chore: import upstream snapshot with attribution
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<meta property="og:description" content="This experiment generates MNIST images using convolutional neural network."/>
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<title>WGAN experiment with MNIST</title>
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<a class="parent" href="/">home</a>
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<a class="parent" href="../index.html">gan</a>
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<a class="parent" href="index.html">wasserstein</a>
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</p>
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<p>
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<a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations" target="_blank">
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<a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/gan/wasserstein/experiment.py" target="_blank">
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View code on Github</a>
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</p>
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</div>
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</div>
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<div class='section' id='section-0'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-0'>#</a>
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</div>
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<h1>WGAN 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">9</span><span></span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">experiment</span>
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<span class="lineno">10</span>
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<span class="lineno">11</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">calculate</span></pre></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>Import configurations from <a href="../dcgan/index.html">DCGAN experiment</a> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">13</span><span class="kn">from</span> <span class="nn">labml_nn.gan.dcgan</span> <span class="kn">import</span> <span class="n">Configs</span></pre></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>Import <a href="./index.html">Wasserstein GAN losses</a> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">16</span><span class="kn">from</span> <span class="nn">labml_nn.gan.wasserstein</span> <span class="kn">import</span> <span class="n">GeneratorLoss</span><span class="p">,</span> <span class="n">DiscriminatorLoss</span></pre></div>
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<div class='section' id='section-3'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<p>Set configurations options for Wasserstein GAN losses </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">19</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">generator_loss</span><span class="p">,</span> <span class="s1">'wasserstein'</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">GeneratorLoss</span><span class="p">())</span>
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<span class="lineno">20</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">discriminator_loss</span><span class="p">,</span> <span class="s1">'wasserstein'</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">DiscriminatorLoss</span><span class="p">())</span></pre></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 class='code'>
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<div class="highlight"><pre><span class="lineno">23</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span></pre></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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<p>Create configs object </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">25</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span></pre></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>Create experiment </p>
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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="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_wassertein_dcgan'</span><span class="p">,</span> <span class="n">comment</span><span class="o">=</span><span class="s1">'test'</span><span class="p">)</span></pre></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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<p>Override configurations </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">29</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">30</span> <span class="p">{</span>
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<span class="lineno">31</span> <span class="s1">'discriminator'</span><span class="p">:</span> <span class="s1">'cnn'</span><span class="p">,</span>
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<span class="lineno">32</span> <span class="s1">'generator'</span><span class="p">:</span> <span class="s1">'cnn'</span><span class="p">,</span>
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<span class="lineno">33</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">34</span> <span class="s1">'generator_loss'</span><span class="p">:</span> <span class="s1">'wasserstein'</span><span class="p">,</span>
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<span class="lineno">35</span> <span class="s1">'discriminator_loss'</span><span class="p">:</span> <span class="s1">'wasserstein'</span><span class="p">,</span>
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<span class="lineno">36</span> <span class="p">})</span></pre></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>Start the experiment and run training loop </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">39</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">40</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">41</span>
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<span class="lineno">42</span>
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<span class="lineno">43</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">44</span> <span class="n">main</span><span class="p">()</span></pre></div>
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<head>
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<meta http-equiv="content-type" content="text/html;charset=utf-8"/>
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<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
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<meta name="description" content="This experiment generates MNIST images using convolutional neural network."/>
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<meta name="twitter:card" content="summary"/>
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<meta name="twitter:image:src" content="https://avatars1.githubusercontent.com/u/64068543?s=400&v=4"/>
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<meta name="twitter:title" content="WGAN-GP experiment with MNIST"/>
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<meta property="og:title" content="WGAN-GP experiment with MNIST"/>
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<meta property="og:image" content="https://avatars1.githubusercontent.com/u/64068543?s=400&v=4"/>
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<meta property="og:site_name" content="WGAN-GP experiment with MNIST"/>
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<meta property="og:type" content="object"/>
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<meta property="og:title" content="WGAN-GP experiment with MNIST"/>
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<meta property="og:description" content="This experiment generates MNIST images using convolutional neural network."/>
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<title>WGAN-GP experiment with MNIST</title>
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<div class='docs'>
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<a class="parent" href="/">home</a>
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<a class="parent" href="../../index.html">gan</a>
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<a class="parent" href="../index.html">wasserstein</a>
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<a class="parent" href="index.html">gradient_penalty</a>
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<div class='section' id='section-0'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-0'>#</a>
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</div>
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<h1>WGAN-GP 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">import</span> <span class="nn">torch</span>
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<span class="lineno">11</span>
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<span class="lineno">12</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">experiment</span><span class="p">,</span> <span class="n">tracker</span></pre></div>
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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>Import configurations from <a href="../experiment.html">Wasserstein experiment</a> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">14</span><span class="kn">from</span> <span class="nn">labml_nn.gan.wasserstein.experiment</span> <span class="kn">import</span> <span class="n">Configs</span> <span class="k">as</span> <span class="n">OriginalConfigs</span></pre></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> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">16</span><span class="kn">from</span> <span class="nn">labml_nn.gan.wasserstein.gradient_penalty</span> <span class="kn">import</span> <span class="n">GradientPenalty</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 doc-strings'>
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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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<h2>Configuration class</h2>
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<p>We extend <a href="../../original/experiment.html">original GAN implementation</a> and override the discriminator (critic) loss calculation to include gradient penalty.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">19</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">OriginalConfigs</span><span class="p">):</span></pre></div>
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</div>
|
||||
</div>
|
||||
<div class='section' id='section-4'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-4'>#</a>
|
||||
</div>
|
||||
<p>Gradient penalty coefficient <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal">λ</span></span></span></span></span> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">28</span> <span class="n">gradient_penalty_coefficient</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">10.0</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-5'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-5'>#</a>
|
||||
</div>
|
||||
<p> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">30</span> <span class="n">gradient_penalty</span> <span class="o">=</span> <span class="n">GradientPenalty</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-6'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-6'>#</a>
|
||||
</div>
|
||||
<p> This overrides the original discriminator loss calculation and includes gradient penalty.</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">32</span> <span class="k">def</span> <span class="nf">calc_discriminator_loss</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-7'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-7'>#</a>
|
||||
</div>
|
||||
<p>Require gradients on <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord coloredeq eqe" style=""><span class="mord mathnormal" style="">x</span></span></span></span></span></span> to calculate gradient penalty </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">38</span> <span class="n">data</span><span class="o">.</span><span class="n">requires_grad_</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-8'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-8'>#</a>
|
||||
</div>
|
||||
<p>Sample <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">∼</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">p</span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mclose">)</span></span></span></span></span> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">40</span> <span class="n">latent</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sample_z</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></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-9'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-9'>#</a>
|
||||
</div>
|
||||
<p><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.02778em;">D</span><span class="mopen">(</span><span class="mord coloredeq eqe" style=""><span class="mord mathnormal" style="">x</span></span><span class="mclose">)</span></span></span></span></span> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">42</span> <span class="n">f_real</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></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-10'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-10'>#</a>
|
||||
</div>
|
||||
<p><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.02778em;">D</span><span class="mopen">(</span><span class="mord"><span class="mord mathnormal">G</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.02778em;">θ</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mclose">))</span></span></span></span></span> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">44</span> <span class="n">f_fake</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></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-11'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-11'>#</a>
|
||||
</div>
|
||||
<p>Get discriminator losses </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">46</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">f_real</span><span class="p">,</span> <span class="n">f_fake</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>Calculate gradient penalties in training mode </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">48</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">49</span> <span class="n">gradient_penalty</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">gradient_penalty</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">f_real</span><span class="p">)</span>
|
||||
<span class="lineno">50</span> <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">"loss.gp."</span><span class="p">,</span> <span class="n">gradient_penalty</span><span class="p">)</span>
|
||||
<span class="lineno">51</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> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">gradient_penalty_coefficient</span> <span class="o">*</span> <span class="n">gradient_penalty</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>Skip gradient penalty otherwise </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">53</span> <span class="k">else</span><span class="p">:</span>
|
||||
<span class="lineno">54</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-14'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-14'>#</a>
|
||||
</div>
|
||||
<p>Log stuff </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">57</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">58</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">59</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>
|
||||
<span class="lineno">60</span>
|
||||
<span class="lineno">61</span> <span class="k">return</span> <span class="n">loss</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">64</span><span class="k">def</span> <span class="nf">main</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>Create configs object </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">66</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-17'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-17'>#</a>
|
||||
</div>
|
||||
<p>Create experiment </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">68</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_wassertein_gp_dcgan'</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>Override configurations </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">70</span> <span class="n">experiment</span><span class="o">.</span><span class="n">configs</span><span class="p">(</span><span class="n">conf</span><span class="p">,</span>
|
||||
<span class="lineno">71</span> <span class="p">{</span>
|
||||
<span class="lineno">72</span> <span class="s1">'discriminator'</span><span class="p">:</span> <span class="s1">'cnn'</span><span class="p">,</span>
|
||||
<span class="lineno">73</span> <span class="s1">'generator'</span><span class="p">:</span> <span class="s1">'cnn'</span><span class="p">,</span>
|
||||
<span class="lineno">74</span> <span class="s1">'label_smoothing'</span><span class="p">:</span> <span class="mf">0.01</span><span class="p">,</span>
|
||||
<span class="lineno">75</span> <span class="s1">'generator_loss'</span><span class="p">:</span> <span class="s1">'wasserstein'</span><span class="p">,</span>
|
||||
<span class="lineno">76</span> <span class="s1">'discriminator_loss'</span><span class="p">:</span> <span class="s1">'wasserstein'</span><span class="p">,</span>
|
||||
<span class="lineno">77</span> <span class="s1">'discriminator_k'</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
|
||||
<span class="lineno">78</span> <span class="p">})</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>Start the experiment and run training loop </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">81</span> <span class="k">with</span> <span class="n">experiment</span><span class="o">.</span><span class="n">start</span><span class="p">():</span>
|
||||
<span class="lineno">82</span> <span class="n">conf</span><span class="o">.</span><span class="n">run</span><span class="p">()</span>
|
||||
<span class="lineno">83</span>
|
||||
<span class="lineno">84</span>
|
||||
<span class="lineno">85</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
|
||||
<span class="lineno">86</span> <span class="n">main</span><span class="p">()</span></pre></div>
|
||||
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|
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<h1><a href="https://nn.labml.ai/gan/wasserstein/gradient_penalty/index.html">Gradient Penalty for Wasserstein GAN (WGAN-GP)</a></h1>
|
||||
<p>This is an implementation of <a href="https://arxiv.org/abs/1704.00028">Improved Training of Wasserstein GANs</a>.</p>
|
||||
<p><a href="https://nn.labml.ai/gan/wasserstein/index.html">WGAN</a> suggests clipping weights to enforce Lipschitz constraint on the discriminator network (critic). This and other weight constraints like L2 norm clipping, weight normalization, L1, L2 weight decay have problems:</p>
|
||||
<p>1. Limiting the capacity of the discriminator 2. Exploding and vanishing gradients (without <a href="https://nn.labml.ai/normalization/batch_norm/index.html">Batch Normalization</a>).</p>
|
||||
<p>The paper <a href="https://arxiv.org/abs/1704.00028">Improved Training of Wasserstein GANs</a> proposal a better way to improve Lipschitz constraint, a gradient penalty. </p>
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