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<a href='#section-0'>#</a>
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<h1>Train a Graph Attention Network (GAT) on Cora dataset</h1>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">11</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Dict</span>
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<span class="lineno">12</span>
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<span class="lineno">13</span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
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<span class="lineno">14</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">15</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span>
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<span class="lineno">16</span>
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<span class="lineno">17</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">lab</span><span class="p">,</span> <span class="n">monit</span><span class="p">,</span> <span class="n">tracker</span><span class="p">,</span> <span class="n">experiment</span>
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<span class="lineno">18</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">BaseConfigs</span><span class="p">,</span> <span class="n">option</span><span class="p">,</span> <span class="n">calculate</span>
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<span class="lineno">19</span><span class="kn">from</span> <span class="nn">labml.utils</span> <span class="kn">import</span> <span class="n">download</span>
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<span class="lineno">20</span><span class="kn">from</span> <span class="nn">labml_nn.helpers.device</span> <span class="kn">import</span> <span class="n">DeviceConfigs</span>
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<span class="lineno">21</span><span class="kn">from</span> <span class="nn">labml_nn.graphs.gat</span> <span class="kn">import</span> <span class="n">GraphAttentionLayer</span>
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<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml_nn.optimizers.configs</span> <span class="kn">import</span> <span class="n">OptimizerConfigs</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<h2><a href="https://linqs.soe.ucsc.edu/data">Cora Dataset</a></h2>
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<p>Cora dataset is a dataset of research papers. For each paper we are given a binary feature vector that indicates the presence of words. Each paper is classified into one of 7 classes. The dataset also has the citation network.</p>
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<p>The papers are the nodes of the graph and the edges are the citations.</p>
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<p>The task is to classify the nodes to the 7 classes with feature vectors and citation network as input.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">25</span><span class="k">class</span> <span class="nc">CoraDataset</span><span class="p">:</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-2'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-2'>#</a>
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</div>
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<p>Labels for each node </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">40</span> <span class="n">labels</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-3'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<p>Set of class names and an unique integer index </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">42</span> <span class="n">classes</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-4'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-4'>#</a>
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</div>
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<p>Feature vectors for all nodes </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">44</span> <span class="n">features</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-5'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-5'>#</a>
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</div>
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<p>Adjacency matrix with the edge information. <code class="highlight"><span></span><span class="n">adj_mat</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span></code>
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is <code class="highlight"><span></span><span class="kc">True</span></code>
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if there is an edge from <code class="highlight"><span></span><span class="n">i</span></code>
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to <code class="highlight"><span></span><span class="n">j</span></code>
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. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">47</span> <span class="n">adj_mat</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-6'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-6'>#</a>
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</div>
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<p> Download the dataset</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">49</span> <span class="nd">@staticmethod</span>
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<span class="lineno">50</span> <span class="k">def</span> <span class="nf">_download</span><span class="p">():</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-7'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-7'>#</a>
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</div>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">54</span> <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'cora'</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
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<span class="lineno">55</span> <span class="n">download</span><span class="o">.</span><span class="n">download_file</span><span class="p">(</span><span class="s1">'https://linqs-data.soe.ucsc.edu/public/lbc/cora.tgz'</span><span class="p">,</span>
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<span class="lineno">56</span> <span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'cora.tgz'</span><span class="p">)</span>
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<span class="lineno">57</span> <span class="n">download</span><span class="o">.</span><span class="n">extract_tar</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'cora.tgz'</span><span class="p">,</span> <span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">())</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-8'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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</div>
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<p> Load the dataset</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">59</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">include_edges</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-9'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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</div>
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<p>Whether to include edges. This is test how much accuracy is lost if we ignore the citation network. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">66</span> <span class="bp">self</span><span class="o">.</span><span class="n">include_edges</span> <span class="o">=</span> <span class="n">include_edges</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-10'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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</div>
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<p>Download dataset </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">69</span> <span class="bp">self</span><span class="o">.</span><span class="n">_download</span><span class="p">()</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-11'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-11'>#</a>
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</div>
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<p>Read the paper ids, feature vectors, and labels </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">72</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Read content file'</span><span class="p">):</span>
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<span class="lineno">73</span> <span class="n">content</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">genfromtxt</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'cora/cora.content'</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">dtype</span><span class="p">(</span><span class="nb">str</span><span class="p">))</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-12'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-12'>#</a>
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</div>
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<p>Load the citations, it's a list of pairs of integers. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">75</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Read citations file'</span><span class="p">):</span>
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<span class="lineno">76</span> <span class="n">citations</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">genfromtxt</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'cora/cora.cites'</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-13'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-13'>#</a>
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</div>
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<p>Get the feature vectors </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">79</span> <span class="n">features</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">content</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">))</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-14'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-14'>#</a>
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</div>
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<p>Normalize the feature vectors </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">81</span> <span class="bp">self</span><span class="o">.</span><span class="n">features</span> <span class="o">=</span> <span class="n">features</span> <span class="o">/</span> <span class="n">features</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-15'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-15'>#</a>
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</div>
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<p>Get the class names and assign an unique integer to each of them </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">84</span> <span class="bp">self</span><span class="o">.</span><span class="n">classes</span> <span class="o">=</span> <span class="p">{</span><span class="n">s</span><span class="p">:</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">content</span><span class="p">[:,</span> <span class="o">-</span><span class="mi">1</span><span class="p">]))}</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-16'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-16'>#</a>
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</div>
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<p>Get the labels as those integers </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">86</span> <span class="bp">self</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">classes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">content</span><span class="p">[:,</span> <span class="o">-</span><span class="mi">1</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">long</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-17'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-17'>#</a>
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</div>
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<p>Get the paper ids </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">89</span> <span class="n">paper_ids</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">content</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-18'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-18'>#</a>
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</div>
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<p>Map of paper id to index </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">91</span> <span class="n">ids_to_idx</span> <span class="o">=</span> <span class="p">{</span><span class="n">id_</span><span class="p">:</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">id_</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">paper_ids</span><span class="p">)}</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-19'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-19'>#</a>
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</div>
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<p>Empty adjacency matrix - an identity matrix </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">94</span> <span class="bp">self</span><span class="o">.</span><span class="n">adj_mat</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">labels</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">bool</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-20'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-20'>#</a>
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</div>
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<p>Mark the citations in the adjacency matrix </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">97</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">include_edges</span><span class="p">:</span>
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<span class="lineno">98</span> <span class="k">for</span> <span class="n">e</span> <span class="ow">in</span> <span class="n">citations</span><span class="p">:</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-21'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-21'>#</a>
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</div>
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<p>The pair of paper indexes </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">100</span> <span class="n">e1</span><span class="p">,</span> <span class="n">e2</span> <span class="o">=</span> <span class="n">ids_to_idx</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span> <span class="n">ids_to_idx</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-22'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-22'>#</a>
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</div>
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<p>We build a symmetrical graph, where if paper <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.65952em;vertical-align:0em;"></span><span class="mord coloredeq eqa" style=""><span class="mord mathnormal" style="">i</span></span></span></span></span></span> referenced paper <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.85396em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqb" style=""><span class="mord mathnormal" style="margin-right:0.05724em">j</span></span></span></span></span></span> we place an adge from <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.65952em;vertical-align:0em;"></span><span class="mord coloredeq eqa" style=""><span class="mord mathnormal" style="">i</span></span></span></span></span></span> to <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.85396em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqb" style=""><span class="mord mathnormal" style="margin-right:0.05724em">j</span></span></span></span></span></span> as well as an edge from <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.85396em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqb" style=""><span class="mord mathnormal" style="margin-right:0.05724em">j</span></span></span></span></span></span> to <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.65952em;vertical-align:0em;"></span><span class="mord coloredeq eqa" style=""><span class="mord mathnormal" style="">i</span></span></span></span></span></span>. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">104</span> <span class="bp">self</span><span class="o">.</span><span class="n">adj_mat</span><span class="p">[</span><span class="n">e1</span><span class="p">][</span><span class="n">e2</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span>
|
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<span class="lineno">105</span> <span class="bp">self</span><span class="o">.</span><span class="n">adj_mat</span><span class="p">[</span><span class="n">e2</span><span class="p">][</span><span class="n">e1</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span></pre></div>
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</div>
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</div>
|
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<div class='section' id='section-23'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-23'>#</a>
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</div>
|
|
<h2>Graph Attention Network (GAT)</h2>
|
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<p>This graph attention network has two <a href="index.html">graph attention layers</a>.</p>
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</div>
|
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">108</span><span class="k">class</span> <span class="nc">GAT</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
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</div>
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</div>
|
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<div class='section' id='section-24'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-24'>#</a>
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</div>
|
|
<ul><li><code class="highlight"><span></span><span class="n">in_features</span></code>
|
|
is the number of features per node </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_hidden</span></code>
|
|
is the number of features in the first graph attention layer </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_classes</span></code>
|
|
is the number of classes </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_heads</span></code>
|
|
is the number of heads in the graph attention layers </li>
|
|
<li><code class="highlight"><span></span><span class="n">dropout</span></code>
|
|
is the dropout probability</li></ul>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">115</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_features</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">n_hidden</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">n_heads</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">dropout</span><span class="p">:</span> <span class="nb">float</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-25'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-25'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">123</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
|
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</div>
|
|
</div>
|
|
<div class='section' id='section-26'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-26'>#</a>
|
|
</div>
|
|
<p>First graph attention layer where we concatenate the heads </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">126</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer1</span> <span class="o">=</span> <span class="n">GraphAttentionLayer</span><span class="p">(</span><span class="n">in_features</span><span class="p">,</span> <span class="n">n_hidden</span><span class="p">,</span> <span class="n">n_heads</span><span class="p">,</span> <span class="n">is_concat</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">dropout</span><span class="o">=</span><span class="n">dropout</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-27'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-27'>#</a>
|
|
</div>
|
|
<p>Activation function after first graph attention layer </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">128</span> <span class="bp">self</span><span class="o">.</span><span class="n">activation</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">ELU</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-28'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-28'>#</a>
|
|
</div>
|
|
<p>Final graph attention layer where we average the heads </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">130</span> <span class="bp">self</span><span class="o">.</span><span class="n">output</span> <span class="o">=</span> <span class="n">GraphAttentionLayer</span><span class="p">(</span><span class="n">n_hidden</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">is_concat</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dropout</span><span class="o">=</span><span class="n">dropout</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-29'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-29'>#</a>
|
|
</div>
|
|
<p>Dropout </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">132</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">dropout</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-30'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-30'>#</a>
|
|
</div>
|
|
<ul><li><code class="highlight"><span></span><span class="n">x</span></code>
|
|
is the features vectors of shape <code class="highlight"><span></span><span class="p">[</span><span class="n">n_nodes</span><span class="p">,</span> <span class="n">in_features</span><span class="p">]</span></code>
|
|
</li>
|
|
<li><code class="highlight"><span></span><span class="n">adj_mat</span></code>
|
|
is the adjacency matrix of the form <code class="highlight"><span></span><span class="p">[</span><span class="n">n_nodes</span><span class="p">,</span> <span class="n">n_nodes</span><span class="p">,</span> <span class="n">n_heads</span><span class="p">]</span></code>
|
|
or <code class="highlight"><span></span><span class="p">[</span><span class="n">n_nodes</span><span class="p">,</span> <span class="n">n_nodes</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
|
</li></ul>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">134</span> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">adj_mat</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-31'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-31'>#</a>
|
|
</div>
|
|
<p>Apply dropout to the input </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">141</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-32'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-32'>#</a>
|
|
</div>
|
|
<p>First graph attention layer </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">143</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer1</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">adj_mat</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-33'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-33'>#</a>
|
|
</div>
|
|
<p>Activation function </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">145</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">activation</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-34'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-34'>#</a>
|
|
</div>
|
|
<p>Dropout </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">147</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-35'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-35'>#</a>
|
|
</div>
|
|
<p>Output layer (without activation) for logits </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">149</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">adj_mat</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-36'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-36'>#</a>
|
|
</div>
|
|
<p> A simple function to calculate the accuracy</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">152</span><span class="k">def</span> <span class="nf">accuracy</span><span class="p">(</span><span class="n">output</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-37'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-37'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
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<div class="highlight"><pre><span class="lineno">156</span> <span class="k">return</span> <span class="n">output</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">eq</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-38'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-38'>#</a>
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</div>
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<h2>Configurations</h2>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">159</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">BaseConfigs</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-39'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-39'>#</a>
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</div>
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<p>Model </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">165</span> <span class="n">model</span><span class="p">:</span> <span class="n">GAT</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-40'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-40'>#</a>
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</div>
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<p>Number of nodes to train on </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">167</span> <span class="n">training_samples</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">500</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-41'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-41'>#</a>
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</div>
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<p>Number of features per node in the input </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">169</span> <span class="n">in_features</span><span class="p">:</span> <span class="nb">int</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-42'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-42'>#</a>
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</div>
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<p>Number of features in the first graph attention layer </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">171</span> <span class="n">n_hidden</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">64</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-43'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-43'>#</a>
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</div>
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<p>Number of heads </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">173</span> <span class="n">n_heads</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">8</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-44'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-44'>#</a>
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</div>
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<p>Number of classes for classification </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">175</span> <span class="n">n_classes</span><span class="p">:</span> <span class="nb">int</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-45'>
|
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-45'>#</a>
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</div>
|
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<p>Dropout probability </p>
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</div>
|
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">177</span> <span class="n">dropout</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.6</span></pre></div>
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</div>
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</div>
|
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<div class='section' id='section-46'>
|
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-46'>#</a>
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</div>
|
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<p>Whether to include the citation network </p>
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</div>
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">179</span> <span class="n">include_edges</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span></pre></div>
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</div>
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</div>
|
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<div class='section' id='section-47'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-47'>#</a>
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</div>
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<p>Dataset </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">181</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">CoraDataset</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-48'>
|
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-48'>#</a>
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</div>
|
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<p>Number of training iterations </p>
|
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|
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</div>
|
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">183</span> <span class="n">epochs</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1_000</span></pre></div>
|
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</div>
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</div>
|
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<div class='section' id='section-49'>
|
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-49'>#</a>
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</div>
|
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<p>Loss function </p>
|
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</div>
|
|
<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">185</span> <span class="n">loss_func</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">CrossEntropyLoss</span><span class="p">()</span></pre></div>
|
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</div>
|
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</div>
|
|
<div class='section' id='section-50'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-50'>#</a>
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</div>
|
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<p>Device to train on</p>
|
|
<p>This creates configs for device, so that we can change the device by passing a config value </p>
|
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</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">190</span> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">DeviceConfigs</span><span class="p">()</span></pre></div>
|
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</div>
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</div>
|
|
<div class='section' id='section-51'>
|
|
<div class='docs'>
|
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<div class='section-link'>
|
|
<a href='#section-51'>#</a>
|
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</div>
|
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<p>Optimizer </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">192</span> <span class="n">optimizer</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-52'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-52'>#</a>
|
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</div>
|
|
<h3>Training loop</h3>
|
|
<p>We do full batch training since the dataset is small. If we were to sample and train we will have to sample a set of nodes for each training step along with the edges that span across those selected nodes.</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">194</span> <span class="k">def</span> <span class="nf">run</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
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</div>
|
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</div>
|
|
<div class='section' id='section-53'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-53'>#</a>
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|
</div>
|
|
<p>Move the feature vectors to the device </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">204</span> <span class="n">features</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">features</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-54'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-54'>#</a>
|
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</div>
|
|
<p>Move the labels to the device </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">206</span> <span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-55'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-55'>#</a>
|
|
</div>
|
|
<p>Move the adjacency matrix to the device </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">208</span> <span class="n">edges_adj</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">adj_mat</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-56'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-56'>#</a>
|
|
</div>
|
|
<p>Add an empty third dimension for the heads </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">210</span> <span class="n">edges_adj</span> <span class="o">=</span> <span class="n">edges_adj</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-57'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-57'>#</a>
|
|
</div>
|
|
<p>Random indexes </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">213</span> <span class="n">idx_rand</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randperm</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-58'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-58'>#</a>
|
|
</div>
|
|
<p>Nodes for training </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">215</span> <span class="n">idx_train</span> <span class="o">=</span> <span class="n">idx_rand</span><span class="p">[:</span><span class="bp">self</span><span class="o">.</span><span class="n">training_samples</span><span class="p">]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-59'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-59'>#</a>
|
|
</div>
|
|
<p>Nodes for validation </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">217</span> <span class="n">idx_valid</span> <span class="o">=</span> <span class="n">idx_rand</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">training_samples</span><span class="p">:]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-60'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-60'>#</a>
|
|
</div>
|
|
<p>Training loop </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">220</span> <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="n">monit</span><span class="o">.</span><span class="n">loop</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">epochs</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-61'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-61'>#</a>
|
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</div>
|
|
<p>Set the model to training mode </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">222</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-62'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-62'>#</a>
|
|
</div>
|
|
<p>Make all the gradients zero </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">224</span> <span class="bp">self</span><span class="o">.</span><span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-63'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-63'>#</a>
|
|
</div>
|
|
<p>Evaluate the model </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">226</span> <span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">(</span><span class="n">features</span><span class="p">,</span> <span class="n">edges_adj</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-64'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-64'>#</a>
|
|
</div>
|
|
<p>Get the loss for training nodes </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">228</span> <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">loss_func</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">idx_train</span><span class="p">],</span> <span class="n">labels</span><span class="p">[</span><span class="n">idx_train</span><span class="p">])</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-65'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-65'>#</a>
|
|
</div>
|
|
<p>Calculate gradients </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">230</span> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-66'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-66'>#</a>
|
|
</div>
|
|
<p>Take optimization step </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">232</span> <span class="bp">self</span><span class="o">.</span><span class="n">optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-67'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-67'>#</a>
|
|
</div>
|
|
<p>Log the loss </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">234</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'loss.train'</span><span class="p">,</span> <span class="n">loss</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-68'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-68'>#</a>
|
|
</div>
|
|
<p>Log the accuracy </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">236</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'accuracy.train'</span><span class="p">,</span> <span class="n">accuracy</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">idx_train</span><span class="p">],</span> <span class="n">labels</span><span class="p">[</span><span class="n">idx_train</span><span class="p">]))</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-69'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-69'>#</a>
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</div>
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<p>Set mode to evaluation mode for validation </p>
|
|
|
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</div>
|
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">239</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span></pre></div>
|
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</div>
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</div>
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<div class='section' id='section-70'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-70'>#</a>
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</div>
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<p>No need to compute gradients </p>
|
|
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</div>
|
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">242</span> <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-71'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-71'>#</a>
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</div>
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<p>Evaluate the model again </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">244</span> <span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">(</span><span class="n">features</span><span class="p">,</span> <span class="n">edges_adj</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-72'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-72'>#</a>
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</div>
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<p>Calculate the loss for validation nodes </p>
|
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</div>
|
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">246</span> <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">loss_func</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">idx_valid</span><span class="p">],</span> <span class="n">labels</span><span class="p">[</span><span class="n">idx_valid</span><span class="p">])</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-73'>
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-73'>#</a>
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</div>
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<p>Log the loss </p>
|
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</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">248</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'loss.valid'</span><span class="p">,</span> <span class="n">loss</span><span class="p">)</span></pre></div>
|
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</div>
|
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</div>
|
|
<div class='section' id='section-74'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-74'>#</a>
|
|
</div>
|
|
<p>Log the accuracy </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">250</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'accuracy.valid'</span><span class="p">,</span> <span class="n">accuracy</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">idx_valid</span><span class="p">],</span> <span class="n">labels</span><span class="p">[</span><span class="n">idx_valid</span><span class="p">]))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-75'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-75'>#</a>
|
|
</div>
|
|
<p>Save logs </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">253</span> <span class="n">tracker</span><span class="o">.</span><span class="n">save</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-76'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-76'>#</a>
|
|
</div>
|
|
<p> Create Cora dataset</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">256</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">dataset</span><span class="p">)</span>
|
|
<span class="lineno">257</span><span class="k">def</span> <span class="nf">cora_dataset</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-77'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-77'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">261</span> <span class="k">return</span> <span class="n">CoraDataset</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">include_edges</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-78'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-78'>#</a>
|
|
</div>
|
|
<p>Get the number of classes </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">265</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">classes</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-79'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-79'>#</a>
|
|
</div>
|
|
<p>Number of features in the input </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">267</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">in_features</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">c</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">features</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-80'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-80'>#</a>
|
|
</div>
|
|
<p> Create GAT model</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">270</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
|
|
<span class="lineno">271</span><span class="k">def</span> <span class="nf">gat_model</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-81'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-81'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">275</span> <span class="k">return</span> <span class="n">GAT</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">in_features</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">n_hidden</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">n_heads</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">dropout</span><span class="p">)</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-82'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-82'>#</a>
|
|
</div>
|
|
<p> Create configurable optimizer</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">278</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">)</span>
|
|
<span class="lineno">279</span><span class="k">def</span> <span class="nf">_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-83'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-83'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">283</span> <span class="n">opt_conf</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span>
|
|
<span class="lineno">284</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">()</span>
|
|
<span class="lineno">285</span> <span class="k">return</span> <span class="n">opt_conf</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-84'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-84'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">288</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-85'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-85'>#</a>
|
|
</div>
|
|
<p>Create configurations </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">290</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-86'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-86'>#</a>
|
|
</div>
|
|
<p>Create an experiment </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">292</span> <span class="n">experiment</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'gat'</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-87'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-87'>#</a>
|
|
</div>
|
|
<p>Calculate configurations. </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">294</span> <span class="n">experiment</span><span class="o">.</span><span class="n">configs</span><span class="p">(</span><span class="n">conf</span><span class="p">,</span> <span class="p">{</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-88'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-88'>#</a>
|
|
</div>
|
|
<p>Adam optimizer </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">296</span> <span class="s1">'optimizer.optimizer'</span><span class="p">:</span> <span class="s1">'Adam'</span><span class="p">,</span>
|
|
<span class="lineno">297</span> <span class="s1">'optimizer.learning_rate'</span><span class="p">:</span> <span class="mf">5e-3</span><span class="p">,</span>
|
|
<span class="lineno">298</span> <span class="s1">'optimizer.weight_decay'</span><span class="p">:</span> <span class="mf">5e-4</span><span class="p">,</span>
|
|
<span class="lineno">299</span> <span class="p">})</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-89'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-89'>#</a>
|
|
</div>
|
|
<p>Start and watch the experiment </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">302</span> <span class="k">with</span> <span class="n">experiment</span><span class="o">.</span><span class="n">start</span><span class="p">():</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-90'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-90'>#</a>
|
|
</div>
|
|
<p>Run the training </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">304</span> <span class="n">conf</span><span class="o">.</span><span class="n">run</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-91'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-91'>#</a>
|
|
</div>
|
|
<p> </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">308</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
|
|
<span class="lineno">309</span> <span class="n">main</span><span class="p">()</span></pre></div>
|
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