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<div class="highlight"><pre><span class="lineno">3</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">4</span>
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<span class="lineno">5</span><span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="kn">import</span> <span class="n">Subset</span>
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<span class="lineno">6</span>
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<span class="lineno">7</span><span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <span class="n">KFold</span>
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<span class="lineno">8</span><span class="kn">from</span> <span class="nn">torch.utils.data.sampler</span> <span class="kn">import</span> <span class="n">SubsetRandomSampler</span>
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<span class="lineno">9</span><span class="kn">from</span> <span class="nn">models.cnn</span> <span class="kn">import</span> <span class="n">GetCNN</span>
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<span class="lineno">10</span><span class="kn">from</span> <span class="nn">torchsummary</span> <span class="kn">import</span> <span class="n">summary</span>
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<span class="lineno">11</span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>
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<span class="lineno">12</span><span class="kn">import</span> <span class="nn">os</span>
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<span class="lineno">13</span>
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<span class="lineno">14</span><span class="kn">from</span> <span class="nn">torch.utils.tensorboard</span> <span class="kn">import</span> <span class="n">SummaryWriter</span>
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<span class="lineno">15</span>
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<span class="lineno">16</span><span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
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<span class="lineno">17</span><span class="kn">from</span> <span class="nn">glob</span> <span class="kn">import</span> <span class="n">glob</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'>
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<a href='#section-1'>#</a>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">21</span><span class="k">def</span> <span class="nf">cross_val_train</span><span class="p">(</span><span class="n">cost</span><span class="p">,</span> <span class="n">trainset</span><span class="p">,</span> <span class="n">epochs</span><span class="p">,</span> <span class="n">splits</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
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<span class="lineno">22</span>
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<span class="lineno">23</span> <span class="n">patience</span> <span class="o">=</span> <span class="mi">4</span>
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<span class="lineno">24</span> <span class="n">history</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">25</span> <span class="n">kf</span> <span class="o">=</span> <span class="n">KFold</span><span class="p">(</span><span class="n">n_splits</span><span class="o">=</span><span class="n">splits</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<span class="lineno">26</span> <span class="n">batch_size</span> <span class="o">=</span> <span class="mi">64</span>
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<span class="lineno">27</span> <span class="n">now</span> <span class="o">=</span> <span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()</span>
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<span class="lineno">28</span> <span class="n">date_time</span> <span class="o">=</span> <span class="n">now</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"</span><span class="si">%d</span><span class="s2">-%m-%Y_%H:%M:%S"</span><span class="p">)</span>
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<span class="lineno">29</span> <span class="n">directory</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="s1">'./save/tensorboard-</span><span class="si">%s</span><span class="s1">/'</span><span class="o">%</span><span class="p">(</span><span class="n">date_time</span><span class="p">))</span>
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<span class="lineno">30</span>
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<span class="lineno">31</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">directory</span><span class="p">):</span>
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<span class="lineno">32</span> <span class="n">os</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span>
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<span class="lineno">33</span>
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<span class="lineno">34</span> <span class="k">for</span> <span class="n">fold</span><span class="p">,</span> <span class="p">(</span><span class="n">train_index</span><span class="p">,</span> <span class="n">test_index</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">kf</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="n">trainset</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="n">trainset</span><span class="o">.</span><span class="n">targets</span><span class="p">)):</span> <span class="c1">#dataset required - compelete training set</span>
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<span class="lineno">35</span> <span class="n">comment</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">directory</span><span class="si">}</span><span class="s1">/fold-</span><span class="si">{</span><span class="n">fold</span><span class="si">}</span><span class="s1">'</span>
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<span class="lineno">36</span> <span class="n">writer</span> <span class="o">=</span> <span class="n">SummaryWriter</span><span class="p">(</span><span class="n">log_dir</span><span class="o">=</span><span class="n">comment</span><span class="p">)</span>
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<span class="lineno">37</span>
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<span class="lineno">38</span> <span class="n">train_sampler</span> <span class="o">=</span> <span class="n">SubsetRandomSampler</span><span class="p">(</span><span class="n">train_index</span><span class="p">)</span>
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<span class="lineno">39</span> <span class="n">valid_sampler</span> <span class="o">=</span> <span class="n">SubsetRandomSampler</span><span class="p">(</span><span class="n">test_index</span><span class="p">)</span>
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<span class="lineno">40</span> <span class="n">traindata</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">trainset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">sampler</span><span class="o">=</span><span class="n">train_sampler</span><span class="p">,</span>
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<span class="lineno">41</span> <span class="n">num_workers</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
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<span class="lineno">42</span> <span class="n">valdata</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">trainset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">sampler</span><span class="o">=</span><span class="n">valid_sampler</span><span class="p">,</span>
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<span class="lineno">43</span> <span class="n">num_workers</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
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<span class="lineno">44</span>
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<span class="lineno">45</span> <span class="n">net</span> <span class="o">=</span> <span class="n">GetCNN</span><span class="p">()</span>
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<span class="lineno">46</span> <span class="n">net</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
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<span class="lineno">47</span> <span class="k">if</span> <span class="n">fold</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="c1">#Printing model detials for the first time</span>
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<span class="lineno">48</span> <span class="n">summary</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</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>Specify optimizer</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">52</span> <span class="n">optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">net</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.0005</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="mf">0.95</span><span class="p">))</span>
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<span class="lineno">53</span> <span class="n">losses</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">epochs</span><span class="p">)</span>
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<span class="lineno">54</span> <span class="n">accuracies</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">epochs</span><span class="p">)</span>
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<span class="lineno">55</span> <span class="n">min_loss</span> <span class="o">=</span> <span class="kc">None</span>
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<span class="lineno">56</span> <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="lineno">57</span> <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">epochs</span><span class="p">):</span>
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<span class="lineno">58</span> <span class="n">valid_loss</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="lineno">59</span> <span class="n">running_loss</span> <span class="o">=</span> <span class="mf">0.0</span>
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<span class="lineno">60</span> <span class="n">epoch_loss</span> <span class="o">=</span> <span class="mf">0.0</span>
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<span class="lineno">61</span> <span class="n">train_loss</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">epochs</span><span class="p">)</span>
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<span class="lineno">62</span> <span class="n">train_steps</span> <span class="o">=</span> <span class="mf">0.0</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>training steps</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">65</span> <span class="n">net</span><span class="o">.</span><span class="n">train</span><span class="p">()</span> <span class="c1"># Enable Dropout</span>
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<span class="lineno">66</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">data</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">traindata</span><span class="p">,</span> <span class="mi">0</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>Get the inputs; data is a list of [inputs, 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">68</span> <span class="k">if</span> <span class="n">device</span><span class="p">:</span>
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<span class="lineno">69</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
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<span class="lineno">70</span> <span class="k">else</span><span class="p">:</span>
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<span class="lineno">71</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">data</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>Forward + backward + optimize</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">74</span> <span class="n">outputs</span> <span class="o">=</span> <span class="n">net</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
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<span class="lineno">75</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">cost</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span>
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<span class="lineno">76</span> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
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<span class="lineno">77</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">step</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-6'>
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<div class='docs'>
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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>Zero the parameter 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">79</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_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-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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<p>Print loss</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">82</span> <span class="n">running_loss</span> <span class="o">+=</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
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<span class="lineno">83</span> <span class="n">epoch_loss</span> <span class="o">+=</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
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<span class="lineno">84</span> <span class="n">train_loss</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o">+=</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
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<span class="lineno">85</span> <span class="n">train_steps</span> <span class="o">+=</span> <span class="mi">1</span>
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<span class="lineno">86</span>
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<span class="lineno">87</span> <span class="n">loss_train</span> <span class="o">=</span> <span class="n">train_loss</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o">/</span> <span class="n">train_steps</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'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
|
|
</div>
|
|
<p>Validation</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">90</span> <span class="n">loss_accuracy</span> <span class="o">=</span> <span class="n">Test</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">cost</span><span class="p">,</span> <span class="n">valdata</span><span class="p">,</span> <span class="n">device</span><span class="p">)</span>
|
|
<span class="lineno">91</span>
|
|
<span class="lineno">92</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o">=</span> <span class="n">loss_accuracy</span><span class="p">[</span><span class="s1">'val_loss'</span><span class="p">]</span>
|
|
<span class="lineno">93</span> <span class="n">accuracies</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o">=</span> <span class="n">loss_accuracy</span><span class="p">[</span><span class="s1">'val_acc'</span><span class="p">]</span>
|
|
<span class="lineno">94</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"Fold </span><span class="si">%d</span><span class="s2">, Epoch </span><span class="si">%d</span><span class="s2">, Train Loss </span><span class="si">%.4f</span><span class="s2"> Validation Loss: </span><span class="si">%.4f</span><span class="s2">, Validation Accuracy: </span><span class="si">%.4f</span><span class="s2">"</span> <span class="o">%</span> <span class="p">(</span><span class="n">fold</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">epoch</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">loss_train</span><span class="p">,</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">],</span> <span class="n">accuracies</span><span class="p">[</span><span class="n">epoch</span><span class="p">]))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-9'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-9'>#</a>
|
|
</div>
|
|
<p>TensorBoard</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">97</span> <span class="n">info</span> <span class="o">=</span> <span class="p">{</span>
|
|
<span class="lineno">98</span> <span class="s2">"Loss/train"</span><span class="p">:</span> <span class="n">loss_train</span><span class="p">,</span>
|
|
<span class="lineno">99</span> <span class="s2">"Loss/valid"</span><span class="p">:</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">],</span>
|
|
<span class="lineno">100</span> <span class="s2">"Accuracy/valid"</span><span class="p">:</span> <span class="n">accuracies</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span>
|
|
<span class="lineno">101</span> <span class="p">}</span>
|
|
<span class="lineno">102</span>
|
|
<span class="lineno">103</span> <span class="k">for</span> <span class="n">tag</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">info</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
|
|
<span class="lineno">104</span> <span class="n">writer</span><span class="o">.</span><span class="n">add_scalar</span><span class="p">(</span><span class="n">tag</span><span class="p">,</span> <span class="n">item</span><span class="p">,</span> <span class="n">global_step</span><span class="o">=</span><span class="n">epoch</span><span class="p">)</span>
|
|
<span class="lineno">105</span>
|
|
<span class="lineno">106</span> <span class="k">if</span> <span class="n">min_loss</span> <span class="o">==</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="lineno">107</span> <span class="n">min_loss</span> <span class="o">=</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-10'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-10'>#</a>
|
|
</div>
|
|
<p>Early stopping refered from https://github.com/Bjarten/early-stopping-pytorch/blob/master/pytorchtools.py</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">110</span> <span class="k">if</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o">></span> <span class="n">min_loss</span><span class="p">:</span>
|
|
<span class="lineno">111</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"Epoch loss: </span><span class="si">%.4f</span><span class="s2">, Min loss: </span><span class="si">%.4f</span><span class="s2">"</span><span class="o">%</span><span class="p">(</span><span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">],</span> <span class="n">min_loss</span><span class="p">))</span>
|
|
<span class="lineno">112</span> <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
|
<span class="lineno">113</span> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Early stopping counter: </span><span class="si">{</span><span class="n">count</span><span class="si">}</span><span class="s1"> out of </span><span class="si">{</span><span class="n">patience</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
|
|
<span class="lineno">114</span> <span class="k">if</span> <span class="n">count</span> <span class="o">>=</span> <span class="n">patience</span><span class="p">:</span>
|
|
<span class="lineno">115</span> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'############### EarlyStopping ##################'</span><span class="p">)</span>
|
|
<span class="lineno">116</span> <span class="k">break</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-11'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-11'>#</a>
|
|
</div>
|
|
<p>Saving best model</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">119</span> <span class="k">elif</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span> <span class="o"><=</span> <span class="n">min_loss</span><span class="p">:</span>
|
|
<span class="lineno">120</span> <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
|
|
<span class="lineno">121</span> <span class="n">save_best_model</span><span class="p">({</span>
|
|
<span class="lineno">122</span> <span class="s1">'epoch'</span><span class="p">:</span> <span class="n">epoch</span><span class="p">,</span>
|
|
<span class="lineno">123</span> <span class="s1">'state_dict'</span><span class="p">:</span> <span class="n">net</span><span class="o">.</span><span class="n">state_dict</span><span class="p">(),</span>
|
|
<span class="lineno">124</span> <span class="s1">'optimizer'</span><span class="p">:</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">state_dict</span><span class="p">(),</span>
|
|
<span class="lineno">125</span> <span class="s1">'accuracy'</span> <span class="p">:</span> <span class="n">accuracies</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span>
|
|
<span class="lineno">126</span> <span class="p">},</span> <span class="n">fold</span><span class="o">=</span><span class="n">fold</span><span class="p">,</span> <span class="n">date_time</span><span class="o">=</span><span class="n">date_time</span><span class="p">)</span>
|
|
<span class="lineno">127</span> <span class="n">min_loss</span> <span class="o">=</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">]</span>
|
|
<span class="lineno">128</span>
|
|
<span class="lineno">129</span> <span class="n">history</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s1">'val_loss'</span><span class="p">:</span> <span class="n">losses</span><span class="p">[</span><span class="n">epoch</span><span class="p">],</span> <span class="s1">'val_acc'</span><span class="p">:</span> <span class="n">accuracies</span><span class="p">[</span><span class="n">epoch</span><span class="p">]})</span>
|
|
<span class="lineno">130</span> <span class="k">return</span> <span class="n">history</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-12'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-12'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">132</span><span class="k">def</span> <span class="nf">save_best_model</span><span class="p">(</span><span class="n">state</span><span class="p">,</span> <span class="n">fold</span><span class="p">,</span> <span class="n">date_time</span><span class="p">):</span>
|
|
<span class="lineno">133</span> <span class="n">directory</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="s2">"./save/CV_models-</span><span class="si">%s</span><span class="s2">/"</span><span class="o">%</span><span class="p">(</span><span class="n">date_time</span><span class="p">))</span>
|
|
<span class="lineno">134</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">directory</span><span class="p">):</span>
|
|
<span class="lineno">135</span> <span class="n">os</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span>
|
|
<span class="lineno">136</span> <span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">state</span><span class="p">,</span> <span class="s2">"</span><span class="si">%s</span><span class="s2">/fold-</span><span class="si">%d</span><span class="s2">-model.pt"</span> <span class="o">%</span> <span class="p">(</span><span class="n">directory</span><span class="p">,</span> <span class="n">fold</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-13'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-13'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">138</span><span class="k">def</span> <span class="nf">retreive_best_trial</span><span class="p">():</span>
|
|
<span class="lineno">139</span> <span class="n">PATH</span> <span class="o">=</span> <span class="s2">"./save/"</span>
|
|
<span class="lineno">140</span> <span class="n">best_model</span> <span class="o">=</span> <span class="n">GetCNN</span><span class="p">()</span>
|
|
<span class="lineno">141</span>
|
|
<span class="lineno">142</span> <span class="n">content</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="n">PATH</span><span class="p">)</span>
|
|
<span class="lineno">143</span> <span class="n">latest_time</span> <span class="o">=</span> <span class="mi">0</span>
|
|
<span class="lineno">144</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">content</span><span class="p">:</span>
|
|
<span class="lineno">145</span> <span class="k">if</span> <span class="s1">'CV_models'</span> <span class="ow">in</span> <span class="n">item</span><span class="p">:</span>
|
|
<span class="lineno">146</span> <span class="n">foldername</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">PATH</span><span class="p">,</span> <span class="n">item</span><span class="p">)</span>
|
|
<span class="lineno">147</span> <span class="n">tm</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">getmtime</span><span class="p">(</span><span class="n">foldername</span><span class="p">)</span>
|
|
<span class="lineno">148</span> <span class="k">if</span> <span class="n">tm</span> <span class="o">></span> <span class="n">latest_time</span><span class="p">:</span>
|
|
<span class="lineno">149</span> <span class="n">latest_folder</span> <span class="o">=</span> <span class="n">foldername</span>
|
|
<span class="lineno">150</span>
|
|
<span class="lineno">151</span> <span class="n">file_type</span> <span class="o">=</span> <span class="s1">'/*.pt'</span>
|
|
<span class="lineno">152</span> <span class="n">files</span> <span class="o">=</span> <span class="n">glob</span><span class="p">(</span><span class="n">latest_folder</span> <span class="o">+</span> <span class="n">file_type</span><span class="p">)</span>
|
|
<span class="lineno">153</span>
|
|
<span class="lineno">154</span> <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
|
|
<span class="lineno">155</span> <span class="k">for</span> <span class="n">model_file</span> <span class="ow">in</span> <span class="n">files</span><span class="p">:</span>
|
|
<span class="lineno">156</span> <span class="n">checkpoint</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">model_file</span><span class="p">)</span>
|
|
<span class="lineno">157</span> <span class="k">if</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">]</span> <span class="o">></span> <span class="n">accuracy</span><span class="p">:</span>
|
|
<span class="lineno">158</span> <span class="n">best_model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">'state_dict'</span><span class="p">])</span>
|
|
<span class="lineno">159</span> <span class="n">best_val_accuracy</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-14'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-14'>#</a>
|
|
</div>
|
|
<p>Test(best_model,)</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">162</span> <span class="k">return</span> <span class="n">best_model</span><span class="p">,</span> <span class="n">best_val_accuracy</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-15'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-15'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">164</span><span class="k">def</span> <span class="nf">val_step</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">cost</span><span class="p">,</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-16'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-16'>#</a>
|
|
</div>
|
|
<p>forward pass</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">166</span> <span class="n">output</span> <span class="o">=</span> <span class="n">net</span><span class="p">(</span><span class="n">images</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-17'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-17'>#</a>
|
|
</div>
|
|
<p>loss in batch</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">168</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">cost</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-18'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-18'>#</a>
|
|
</div>
|
|
<p>update validation loss</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">171</span> <span class="n">_</span><span class="p">,</span> <span class="n">preds</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">output</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="lineno">172</span> <span class="n">acc</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">torch</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">preds</span> <span class="o">==</span> <span class="n">labels</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">preds</span><span class="p">))</span>
|
|
<span class="lineno">173</span> <span class="n">acc_output</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'val_loss'</span><span class="p">:</span> <span class="n">loss</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span> <span class="s1">'val_acc'</span><span class="p">:</span> <span class="n">acc</span><span class="p">}</span>
|
|
<span class="lineno">174</span> <span class="k">return</span> <span class="n">acc_output</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-19'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-19'>#</a>
|
|
</div>
|
|
<p>Test over testloader/valloader loop</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">177</span><span class="k">def</span> <span class="nf">Test</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">cost</span><span class="p">,</span> <span class="n">testloader</span><span class="p">,</span> <span class="n">device</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-20'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-20'>#</a>
|
|
</div>
|
|
<p>Disable Dropout</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">179</span> <span class="n">net</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-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>Bookkeeping</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">182</span> <span class="n">correct</span> <span class="o">=</span> <span class="mf">0.0</span>
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<span class="lineno">183</span> <span class="n">total</span> <span class="o">=</span> <span class="mf">0.0</span>
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<span class="lineno">184</span> <span class="n">loss</span> <span class="o">=</span> <span class="mf">0.0</span>
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<span class="lineno">185</span> <span class="n">train_steps</span> <span class="o">=</span> <span class="mf">0.0</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>Infer the 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">188</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>
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<span class="lineno">189</span> <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">testloader</span><span class="p">:</span>
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<span class="lineno">190</span> <span class="k">if</span> <span class="n">device</span><span class="p">:</span>
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<span class="lineno">191</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
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<span class="lineno">192</span> <span class="k">else</span><span class="p">:</span>
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<span class="lineno">193</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
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<span class="lineno">194</span>
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<span class="lineno">195</span> <span class="n">outputs</span> <span class="o">=</span> <span class="n">net</span><span class="p">(</span><span class="n">images</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-23'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-23'>#</a>
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</div>
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<p>loss in batch</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">197</span> <span class="n">loss</span> <span class="o">+=</span> <span class="n">cost</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span>
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<span class="lineno">198</span> <span class="n">train_steps</span><span class="o">+=</span><span class="mi">1</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-24'>
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<div class='docs'>
|
|
<div class='section-link'>
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<a href='#section-24'>#</a>
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</div>
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<p>losses[epoch] += loss.item()</p>
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</div>
|
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<div class='code'>
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|
<div class="highlight"><pre><span class="lineno">201</span> <span class="n">_</span><span class="p">,</span> <span class="n">predicted</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">outputs</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
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<span class="lineno">202</span> <span class="n">total</span> <span class="o">+=</span> <span class="n">labels</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
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<span class="lineno">203</span> <span class="n">correct</span> <span class="o">+=</span> <span class="p">(</span><span class="n">predicted</span> <span class="o">==</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>
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<span class="lineno">204</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">loss</span><span class="o">/</span><span class="n">train_steps</span>
|
|
<span class="lineno">205</span>
|
|
<span class="lineno">206</span> <span class="n">accuracy</span> <span class="o">=</span> <span class="n">correct</span> <span class="o">/</span> <span class="n">total</span>
|
|
<span class="lineno">207</span> <span class="n">loss_accuracy</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'val_loss'</span><span class="p">:</span> <span class="n">loss</span><span class="p">,</span> <span class="s1">'val_acc'</span><span class="p">:</span> <span class="n">accuracy</span><span class="p">}</span> <span class="c1">#accuracy</span>
|
|
<span class="lineno">208</span> <span class="k">return</span> <span class="n">loss_accuracy</span></pre></div>
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</div>
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</div>
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</div>
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</div>
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