno"> 110</span> <span class="keywordflow">for</span> (<span class="keyword">auto</span> parent : parents) {</div>
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<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"> 111</span> pos = find(features.begin(), features.end(), parent->getName());</div>
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<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"> 112</span> <span class="keywordflow">if</span> (pos == features.end()) {</div>
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<div class="line"><a id="l00113" name="l00113"></a><span class="lineno"> 113</span> <span class="keywordflow">throw</span> std::logic_error(<span class="stringliteral">"Feature parent "</span> + parent->getName() + <span class="stringliteral">" not found in dataset"</span>);</div>
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<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"> 114</span> }</div>
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<div class="line"><a id="l00115" name="l00115"></a><span class="lineno"> 115</span> <span class="keywordtype">int</span> parent_index = pos - features.begin();</div>
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<div class="line"><a id="l00116" name="l00116"></a><span class="lineno"> 116</span> coordinates.push_back(dataset.index({ parent_index, n_sample }));</div>
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<div class="line"><a id="l00117" name="l00117"></a><span class="lineno"> 117</span> }</div>
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<div class="line"><a id="l00118" name="l00118"></a><span class="lineno"> 118</span> <span class="comment">// Increment the count of the corresponding coordinate</span></div>
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<div class="line"><a id="l00119" name="l00119"></a><span class="lineno"> 119</span> cpTable.index_put_({ coordinates }, cpTable.index({ coordinates }) + weights.index({ n_sample }).item<<span class="keywordtype">double</span>>());</div>
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<div class="line"><a id="l00120" name="l00120"></a><span class="lineno"> 120</span> }</div>
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<div class="line"><a id="l00121" name="l00121"></a><span class="lineno"> 121</span> <span class="comment">// Normalize the counts</span></div>
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<div class="line"><a id="l00122" name="l00122"></a><span class="lineno"> 122</span> cpTable = cpTable / cpTable.sum(0);</div>
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<div class="line"><a id="l00123" name="l00123"></a><span class="lineno"> 123</span> }</div>
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<div class="line"><a id="l00124" name="l00124"></a><span class="lineno"> 124</span> <span class="keywordtype">float</span> Node::getFactorValue(std::map<std::string, int>& evidence)</div>
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<div class="line"><a id="l00125" name="l00125"></a><span class="lineno"> 125</span> {</div>
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<div class="line"><a id="l00126" name="l00126"></a><span class="lineno"> 126</span> c10::List<c10::optional<at::Tensor>> coordinates;</div>
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<div class="line"><a id="l00127" name="l00127"></a><span class="lineno"> 127</span> <span class="comment">// following predetermined order of indices in the cpTable (see Node.h)</span></div>
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<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"> 128</span> coordinates.push_back(at::tensor(evidence[name]));</div>
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<div class="line"><a id="l00129" name="l00129"></a><span class="lineno"> 129</span> transform(parents.begin(), parents.end(), std::back_inserter(coordinates), [&evidence](<span class="keyword">const</span> <span class="keyword">auto</span>& parent) { return at::tensor(evidence[parent->getName()]); });</div>
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<div class="line"><a id="l00130" name="l00130"></a><span class="lineno"> 130</span> <span class="keywordflow">return</span> cpTable.index({ coordinates }).item<float>();</div>
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<div class="line"><a id="l00131" name="l00131"></a><span class="lineno"> 131</span> }</div>
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<div class="line"><a id="l00132" name="l00132"></a><span class="lineno"> 132</span> std::vector<std::string> Node::graph(<span class="keyword">const</span> std::string& className)</div>
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<div class="line"><a id="l00133" name="l00133"></a><span class="lineno"> 133</span> {</div>
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<div class="line"><a id="l00134" name="l00134"></a><span class="lineno"> 134</span> <span class="keyword">auto</span> output = std::vector<std::string>();</div>
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<div class="line"><a id="l00135" name="l00135"></a><span class="lineno"> 135</span> <span class="keyword">auto</span> suffix = name == className ? <span class="stringliteral">", fontcolor=red, fillcolor=lightblue, style=filled "</span> : <span class="stringliteral">""</span>;</div>
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<div class="line"><a id="l00136" name="l00136"></a><span class="lineno"> 136</span> output.push_back(name + <span class="stringliteral">" [shape=circle"</span> + suffix + <span class="stringliteral">"] \n"</span>);</div>
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<div class="line"><a id="l00137" name="l00137"></a><span class="lineno"> 137</span> transform(children.begin(), children.end(), back_inserter(output), [<span class="keyword">this</span>](<span class="keyword">const</span> <span class="keyword">auto</span>& child) { <span class="keywordflow">return</span> name + <span class="stringliteral">" -> "</span> + child->getName(); });</div>
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<div class="line"><a id="l00138" name="l00138"></a><span class="lineno"> 138</span> <span class="keywordflow">return</span> output;</div>
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<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"> 139</span> }</div>
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<div class="line"><a id="l00140" name="l00140"></a><span class="lineno"> 140</span>}</div>
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