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<div class="highlight"><pre><span class="lineno">2</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">3</span><span class="kn">import</span> <span class="nn">torchvision</span>
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<span class="lineno">4</span><span class="kn">import</span> <span class="nn">torchvision.transforms</span> <span class="k">as</span> <span class="nn">transforms</span>
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<span class="lineno">5</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">6</span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
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<span class="lineno">7</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">8</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">9</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">10</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</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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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<p>from models.mlp import MLP
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from utils.utils import *
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from utils.train_dataset import *
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from nutsflow import Take, Consume
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from nutsml import *</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">17</span><span class="kn">from</span> <span class="nn">utils.dataloader</span> <span class="kn">import</span> <span class="o">*</span>
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<span class="lineno">18</span><span class="kn">from</span> <span class="nn">models.cnn</span> <span class="kn">import</span> <span class="n">CNN</span>
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<span class="lineno">19</span><span class="kn">from</span> <span class="nn">utils.train</span> <span class="kn">import</span> <span class="n">Trainer</span>
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<span class="lineno">20</span>
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<span class="lineno">21</span><span class="kn">from</span> <span class="nn">utils.cv_train</span> <span class="kn">import</span> <span class="o">*</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>Check if GPU is available</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">24</span><span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">"cuda:0"</span> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span> <span class="k">else</span> <span class="s2">"cpu"</span><span class="p">)</span>
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<span class="lineno">25</span><span class="nb">print</span><span class="p">(</span><span class="s2">"Device: "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">device</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-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>Cifar 10 Datasets location</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">28</span><span class="n">save</span><span class="o">=</span><span class="s1">'./data/Cifar10'</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>Transformations train</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">31</span><span class="n">transform_train</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">(</span>
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<span class="lineno">32</span> <span class="p">[</span><span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
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<span class="lineno">33</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">((</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">),</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</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-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>Load train dataset and dataloader</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">36</span><span class="n">trainset</span> <span class="o">=</span> <span class="n">LoadCifar10DatasetTrain</span><span class="p">(</span><span class="n">save</span><span class="p">,</span> <span class="n">transform_train</span><span class="p">)</span>
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<span class="lineno">37</span><span class="n">trainloader</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="mi">64</span><span class="p">,</span>
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<span class="lineno">38</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">num_workers</span><span class="o">=</span><span class="mi">4</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>Transformations test (for inference later)</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">41</span><span class="n">transform_test</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">(</span>
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<span class="lineno">42</span> <span class="p">[</span><span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
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<span class="lineno">43</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">((</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">),</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</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>Load test dataset and dataloader (for inference later)</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">46</span><span class="n">testset</span> <span class="o">=</span> <span class="n">LoadCifar10DatasetTest</span><span class="p">(</span><span class="n">save</span><span class="p">,</span> <span class="n">transform_test</span><span class="p">)</span>
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<span class="lineno">47</span><span class="n">testloader</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">testset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span>
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<span class="lineno">48</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">num_workers</span><span class="o">=</span><span class="mi">4</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'>
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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>Specify loss function</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">51</span><span class="n">cost</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">CrossEntropyLoss</span><span class="p">()</span>
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<span class="lineno">52</span>
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<span class="lineno">53</span><span class="n">epochs</span><span class="o">=</span><span class="mi">25</span> <span class="c1">#10</span>
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<span class="lineno">54</span><span class="n">splits</span> <span class="o">=</span> <span class="mi">4</span> <span class="c1">#5</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>Training - Cross-validation</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">57</span><span class="n">history</span> <span class="o">=</span> <span class="n">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="n">device</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-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>Inference</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">60</span><span class="n">best_model</span><span class="p">,</span> <span class="n">best_val_accuracy</span> <span class="o">=</span> <span class="n">retreive_best_trial</span><span class="p">()</span>
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<span class="lineno">61</span><span class="nb">print</span><span class="p">(</span><span class="s2">"Best Validation Accuracy = </span><span class="si">%.3f</span><span class="s2">"</span><span class="o">%</span><span class="p">(</span><span class="n">best_val_accuracy</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>Testing</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">64</span><span class="n">accuracy</span> <span class="o">=</span> <span class="n">Test</span><span class="p">(</span><span class="n">best_model</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="o">=</span><span class="n">device</span><span class="p">)</span>
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<span class="lineno">65</span><span class="nb">print</span><span class="p">(</span><span class="s2">"Test Accuracy = </span><span class="si">%.3f</span><span class="s2">"</span><span class="o">%</span><span class="p">(</span><span class="n">accuracy</span><span class="p">[</span><span class="s1">'val_acc'</span><span class="p">]))</span></pre></div>
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