chore: import upstream snapshot with attribution
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wehub-resource-sync
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<a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/diffusion/stable_diffusion/__init__.py" target="_blank">
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View code on Github</a>
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<h1>安定拡散</h1>
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<p><a href="https://github.com/CompVis/stable-diffusion">これは公式の安定版ディフュージョンリポジトリ compVis/安定版 Diffusion に基づいています。</a>オープンソースのウェイトを直接読み込めるように、モデル構造は同じままにしました。この実装にはトレーニングコードは含まれていません。</p>
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<h3><a href="https://promptart.labml.ai">プロンプトアート</a></h3>
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<p><img alt="PromptArt" src="https://labml.ai/images/promptart-feed.webp"></p>
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<p><a href="https://promptart.labml.ai">promptart.labml.aiに安定した拡散ベースの画像生成サービスを展開しました</a></p>
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<h3><a href="latent_diffusion.html">潜在拡散モデル</a></h3>
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<p><a href="latent_diffusion.html">コアは潜在拡散モデルです</a>。以下で構成されています。</p>
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<ul><li><a href="model/autoencoder.html">オートエンコーダ</a></li>
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</ul><li><a href="model/unet.html"><a href="model/unet_attention.html">注意を向けたU-Net</a></a></li>
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<p>また、（オプションで）<a href="https://github.com/HazyResearch/flash-attention"><a href="model/unet_attention.html">フラッシュアテンションをU-Netアテンションに統合しました</a></a>。これにより、RTX A6000 GPUのパフォーマンスを50％近くスピードアップできます。</p>
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<p><a href="model/clip_embedder.html">拡散はCLIP埋め込みに基づいて調整されます</a>。</p>
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<h3><a href="sampler/index.html">サンプリングアルゴリズム</a></h3>
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<p><a href="sampler/index.html">以下のサンプリングアルゴリズムを実装しました</a>。</p>
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<ul><li><a href="sampler/ddpm.html">ノイズ除去拡散確率モデル (DDPM) サンプリング</a></li>
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</ul><li><a href="sampler/ddim.html">ノイズ除去拡散暗黙モデル (DDIM) サンプリシットサンプリシット</a></li>
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<p>画像生成スクリプトは次のとおりです。</p>
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<ul><li><a href="scripts/text_to_image.html">テキストプロンプトから画像を生成</a></li>
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<li><a href="scripts/image_to_image.html">プロンプトに従って、与えられた画像に基づいて画像を生成します</a></li>
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<li><a href="scripts/in_paint.html">テキストプロンプトに基づいて特定の画像の一部を変更する</a></li></ul>
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<h4><a href="util.html">ユーティリティ</a></h4>
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<p><a href="util.html"><code class="highlight"><span></span><span class="n">util</span><span class="o">.</span><span class="n">py</span></code>
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</a>ユーティリティ関数を定義します。</p>
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<a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/diffusion/stable_diffusion/latent_diffusion.py" target="_blank">
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View code on Github</a>
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<h1>潜在拡散モデル</h1>
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<p>潜在拡散モデルでは、オートエンコーダーを使用して画像空間と潜在空間をマッピングします。拡散モデルは潜在空間で機能するため、トレーニングがはるかに簡単になります。これは、<a href="https://papers.labml.ai/paper/2112.10752">潜在拡散モデルを用いた論文の高解像度画像合成に基づいています</a></p>。
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<p>事前にトレーニングされたオートエンコーダーを使用し、事前トレーニング済みのオートエンコーダーの潜在空間で拡散 U-Net をトレーニングします。</p>
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<p><a href="../ddpm/index.html">より単純な拡散実装については、DDPM 実装を参照してください。</a><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqe" style=""><span class="mord" style=""><span class="mord" style=""><span class="mord mathnormal coloredeq eqf" style="margin-right:0.05278em">β</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span>スケジュールなどにも同じ表記を使います</p>。<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.58056em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqd" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.0037em">α</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:-0.0037em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">24</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span>
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<span class="lineno">25</span>
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<span class="lineno">26</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">27</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
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<span class="lineno">28</span>
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<span class="lineno">29</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.autoencoder</span> <span class="kn">import</span> <span class="n">Autoencoder</span>
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<span class="lineno">30</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.clip_embedder</span> <span class="kn">import</span> <span class="n">CLIPTextEmbedder</span>
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<span class="lineno">31</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.unet</span> <span class="kn">import</span> <span class="n">UNetModel</span></pre></div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<p><em>これは <a href="model/unet.html">U-Net</a> 周辺の空のラッパークラスです。チェックポイントの重みを明示的にマッピングする必要がないように、これを <a href="https://github.com/CompVis/stable-diffusion">compVis/Stable-Diffusion</a> と同じモデル構造にしておきます</em></p>。
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">34</span><span class="k">class</span> <span class="nc">DiffusionWrapper</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
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<a href='#section-2'>#</a>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">42</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">diffusion_model</span><span class="p">:</span> <span class="n">UNetModel</span><span class="p">):</span>
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<span class="lineno">43</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
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<span class="lineno">44</span> <span class="bp">self</span><span class="o">.</span><span class="n">diffusion_model</span> <span class="o">=</span> <span class="n">diffusion_model</span></pre></div>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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|
||||
<div class="highlight"><pre><span class="lineno">46</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> <span class="n">time_steps</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">context</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span>
|
||||
<span class="lineno">47</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">diffusion_model</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">time_steps</span><span class="p">,</span> <span class="n">context</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-4'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-4'>#</a>
|
||||
</div>
|
||||
<h2>潜伏拡散モデル</h2>
|
||||
<p>これには以下のコンポーネントが含まれます。</p>
|
||||
<ul><li><a href="model/autoencoder.html">オートエンコーダ</a></li>
|
||||
<li><a href="model/unet.html"><a href="model/unet_attention.html">注意を向けたU-Net</a></a></li>
|
||||
<li><a href="model/clip_embedder.html">CLIP 埋め込みジェネレーター</a></li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">50</span><span class="k">class</span> <span class="nc">LatentDiffusion</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</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>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">60</span> <span class="n">model</span><span class="p">:</span> <span class="n">DiffusionWrapper</span>
|
||||
<span class="lineno">61</span> <span class="n">first_stage_model</span><span class="p">:</span> <span class="n">Autoencoder</span>
|
||||
<span class="lineno">62</span> <span class="n">cond_stage_model</span><span class="p">:</span> <span class="n">CLIPTextEmbedder</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-6'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-6'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">unet_model</span></code>
|
||||
<a href="model/unet.html"><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqb" style=""><span class="mord" style=""><span class="mord mathnormal" style="">ϵ</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord text mtight" style=""><span class="mord mtight" style=""><span class="mord mtight coloredeq eqi" style="">c</span></span><span class="mord mtight" style="">ond</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mopen" style="">(</span><span class="mord" style=""><span class="mord coloredeq eqg" style=""><span class="mord mathnormal" style="">x</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mpunct" style="">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord" style=""><span class="mord mathnormal coloredeq eqi" style="">c</span></span><span class="mclose" style="">)</span></span></span></span></span></span>潜伏空間のノイズを予測するU-Netです</a></li>
|
||||
<li><code class="highlight"><span></span><span class="n">autoencoder</span></code>
|
||||
<a href="model/autoencoder.html">はオートエンコーダです</a></li>
|
||||
<li><code class="highlight"><span></span><span class="n">clip_embedder</span></code>
|
||||
<a href="model/clip_embedder.html">CLIP 埋め込みジェネレータです</a></li>
|
||||
<li><code class="highlight"><span></span><span class="n">latent_scaling_factor</span></code>
|
||||
は潜在空間のスケーリング係数です。オートエンコーダのエンコーディングは、U-Netにフィードする前にこれによってスケーリングされます</li>。
|
||||
<li><code class="highlight"><span></span><span class="n">n_steps</span></code>
|
||||
は拡散ステップの数です。<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord coloredeq eqh" style=""><span class="mord mathnormal" style="margin-right:0.13889em">T</span></span></span></span></span></span></li>
|
||||
<li><code class="highlight"><span></span><span class="n">linear_start</span></code>
|
||||
<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="margin-right:0.05278em">β</span></span></span></span></span></span>スケジュールの始まりです。</li>
|
||||
<li><code class="highlight"><span></span><span class="n">linear_end</span></code>
|
||||
<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="margin-right:0.05278em">β</span></span></span></span></span></span>スケジュールは終了です。</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">64</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="lineno">65</span> <span class="n">unet_model</span><span class="p">:</span> <span class="n">UNetModel</span><span class="p">,</span>
|
||||
<span class="lineno">66</span> <span class="n">autoencoder</span><span class="p">:</span> <span class="n">Autoencoder</span><span class="p">,</span>
|
||||
<span class="lineno">67</span> <span class="n">clip_embedder</span><span class="p">:</span> <span class="n">CLIPTextEmbedder</span><span class="p">,</span>
|
||||
<span class="lineno">68</span> <span class="n">latent_scaling_factor</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
|
||||
<span class="lineno">69</span> <span class="n">n_steps</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
||||
<span class="lineno">70</span> <span class="n">linear_start</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
|
||||
<span class="lineno">71</span> <span class="n">linear_end</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
|
||||
<span class="lineno">72</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>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">84</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-8'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-8'>#</a>
|
||||
</div>
|
||||
<p><a href="https://github.com/CompVis/stable-diffusion">CompVis/Stable-Diffusionと同じモデル構造を保つために</a> <a href="model/unet.html">U-Net</a> をラップしてください。</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">87</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">DiffusionWrapper</span><span class="p">(</span><span class="n">unet_model</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>オートエンコーダとスケーリングファクター</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">89</span> <span class="bp">self</span><span class="o">.</span><span class="n">first_stage_model</span> <span class="o">=</span> <span class="n">autoencoder</span>
|
||||
<span class="lineno">90</span> <span class="bp">self</span><span class="o">.</span><span class="n">latent_scaling_factor</span> <span class="o">=</span> <span class="n">latent_scaling_factor</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><a href="model/clip_embedder.html">CLIP 埋め込みジェネレーター</a></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">92</span> <span class="bp">self</span><span class="o">.</span><span class="n">cond_stage_model</span> <span class="o">=</span> <span class="n">clip_embedder</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>ステップ数 <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord coloredeq eqh" style=""><span class="mord mathnormal" style="margin-right:0.13889em">T</span></span></span></span></span></span></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">95</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_steps</span> <span class="o">=</span> <span class="n">n_steps</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><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqf" style=""><span class="mord mathnormal" style="margin-right:0.05278em">β</span></span></span></span></span></span>スケジュール</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">98</span> <span class="n">beta</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">linear_start</span> <span class="o">**</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">linear_end</span> <span class="o">**</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">n_steps</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
<span class="lineno">99</span> <span class="bp">self</span><span class="o">.</span><span class="n">beta</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="n">beta</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">),</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</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><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.58056em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqd" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.0037em">α</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:-0.0037em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.72777em;vertical-align:-0.08333em;"></span><span class="mord">1</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:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqe" style=""><span class="mord" style=""><span class="mord" style=""><span class="mord mathnormal coloredeq eqf" style="margin-right:0.05278em">β</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">101</span> <span class="n">alpha</span> <span class="o">=</span> <span class="mf">1.</span> <span class="o">-</span> <span class="n">beta</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><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.71778em;vertical-align:-0.15em;"></span><span class="mord accent"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.56778em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord coloredeq eqd" style=""><span class="mord mathnormal" style="margin-right:0.0037em">α</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:-0.0037em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="accent-body" style="left:-0.25em;"><span class="mord">ˉ</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1.233166em;vertical-align:-0.29971000000000003em;"></span><span class="mop"><span class="mop op-symbol small-op" style="position:relative;top:-0.0000050000000000050004em;">∏</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.933456em;"><span style="top:-2.40029em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">s</span><span class="mrel mtight">=</span><span class="mord mtight">1</span></span></span></span><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight coloredeq eqj" style=""><span class="mord mathnormal mtight" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.29971000000000003em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0037em;">α</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.151392em;"><span style="top:-2.5500000000000003em;margin-left:-0.0037em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">s</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">103</span> <span class="n">alpha_bar</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cumprod</span><span class="p">(</span><span class="n">alpha</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="lineno">104</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_bar</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="n">alpha_bar</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">),</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-15'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-15'>#</a>
|
||||
</div>
|
||||
<h3>モデルデバイスを取得</h3>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">106</span> <span class="nd">@property</span>
|
||||
<span class="lineno">107</span> <span class="k">def</span> <span class="nf">device</span><span class="p">(</span><span class="bp">self</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>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">111</span> <span class="k">return</span> <span class="nb">next</span><span class="p">(</span><span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">()))</span><span class="o">.</span><span class="n">device</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>
|
||||
<h3>テキストプロンプトのリストの <a href="model/clip_embedder.html">CLIP 埋め込みを取得する</a></h3>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">113</span> <span class="k">def</span> <span class="nf">get_text_conditioning</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">prompts</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</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">117</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">cond_stage_model</span><span class="p">(</span><span class="n">prompts</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-19'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-19'>#</a>
|
||||
</div>
|
||||
<h3>画像の拡大縮小された潜在空間表現を取得</h3>
|
||||
<p>エンコーダ出力はディストリビューションです。そこからサンプリングし、スケーリング係数を掛けます</p>。
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">119</span> <span class="k">def</span> <span class="nf">autoencoder_encode</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">image</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-20'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-20'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">126</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">latent_scaling_factor</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">first_stage_model</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span><span class="n">image</span><span class="p">)</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-21'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-21'>#</a>
|
||||
</div>
|
||||
<h3>潜在表現から画像を取得</h3>
|
||||
<p>スケーリング係数でスケールダウンしてからデコードします。</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">128</span> <span class="k">def</span> <span class="nf">autoencoder_decode</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z</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-22'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-22'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">134</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">first_stage_model</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="n">z</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">latent_scaling_factor</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-23'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-23'>#</a>
|
||||
</div>
|
||||
<h3>ノイズを予測</h3>
|
||||
<p>潜在表現、タイムステップ<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.58056em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqg" style=""><span class="mord" style=""><span class="mord mathnormal" style="">x</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.61508em;vertical-align:0em;"></span><span class="mord coloredeq eqj" style=""><span class="mord mathnormal" style="">t</span></span></span></span></span></span>、<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord coloredeq eqi" style=""><span class="mord mathnormal" style="">c</span></span></span></span></span></span>条件付けコンテキストを考慮してノイズを予測します。</p>
|
||||
<p><span ><span class="katex-display"><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqb" style=""><span class="mord" style=""><span class="mord mathnormal" style="">ϵ</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord text mtight" style=""><span class="mord mtight" style=""><span class="mord mtight coloredeq eqi" style="">c</span></span><span class="mord mtight" style="">ond</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mopen" style="">(</span><span class="mord" style=""><span class="mord coloredeq eqg" style=""><span class="mord mathnormal" style="">x</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight coloredeq eqj" style="">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mpunct" style="">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord" style=""><span class="mord mathnormal coloredeq eqi" style="">c</span></span><span class="mclose" style="">)</span></span></span></span></span></span></span></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">136</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> <span class="n">t</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">context</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-24'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-24'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">145</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">context</span><span class="p">)</span></pre></div>
|
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<a href="https://papers.labml.ai">Trending Research Papers</a>
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<a href='#section-0'>#</a>
|
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</div>
|
||||
<h1>CLIP テキストエンベダー</h1>
|
||||
<p><a href="../index.html">これを使うと、高速に埋め込むことができ、安定した拡散が得られます。</a>ハギングフェイストランスフォーマーCLIPモデルを使用しています</p>。
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">14</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span>
|
||||
<span class="lineno">15</span>
|
||||
<span class="lineno">16</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span>
|
||||
<span class="lineno">17</span><span class="kn">from</span> <span class="nn">transformers</span> <span class="kn">import</span> <span class="n">CLIPTokenizer</span><span class="p">,</span> <span class="n">CLIPTextModel</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>
|
||||
<h2>CLIP テキストエンベダー</h2>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">20</span><span class="k">class</span> <span class="nc">CLIPTextEmbedder</span><span class="p">(</span><span class="n">nn</span><span class="o">.</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">version</span></code>
|
||||
モデルバージョンです</li>
|
||||
<li><code class="highlight"><span></span><span class="n">device</span></code>
|
||||
デバイスです</li>
|
||||
<li><code class="highlight"><span></span><span class="n">max_length</span></code>
|
||||
トークン化されたプロンプトの最大長です</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">25</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">version</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"openai/clip-vit-large-patch14"</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="s2">"cuda:0"</span><span class="p">,</span> <span class="n">max_length</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">77</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">31</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>トークナイザーをロード</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">33</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span> <span class="o">=</span> <span class="n">CLIPTokenizer</span><span class="o">.</span><span class="n">from_pretrained</span><span class="p">(</span><span class="n">version</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>CLIP トランスをロードします</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">35</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformer</span> <span class="o">=</span> <span class="n">CLIPTextModel</span><span class="o">.</span><span class="n">from_pretrained</span><span class="p">(</span><span class="n">version</span><span class="p">)</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
|
||||
<span class="lineno">36</span>
|
||||
<span class="lineno">37</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">device</span>
|
||||
<span class="lineno">38</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_length</span> <span class="o">=</span> <span class="n">max_length</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-6'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-6'>#</a>
|
||||
</div>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">prompts</span></code>
|
||||
埋め込むプロンプトのリストです</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">40</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">prompts</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</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>プロンプトをトークン化</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">45</span> <span class="n">batch_encoding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">(</span><span class="n">prompts</span><span class="p">,</span> <span class="n">truncation</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">max_length</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">max_length</span><span class="p">,</span> <span class="n">return_length</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
|
||||
<span class="lineno">46</span> <span class="n">return_overflowing_tokens</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="s2">"max_length"</span><span class="p">,</span> <span class="n">return_tensors</span><span class="o">=</span><span class="s2">"pt"</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>トークン ID を取得</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">48</span> <span class="n">tokens</span> <span class="o">=</span> <span class="n">batch_encoding</span><span class="p">[</span><span class="s2">"input_ids"</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-9'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-9'>#</a>
|
||||
</div>
|
||||
<p>CLIP 埋め込みを取得</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">50</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformer</span><span class="p">(</span><span class="n">input_ids</span><span class="o">=</span><span class="n">tokens</span><span class="p">)</span><span class="o">.</span><span class="n">last_hidden_state</span></pre></div>
|
||||
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|
||||
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|
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|
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<h1><a href="index.html">安定した拡散のためのユーティリティ関数</a></h1>
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</div>
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">11</span><span></span><span class="kn">import</span> <span class="nn">os</span>
|
||||
<span class="lineno">12</span><span class="kn">import</span> <span class="nn">random</span>
|
||||
<span class="lineno">13</span><span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
|
||||
<span class="lineno">14</span>
|
||||
<span class="lineno">15</span><span class="kn">import</span> <span class="nn">PIL</span>
|
||||
<span class="lineno">16</span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="lineno">17</span><span class="kn">import</span> <span class="nn">torch</span>
|
||||
<span class="lineno">18</span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
|
||||
<span class="lineno">19</span>
|
||||
<span class="lineno">20</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">monit</span>
|
||||
<span class="lineno">21</span><span class="kn">from</span> <span class="nn">labml.logger</span> <span class="kn">import</span> <span class="n">inspect</span>
|
||||
<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.latent_diffusion</span> <span class="kn">import</span> <span class="n">LatentDiffusion</span>
|
||||
<span class="lineno">23</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.autoencoder</span> <span class="kn">import</span> <span class="n">Encoder</span><span class="p">,</span> <span class="n">Decoder</span><span class="p">,</span> <span class="n">Autoencoder</span>
|
||||
<span class="lineno">24</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.clip_embedder</span> <span class="kn">import</span> <span class="n">CLIPTextEmbedder</span>
|
||||
<span class="lineno">25</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.unet</span> <span class="kn">import</span> <span class="n">UNetModel</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>
|
||||
<h3>ランダムシードを設定</h3>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">28</span><span class="k">def</span> <span class="nf">set_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">:</span> <span class="nb">int</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>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">32</span> <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||||
<span class="lineno">33</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||||
<span class="lineno">34</span> <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||||
<span class="lineno">35</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-3'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-3'>#</a>
|
||||
</div>
|
||||
<h3><a href="latent_diffusion.html"><code class="highlight"><span></span><span class="n">LatentDiffusion</span></code>
|
||||
モデルを読み込む</a></h3>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">38</span><span class="k">def</span> <span class="nf">load_model</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">Path</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="n">LatentDiffusion</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>オートエンコーダを初期化</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">44</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize autoencoder'</span><span class="p">):</span>
|
||||
<span class="lineno">45</span> <span class="n">encoder</span> <span class="o">=</span> <span class="n">Encoder</span><span class="p">(</span><span class="n">z_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
|
||||
<span class="lineno">46</span> <span class="n">in_channels</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
|
||||
<span class="lineno">47</span> <span class="n">channels</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
|
||||
<span class="lineno">48</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
|
||||
<span class="lineno">49</span> <span class="n">n_resnet_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="lineno">50</span>
|
||||
<span class="lineno">51</span> <span class="n">decoder</span> <span class="o">=</span> <span class="n">Decoder</span><span class="p">(</span><span class="n">out_channels</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
|
||||
<span class="lineno">52</span> <span class="n">z_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
|
||||
<span class="lineno">53</span> <span class="n">channels</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
|
||||
<span class="lineno">54</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
|
||||
<span class="lineno">55</span> <span class="n">n_resnet_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="lineno">56</span>
|
||||
<span class="lineno">57</span> <span class="n">autoencoder</span> <span class="o">=</span> <span class="n">Autoencoder</span><span class="p">(</span><span class="n">emb_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
|
||||
<span class="lineno">58</span> <span class="n">encoder</span><span class="o">=</span><span class="n">encoder</span><span class="p">,</span>
|
||||
<span class="lineno">59</span> <span class="n">decoder</span><span class="o">=</span><span class="n">decoder</span><span class="p">,</span>
|
||||
<span class="lineno">60</span> <span class="n">z_channels</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>CLIP テキストエンベダーを初期化</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">63</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize CLIP Embedder'</span><span class="p">):</span>
|
||||
<span class="lineno">64</span> <span class="n">clip_text_embedder</span> <span class="o">=</span> <span class="n">CLIPTextEmbedder</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>U-Net を初期化します</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">67</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize U-Net'</span><span class="p">):</span>
|
||||
<span class="lineno">68</span> <span class="n">unet_model</span> <span class="o">=</span> <span class="n">UNetModel</span><span class="p">(</span><span class="n">in_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
|
||||
<span class="lineno">69</span> <span class="n">out_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
|
||||
<span class="lineno">70</span> <span class="n">channels</span><span class="o">=</span><span class="mi">320</span><span class="p">,</span>
|
||||
<span class="lineno">71</span> <span class="n">attention_levels</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span>
|
||||
<span class="lineno">72</span> <span class="n">n_res_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
|
||||
<span class="lineno">73</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
|
||||
<span class="lineno">74</span> <span class="n">n_heads</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span>
|
||||
<span class="lineno">75</span> <span class="n">tf_layers</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
|
||||
<span class="lineno">76</span> <span class="n">d_cond</span><span class="o">=</span><span class="mi">768</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>潜在拡散モデルを初期化</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">79</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize Latent Diffusion model'</span><span class="p">):</span>
|
||||
<span class="lineno">80</span> <span class="n">model</span> <span class="o">=</span> <span class="n">LatentDiffusion</span><span class="p">(</span><span class="n">linear_start</span><span class="o">=</span><span class="mf">0.00085</span><span class="p">,</span>
|
||||
<span class="lineno">81</span> <span class="n">linear_end</span><span class="o">=</span><span class="mf">0.0120</span><span class="p">,</span>
|
||||
<span class="lineno">82</span> <span class="n">n_steps</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span>
|
||||
<span class="lineno">83</span> <span class="n">latent_scaling_factor</span><span class="o">=</span><span class="mf">0.18215</span><span class="p">,</span>
|
||||
<span class="lineno">84</span>
|
||||
<span class="lineno">85</span> <span class="n">autoencoder</span><span class="o">=</span><span class="n">autoencoder</span><span class="p">,</span>
|
||||
<span class="lineno">86</span> <span class="n">clip_embedder</span><span class="o">=</span><span class="n">clip_text_embedder</span><span class="p">,</span>
|
||||
<span class="lineno">87</span> <span class="n">unet_model</span><span class="o">=</span><span class="n">unet_model</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>チェックポイントをロード</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">90</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loading model from </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s2">"</span><span class="p">):</span>
|
||||
<span class="lineno">91</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> <span class="n">map_location</span><span class="o">=</span><span class="s2">"cpu"</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>モデルステートの設定</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">94</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Load state'</span><span class="p">):</span>
|
||||
<span class="lineno">95</span> <span class="n">missing_keys</span><span class="p">,</span> <span class="n">extra_keys</span> <span class="o">=</span> <span class="n">model</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="s2">"state_dict"</span><span class="p">],</span> <span class="n">strict</span><span class="o">=</span><span class="kc">False</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>デバッグ出力</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">98</span> <span class="n">inspect</span><span class="p">(</span><span class="n">global_step</span><span class="o">=</span><span class="n">checkpoint</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'global_step'</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">missing_keys</span><span class="o">=</span><span class="n">missing_keys</span><span class="p">,</span> <span class="n">extra_keys</span><span class="o">=</span><span class="n">extra_keys</span><span class="p">,</span>
|
||||
<span class="lineno">99</span> <span class="n">_expand</span><span class="o">=</span><span class="kc">True</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></p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">102</span> <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
|
||||
<span class="lineno">103</span> <span class="k">return</span> <span class="n">model</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-12'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-12'>#</a>
|
||||
</div>
|
||||
<h3>画像を読み込む</h3>
|
||||
<p>これはファイルから画像をロードし、PyTorch テンソルを返します。</p>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">path</span></code>
|
||||
画像のパスです</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">106</span><span class="k">def</span> <span class="nf">load_img</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</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>[イメージを開く]</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">115</span> <span class="n">image</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">path</span><span class="p">)</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">"RGB"</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>画像サイズを取得</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">117</span> <span class="n">w</span><span class="p">,</span> <span class="n">h</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">size</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>32 の倍数にリサイズ</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">119</span> <span class="n">w</span> <span class="o">=</span> <span class="n">w</span> <span class="o">-</span> <span class="n">w</span> <span class="o">%</span> <span class="mi">32</span>
|
||||
<span class="lineno">120</span> <span class="n">h</span> <span class="o">=</span> <span class="n">h</span> <span class="o">-</span> <span class="n">h</span> <span class="o">%</span> <span class="mi">32</span>
|
||||
<span class="lineno">121</span> <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="n">w</span><span class="p">,</span> <span class="n">h</span><span class="p">),</span> <span class="n">resample</span><span class="o">=</span><span class="n">PIL</span><span class="o">.</span><span class="n">Image</span><span class="o">.</span><span class="n">LANCZOS</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>numpy に変換して for にマップする <code class="highlight"><span></span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
||||
<code class="highlight"><span></span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">]</span></code>
|
||||
</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">123</span> <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">image</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="mf">2.</span> <span class="o">/</span> <span class="mf">255.0</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</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>シェイプに転置 <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>
|
||||
</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">125</span> <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="p">[</span><span class="kc">None</span><span class="p">]</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</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>トーチに変換</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">127</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">image</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-19'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-19'>#</a>
|
||||
</div>
|
||||
<h3>画像を保存する</h3>
|
||||
<ul><li><code class="highlight"><span></span><span class="n">images</span></code>
|
||||
形状の画像を含むテンソルです <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>
|
||||
<li><code class="highlight"><span></span><span class="n">dest_path</span></code>
|
||||
画像を保存するフォルダーです</li>
|
||||
<li><code class="highlight"><span></span><span class="n">prefix</span></code>
|
||||
ファイル名に追加するプレフィックスです</li>
|
||||
<li><code class="highlight"><span></span><span class="n">img_format</span></code>
|
||||
は画像形式です</li></ul>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">130</span><span class="k">def</span> <span class="nf">save_images</span><span class="p">(</span><span class="n">images</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">dest_path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">prefix</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">''</span><span class="p">,</span> <span class="n">img_format</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">'jpeg'</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>保存先フォルダーの作成</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">141</span> <span class="n">os</span><span class="o">.</span><span class="n">makedirs</span><span class="p">(</span><span class="n">dest_path</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</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><code class="highlight"><span></span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
||||
画像をスペースにマップしてクリップする</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">144</span> <span class="n">images</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">clamp</span><span class="p">((</span><span class="n">images</span> <span class="o">+</span> <span class="mf">1.0</span><span class="p">)</span> <span class="o">/</span> <span class="mf">2.0</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mf">1.0</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><code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">channels</span><span class="p">]</span></code>
|
||||
numpyへの転置とnumpyへの変換</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">146</span> <span class="n">images</span> <span class="o">=</span> <span class="n">images</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">permute</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</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-23'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-23'>#</a>
|
||||
</div>
|
||||
<p>画像を保存</p>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">149</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">images</span><span class="p">):</span>
|
||||
<span class="lineno">150</span> <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">((</span><span class="mf">255.</span> <span class="o">*</span> <span class="n">img</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">))</span>
|
||||
<span class="lineno">151</span> <span class="n">img</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">dest_path</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">prefix</span><span class="si">}{</span><span class="n">i</span><span class="si">:</span><span class="s2">05</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">img_format</span><span class="si">}</span><span class="s2">"</span><span class="p">),</span> <span class="nb">format</span><span class="o">=</span><span class="n">img_format</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='footer'>
|
||||
<a href="https://papers.labml.ai">Trending Research Papers</a>
|
||||
<a href="https://labml.ai">labml.ai</a>
|
||||
</div>
|
||||
</div>
|
||||
<script src=../../interactive.js?v=1"></script>
|
||||
<script>
|
||||
function handleImages() {
|
||||
var images = document.querySelectorAll('p>img')
|
||||
|
||||
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>
|
||||
Reference in New Issue
Block a user