mirror of
https://github.com/labmlai/annotated_deep_learning_paper_implementations.git
synced 2025-08-14 09:31:42 +08:00
494 lines
40 KiB
HTML
494 lines
40 KiB
HTML
<!DOCTYPE html>
|
|
<html>
|
|
<head>
|
|
<meta http-equiv="content-type" content="text/html;charset=utf-8"/>
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
|
|
<meta name="description" content=""/>
|
|
|
|
<meta name="twitter:card" content="summary"/>
|
|
<meta name="twitter:image:src" content="https://avatars1.githubusercontent.com/u/64068543?s=400&v=4"/>
|
|
<meta name="twitter:title" content="cnn_visualization.py"/>
|
|
<meta name="twitter:description" content=""/>
|
|
<meta name="twitter:site" content="@labmlai"/>
|
|
<meta name="twitter:creator" content="@labmlai"/>
|
|
|
|
<meta property="og:url" content="https://nn.labml.ai/cnn/cnn_visualization.html"/>
|
|
<meta property="og:title" content="cnn_visualization.py"/>
|
|
<meta property="og:image" content="https://avatars1.githubusercontent.com/u/64068543?s=400&v=4"/>
|
|
<meta property="og:site_name" content="LabML Neural Networks"/>
|
|
<meta property="og:type" content="object"/>
|
|
<meta property="og:title" content="cnn_visualization.py"/>
|
|
<meta property="og:description" content=""/>
|
|
|
|
<title>cnn_visualization.py</title>
|
|
<link rel="shortcut icon" href="/icon.png"/>
|
|
<link rel="stylesheet" href="../pylit.css">
|
|
<link rel="canonical" href="https://nn.labml.ai/cnn/cnn_visualization.html"/>
|
|
<!-- Global site tag (gtag.js) - Google Analytics -->
|
|
<script async src="https://www.googletagmanager.com/gtag/js?id=G-4V3HC8HBLH"></script>
|
|
<script>
|
|
window.dataLayer = window.dataLayer || [];
|
|
|
|
function gtag() {
|
|
dataLayer.push(arguments);
|
|
}
|
|
|
|
gtag('js', new Date());
|
|
|
|
gtag('config', 'G-4V3HC8HBLH');
|
|
</script>
|
|
</head>
|
|
<body>
|
|
<div id='container'>
|
|
<div id="background"></div>
|
|
<div class='section'>
|
|
<div class='docs'>
|
|
<p>
|
|
<a class="parent" href="/">home</a>
|
|
<a class="parent" href="index.html">cnn</a>
|
|
</p>
|
|
<p>
|
|
|
|
<a href="https://github.com/lab-ml/labml_nn/tree/master/labml_nn/cnn/cnn_visualization.py">
|
|
<img alt="Github"
|
|
src="https://img.shields.io/github/stars/lab-ml/nn?style=social"
|
|
style="max-width:100%;"/></a>
|
|
<a href="https://twitter.com/labmlai"
|
|
rel="nofollow">
|
|
<img alt="Twitter"
|
|
src="https://img.shields.io/twitter/follow/labmlai?style=social"
|
|
style="max-width:100%;"/></a>
|
|
</p>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-0'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-0'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">3</span><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
|
|
<span class="lineno">4</span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>
|
|
<span class="lineno">5</span><span class="kn">from</span> <span class="nn">torchsummary</span> <span class="kn">import</span> <span class="n">summary</span>
|
|
<span class="lineno">6</span><span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">partial</span>
|
|
<span class="lineno">7</span><span class="kn">from</span> <span class="nn">skimage.filters</span> <span class="kn">import</span> <span class="n">sobel</span><span class="p">,</span> <span class="n">sobel_h</span><span class="p">,</span> <span class="n">roberts</span>
|
|
<span class="lineno">8</span><span class="kn">from</span> <span class="nn">models.cnn</span> <span class="kn">import</span> <span class="n">CNN</span>
|
|
<span class="lineno">9</span><span class="kn">from</span> <span class="nn">utils.dataloader</span> <span class="kn">import</span> <span class="o">*</span>
|
|
<span class="lineno">10</span><span class="kn">from</span> <span class="nn">utils.train</span> <span class="kn">import</span> <span class="n">Trainer</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-1'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-1'>#</a>
|
|
</div>
|
|
<p>Check if GPU is available</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">13</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>
|
|
<span class="lineno">14</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>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-2'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-2'>#</a>
|
|
</div>
|
|
<p>Cifar 10 Datasets location</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">17</span><span class="n">save</span><span class="o">=</span><span class="s1">'./data/Cifar10'</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-3'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-3'>#</a>
|
|
</div>
|
|
<p>Transformations train</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">20</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>
|
|
<span class="lineno">21</span> <span class="p">[</span><span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
|
|
<span class="lineno">22</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>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-4'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-4'>#</a>
|
|
</div>
|
|
<p>Load train dataset and dataloader</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">25</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>
|
|
<span class="lineno">26</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>
|
|
<span class="lineno">27</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>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-5'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-5'>#</a>
|
|
</div>
|
|
<p>Transformations test</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">30</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>
|
|
<span class="lineno">31</span> <span class="p">[</span><span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
|
|
<span class="lineno">32</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>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-6'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-6'>#</a>
|
|
</div>
|
|
<p>Load test dataset and dataloader</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">35</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>
|
|
<span class="lineno">36</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>
|
|
<span class="lineno">37</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>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-7'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-7'>#</a>
|
|
</div>
|
|
<p>Create CNN model</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">40</span><span class="k">def</span> <span class="nf">GetCNN</span><span class="p">():</span>
|
|
<span class="lineno">41</span> <span class="n">cnn</span> <span class="o">=</span> <span class="n">CNN</span><span class="p">(</span> <span class="n">in_features</span><span class="o">=</span><span class="p">(</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">3</span><span class="p">),</span>
|
|
<span class="lineno">42</span> <span class="n">out_features</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
|
|
<span class="lineno">43</span> <span class="n">conv_filters</span><span class="o">=</span><span class="p">[</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">64</span><span class="p">,</span><span class="mi">64</span><span class="p">],</span>
|
|
<span class="lineno">44</span> <span class="n">conv_kernel_size</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">],</span>
|
|
<span class="lineno">45</span> <span class="n">conv_strides</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span>
|
|
<span class="lineno">46</span> <span class="n">conv_pad</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">],</span>
|
|
<span class="lineno">47</span> <span class="n">max_pool_kernels</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">)],</span>
|
|
<span class="lineno">48</span> <span class="n">max_pool_strides</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="kc">None</span><span class="p">,</span><span class="mi">2</span><span class="p">],</span>
|
|
<span class="lineno">49</span> <span class="n">use_dropout</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
|
<span class="lineno">50</span> <span class="n">use_batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="c1">#False</span>
|
|
<span class="lineno">51</span> <span class="n">actv_func</span><span class="o">=</span><span class="p">[</span><span class="s2">"relu"</span><span class="p">,</span> <span class="s2">"relu"</span><span class="p">,</span> <span class="s2">"relu"</span><span class="p">,</span> <span class="s2">"relu"</span><span class="p">],</span>
|
|
<span class="lineno">52</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span>
|
|
<span class="lineno">53</span> <span class="p">)</span>
|
|
<span class="lineno">54</span>
|
|
<span class="lineno">55</span> <span class="k">return</span> <span class="n">cnn</span>
|
|
<span class="lineno">56</span>
|
|
<span class="lineno">57</span><span class="n">model</span> <span class="o">=</span> <span class="n">GetCNN</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>Display model specifications</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">60</span><span class="n">summary</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-9'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-9'>#</a>
|
|
</div>
|
|
<p>Send model to GPU</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">63</span><span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</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>Specify optimizer</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">66</span><span class="n">opt</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.0005</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="mf">0.95</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-11'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-11'>#</a>
|
|
</div>
|
|
<p>Specify loss function</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">69</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></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 model</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">72</span><span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Basic_CNN"</span><span class="p">)</span>
|
|
<span class="lineno">73</span><span class="n">epochs</span> <span class="o">=</span> <span class="mi">5</span>
|
|
<span class="lineno">74</span><span class="n">trainer</span><span class="o">.</span><span class="n">Train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">trainloader</span><span class="p">,</span> <span class="n">testloader</span><span class="p">,</span> <span class="n">cost</span><span class="o">=</span><span class="n">cost</span><span class="p">,</span> <span class="n">opt</span><span class="o">=</span><span class="n">opt</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="n">epochs</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-13'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-13'>#</a>
|
|
</div>
|
|
<p>Load best saved model for inference</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">77</span><span class="n">model_loaded</span> <span class="o">=</span> <span class="n">GetCNN</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>Specify location of saved model</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">80</span><span class="n">PATH</span> <span class="o">=</span> <span class="s2">"./save/Basic_CNN-best-model/model.pt"</span>
|
|
<span class="lineno">81</span><span class="n">checkpoint</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">PATH</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>load the saved model</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">84</span><span class="n">model_loaded</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">'state_dict'</span><span class="p">])</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-16'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-16'>#</a>
|
|
</div>
|
|
<p>intialization for hooks and storing activation of ReLU layers</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">87</span><span class="n">activation</span> <span class="o">=</span> <span class="p">{}</span>
|
|
<span class="lineno">88</span><span class="n">hooks</span> <span class="o">=</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>Hook function saves activation of a particular layer</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">91</span><span class="k">def</span> <span class="nf">hook_fn</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span>
|
|
<span class="lineno">92</span> <span class="n">activation</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</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>Registering hooks</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">95</span><span class="n">count</span> <span class="o">=</span><span class="mi">0</span>
|
|
<span class="lineno">96</span><span class="n">conv_count</span> <span class="o">=</span> <span class="mi">0</span>
|
|
<span class="lineno">97</span><span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="n">model_loaded</span><span class="o">.</span><span class="n">named_modules</span><span class="p">():</span>
|
|
<span class="lineno">98</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">):</span>
|
|
<span class="lineno">99</span> <span class="n">count</span> <span class="o">+=</span><span class="mi">1</span>
|
|
<span class="lineno">100</span> <span class="n">hook</span> <span class="o">=</span> <span class="n">layer</span><span class="o">.</span><span class="n">register_forward_hook</span><span class="p">(</span><span class="n">partial</span><span class="p">(</span><span class="n">hook_fn</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">layer</span><span class="o">.</span><span class="n">_get_name</span><span class="p">()</span><span class="si">}</span><span class="s2">-</span><span class="si">{</span><span class="n">count</span><span class="si">}</span><span class="s2">"</span><span class="p">))</span> <span class="c1">#f"{type(layer).__name__}-{name}"</span>
|
|
<span class="lineno">101</span> <span class="n">hooks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">hook</span><span class="p">)</span>
|
|
<span class="lineno">102</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">):</span>
|
|
<span class="lineno">103</span> <span class="n">conv_count</span> <span class="o">+=</span> <span class="mi">1</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>Displaying image used for inference</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">106</span><span class="n">data</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">trainset</span><span class="p">[</span><span class="mi">15</span><span class="p">]</span>
|
|
<span class="lineno">107</span><span class="n">imshow</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-20'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-20'>#</a>
|
|
</div>
|
|
<p>Infering model to save activation of ReLU layers</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">110</span><span class="n">output</span> <span class="o">=</span> <span class="n">model_loaded</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="kc">None</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-21'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-21'>#</a>
|
|
</div>
|
|
<p>Removing hooks</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">113</span><span class="k">for</span> <span class="n">hook</span> <span class="ow">in</span> <span class="n">hooks</span><span class="p">:</span>
|
|
<span class="lineno">114</span> <span class="n">hook</span><span class="o">.</span><span class="n">remove</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-22'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-22'>#</a>
|
|
</div>
|
|
<p>Function to display output of a particular ReLU layer</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">117</span><span class="k">def</span> <span class="nf">output_one_layer</span><span class="p">(</span><span class="n">layer_num</span><span class="p">):</span>
|
|
<span class="lineno">118</span> <span class="k">assert</span> <span class="mi">1</span> <span class="o"><=</span> <span class="n">layer_num</span> <span class="o"><=</span> <span class="nb">len</span><span class="p">(</span><span class="n">activation</span><span class="p">),</span> <span class="s2">"Wrong layer number"</span>
|
|
<span class="lineno">119</span>
|
|
<span class="lineno">120</span> <span class="n">layer_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"ReLu-</span><span class="si">{</span><span class="n">layer_num</span><span class="si">}</span><span class="s2">"</span>
|
|
<span class="lineno">121</span> <span class="n">act</span> <span class="o">=</span> <span class="n">activation</span><span class="p">[</span><span class="sa">f</span><span class="s2">"ReLU-</span><span class="si">{</span><span class="n">layer_num</span><span class="si">}</span><span class="s2">"</span><span class="p">]</span>
|
|
<span class="lineno">122</span> <span class="k">if</span> <span class="n">act</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">==</span><span class="mi">32</span><span class="p">:</span>
|
|
<span class="lineno">123</span> <span class="n">rows</span> <span class="o">=</span> <span class="mi">4</span>
|
|
<span class="lineno">124</span> <span class="n">columns</span> <span class="o">=</span> <span class="mi">8</span>
|
|
<span class="lineno">125</span> <span class="k">elif</span> <span class="n">act</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">==</span><span class="mi">64</span><span class="p">:</span>
|
|
<span class="lineno">126</span> <span class="n">rows</span> <span class="o">=</span> <span class="mi">8</span>
|
|
<span class="lineno">127</span> <span class="n">columns</span> <span class="o">=</span> <span class="mi">8</span>
|
|
<span class="lineno">128</span>
|
|
<span class="lineno">129</span> <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">columns</span><span class="p">))</span>
|
|
<span class="lineno">130</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">columns</span> <span class="o">*</span> <span class="n">rows</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
|
<span class="lineno">131</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">columns</span><span class="p">,</span> <span class="n">idx</span><span class="p">)</span>
|
|
<span class="lineno">132</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">sobel</span><span class="p">(</span><span class="n">act</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="n">idx</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">gray</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-23'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-23'>#</a>
|
|
</div>
|
|
<p>try different filters
|
|
plt.imshow(act[0][idx-1], cmap=’viridis’, vmin=0, vmax=act.max())
|
|
plt.imshow(act[0][idx - 1], cmap=’hot’)
|
|
plt.imshow(roberts(act[0][idx - 1]), cmap=plt.cm.gray)
|
|
plt.imshow(sobel_h(act[0][idx-1]), cmap=plt.cm.gray)</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">140</span> <span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">'off'</span><span class="p">)</span>
|
|
<span class="lineno">141</span>
|
|
<span class="lineno">142</span> <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
|
<span class="lineno">143</span> <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-24'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-24'>#</a>
|
|
</div>
|
|
<p>Function to display output of all ReLU layer after Convulution layers</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">146</span><span class="k">def</span> <span class="nf">output_all_layers</span><span class="p">():</span>
|
|
<span class="lineno">147</span> <span class="k">for</span> <span class="p">[</span><span class="n">name</span><span class="p">,</span> <span class="n">output</span><span class="p">],</span> <span class="n">count</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">activation</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="nb">range</span><span class="p">(</span><span class="n">conv_count</span><span class="p">)):</span>
|
|
<span class="lineno">148</span> <span class="k">if</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">==</span> <span class="mi">32</span><span class="p">:</span>
|
|
<span class="lineno">149</span> <span class="n">_</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
|
|
<span class="lineno">150</span> <span class="k">elif</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">==</span> <span class="mi">64</span><span class="p">:</span>
|
|
<span class="lineno">151</span> <span class="n">_</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">))</span>
|
|
<span class="lineno">152</span>
|
|
<span class="lineno">153</span> <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">out</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">axs</span><span class="p">),</span> <span class="n">output</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
|
|
<span class="lineno">154</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">sobel</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">gray</span><span class="p">)</span>
|
|
<span class="lineno">155</span> <span class="n">ax</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">'off'</span><span class="p">)</span>
|
|
<span class="lineno">156</span>
|
|
<span class="lineno">157</span> <span class="n">plt</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
|
|
<span class="lineno">158</span> <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
|
<span class="lineno">159</span> <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-25'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-25'>#</a>
|
|
</div>
|
|
<p>Choose either one to display</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">162</span><span class="n">output_one_layer</span><span class="p">(</span><span class="n">layer_num</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># choose layer number</span>
|
|
<span class="lineno">163</span><span class="n">output_all_layers</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.4/MathJax.js?config=TeX-AMS_HTML">
|
|
</script>
|
|
<!-- MathJax configuration -->
|
|
<script type="text/x-mathjax-config">
|
|
MathJax.Hub.Config({
|
|
tex2jax: {
|
|
inlineMath: [ ['$','$'] ],
|
|
displayMath: [ ['$$','$$'] ],
|
|
processEscapes: true,
|
|
processEnvironments: true
|
|
},
|
|
// Center justify equations in code and markdown cells. Elsewhere
|
|
// we use CSS to left justify single line equations in code cells.
|
|
displayAlign: 'center',
|
|
"HTML-CSS": { fonts: ["TeX"] }
|
|
});
|
|
</script>
|
|
<script>
|
|
function handleImages() {
|
|
var images = document.querySelectorAll('p>img')
|
|
|
|
console.log(images);
|
|
for (var i = 0; i < images.length; ++i) {
|
|
handleImage(images[i])
|
|
}
|
|
}
|
|
|
|
function handleImage(img) {
|
|
img.parentElement.style.textAlign = 'center'
|
|
|
|
var modal = document.createElement('div')
|
|
modal.id = 'modal'
|
|
|
|
var modalContent = document.createElement('div')
|
|
modal.appendChild(modalContent)
|
|
|
|
var modalImage = document.createElement('img')
|
|
modalContent.appendChild(modalImage)
|
|
|
|
var span = document.createElement('span')
|
|
span.classList.add('close')
|
|
span.textContent = 'x'
|
|
modal.appendChild(span)
|
|
|
|
img.onclick = function () {
|
|
console.log('clicked')
|
|
document.body.appendChild(modal)
|
|
modalImage.src = img.src
|
|
}
|
|
|
|
span.onclick = function () {
|
|
document.body.removeChild(modal)
|
|
}
|
|
}
|
|
|
|
handleImages()
|
|
</script>
|
|
</body>
|
|
</html> |