chore: import upstream snapshot with attribution
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<title>CIFAR 10 මත දුම්රිය කොන්වී මික්සර්</title>
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<h1><a href="index.html">CIFAR 10 මත කොන්වී මික්සර්</a> පුහුණු කරන්න</h1>
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<p>මෙමතිර රචනය CIFAR මත ConvMixer දුම්රිය 10 දත්ත සමුදාය. </p>
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<p>මෙයකඩදාසි ප්රති results ල ප්රතිනිෂ්පාදනය කිරීමේ උත්සාහයක් නොවේ. පුහුණුව සඳහා <a href="https://github.com/rwightman/pytorch-image-models">PyTorch Image Models (timm)</a> හි ඇති රූප වැඩිදියුණු කිරීම් භාවිතා කරයි. සරල බව සඳහා අපි මෙය කර නැත - එමඟින් අපගේ වලංගු කිරීමේ නිරවද්යතාවය පහත වැටීමට හේතු වේ. </p>
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<p><a href="https://app.labml.ai/run/0fc344da2cd011ecb0bc3fdb2e774a3d"><img alt="View Run" src="https://img.shields.io/badge/labml-experiment-brightgreen"></a></p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">20</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">21</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">22</span><span class="kn">from</span> <span class="nn">labml_nn.experiments.cifar10</span> <span class="kn">import</span> <span class="n">CIFAR10Configs</span></pre></div>
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<a href='#section-1'>#</a>
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<h2>වින්යාසකිරීම්</h2>
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<p>සියලුමදත්ත කට්ටල ආශ්රිත වින්යාසයන්, ප්රශස්තකරණය සහ පුහුණු ලූපයක් නිර්වචනය කරන අපි භාවිතා <a href="../experiments/cifar10.html"><code class="highlight"><span></span><span class="n">CIFAR10Configs</span></code>
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</a> කරමු. </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">25</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="p">):</span></pre></div>
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<a href='#section-2'>#</a>
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<p>පැච්එකක ප්රමාණය, <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.19444em;"></span><span class="mord mathnormal">p</span></span></span></span></span> </p>
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<div class="highlight"><pre><span class="lineno">34</span> <span class="n">patch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span></pre></div>
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<p>පැච්කාවැද්දීම් වල නාලිකා ගණන, <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">h</span></span></span></span></span> </p>
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<div class="highlight"><pre><span class="lineno">36</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">256</span></pre></div>
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<a href='#section-4'>#</a>
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<p><a href="#ConvMixerLayer">ConvMixer ස්ථර</a> හෝ ගැඹුර ගණන, <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">d</span></span></span></span></span> </p>
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<div class="highlight"><pre><span class="lineno">38</span> <span class="n">n_layers</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">8</span></pre></div>
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<p>ගැඹුර-නැණවත්සංවහනයේ කර්නල් ප්රමාණය, <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" style="margin-right:0.03148em;">k</span></span></span></span></span> </p>
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<div class="highlight"><pre><span class="lineno">40</span> <span class="n">kernel_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">7</span></pre></div>
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<p>කර්තව්යයේපන්ති ගණන </p>
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<div class="highlight"><pre><span class="lineno">42</span> <span class="n">n_classes</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span></pre></div>
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<h3>ආකෘතියසාදන්න</h3>
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<div class="highlight"><pre><span class="lineno">45</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
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<span class="lineno">46</span><span class="k">def</span> <span class="nf">_conv_mixer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span></pre></div>
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<a href='#section-8'>#</a>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">50</span> <span class="kn">from</span> <span class="nn">labml_nn.conv_mixer</span> <span class="kn">import</span> <span class="n">ConvMixerLayer</span><span class="p">,</span> <span class="n">ConvMixer</span><span class="p">,</span> <span class="n">ClassificationHead</span><span class="p">,</span> <span class="n">PatchEmbeddings</span></pre></div>
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<div class='section' id='section-9'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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<p>ConvMixerනිර්මාණය </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">53</span> <span class="k">return</span> <span class="n">ConvMixer</span><span class="p">(</span><span class="n">ConvMixerLayer</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">kernel_size</span><span class="p">),</span> <span class="n">c</span><span class="o">.</span><span class="n">n_layers</span><span class="p">,</span>
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<span class="lineno">54</span> <span class="n">PatchEmbeddings</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">patch_size</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span>
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<span class="lineno">55</span> <span class="n">ClassificationHead</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">n_classes</span><span class="p">))</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">58</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span></pre></div>
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<p>අත්හදාබැලීම සාදන්න </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">60</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">'ConvMixer'</span><span class="p">,</span> <span class="n">comment</span><span class="o">=</span><span class="s1">'cifar10'</span><span class="p">)</span></pre></div>
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<p>වින්යාසයන්සාදන්න </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">62</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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<p>වින්යාසයන්පූරණය කරන්න </p>
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<div class="highlight"><pre><span class="lineno">64</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="p">{</span></pre></div>
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<p>ප්රශස්තකරණය </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">66</span> <span class="s1">'optimizer.optimizer'</span><span class="p">:</span> <span class="s1">'Adam'</span><span class="p">,</span>
|
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<span class="lineno">67</span> <span class="s1">'optimizer.learning_rate'</span><span class="p">:</span> <span class="mf">2.5e-4</span><span class="p">,</span></pre></div>
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<p>ඊපොච්සහ කණ්ඩායම් ප්රමාණය පුහුණු කිරීම </p>
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<div class="highlight"><pre><span class="lineno">70</span> <span class="s1">'epochs'</span><span class="p">:</span> <span class="mi">150</span><span class="p">,</span>
|
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<span class="lineno">71</span> <span class="s1">'train_batch_size'</span><span class="p">:</span> <span class="mi">64</span><span class="p">,</span></pre></div>
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<div class='section-link'>
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<a href='#section-16'>#</a>
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<p>සරලරූප වැඩි කිරීම </p>
|
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<div class="highlight"><pre><span class="lineno">74</span> <span class="s1">'train_dataset'</span><span class="p">:</span> <span class="s1">'cifar10_train_augmented'</span><span class="p">,</span></pre></div>
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<a href='#section-17'>#</a>
|
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</div>
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<p>වලංගුකිරීම සඳහා රූප වැඩි නොකරන්න </p>
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<div class="highlight"><pre><span class="lineno">76</span> <span class="s1">'valid_dataset'</span><span class="p">:</span> <span class="s1">'cifar10_valid_no_augment'</span><span class="p">,</span>
|
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<span class="lineno">77</span> <span class="p">})</span></pre></div>
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<div class='section-link'>
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<a href='#section-18'>#</a>
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</div>
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<p>ඉතිරිකිරීම/පැටවීම සඳහා ආකෘතිය සකසන්න </p>
|
||||
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||||
<div class="highlight"><pre><span class="lineno">79</span> <span class="n">experiment</span><span class="o">.</span><span class="n">add_pytorch_models</span><span class="p">({</span><span class="s1">'model'</span><span class="p">:</span> <span class="n">conf</span><span class="o">.</span><span class="n">model</span><span class="p">})</span></pre></div>
|
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<div class='section-link'>
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<a href='#section-19'>#</a>
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<p>අත්හදාබැලීම ආරම්භ කර පුහුණු ලූපය ක්රියාත්මක කරන්න </p>
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<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></pre></div>
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<div class="highlight"><pre><span class="lineno">86</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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<h1>පැච්ඔබට අවශ්ය සියලුම ද? (කොන්වී මික්සර්)</h1>
|
||||
<p>මෙය <a href="https://pytorch.org">PyTorch</a> කඩදාසි ක්රියාත්මක කිරීමයි <a href="https://papers.labml.ai/paper/2201.09792">පැච් ඔබට අවශ්යද? </a>. </p>
|
||||
<p><img alt="ConvMixer diagram from the paper" src="conv_mixer.png"></p>
|
||||
<p>ConvMixer <a href="../transformers/mlp_mixer/index.html">MLP-මික්සර්</a>සමාන වේ. එම්එල්පී-මික්සර් අවකාශීය හා නාලිකා මානයන් මිශ්ර කිරීම වෙන් කරයි, අවකාශීය මානය හරහා එම්එල්පී යෙදීමෙන් සහ පසුව නාලිකා මානය හරහා එම්එල්පී යෙදීමෙන් (අවකාශීය එම්එල්පී <a href="../transformers/vit/index.html">වීඅයිටී</a> අවධානය ප්රතිස්ථාපනය කරන අතර නාලිකාව එම්එල්පී යනු <a href="../transformers/feed_forward.html">එෆ්එෆ්එන්</a> වේ vit). </p>
|
||||
<p>ConvMixerනාලිකාව මිශ්ර <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.72777em;vertical-align:-0.08333em;"></span><span class="mord coloredeq eqa" style=""><span class="mord" style="">1</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin" style="">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mord" style="">1</span></span></span></span></span></span> කිරීම සඳහා convvolution සහ අවකාශීය මිශ්ර කිරීම සඳහා ගැඹුර-wise convolution භාවිතා කරයි. එය අවකාශය හරහා සම්පූර්ණ එම්එල්පී වෙනුවට කැටි ගැස්වීමක් බැවින්, එය VIT හෝ MLP-මික්සර් වලට වඩා වෙනස්ව අසල ඇති කාණ්ඩ පමණක් මිශ්ර කරයි. එසේම, MLP-මික්සර් එක් එක් මිශ්රණය සඳහා ස්ථර දෙකක MLPs භාවිතා කරන අතර ConvMixer එක් එක් මිශ්රණය සඳහා තනි ස්ථරයක් භාවිතා කරයි. </p>
|
||||
<p>කඩදාසිනිර්දේශ කරන්නේ නාලිකා මිශ්රණය හරහා ඇති අවශේෂ සම්බන්ධතාවය ඉවත් කිරීම (ලක්ෂ්ය-අනුව කැටි ගැන්විම) සහ අවකාශීය මිශ්රණයට වඩා අවශේෂ සම්බන්ධතාවයක් පමණක් තිබීම (ගැඹුර-wise convolution) ය. <a href="../normalization/layer_norm/index.html">ස්ථර</a> <a href="../normalization/batch_norm/index.html">සාමාන්යකරණය වෙනුවට කණ්ඩායම් සාමාන්යකරණය</a> ද ඔවුන් භාවිතා කරයි. </p>
|
||||
<p><a href="experiment.html">CIFRA-10 හි ConvMixer පුහුණු කරන අත්හදා බැලීමක්</a> මෙන්න. </p>
|
||||
<p><a href="https://app.labml.ai/run/0fc344da2cd011ecb0bc3fdb2e774a3d"><img alt="View Run" src="https://img.shields.io/badge/labml-experiment-brightgreen"></a></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">38</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
|
||||
<span class="lineno">39</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span>
|
||||
<span class="lineno">40</span>
|
||||
<span class="lineno">41</span><span class="kn">from</span> <span class="nn">labml_helpers.module</span> <span class="kn">import</span> <span class="n">Module</span>
|
||||
<span class="lineno">42</span><span class="kn">from</span> <span class="nn">labml_nn.utils</span> <span class="kn">import</span> <span class="n">clone_module_list</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-1'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-1'>#</a>
|
||||
</div>
|
||||
<p> <a id="ConvMixerLayer"></a></p>
|
||||
<h2>කොන්ක්රීට්මික්සර් ස්ථරය</h2>
|
||||
<p>මෙයතනි කොන්වීමික්සර් ස්ථරයකි. ආකෘතියට මේවායින් මාලාවක් ඇත. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">45</span><span class="k">class</span> <span class="nc">ConvMixerLayer</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-2'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-2'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">d_model</span></code>
|
||||
පැච් කාවැද්දීම් වල නාලිකා ගණන, <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 coloredeq eqd" style=""><span class="mord mathnormal" style="">h</span></span></span></span></span></span> </li>
|
||||
<li><code class="highlight"><span></span><span class="n">kernel_size</span></code>
|
||||
අවකාශීය සංවහනයේ කර්නලයේ ප්රමාණය, <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" style="margin-right:0.03148em;">k</span></span></span></span></span></li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">54</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-3'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-3'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">59</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</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>ගැඹුරු-ප්රඥාවන්තසංකෝචනය යනු එක් එක් නාලිකාව සඳහා වෙනම කැටි ගැසුමකි. නාලිකා සංඛ්යාවට සමාන කණ්ඩායම් සංඛ්යාවක් සමඟ සංකෝචනය වන ස්ථරයක් සමඟ අපි මෙය සිදු කරමු. එබැවින් සෑම නාලිකාවක්ම තමන්ගේම කණ්ඩායමක් වේ. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">63</span> <span class="bp">self</span><span class="o">.</span><span class="n">depth_wise_conv</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">d_model</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span>
|
||||
<span class="lineno">64</span> <span class="n">kernel_size</span><span class="o">=</span><span class="n">kernel_size</span><span class="p">,</span>
|
||||
<span class="lineno">65</span> <span class="n">groups</span><span class="o">=</span><span class="n">d_model</span><span class="p">,</span>
|
||||
<span class="lineno">66</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="n">kernel_size</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</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>ගැඹුරු-අනුවකැටි ගැසීමෙන් පසු සක්රිය කිරීම </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">68</span> <span class="bp">self</span><span class="o">.</span><span class="n">act1</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">GELU</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>ගැඹුරු-අනුවකැටි ගැසීමෙන් පසු සාමාන්යකරණය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">70</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm1</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">d_model</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>ලක්ෂ්ය-නැණවත්කැටි <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.72777em;vertical-align:-0.08333em;"></span><span class="mord coloredeq eqa" style=""><span class="mord" style="">1</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin" style="">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mord" style="">1</span></span></span></span></span></span> ගැසීමකි. එනම් පැච් කාවැද්දීම් රේඛීය පරිවර්තනයකි </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">74</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_wise_conv</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">d_model</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">1</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>ලක්ෂ්යයඅනුව කැටි ගැසීමෙන් පසු සක්රිය කිරීම </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">76</span> <span class="bp">self</span><span class="o">.</span><span class="n">act2</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">GELU</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>ලක්ෂ්යයඅනුව කැටි ගැසීමෙන් පසු සාමාන්යකරණය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">78</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm2</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">d_model</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>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">80</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> <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-11'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-11'>#</a>
|
||||
</div>
|
||||
<p>ගැඹුර-නැණවත්කැටි කිරීම වටා ඇති අවශේෂ සම්බන්ධතාවය සඳහා </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">82</span> <span class="n">residual</span> <span class="o">=</span> <span class="n">x</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>ගැඹුරු-නැණවත්කැටි කිරීම, සක්රිය කිරීම සහ සාමාන්යකරණය කිරීම </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">85</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">depth_wise_conv</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="lineno">86</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">act1</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="lineno">87</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm1</span><span class="p">(</span><span class="n">x</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>අවශේෂසම්බන්ධතාවය එක් කරන්න </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">90</span> <span class="n">x</span> <span class="o">+=</span> <span class="n">residual</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>ලක්ෂ්ය-නැණවත්කැටි ගැන්විම, සක්රිය කිරීම සහ සාමාන්යකරණය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">93</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_wise_conv</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="lineno">94</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">act2</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="lineno">95</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm2</span><span class="p">(</span><span class="n">x</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> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">98</span> <span class="k">return</span> <span class="n">x</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-16'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-16'>#</a>
|
||||
</div>
|
||||
<p> <a id="PatchEmbeddings"></a></p>
|
||||
<h2>පැච්කාවැද්දීම් ලබා ගන්න</h2>
|
||||
<p>මෙයරූපය ප්රමාණයෙන් පැච් වලට බෙදෙන <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.7777700000000001em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="">p</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="">p</span></span></span></span></span></span> අතර එක් එක් පැච් සඳහා කාවැද්දීම ලබා දෙයි. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">101</span><span class="k">class</span> <span class="nc">PatchEmbeddings</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-17'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-17'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">d_model</span></code>
|
||||
පැච් කාවැද්දීම් වල නාලිකා ගණන <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 coloredeq eqd" style=""><span class="mord mathnormal" style="">h</span></span></span></span></span></span> </li>
|
||||
<li><code class="highlight"><span></span><span class="n">patch_size</span></code>
|
||||
පැච් වල ප්රමාණය, <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="">p</span></span></span></span></span></span> </li>
|
||||
<li><code class="highlight"><span></span><span class="n">in_channels</span></code>
|
||||
ආදාන රූපයේ නාලිකා ගණන (rgb සඳහා 3)</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">110</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">patch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">in_channels</span><span class="p">:</span> <span class="nb">int</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">116</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</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>අපිකර්නල් ප්රමාණයෙන් හා ලප ප්රමාණය සමාන stride දිග සමග convolution ස්ථරය නිර්මාණය කරන්න. මෙය රූපය පැච් වලට බෙදීමට හා එක් එක් පැච් එකේ රේඛීය පරිවර්තනයක් කිරීමට සමාන වේ. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">121</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="n">patch_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="n">patch_size</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>සක්රියකිරීමේ කාර්යය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">123</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">GELU</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>කණ්ඩායම්සාමාන්යකරණය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">125</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">d_model</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-22'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-22'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">x</span></code>
|
||||
යනු හැඩයේ ආදාන රූපයයි <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">]</span></code>
|
||||
</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">127</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> <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-23'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-23'>#</a>
|
||||
</div>
|
||||
<p>කැටිගැසුණු ස්ථරය යොදන්න </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">132</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv</span><span class="p">(</span><span class="n">x</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>සක්රියකිරීම සහ සාමාන්යකරණය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">134</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="lineno">135</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="n">x</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> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">138</span> <span class="k">return</span> <span class="n">x</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-26'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-26'>#</a>
|
||||
</div>
|
||||
<p> <a id="ClassificationHead"></a></p>
|
||||
<h2>වර්ගීකරණහිස</h2>
|
||||
<p>රූපපංතිවල ලොග්-සම්භාවිතාවන් පුරෝකථනය කිරීම සඳහා ඔවුන් සාමාන්ය තටාක කිරීම (සියලු පැච් කාවැද්දීම් වල මධ්යන්යය ගනිමින්) සහ අවසාන රේඛීය පරිවර්තනයක් සිදු කරයි. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">141</span><span class="k">class</span> <span class="nc">ClassificationHead</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-27'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-27'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">d_model</span></code>
|
||||
පැච් කාවැද්දීම් වල නාලිකා ගණන, <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 coloredeq eqd" style=""><span class="mord mathnormal" style="">h</span></span></span></span></span></span> </li>
|
||||
<li><code class="highlight"><span></span><span class="n">n_classes</span></code>
|
||||
වර්ගීකරණ කාර්යයේ පන්ති ගණන වේ</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">151</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-28'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-28'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">156</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-29'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-29'>#</a>
|
||||
</div>
|
||||
<p>සාමාන්යතටාකය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">158</span> <span class="bp">self</span><span class="o">.</span><span class="n">pool</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">AdaptiveAvgPool2d</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-30'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-30'>#</a>
|
||||
</div>
|
||||
<p>රේඛීයස්ථරය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">160</span> <span class="bp">self</span><span class="o">.</span><span class="n">linear</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_model</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-31'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-31'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">162</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> <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-32'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-32'>#</a>
|
||||
</div>
|
||||
<p>සාමාන්යතටාක </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">164</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pool</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-33'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-33'>#</a>
|
||||
</div>
|
||||
<p>කාවැද්දීමලබා ගන්න, හැඩය <code class="highlight"><span></span><span class="n">x</span></code>
|
||||
ඇත <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
||||
</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">166</span> <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span></pre></div>
|
||||
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|
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|
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<div class='section' id='section-34'>
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||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-34'>#</a>
|
||||
</div>
|
||||
<p>රේඛීයස්ථරය </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">168</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">linear</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
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|
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</div>
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<div class='section' id='section-35'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-35'>#</a>
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|
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<p> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
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<div class="highlight"><pre><span class="lineno">171</span> <span class="k">return</span> <span class="n">x</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-36'>
|
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<div class='docs doc-strings'>
|
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<div class='section-link'>
|
||||
<a href='#section-36'>#</a>
|
||||
</div>
|
||||
<h2>ConvMixer</h2>
|
||||
<p>මෙයපැච් කාවැද්දීම් බ්ලොක්, කොන්වීමික්සර් ස්ථර ගණනාවක් සහ වර්ගීකරණ හිසක් ඒකාබද්ධ කරයි. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">174</span><span class="k">class</span> <span class="nc">ConvMixer</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-37'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-37'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">conv_mixer_layer</span></code>
|
||||
තනි <a href="#ConvMixerLayer">ConvMixer ස්ථරයේ</a>පිටපතක් වේ. ConvMixer සමඟ එය සෑදීමට අපි එහි පිටපත් සාදන්නෙමු <code class="highlight"><span></span><span class="n">n_layers</span></code>
|
||||
. </li>
|
||||
<li><code class="highlight"><span></span><span class="n">n_layers</span></code>
|
||||
ConVMixer ස්ථර (හෝ ගැඹුර) සංඛ්යාව <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">d</span></span></span></span></span>වේ. </li>
|
||||
<li><code class="highlight"><span></span><span class="n">patch_emb</span></code>
|
||||
<a href="#PatchEmbeddings">පැච් කාවැද්දීම් ස්ථරය</a>වේ. </li>
|
||||
<li><code class="highlight"><span></span><span class="n">classification</span></code>
|
||||
<a href="#ClassificationHead">වර්ගීකරණ හිස</a>වේ. </li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">181</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">conv_mixer_layer</span><span class="p">:</span> <span class="n">ConvMixerLayer</span><span class="p">,</span> <span class="n">n_layers</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
||||
<span class="lineno">182</span> <span class="n">patch_emb</span><span class="p">:</span> <span class="n">PatchEmbeddings</span><span class="p">,</span>
|
||||
<span class="lineno">183</span> <span class="n">classification</span><span class="p">:</span> <span class="n">ClassificationHead</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-38'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-38'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">191</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-39'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-39'>#</a>
|
||||
</div>
|
||||
<p>පැච්කාවැද්දීම් </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">193</span> <span class="bp">self</span><span class="o">.</span><span class="n">patch_emb</span> <span class="o">=</span> <span class="n">patch_emb</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-40'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-40'>#</a>
|
||||
</div>
|
||||
<p>වර්ගීකරණහිස </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">195</span> <span class="bp">self</span><span class="o">.</span><span class="n">classification</span> <span class="o">=</span> <span class="n">classification</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-41'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-41'>#</a>
|
||||
</div>
|
||||
<p><a href="#ConvMixerLayer">ConvMixer ස්ථරයේ</a> පිටපත් සාදන්න </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">197</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_mixer_layers</span> <span class="o">=</span> <span class="n">clone_module_list</span><span class="p">(</span><span class="n">conv_mixer_layer</span><span class="p">,</span> <span class="n">n_layers</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-42'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-42'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">x</span></code>
|
||||
යනු හැඩයේ ආදාන රූපයයි <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">]</span></code>
|
||||
</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">199</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> <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-43'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-43'>#</a>
|
||||
</div>
|
||||
<p>පැච්කාවැද්දීම් ලබා ගන්න. මෙය හැඩයේ ආතතිකයක් ලබා දෙයි <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span> <span class="n">height</span> <span class="o">/</span> <span class="n">patch_size</span><span class="p">,</span> <span class="n">width</span> <span class="o">/</span> <span class="n">patch_size</span><span class="p">]</span></code>
|
||||
. </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">204</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">patch_emb</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-44'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-44'>#</a>
|
||||
</div>
|
||||
<p><a href="#ConvMixerLayer">ConvMixer ස්ථර</a> හරහා ගමන් කරන්න </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">207</span> <span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_mixer_layers</span><span class="p">:</span>
|
||||
<span class="lineno">208</span> <span class="n">x</span> <span class="o">=</span> <span class="n">layer</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-45'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-45'>#</a>
|
||||
</div>
|
||||
<p>වර්ගීකරණහිස, පිවිසුම් ලබා ගැනීමට </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">211</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classification</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||||
</div>
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||||
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|
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<div class='docs'>
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||||
<div class='section-link'>
|
||||
<a href='#section-46'>#</a>
|
||||
</div>
|
||||
<p> </p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">214</span> <span class="k">return</span> <span class="n">x</span></pre></div>
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<h1><a href="https://nn.labml.ai/conv_mixer/index.html">පැච් ඔබට අවශ්ය සියලුම ද? </a></h1>
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<p>මෙය <a href="https://pytorch.org">PyTorch</a> කඩදාසි ක්රියාත්මක කිරීමයි <a href="https://papers.labml.ai/paper/2201.09792">පැච් ඔබට අවශ්යද? </a>. </p>
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<p>ConvMixer <a href="https://nn.labml.ai/transformers/mlp_mixer/index.html">MLP-මික්සර්</a>සමාන වේ. එම්එල්පී-මික්සර් අවකාශීය මානය හරහා එම්එල්පී යෙදීමෙන් අවකාශීය හා නාලිකා මානයන් මිශ්ර කිරීම වෙන් කරයි, පසුව නාලිකා මානය හරහා එම්එල්පී යෙදීමෙන් (අවකාශීය එම්එල්පී <a href="https://nn.labml.ai/transformers/vit/index.html">වීඅයිටී</a> අවධානය ප්රතිස්ථාපනය කරන අතර නාලිකාව එම්එල්පී යනු එම්එල්පී ය <a href="https://nn.labml.ai/transformers/feed_forward.html">FFN</a> හෝ VIT). </p>
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<p>ConvMixerනාලිකා මිශ්ර කිරීම සඳහා 1x1 convolution සහ අවකාශීය මිශ්ර කිරීම සඳහා ගැඹුර-wise convolution භාවිතා කරයි. එය අවකාශය හරහා සම්පූර්ණ එම්එල්පී වෙනුවට කැටි ගැස්වීමක් බැවින්, එය VIT හෝ MLP-මික්සර් වලට වඩා වෙනස්ව අසල ඇති කාණ්ඩ පමණක් මිශ්ර කරයි. එසේම, MLP-මික්සර් එක් එක් මිශ්රණය සඳහා ස්ථර දෙකක MLPs භාවිතා කරන අතර ConvMixer එක් එක් මිශ්රණය සඳහා තනි ස්ථරයක් භාවිතා කරයි. </p>
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<p>කඩදාසිනිර්දේශ කරන්නේ නාලිකා මිශ්රණය හරහා ඇති අවශේෂ සම්බන්ධතාවය ඉවත් කිරීම (ලක්ෂ්ය-අනුව කැටි ගැන්විම) සහ අවකාශීය මිශ්රණයට වඩා අවශේෂ සම්බන්ධතාවයක් පමණක් තිබීම (ගැඹුර-wise convolution) ය. <a href="../normalization/layer_norm/index.html">ස්ථර</a> <a href="https://nn.labml.ai/normalization/batch_norm/index.html">සාමාන්යකරණය වෙනුවට කණ්ඩායම් සාමාන්යකරණය</a> ද ඔවුන් භාවිතා කරයි. </p>
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<p><a href="https://nn.labml.ai/conv_mixer/experiment.html">CIFRA-10 හි ConvMixer පුහුණු කරන අත්හදා බැලීමක්</a> මෙන්න. </p>
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<p><a href="https://app.labml.ai/run/0fc344da2cd011ecb0bc3fdb2e774a3d"><img alt="View Run" src="https://img.shields.io/badge/labml-experiment-brightgreen"></a></p>
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