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<h1>Generative Adversarial Networks experiment with MNIST</h1>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">10</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span>
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<span class="lineno">11</span>
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<span class="lineno">12</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">13</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
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<span class="lineno">14</span><span class="kn">import</span> <span class="nn">torch.utils.data</span>
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<span class="lineno">15</span><span class="kn">from</span> <span class="nn">torchvision</span> <span class="kn">import</span> <span class="n">transforms</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">tracker</span><span class="p">,</span> <span class="n">monit</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">option</span>
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<span class="lineno">19</span><span class="kn">from</span> <span class="nn">labml_helpers.datasets.mnist</span> <span class="kn">import</span> <span class="n">MNISTConfigs</span>
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<span class="lineno">20</span><span class="kn">from</span> <span class="nn">labml_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_helpers.module</span> <span class="kn">import</span> <span class="n">Module</span>
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<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml_helpers.optimizer</span> <span class="kn">import</span> <span class="n">OptimizerConfigs</span>
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<span class="lineno">23</span><span class="kn">from</span> <span class="nn">labml_helpers.train_valid</span> <span class="kn">import</span> <span class="n">TrainValidConfigs</span><span class="p">,</span> <span class="n">hook_model_outputs</span><span class="p">,</span> <span class="n">BatchIndex</span>
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<span class="lineno">24</span><span class="kn">from</span> <span class="nn">labml_nn.gan</span> <span class="kn">import</span> <span class="n">DiscriminatorLogitsLoss</span><span class="p">,</span> <span class="n">GeneratorLogitsLoss</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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">27</span><span class="k">def</span> <span class="nf">weights_init</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
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<span class="lineno">28</span> <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
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<span class="lineno">29</span> <span class="k">if</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">'Linear'</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
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<span class="lineno">30</span> <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
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<span class="lineno">31</span> <span class="k">elif</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">'BatchNorm'</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
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<span class="lineno">32</span> <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
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<span class="lineno">33</span> <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</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-2'>
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<div class='docs doc-strings'>
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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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<h3>Simple MLP Generator</h3>
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<p>This has three linear layers of increasing size with <code>LeakyReLU</code> activations.
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The final layer has a $tanh$ activation.</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="k">class</span> <span class="nc">Generator</span><span class="p">(</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-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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">44</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">45</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
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<span class="lineno">46</span> <span class="n">layer_sizes</span> <span class="o">=</span> <span class="p">[</span><span class="mi">256</span><span class="p">,</span> <span class="mi">512</span><span class="p">,</span> <span class="mi">1024</span><span class="p">]</span>
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<span class="lineno">47</span> <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">48</span> <span class="n">d_prev</span> <span class="o">=</span> <span class="mi">100</span>
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<span class="lineno">49</span> <span class="k">for</span> <span class="n">size</span> <span class="ow">in</span> <span class="n">layer_sizes</span><span class="p">:</span>
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<span class="lineno">50</span> <span class="n">layers</span> <span class="o">=</span> <span class="n">layers</span> <span class="o">+</span> <span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="n">size</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">LeakyReLU</span><span class="p">(</span><span class="mf">0.2</span><span class="p">)]</span>
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<span class="lineno">51</span> <span class="n">d_prev</span> <span class="o">=</span> <span class="n">size</span>
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<span class="lineno">52</span>
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<span class="lineno">53</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="mi">28</span> <span class="o">*</span> <span class="mi">28</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span>
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<span class="lineno">54</span>
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<span class="lineno">55</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init</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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">57</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>
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<span class="lineno">58</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">28</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 doc-strings'>
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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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<h3>Simple MLP Discriminator</h3>
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<p>This has three linear layers of decreasing size with <code>LeakyReLU</code> activations.
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The final layer has a single output that gives the logit of whether input
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is real or fake. You can get the probability by calculating the sigmoid of it.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">61</span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</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-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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">70</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">71</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
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<span class="lineno">72</span> <span class="n">layer_sizes</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1024</span><span class="p">,</span> <span class="mi">512</span><span class="p">,</span> <span class="mi">256</span><span class="p">]</span>
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<span class="lineno">73</span> <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">74</span> <span class="n">d_prev</span> <span class="o">=</span> <span class="mi">28</span> <span class="o">*</span> <span class="mi">28</span>
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<span class="lineno">75</span> <span class="k">for</span> <span class="n">size</span> <span class="ow">in</span> <span class="n">layer_sizes</span><span class="p">:</span>
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<span class="lineno">76</span> <span class="n">layers</span> <span class="o">=</span> <span class="n">layers</span> <span class="o">+</span> <span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="n">size</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">LeakyReLU</span><span class="p">(</span><span class="mf">0.2</span><span class="p">)]</span>
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<span class="lineno">77</span> <span class="n">d_prev</span> <span class="o">=</span> <span class="n">size</span>
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<span class="lineno">78</span>
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<span class="lineno">79</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
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<span class="lineno">80</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init</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">82</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>
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<span class="lineno">83</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</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-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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">86</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="p">,</span> <span class="n">TrainValidConfigs</span><span class="p">):</span>
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<span class="lineno">87</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>
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<span class="lineno">88</span> <span class="n">epochs</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span>
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<span class="lineno">89</span>
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<span class="lineno">90</span> <span class="n">is_save_models</span> <span class="o">=</span> <span class="kc">True</span>
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<span class="lineno">91</span> <span class="n">discriminator</span><span class="p">:</span> <span class="n">Module</span>
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<span class="lineno">92</span> <span class="n">generator</span><span class="p">:</span> <span class="n">Module</span>
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<span class="lineno">93</span> <span class="n">generator_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>
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<span class="lineno">94</span> <span class="n">discriminator_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>
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<span class="lineno">95</span> <span class="n">generator_loss</span><span class="p">:</span> <span class="n">GeneratorLogitsLoss</span>
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<span class="lineno">96</span> <span class="n">discriminator_loss</span><span class="p">:</span> <span class="n">DiscriminatorLogitsLoss</span>
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<span class="lineno">97</span> <span class="n">label_smoothing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span>
|
|
<span class="lineno">98</span> <span class="n">discriminator_k</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-9'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-9'>#</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">100</span> <span class="k">def</span> <span class="nf">init</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
|
<span class="lineno">101</span> <span class="bp">self</span><span class="o">.</span><span class="n">state_modules</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">102</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span> <span class="o">=</span> <span class="n">Generator</span><span class="p">()</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>
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<span class="lineno">103</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span> <span class="o">=</span> <span class="n">Discriminator</span><span class="p">()</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>
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<span class="lineno">104</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator_loss</span> <span class="o">=</span> <span class="n">GeneratorLogitsLoss</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_smoothing</span><span class="p">)</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>
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<span class="lineno">105</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_loss</span> <span class="o">=</span> <span class="n">DiscriminatorLogitsLoss</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_smoothing</span><span class="p">)</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>
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<span class="lineno">106</span>
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<span class="lineno">107</span> <span class="n">hook_model_outputs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">,</span> <span class="s1">'generator'</span><span class="p">)</span>
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<span class="lineno">108</span> <span class="n">hook_model_outputs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">,</span> <span class="s1">'discriminator'</span><span class="p">)</span>
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|
<span class="lineno">109</span> <span class="n">tracker</span><span class="o">.</span><span class="n">set_scalar</span><span class="p">(</span><span class="s2">"loss.generator.*"</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
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|
<span class="lineno">110</span> <span class="n">tracker</span><span class="o">.</span><span class="n">set_scalar</span><span class="p">(</span><span class="s2">"loss.discriminator.*"</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
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<span class="lineno">111</span> <span class="n">tracker</span><span class="o">.</span><span class="n">set_image</span><span class="p">(</span><span class="s2">"generated"</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="mi">1</span> <span class="o">/</span> <span class="mi">100</span><span class="p">)</span></pre></div>
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</div>
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</div>
|
|
<div class='section' id='section-10'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-10'>#</a>
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</div>
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|
</div>
|
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">113</span> <span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">batch_idx</span><span class="p">:</span> <span class="n">BatchIndex</span><span class="p">):</span>
|
|
<span class="lineno">114</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">)</span>
|
|
<span class="lineno">115</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">)</span>
|
|
<span class="lineno">116</span>
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|
<span class="lineno">117</span> <span class="n">data</span><span class="p">,</span> <span class="n">target</span> <span class="o">=</span> <span class="n">batch</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="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">),</span> <span class="n">batch</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="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-11'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-11'>#</a>
|
|
</div>
|
|
<p>Increment step in training mode</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">120</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
|
|
<span class="lineno">121</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add_global_step</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-12'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-12'>#</a>
|
|
</div>
|
|
<p>Train the discriminator</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">124</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="s2">"discriminator"</span><span class="p">):</span>
|
|
<span class="lineno">125</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">discriminator_k</span><span class="p">):</span>
|
|
<span class="lineno">126</span> <span class="n">latent</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">100</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span>
|
|
<span class="lineno">127</span> <span class="n">logits_true</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
|
<span class="lineno">128</span> <span class="n">logits_false</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">(</span><span class="n">latent</span><span class="p">)</span><span class="o">.</span><span class="n">detach</span><span class="p">())</span>
|
|
<span class="lineno">129</span> <span class="n">loss_true</span><span class="p">,</span> <span class="n">loss_false</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_loss</span><span class="p">(</span><span class="n">logits_true</span><span class="p">,</span> <span class="n">logits_false</span><span class="p">)</span>
|
|
<span class="lineno">130</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">loss_true</span> <span class="o">+</span> <span class="n">loss_false</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-13'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-13'>#</a>
|
|
</div>
|
|
<p>Log stuff</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">133</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">"loss.discriminator.true."</span><span class="p">,</span> <span class="n">loss_true</span><span class="p">)</span>
|
|
<span class="lineno">134</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">"loss.discriminator.false."</span><span class="p">,</span> <span class="n">loss_false</span><span class="p">)</span>
|
|
<span class="lineno">135</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">"loss.discriminator."</span><span class="p">,</span> <span class="n">loss</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>Train</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">138</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
|
|
<span class="lineno">139</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
|
|
<span class="lineno">140</span> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
|
|
<span class="lineno">141</span> <span class="k">if</span> <span class="n">batch_idx</span><span class="o">.</span><span class="n">is_last</span><span class="p">:</span>
|
|
<span class="lineno">142</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'discriminator'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">)</span>
|
|
<span class="lineno">143</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-15'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-15'>#</a>
|
|
</div>
|
|
<p>Train the generator</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">146</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="s2">"generator"</span><span class="p">):</span>
|
|
<span class="lineno">147</span> <span class="n">latent</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">100</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span>
|
|
<span class="lineno">148</span> <span class="n">generated_images</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">(</span><span class="n">latent</span><span class="p">)</span>
|
|
<span class="lineno">149</span> <span class="n">logits</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="n">generated_images</span><span class="p">)</span>
|
|
<span class="lineno">150</span> <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator_loss</span><span class="p">(</span><span class="n">logits</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>Log stuff</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">153</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'generated'</span><span class="p">,</span> <span class="n">generated_images</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">5</span><span class="p">])</span>
|
|
<span class="lineno">154</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">"loss.generator."</span><span class="p">,</span> <span class="n">loss</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>Train</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">157</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
|
|
<span class="lineno">158</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
|
|
<span class="lineno">159</span> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
|
|
<span class="lineno">160</span> <span class="k">if</span> <span class="n">batch_idx</span><span class="o">.</span><span class="n">is_last</span><span class="p">:</span>
|
|
<span class="lineno">161</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">'generator'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">)</span>
|
|
<span class="lineno">162</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
|
|
<span class="lineno">163</span>
|
|
<span class="lineno">164</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-18'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-18'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">167</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
|
|
<span class="lineno">168</span><span class="k">def</span> <span class="nf">mnist_transforms</span><span class="p">():</span>
|
|
<span class="lineno">169</span> <span class="k">return</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
|
|
<span class="lineno">170</span> <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
|
|
<span class="lineno">171</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="p">(</span><span class="mf">0.5</span><span class="p">,))</span>
|
|
<span class="lineno">172</span> <span class="p">])</span>
|
|
<span class="lineno">173</span>
|
|
<span class="lineno">174</span>
|
|
<span class="lineno">175</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="p">)</span>
|
|
<span class="lineno">176</span><span class="k">def</span> <span class="nf">_discriminator_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span>
|
|
<span class="lineno">177</span> <span class="n">opt_conf</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span>
|
|
<span class="lineno">178</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">optimizer</span> <span class="o">=</span> <span class="s1">'Adam'</span>
|
|
<span class="lineno">179</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">discriminator</span><span class="o">.</span><span class="n">parameters</span><span class="p">()</span>
|
|
<span class="lineno">180</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">2.5e-4</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>Setting exponent decay rate for first moment of gradient,
|
|
$\beta_<code>$ to</code>0.5<code>is important.
|
|
Default of</code>0.9` fails.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">184</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">betas</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">)</span>
|
|
<span class="lineno">185</span> <span class="k">return</span> <span class="n">opt_conf</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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">188</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="p">)</span>
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<span class="lineno">189</span><span class="k">def</span> <span class="nf">_generator_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span>
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<span class="lineno">190</span> <span class="n">opt_conf</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span>
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<span class="lineno">191</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">optimizer</span> <span class="o">=</span> <span class="s1">'Adam'</span>
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<span class="lineno">192</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">generator</span><span class="o">.</span><span class="n">parameters</span><span class="p">()</span>
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<span class="lineno">193</span> <span class="n">opt_conf</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">2.5e-4</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>Setting exponent decay rate for first moment of gradient,
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$\beta_<code>$ to</code>0.5<code>is important.
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Default of</code>0.9` fails.</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">opt_conf</span><span class="o">.</span><span class="n">betas</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">)</span>
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<span class="lineno">198</span> <span class="k">return</span> <span class="n">opt_conf</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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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">201</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span>
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<span class="lineno">202</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span>
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<span class="lineno">203</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">'mnist_gan'</span><span class="p">,</span> <span class="n">comment</span><span class="o">=</span><span class="s1">'test'</span><span class="p">)</span>
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<span class="lineno">204</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>
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<span class="lineno">205</span> <span class="p">{</span><span class="s1">'label_smoothing'</span><span class="p">:</span> <span class="mf">0.01</span><span class="p">})</span>
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<span class="lineno">206</span> <span class="k">with</span> <span class="n">experiment</span><span class="o">.</span><span class="n">start</span><span class="p">():</span>
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<span class="lineno">207</span> <span class="n">conf</span><span class="o">.</span><span class="n">run</span><span class="p">()</span>
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<span class="lineno">208</span>
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<span class="lineno">209</span>
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<span class="lineno">210</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
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<span class="lineno">211</span> <span class="n">main</span><span class="p">()</span></pre></div>
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