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</span>
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<code class="doc-symbol doc-symbol-toc doc-symbol-class"></code>&nbsp;DINOv2_small
</span>
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<h1><code class="doc-symbol doc-symbol-nav doc-symbol-module"></code> DINOv2</h1>
<div class="doc doc-object doc-module">
<div class="doc doc-contents first">
<div class="doc doc-children">
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_base" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_base</span>
<a href="#refiners.foundationals.dinov2.DINOv2_base" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_base</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 base model.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>768</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-76">76</a></span>
<span class="normal"><a href="#__codelineno-0-77">77</a></span>
<span class="normal"><a href="#__codelineno-0-78">78</a></span>
<span class="normal"><a href="#__codelineno-0-79">79</a></span>
<span class="normal"><a href="#__codelineno-0-80">80</a></span>
<span class="normal"><a href="#__codelineno-0-81">81</a></span>
<span class="normal"><a href="#__codelineno-0-82">82</a></span>
<span class="normal"><a href="#__codelineno-0-83">83</a></span>
<span class="normal"><a href="#__codelineno-0-84">84</a></span>
<span class="normal"><a href="#__codelineno-0-85">85</a></span>
<span class="normal"><a href="#__codelineno-0-86">86</a></span>
<span class="normal"><a href="#__codelineno-0-87">87</a></span>
<span class="normal"><a href="#__codelineno-0-88">88</a></span>
<span class="normal"><a href="#__codelineno-0-89">89</a></span>
<span class="normal"><a href="#__codelineno-0-90">90</a></span>
<span class="normal"><a href="#__codelineno-0-91">91</a></span>
<span class="normal"><a href="#__codelineno-0-92">92</a></span>
<span class="normal"><a href="#__codelineno-0-93">93</a></span>
<span class="normal"><a href="#__codelineno-0-94">94</a></span>
<span class="normal"><a href="#__codelineno-0-95">95</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-76"><a id="__codelineno-0-76" name="__codelineno-0-76"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-77"><a id="__codelineno-0-77" name="__codelineno-0-77"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-78"><a id="__codelineno-0-78" name="__codelineno-0-78"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-79"><a id="__codelineno-0-79" name="__codelineno-0-79"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-80"><a id="__codelineno-0-80" name="__codelineno-0-80"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-81"><a id="__codelineno-0-81" name="__codelineno-0-81"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 base model.</span>
</span><span id="__span-0-82"><a id="__codelineno-0-82" name="__codelineno-0-82"></a>
</span><span id="__span-0-83"><a id="__codelineno-0-83" name="__codelineno-0-83"></a><span class="sd"> Args:</span>
</span><span id="__span-0-84"><a id="__codelineno-0-84" name="__codelineno-0-84"></a><span class="sd"> device: The PyTorch device to use.</span>
</span><span id="__span-0-85"><a id="__codelineno-0-85" name="__codelineno-0-85"></a><span class="sd"> dtype: The PyTorch data type to use.</span>
</span><span id="__span-0-86"><a id="__codelineno-0-86" name="__codelineno-0-86"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-87"><a id="__codelineno-0-87" name="__codelineno-0-87"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-88"><a id="__codelineno-0-88" name="__codelineno-0-88"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">768</span><span class="p">,</span>
</span><span id="__span-0-89"><a id="__codelineno-0-89" name="__codelineno-0-89"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-90"><a id="__codelineno-0-90" name="__codelineno-0-90"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-91"><a id="__codelineno-0-91" name="__codelineno-0-91"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-92"><a id="__codelineno-0-92" name="__codelineno-0-92"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-93"><a id="__codelineno-0-93" name="__codelineno-0-93"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-94"><a id="__codelineno-0-94" name="__codelineno-0-94"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-95"><a id="__codelineno-0-95" name="__codelineno-0-95"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_base_reg" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_base_reg</span>
<a href="#refiners.foundationals.dinov2.DINOv2_base_reg" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_base_reg</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 base model with register.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
and <a href="https://arxiv.org/abs/2309.16588">[arXiv:2309.16588] Vision Transformers Need Registers</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>768</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.num_registers">num_registers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_base_reg.interpolate_antialias">interpolate_antialias</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></code>
</td>
<td>
<div class="doc-md-description">
<p>True</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-231">231</a></span>
<span class="normal"><a href="#__codelineno-0-232">232</a></span>
<span class="normal"><a href="#__codelineno-0-233">233</a></span>
<span class="normal"><a href="#__codelineno-0-234">234</a></span>
<span class="normal"><a href="#__codelineno-0-235">235</a></span>
<span class="normal"><a href="#__codelineno-0-236">236</a></span>
<span class="normal"><a href="#__codelineno-0-237">237</a></span>
<span class="normal"><a href="#__codelineno-0-238">238</a></span>
<span class="normal"><a href="#__codelineno-0-239">239</a></span>
<span class="normal"><a href="#__codelineno-0-240">240</a></span>
<span class="normal"><a href="#__codelineno-0-241">241</a></span>
<span class="normal"><a href="#__codelineno-0-242">242</a></span>
<span class="normal"><a href="#__codelineno-0-243">243</a></span>
<span class="normal"><a href="#__codelineno-0-244">244</a></span>
<span class="normal"><a href="#__codelineno-0-245">245</a></span>
<span class="normal"><a href="#__codelineno-0-246">246</a></span>
<span class="normal"><a href="#__codelineno-0-247">247</a></span>
<span class="normal"><a href="#__codelineno-0-248">248</a></span>
<span class="normal"><a href="#__codelineno-0-249">249</a></span>
<span class="normal"><a href="#__codelineno-0-250">250</a></span>
<span class="normal"><a href="#__codelineno-0-251">251</a></span>
<span class="normal"><a href="#__codelineno-0-252">252</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-231"><a id="__codelineno-0-231" name="__codelineno-0-231"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-232"><a id="__codelineno-0-232" name="__codelineno-0-232"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-233"><a id="__codelineno-0-233" name="__codelineno-0-233"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-234"><a id="__codelineno-0-234" name="__codelineno-0-234"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-235"><a id="__codelineno-0-235" name="__codelineno-0-235"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-236"><a id="__codelineno-0-236" name="__codelineno-0-236"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 base model with register.</span>
</span><span id="__span-0-237"><a id="__codelineno-0-237" name="__codelineno-0-237"></a>
</span><span id="__span-0-238"><a id="__codelineno-0-238" name="__codelineno-0-238"></a><span class="sd"> Args:</span>
</span><span id="__span-0-239"><a id="__codelineno-0-239" name="__codelineno-0-239"></a><span class="sd"> device (torch.device | str | None): The PyTorch device to use.</span>
</span><span id="__span-0-240"><a id="__codelineno-0-240" name="__codelineno-0-240"></a><span class="sd"> dtype (torch.dtype | None): The PyTorch data type to use.</span>
</span><span id="__span-0-241"><a id="__codelineno-0-241" name="__codelineno-0-241"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-242"><a id="__codelineno-0-242" name="__codelineno-0-242"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-243"><a id="__codelineno-0-243" name="__codelineno-0-243"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">768</span><span class="p">,</span>
</span><span id="__span-0-244"><a id="__codelineno-0-244" name="__codelineno-0-244"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-245"><a id="__codelineno-0-245" name="__codelineno-0-245"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-246"><a id="__codelineno-0-246" name="__codelineno-0-246"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-247"><a id="__codelineno-0-247" name="__codelineno-0-247"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-248"><a id="__codelineno-0-248" name="__codelineno-0-248"></a> <span class="n">num_registers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-249"><a id="__codelineno-0-249" name="__codelineno-0-249"></a> <span class="n">interpolate_antialias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
</span><span id="__span-0-250"><a id="__codelineno-0-250" name="__codelineno-0-250"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-251"><a id="__codelineno-0-251" name="__codelineno-0-251"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-252"><a id="__codelineno-0-252" name="__codelineno-0-252"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_giant" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_giant</span>
<a href="#refiners.foundationals.dinov2.DINOv2_giant" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_giant</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 giant model.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>1536</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.feedforward_dim">feedforward_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4096</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>40</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>24</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-149">149</a></span>
<span class="normal"><a href="#__codelineno-0-150">150</a></span>
<span class="normal"><a href="#__codelineno-0-151">151</a></span>
<span class="normal"><a href="#__codelineno-0-152">152</a></span>
<span class="normal"><a href="#__codelineno-0-153">153</a></span>
<span class="normal"><a href="#__codelineno-0-154">154</a></span>
<span class="normal"><a href="#__codelineno-0-155">155</a></span>
<span class="normal"><a href="#__codelineno-0-156">156</a></span>
<span class="normal"><a href="#__codelineno-0-157">157</a></span>
<span class="normal"><a href="#__codelineno-0-158">158</a></span>
<span class="normal"><a href="#__codelineno-0-159">159</a></span>
<span class="normal"><a href="#__codelineno-0-160">160</a></span>
<span class="normal"><a href="#__codelineno-0-161">161</a></span>
<span class="normal"><a href="#__codelineno-0-162">162</a></span>
<span class="normal"><a href="#__codelineno-0-163">163</a></span>
<span class="normal"><a href="#__codelineno-0-164">164</a></span>
<span class="normal"><a href="#__codelineno-0-165">165</a></span>
<span class="normal"><a href="#__codelineno-0-166">166</a></span>
<span class="normal"><a href="#__codelineno-0-167">167</a></span>
<span class="normal"><a href="#__codelineno-0-168">168</a></span>
<span class="normal"><a href="#__codelineno-0-169">169</a></span>
<span class="normal"><a href="#__codelineno-0-170">170</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-149"><a id="__codelineno-0-149" name="__codelineno-0-149"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-150"><a id="__codelineno-0-150" name="__codelineno-0-150"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-151"><a id="__codelineno-0-151" name="__codelineno-0-151"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-152"><a id="__codelineno-0-152" name="__codelineno-0-152"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-153"><a id="__codelineno-0-153" name="__codelineno-0-153"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-154"><a id="__codelineno-0-154" name="__codelineno-0-154"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 giant model.</span>
</span><span id="__span-0-155"><a id="__codelineno-0-155" name="__codelineno-0-155"></a>
</span><span id="__span-0-156"><a id="__codelineno-0-156" name="__codelineno-0-156"></a><span class="sd"> Args:</span>
</span><span id="__span-0-157"><a id="__codelineno-0-157" name="__codelineno-0-157"></a><span class="sd"> device: The PyTorch device to use.</span>
</span><span id="__span-0-158"><a id="__codelineno-0-158" name="__codelineno-0-158"></a><span class="sd"> dtype: The PyTorch data type to use.</span>
</span><span id="__span-0-159"><a id="__codelineno-0-159" name="__codelineno-0-159"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-160"><a id="__codelineno-0-160" name="__codelineno-0-160"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-161"><a id="__codelineno-0-161" name="__codelineno-0-161"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">1536</span><span class="p">,</span>
</span><span id="__span-0-162"><a id="__codelineno-0-162" name="__codelineno-0-162"></a> <span class="n">feedforward_dim</span><span class="o">=</span><span class="mi">4096</span><span class="p">,</span>
</span><span id="__span-0-163"><a id="__codelineno-0-163" name="__codelineno-0-163"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-164"><a id="__codelineno-0-164" name="__codelineno-0-164"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-165"><a id="__codelineno-0-165" name="__codelineno-0-165"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span>
</span><span id="__span-0-166"><a id="__codelineno-0-166" name="__codelineno-0-166"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">24</span><span class="p">,</span>
</span><span id="__span-0-167"><a id="__codelineno-0-167" name="__codelineno-0-167"></a> <span class="n">activation</span><span class="o">=</span><span class="n">GLU</span><span class="p">(</span><span class="n">SiLU</span><span class="p">()),</span>
</span><span id="__span-0-168"><a id="__codelineno-0-168" name="__codelineno-0-168"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-169"><a id="__codelineno-0-169" name="__codelineno-0-169"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-170"><a id="__codelineno-0-170" name="__codelineno-0-170"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_giant_reg" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_giant_reg</span>
<a href="#refiners.foundationals.dinov2.DINOv2_giant_reg" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_giant_reg</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 giant model with register.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
and <a href="https://arxiv.org/abs/2309.16588">[arXiv:2309.16588] Vision Transformers Need Registers</a></p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>1536</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.feedforward_dim">feedforward_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4096</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>40</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>24</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.num_registers">num_registers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_giant_reg.interpolate_antialias">interpolate_antialias</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></code>
</td>
<td>
<div class="doc-md-description">
<p>True</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-313">313</a></span>
<span class="normal"><a href="#__codelineno-0-314">314</a></span>
<span class="normal"><a href="#__codelineno-0-315">315</a></span>
<span class="normal"><a href="#__codelineno-0-316">316</a></span>
<span class="normal"><a href="#__codelineno-0-317">317</a></span>
<span class="normal"><a href="#__codelineno-0-318">318</a></span>
<span class="normal"><a href="#__codelineno-0-319">319</a></span>
<span class="normal"><a href="#__codelineno-0-320">320</a></span>
<span class="normal"><a href="#__codelineno-0-321">321</a></span>
<span class="normal"><a href="#__codelineno-0-322">322</a></span>
<span class="normal"><a href="#__codelineno-0-323">323</a></span>
<span class="normal"><a href="#__codelineno-0-324">324</a></span>
<span class="normal"><a href="#__codelineno-0-325">325</a></span>
<span class="normal"><a href="#__codelineno-0-326">326</a></span>
<span class="normal"><a href="#__codelineno-0-327">327</a></span>
<span class="normal"><a href="#__codelineno-0-328">328</a></span>
<span class="normal"><a href="#__codelineno-0-329">329</a></span>
<span class="normal"><a href="#__codelineno-0-330">330</a></span>
<span class="normal"><a href="#__codelineno-0-331">331</a></span>
<span class="normal"><a href="#__codelineno-0-332">332</a></span>
<span class="normal"><a href="#__codelineno-0-333">333</a></span>
<span class="normal"><a href="#__codelineno-0-334">334</a></span>
<span class="normal"><a href="#__codelineno-0-335">335</a></span>
<span class="normal"><a href="#__codelineno-0-336">336</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-313"><a id="__codelineno-0-313" name="__codelineno-0-313"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-314"><a id="__codelineno-0-314" name="__codelineno-0-314"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-315"><a id="__codelineno-0-315" name="__codelineno-0-315"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-316"><a id="__codelineno-0-316" name="__codelineno-0-316"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-317"><a id="__codelineno-0-317" name="__codelineno-0-317"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-318"><a id="__codelineno-0-318" name="__codelineno-0-318"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 giant model with register.</span>
</span><span id="__span-0-319"><a id="__codelineno-0-319" name="__codelineno-0-319"></a>
</span><span id="__span-0-320"><a id="__codelineno-0-320" name="__codelineno-0-320"></a><span class="sd"> Args:</span>
</span><span id="__span-0-321"><a id="__codelineno-0-321" name="__codelineno-0-321"></a><span class="sd"> device (torch.device | str | None): The PyTorch device to use.</span>
</span><span id="__span-0-322"><a id="__codelineno-0-322" name="__codelineno-0-322"></a><span class="sd"> dtype (torch.dtype | None): The PyTorch data type to use.</span>
</span><span id="__span-0-323"><a id="__codelineno-0-323" name="__codelineno-0-323"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-324"><a id="__codelineno-0-324" name="__codelineno-0-324"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-325"><a id="__codelineno-0-325" name="__codelineno-0-325"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">1536</span><span class="p">,</span>
</span><span id="__span-0-326"><a id="__codelineno-0-326" name="__codelineno-0-326"></a> <span class="n">feedforward_dim</span><span class="o">=</span><span class="mi">4096</span><span class="p">,</span>
</span><span id="__span-0-327"><a id="__codelineno-0-327" name="__codelineno-0-327"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-328"><a id="__codelineno-0-328" name="__codelineno-0-328"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-329"><a id="__codelineno-0-329" name="__codelineno-0-329"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span>
</span><span id="__span-0-330"><a id="__codelineno-0-330" name="__codelineno-0-330"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">24</span><span class="p">,</span>
</span><span id="__span-0-331"><a id="__codelineno-0-331" name="__codelineno-0-331"></a> <span class="n">num_registers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-332"><a id="__codelineno-0-332" name="__codelineno-0-332"></a> <span class="n">interpolate_antialias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
</span><span id="__span-0-333"><a id="__codelineno-0-333" name="__codelineno-0-333"></a> <span class="n">activation</span><span class="o">=</span><span class="n">GLU</span><span class="p">(</span><span class="n">SiLU</span><span class="p">()),</span>
</span><span id="__span-0-334"><a id="__codelineno-0-334" name="__codelineno-0-334"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-335"><a id="__codelineno-0-335" name="__codelineno-0-335"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-336"><a id="__codelineno-0-336" name="__codelineno-0-336"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_large" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_large</span>
<a href="#refiners.foundationals.dinov2.DINOv2_large" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_large</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 large model.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>1024</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>24</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>16</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-112">112</a></span>
<span class="normal"><a href="#__codelineno-0-113">113</a></span>
<span class="normal"><a href="#__codelineno-0-114">114</a></span>
<span class="normal"><a href="#__codelineno-0-115">115</a></span>
<span class="normal"><a href="#__codelineno-0-116">116</a></span>
<span class="normal"><a href="#__codelineno-0-117">117</a></span>
<span class="normal"><a href="#__codelineno-0-118">118</a></span>
<span class="normal"><a href="#__codelineno-0-119">119</a></span>
<span class="normal"><a href="#__codelineno-0-120">120</a></span>
<span class="normal"><a href="#__codelineno-0-121">121</a></span>
<span class="normal"><a href="#__codelineno-0-122">122</a></span>
<span class="normal"><a href="#__codelineno-0-123">123</a></span>
<span class="normal"><a href="#__codelineno-0-124">124</a></span>
<span class="normal"><a href="#__codelineno-0-125">125</a></span>
<span class="normal"><a href="#__codelineno-0-126">126</a></span>
<span class="normal"><a href="#__codelineno-0-127">127</a></span>
<span class="normal"><a href="#__codelineno-0-128">128</a></span>
<span class="normal"><a href="#__codelineno-0-129">129</a></span>
<span class="normal"><a href="#__codelineno-0-130">130</a></span>
<span class="normal"><a href="#__codelineno-0-131">131</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-112"><a id="__codelineno-0-112" name="__codelineno-0-112"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-113"><a id="__codelineno-0-113" name="__codelineno-0-113"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-114"><a id="__codelineno-0-114" name="__codelineno-0-114"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-115"><a id="__codelineno-0-115" name="__codelineno-0-115"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-116"><a id="__codelineno-0-116" name="__codelineno-0-116"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-117"><a id="__codelineno-0-117" name="__codelineno-0-117"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 large model.</span>
</span><span id="__span-0-118"><a id="__codelineno-0-118" name="__codelineno-0-118"></a>
</span><span id="__span-0-119"><a id="__codelineno-0-119" name="__codelineno-0-119"></a><span class="sd"> Args:</span>
</span><span id="__span-0-120"><a id="__codelineno-0-120" name="__codelineno-0-120"></a><span class="sd"> device: The PyTorch device to use.</span>
</span><span id="__span-0-121"><a id="__codelineno-0-121" name="__codelineno-0-121"></a><span class="sd"> dtype: The PyTorch data type to use.</span>
</span><span id="__span-0-122"><a id="__codelineno-0-122" name="__codelineno-0-122"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-123"><a id="__codelineno-0-123" name="__codelineno-0-123"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-124"><a id="__codelineno-0-124" name="__codelineno-0-124"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
</span><span id="__span-0-125"><a id="__codelineno-0-125" name="__codelineno-0-125"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-126"><a id="__codelineno-0-126" name="__codelineno-0-126"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-127"><a id="__codelineno-0-127" name="__codelineno-0-127"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">24</span><span class="p">,</span>
</span><span id="__span-0-128"><a id="__codelineno-0-128" name="__codelineno-0-128"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span>
</span><span id="__span-0-129"><a id="__codelineno-0-129" name="__codelineno-0-129"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-130"><a id="__codelineno-0-130" name="__codelineno-0-130"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-131"><a id="__codelineno-0-131" name="__codelineno-0-131"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_large_reg" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_large_reg</span>
<a href="#refiners.foundationals.dinov2.DINOv2_large_reg" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_large_reg</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 large model with register.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
and <a href="https://arxiv.org/abs/2309.16588">[arXiv:2309.16588] Vision Transformers Need Registers</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>1024</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>24</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>16</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.num_registers">num_registers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_large_reg.interpolate_antialias">interpolate_antialias</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></code>
</td>
<td>
<div class="doc-md-description">
<p>True</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-272">272</a></span>
<span class="normal"><a href="#__codelineno-0-273">273</a></span>
<span class="normal"><a href="#__codelineno-0-274">274</a></span>
<span class="normal"><a href="#__codelineno-0-275">275</a></span>
<span class="normal"><a href="#__codelineno-0-276">276</a></span>
<span class="normal"><a href="#__codelineno-0-277">277</a></span>
<span class="normal"><a href="#__codelineno-0-278">278</a></span>
<span class="normal"><a href="#__codelineno-0-279">279</a></span>
<span class="normal"><a href="#__codelineno-0-280">280</a></span>
<span class="normal"><a href="#__codelineno-0-281">281</a></span>
<span class="normal"><a href="#__codelineno-0-282">282</a></span>
<span class="normal"><a href="#__codelineno-0-283">283</a></span>
<span class="normal"><a href="#__codelineno-0-284">284</a></span>
<span class="normal"><a href="#__codelineno-0-285">285</a></span>
<span class="normal"><a href="#__codelineno-0-286">286</a></span>
<span class="normal"><a href="#__codelineno-0-287">287</a></span>
<span class="normal"><a href="#__codelineno-0-288">288</a></span>
<span class="normal"><a href="#__codelineno-0-289">289</a></span>
<span class="normal"><a href="#__codelineno-0-290">290</a></span>
<span class="normal"><a href="#__codelineno-0-291">291</a></span>
<span class="normal"><a href="#__codelineno-0-292">292</a></span>
<span class="normal"><a href="#__codelineno-0-293">293</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-272"><a id="__codelineno-0-272" name="__codelineno-0-272"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-273"><a id="__codelineno-0-273" name="__codelineno-0-273"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-274"><a id="__codelineno-0-274" name="__codelineno-0-274"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-275"><a id="__codelineno-0-275" name="__codelineno-0-275"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-276"><a id="__codelineno-0-276" name="__codelineno-0-276"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-277"><a id="__codelineno-0-277" name="__codelineno-0-277"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 large model with register.</span>
</span><span id="__span-0-278"><a id="__codelineno-0-278" name="__codelineno-0-278"></a>
</span><span id="__span-0-279"><a id="__codelineno-0-279" name="__codelineno-0-279"></a><span class="sd"> Args:</span>
</span><span id="__span-0-280"><a id="__codelineno-0-280" name="__codelineno-0-280"></a><span class="sd"> device (torch.device | str | None): The PyTorch device to use.</span>
</span><span id="__span-0-281"><a id="__codelineno-0-281" name="__codelineno-0-281"></a><span class="sd"> dtype (torch.dtype | None): The PyTorch data type to use.</span>
</span><span id="__span-0-282"><a id="__codelineno-0-282" name="__codelineno-0-282"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-283"><a id="__codelineno-0-283" name="__codelineno-0-283"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-284"><a id="__codelineno-0-284" name="__codelineno-0-284"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
</span><span id="__span-0-285"><a id="__codelineno-0-285" name="__codelineno-0-285"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-286"><a id="__codelineno-0-286" name="__codelineno-0-286"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-287"><a id="__codelineno-0-287" name="__codelineno-0-287"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">24</span><span class="p">,</span>
</span><span id="__span-0-288"><a id="__codelineno-0-288" name="__codelineno-0-288"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span>
</span><span id="__span-0-289"><a id="__codelineno-0-289" name="__codelineno-0-289"></a> <span class="n">num_registers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-290"><a id="__codelineno-0-290" name="__codelineno-0-290"></a> <span class="n">interpolate_antialias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
</span><span id="__span-0-291"><a id="__codelineno-0-291" name="__codelineno-0-291"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-292"><a id="__codelineno-0-292" name="__codelineno-0-292"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-293"><a id="__codelineno-0-293" name="__codelineno-0-293"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_small" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_small</span>
<a href="#refiners.foundationals.dinov2.DINOv2_small" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_small</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 small model.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>384</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>6</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-40">40</a></span>
<span class="normal"><a href="#__codelineno-0-41">41</a></span>
<span class="normal"><a href="#__codelineno-0-42">42</a></span>
<span class="normal"><a href="#__codelineno-0-43">43</a></span>
<span class="normal"><a href="#__codelineno-0-44">44</a></span>
<span class="normal"><a href="#__codelineno-0-45">45</a></span>
<span class="normal"><a href="#__codelineno-0-46">46</a></span>
<span class="normal"><a href="#__codelineno-0-47">47</a></span>
<span class="normal"><a href="#__codelineno-0-48">48</a></span>
<span class="normal"><a href="#__codelineno-0-49">49</a></span>
<span class="normal"><a href="#__codelineno-0-50">50</a></span>
<span class="normal"><a href="#__codelineno-0-51">51</a></span>
<span class="normal"><a href="#__codelineno-0-52">52</a></span>
<span class="normal"><a href="#__codelineno-0-53">53</a></span>
<span class="normal"><a href="#__codelineno-0-54">54</a></span>
<span class="normal"><a href="#__codelineno-0-55">55</a></span>
<span class="normal"><a href="#__codelineno-0-56">56</a></span>
<span class="normal"><a href="#__codelineno-0-57">57</a></span>
<span class="normal"><a href="#__codelineno-0-58">58</a></span>
<span class="normal"><a href="#__codelineno-0-59">59</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-40"><a id="__codelineno-0-40" name="__codelineno-0-40"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-41"><a id="__codelineno-0-41" name="__codelineno-0-41"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-42"><a id="__codelineno-0-42" name="__codelineno-0-42"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-43"><a id="__codelineno-0-43" name="__codelineno-0-43"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-44"><a id="__codelineno-0-44" name="__codelineno-0-44"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-45"><a id="__codelineno-0-45" name="__codelineno-0-45"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 small model.</span>
</span><span id="__span-0-46"><a id="__codelineno-0-46" name="__codelineno-0-46"></a>
</span><span id="__span-0-47"><a id="__codelineno-0-47" name="__codelineno-0-47"></a><span class="sd"> Args:</span>
</span><span id="__span-0-48"><a id="__codelineno-0-48" name="__codelineno-0-48"></a><span class="sd"> device: The PyTorch device to use.</span>
</span><span id="__span-0-49"><a id="__codelineno-0-49" name="__codelineno-0-49"></a><span class="sd"> dtype: The PyTorch data type to use.</span>
</span><span id="__span-0-50"><a id="__codelineno-0-50" name="__codelineno-0-50"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-51"><a id="__codelineno-0-51" name="__codelineno-0-51"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-52"><a id="__codelineno-0-52" name="__codelineno-0-52"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">384</span><span class="p">,</span>
</span><span id="__span-0-53"><a id="__codelineno-0-53" name="__codelineno-0-53"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-54"><a id="__codelineno-0-54" name="__codelineno-0-54"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-55"><a id="__codelineno-0-55" name="__codelineno-0-55"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-56"><a id="__codelineno-0-56" name="__codelineno-0-56"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span>
</span><span id="__span-0-57"><a id="__codelineno-0-57" name="__codelineno-0-57"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-58"><a id="__codelineno-0-58" name="__codelineno-0-58"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-59"><a id="__codelineno-0-59" name="__codelineno-0-59"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.DINOv2_small_reg" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">DINOv2_small_reg</span>
<a href="#refiners.foundationals.dinov2.DINOv2_small_reg" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">DINOv2_small_reg</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.foundationals.dinov2.vit.ViT" href="#refiners.foundationals.dinov2.ViT">ViT</a></code></p>
<p>DINOv2 small model with register.</p>
<p>See <a href="https://arxiv.org/abs/2304.07193">[arXiv:2304.07193] DINOv2: Learning Robust Visual Features without Supervision</a>
and <a href="https://arxiv.org/abs/2309.16588">[arXiv:2309.16588] Vision Transformers Need Registers</a>
for more details.</p>
<p><span class="doc-section-title">Attributes:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.embedding_dim">embedding_dim</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>384</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.patch_size">patch_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>14</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.image_size">image_size</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>518</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.num_layers">num_layers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>12</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.num_heads">num_heads</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>6</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.num_registers">num_registers</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>4</p>
</div>
</td>
</tr>
<tr class="doc-section-item">
<td><code><span title="refiners.foundationals.dinov2.DINOv2_small_reg.interpolate_antialias">interpolate_antialias</span></code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></code>
</td>
<td>
<div class="doc-md-description">
<p>True</p>
</div>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-190">190</a></span>
<span class="normal"><a href="#__codelineno-0-191">191</a></span>
<span class="normal"><a href="#__codelineno-0-192">192</a></span>
<span class="normal"><a href="#__codelineno-0-193">193</a></span>
<span class="normal"><a href="#__codelineno-0-194">194</a></span>
<span class="normal"><a href="#__codelineno-0-195">195</a></span>
<span class="normal"><a href="#__codelineno-0-196">196</a></span>
<span class="normal"><a href="#__codelineno-0-197">197</a></span>
<span class="normal"><a href="#__codelineno-0-198">198</a></span>
<span class="normal"><a href="#__codelineno-0-199">199</a></span>
<span class="normal"><a href="#__codelineno-0-200">200</a></span>
<span class="normal"><a href="#__codelineno-0-201">201</a></span>
<span class="normal"><a href="#__codelineno-0-202">202</a></span>
<span class="normal"><a href="#__codelineno-0-203">203</a></span>
<span class="normal"><a href="#__codelineno-0-204">204</a></span>
<span class="normal"><a href="#__codelineno-0-205">205</a></span>
<span class="normal"><a href="#__codelineno-0-206">206</a></span>
<span class="normal"><a href="#__codelineno-0-207">207</a></span>
<span class="normal"><a href="#__codelineno-0-208">208</a></span>
<span class="normal"><a href="#__codelineno-0-209">209</a></span>
<span class="normal"><a href="#__codelineno-0-210">210</a></span>
<span class="normal"><a href="#__codelineno-0-211">211</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-190"><a id="__codelineno-0-190" name="__codelineno-0-190"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-191"><a id="__codelineno-0-191" name="__codelineno-0-191"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-192"><a id="__codelineno-0-192" name="__codelineno-0-192"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-193"><a id="__codelineno-0-193" name="__codelineno-0-193"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-194"><a id="__codelineno-0-194" name="__codelineno-0-194"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-195"><a id="__codelineno-0-195" name="__codelineno-0-195"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize DINOv2 small model with register.</span>
</span><span id="__span-0-196"><a id="__codelineno-0-196" name="__codelineno-0-196"></a>
</span><span id="__span-0-197"><a id="__codelineno-0-197" name="__codelineno-0-197"></a><span class="sd"> Args:</span>
</span><span id="__span-0-198"><a id="__codelineno-0-198" name="__codelineno-0-198"></a><span class="sd"> device (torch.device | str | None): The PyTorch device to use.</span>
</span><span id="__span-0-199"><a id="__codelineno-0-199" name="__codelineno-0-199"></a><span class="sd"> dtype (torch.dtype | None): The PyTorch data type to use.</span>
</span><span id="__span-0-200"><a id="__codelineno-0-200" name="__codelineno-0-200"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-201"><a id="__codelineno-0-201" name="__codelineno-0-201"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-202"><a id="__codelineno-0-202" name="__codelineno-0-202"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="mi">384</span><span class="p">,</span>
</span><span id="__span-0-203"><a id="__codelineno-0-203" name="__codelineno-0-203"></a> <span class="n">patch_size</span><span class="o">=</span><span class="mi">14</span><span class="p">,</span>
</span><span id="__span-0-204"><a id="__codelineno-0-204" name="__codelineno-0-204"></a> <span class="n">image_size</span><span class="o">=</span><span class="mi">518</span><span class="p">,</span>
</span><span id="__span-0-205"><a id="__codelineno-0-205" name="__codelineno-0-205"></a> <span class="n">num_layers</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-206"><a id="__codelineno-0-206" name="__codelineno-0-206"></a> <span class="n">num_heads</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span>
</span><span id="__span-0-207"><a id="__codelineno-0-207" name="__codelineno-0-207"></a> <span class="n">num_registers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-208"><a id="__codelineno-0-208" name="__codelineno-0-208"></a> <span class="n">interpolate_antialias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
</span><span id="__span-0-209"><a id="__codelineno-0-209" name="__codelineno-0-209"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-210"><a id="__codelineno-0-210" name="__codelineno-0-210"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-211"><a id="__codelineno-0-211" name="__codelineno-0-211"></a> <span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-class">
<h2 id="refiners.foundationals.dinov2.ViT" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-class"></code> <span class="doc doc-object-name doc-class-name">ViT</span>
<a href="#refiners.foundationals.dinov2.ViT" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">ViT</span><span class="p">(</span>
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">embedding_dim</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">768</span><span class="p">,</span>
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">patch_size</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span>
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a> <span class="n">image_size</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">224</span><span class="p">,</span>
</span><span id="__span-0-5"><a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a> <span class="n">num_layers</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-6"><a id="__codelineno-0-6" name="__codelineno-0-6" href="#__codelineno-0-6"></a> <span class="n">num_heads</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-7"><a id="__codelineno-0-7" name="__codelineno-0-7" href="#__codelineno-0-7"></a> <span class="n">norm_eps</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#float">float</a></span> <span class="o">=</span> <span class="mf">1e-06</span><span class="p">,</span>
</span><span id="__span-0-8"><a id="__codelineno-0-8" name="__codelineno-0-8" href="#__codelineno-0-8"></a> <span class="n">mlp_ratio</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-9"><a id="__codelineno-0-9" name="__codelineno-0-9" href="#__codelineno-0-9"></a> <span class="n">num_registers</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
</span><span id="__span-0-10"><a id="__codelineno-0-10" name="__codelineno-0-10" href="#__codelineno-0-10"></a> <span class="n">activation</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="refiners.fluxion.layers.activations.Activation" href="../../fluxion/layers/#refiners.fluxion.layers.Activation">Activation</a></span> <span class="o">=</span> <span class="n">fl</span><span class="o">.</span><span class="n">GeLU</span><span class="p">(),</span>
</span><span id="__span-0-11"><a id="__codelineno-0-11" name="__codelineno-0-11" href="#__codelineno-0-11"></a> <span class="n">feedforward_dim</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-12"><a id="__codelineno-0-12" name="__codelineno-0-12" href="#__codelineno-0-12"></a> <span class="n">interpolate_antialias</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
</span><span id="__span-0-13"><a id="__codelineno-0-13" name="__codelineno-0-13" href="#__codelineno-0-13"></a> <span class="n">interpolate_mode</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">=</span> <span class="s2">&quot;bicubic&quot;</span><span class="p">,</span>
</span><span id="__span-0-14"><a id="__codelineno-0-14" name="__codelineno-0-14" href="#__codelineno-0-14"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><span title="torch.device">device</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-15"><a id="__codelineno-0-15" name="__codelineno-0-15" href="#__codelineno-0-15"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><span title="torch.dtype">dtype</span></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-16"><a id="__codelineno-0-16" name="__codelineno-0-16" href="#__codelineno-0-16"></a><span class="p">)</span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><a class="autorefs autorefs-internal" title="refiners.fluxion.layers.Chain" href="../../fluxion/layers/#refiners.fluxion.layers.Chain">Chain</a></code></p>
<p>Vision Transformer (ViT) model.</p>
<p>See <a href="https://arxiv.org/abs/2010.11929">[arXiv:2010.11929] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale</a>
for more details.</p>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>embedding_dim</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The dimension of the embedding.</p>
</div>
</td>
<td>
<code>768</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>patch_size</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The size of the patches.</p>
</div>
</td>
<td>
<code>16</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>image_size</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The size of the input image.</p>
</div>
</td>
<td>
<code>224</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>num_layers</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The number of layers.</p>
</div>
</td>
<td>
<code>12</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>num_heads</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The number of heads.</p>
</div>
</td>
<td>
<code>12</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>norm_eps</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#float">float</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The epsilon value for normalization.</p>
</div>
</td>
<td>
<code>1e-06</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>mlp_ratio</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The ratio for the multi-layer perceptron (MLP).</p>
</div>
</td>
<td>
<code>4</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>num_registers</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The number of registers.</p>
</div>
</td>
<td>
<code>0</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>activation</code></td>
<td>
<code><a class="autorefs autorefs-internal" title="refiners.fluxion.layers.activations.Activation" href="../../fluxion/layers/#refiners.fluxion.layers.Activation">Activation</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The activation function.</p>
</div>
</td>
<td>
<code><a class="autorefs autorefs-internal" title="refiners.fluxion.layers.GeLU" href="../../fluxion/layers/#refiners.fluxion.layers.GeLU">GeLU</a>()</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>feedforward_dim</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The dimension of the feedforward layer.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>interpolate_antialias</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#bool">bool</a></code>
</td>
<td>
<div class="doc-md-description">
<p>Whether to use antialiasing for interpolation.</p>
</div>
</td>
<td>
<code>False</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>interpolate_mode</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The interpolation mode.</p>
</div>
</td>
<td>
<code>&#39;bicubic&#39;</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>device</code></td>
<td>
<code><span title="torch.device">device</span> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch device to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dtype</code></td>
<td>
<code><span title="torch.dtype">dtype</span> | None</code>
</td>
<td>
<div class="doc-md-description">
<p>The PyTorch data type to use.</p>
</div>
</td>
<td>
<code>None</code>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/vit.py</code></summary>
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<span class="normal"><a href="#__codelineno-0-372">372</a></span>
<span class="normal"><a href="#__codelineno-0-373">373</a></span>
<span class="normal"><a href="#__codelineno-0-374">374</a></span>
<span class="normal"><a href="#__codelineno-0-375">375</a></span>
<span class="normal"><a href="#__codelineno-0-376">376</a></span>
<span class="normal"><a href="#__codelineno-0-377">377</a></span>
<span class="normal"><a href="#__codelineno-0-378">378</a></span>
<span class="normal"><a href="#__codelineno-0-379">379</a></span>
<span class="normal"><a href="#__codelineno-0-380">380</a></span>
<span class="normal"><a href="#__codelineno-0-381">381</a></span>
<span class="normal"><a href="#__codelineno-0-382">382</a></span>
<span class="normal"><a href="#__codelineno-0-383">383</a></span>
<span class="normal"><a href="#__codelineno-0-384">384</a></span>
<span class="normal"><a href="#__codelineno-0-385">385</a></span>
<span class="normal"><a href="#__codelineno-0-386">386</a></span>
<span class="normal"><a href="#__codelineno-0-387">387</a></span>
<span class="normal"><a href="#__codelineno-0-388">388</a></span>
<span class="normal"><a href="#__codelineno-0-389">389</a></span>
<span class="normal"><a href="#__codelineno-0-390">390</a></span>
<span class="normal"><a href="#__codelineno-0-391">391</a></span>
<span class="normal"><a href="#__codelineno-0-392">392</a></span>
<span class="normal"><a href="#__codelineno-0-393">393</a></span>
<span class="normal"><a href="#__codelineno-0-394">394</a></span>
<span class="normal"><a href="#__codelineno-0-395">395</a></span>
<span class="normal"><a href="#__codelineno-0-396">396</a></span>
<span class="normal"><a href="#__codelineno-0-397">397</a></span>
<span class="normal"><a href="#__codelineno-0-398">398</a></span>
<span class="normal"><a href="#__codelineno-0-399">399</a></span>
<span class="normal"><a href="#__codelineno-0-400">400</a></span>
<span class="normal"><a href="#__codelineno-0-401">401</a></span>
<span class="normal"><a href="#__codelineno-0-402">402</a></span>
<span class="normal"><a href="#__codelineno-0-403">403</a></span>
<span class="normal"><a href="#__codelineno-0-404">404</a></span>
<span class="normal"><a href="#__codelineno-0-405">405</a></span>
<span class="normal"><a href="#__codelineno-0-406">406</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-296"><a id="__codelineno-0-296" name="__codelineno-0-296"></a><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-297"><a id="__codelineno-0-297" name="__codelineno-0-297"></a> <span class="bp">self</span><span class="p">,</span>
</span><span id="__span-0-298"><a id="__codelineno-0-298" name="__codelineno-0-298"></a> <span class="n">embedding_dim</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">768</span><span class="p">,</span>
</span><span id="__span-0-299"><a id="__codelineno-0-299" name="__codelineno-0-299"></a> <span class="n">patch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span>
</span><span id="__span-0-300"><a id="__codelineno-0-300" name="__codelineno-0-300"></a> <span class="n">image_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">224</span><span class="p">,</span>
</span><span id="__span-0-301"><a id="__codelineno-0-301" name="__codelineno-0-301"></a> <span class="n">num_layers</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-302"><a id="__codelineno-0-302" name="__codelineno-0-302"></a> <span class="n">num_heads</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span>
</span><span id="__span-0-303"><a id="__codelineno-0-303" name="__codelineno-0-303"></a> <span class="n">norm_eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-6</span><span class="p">,</span>
</span><span id="__span-0-304"><a id="__codelineno-0-304" name="__codelineno-0-304"></a> <span class="n">mlp_ratio</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span>
</span><span id="__span-0-305"><a id="__codelineno-0-305" name="__codelineno-0-305"></a> <span class="n">num_registers</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
</span><span id="__span-0-306"><a id="__codelineno-0-306" name="__codelineno-0-306"></a> <span class="n">activation</span><span class="p">:</span> <span class="n">Activation</span> <span class="o">=</span> <span class="n">fl</span><span class="o">.</span><span class="n">GeLU</span><span class="p">(),</span>
</span><span id="__span-0-307"><a id="__codelineno-0-307" name="__codelineno-0-307"></a> <span class="n">feedforward_dim</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-308"><a id="__codelineno-0-308" name="__codelineno-0-308"></a> <span class="n">interpolate_antialias</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
</span><span id="__span-0-309"><a id="__codelineno-0-309" name="__codelineno-0-309"></a> <span class="n">interpolate_mode</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;bicubic&quot;</span><span class="p">,</span>
</span><span id="__span-0-310"><a id="__codelineno-0-310" name="__codelineno-0-310"></a> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-311"><a id="__codelineno-0-311" name="__codelineno-0-311"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="__span-0-312"><a id="__codelineno-0-312" name="__codelineno-0-312"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="__span-0-313"><a id="__codelineno-0-313" name="__codelineno-0-313"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;Initialize a Vision Transformer (ViT) model.</span>
</span><span id="__span-0-314"><a id="__codelineno-0-314" name="__codelineno-0-314"></a>
</span><span id="__span-0-315"><a id="__codelineno-0-315" name="__codelineno-0-315"></a><span class="sd"> Args:</span>
</span><span id="__span-0-316"><a id="__codelineno-0-316" name="__codelineno-0-316"></a><span class="sd"> embedding_dim: The dimension of the embedding.</span>
</span><span id="__span-0-317"><a id="__codelineno-0-317" name="__codelineno-0-317"></a><span class="sd"> patch_size: The size of the patches.</span>
</span><span id="__span-0-318"><a id="__codelineno-0-318" name="__codelineno-0-318"></a><span class="sd"> image_size: The size of the input image.</span>
</span><span id="__span-0-319"><a id="__codelineno-0-319" name="__codelineno-0-319"></a><span class="sd"> num_layers: The number of layers.</span>
</span><span id="__span-0-320"><a id="__codelineno-0-320" name="__codelineno-0-320"></a><span class="sd"> num_heads: The number of heads.</span>
</span><span id="__span-0-321"><a id="__codelineno-0-321" name="__codelineno-0-321"></a><span class="sd"> norm_eps: The epsilon value for normalization.</span>
</span><span id="__span-0-322"><a id="__codelineno-0-322" name="__codelineno-0-322"></a><span class="sd"> mlp_ratio: The ratio for the multi-layer perceptron (MLP).</span>
</span><span id="__span-0-323"><a id="__codelineno-0-323" name="__codelineno-0-323"></a><span class="sd"> num_registers: The number of registers.</span>
</span><span id="__span-0-324"><a id="__codelineno-0-324" name="__codelineno-0-324"></a><span class="sd"> activation: The activation function.</span>
</span><span id="__span-0-325"><a id="__codelineno-0-325" name="__codelineno-0-325"></a><span class="sd"> feedforward_dim: The dimension of the feedforward layer.</span>
</span><span id="__span-0-326"><a id="__codelineno-0-326" name="__codelineno-0-326"></a><span class="sd"> interpolate_antialias: Whether to use antialiasing for interpolation.</span>
</span><span id="__span-0-327"><a id="__codelineno-0-327" name="__codelineno-0-327"></a><span class="sd"> interpolate_mode: The interpolation mode.</span>
</span><span id="__span-0-328"><a id="__codelineno-0-328" name="__codelineno-0-328"></a><span class="sd"> device: The PyTorch device to use.</span>
</span><span id="__span-0-329"><a id="__codelineno-0-329" name="__codelineno-0-329"></a><span class="sd"> dtype: The PyTorch data type to use.</span>
</span><span id="__span-0-330"><a id="__codelineno-0-330" name="__codelineno-0-330"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-331"><a id="__codelineno-0-331" name="__codelineno-0-331"></a> <span class="n">num_patches</span> <span class="o">=</span> <span class="n">image_size</span> <span class="o">//</span> <span class="n">patch_size</span>
</span><span id="__span-0-332"><a id="__codelineno-0-332" name="__codelineno-0-332"></a> <span class="bp">self</span><span class="o">.</span><span class="n">embedding_dim</span> <span class="o">=</span> <span class="n">embedding_dim</span>
</span><span id="__span-0-333"><a id="__codelineno-0-333" name="__codelineno-0-333"></a> <span class="bp">self</span><span class="o">.</span><span class="n">patch_size</span> <span class="o">=</span> <span class="n">patch_size</span>
</span><span id="__span-0-334"><a id="__codelineno-0-334" name="__codelineno-0-334"></a> <span class="bp">self</span><span class="o">.</span><span class="n">image_size</span> <span class="o">=</span> <span class="n">image_size</span>
</span><span id="__span-0-335"><a id="__codelineno-0-335" name="__codelineno-0-335"></a> <span class="bp">self</span><span class="o">.</span><span class="n">num_layers</span> <span class="o">=</span> <span class="n">num_layers</span>
</span><span id="__span-0-336"><a id="__codelineno-0-336" name="__codelineno-0-336"></a> <span class="bp">self</span><span class="o">.</span><span class="n">num_heads</span> <span class="o">=</span> <span class="n">num_heads</span>
</span><span id="__span-0-337"><a id="__codelineno-0-337" name="__codelineno-0-337"></a> <span class="bp">self</span><span class="o">.</span><span class="n">norm_eps</span> <span class="o">=</span> <span class="n">norm_eps</span>
</span><span id="__span-0-338"><a id="__codelineno-0-338" name="__codelineno-0-338"></a> <span class="bp">self</span><span class="o">.</span><span class="n">mlp_ratio</span> <span class="o">=</span> <span class="n">mlp_ratio</span>
</span><span id="__span-0-339"><a id="__codelineno-0-339" name="__codelineno-0-339"></a> <span class="bp">self</span><span class="o">.</span><span class="n">num_registers</span> <span class="o">=</span> <span class="n">num_registers</span>
</span><span id="__span-0-340"><a id="__codelineno-0-340" name="__codelineno-0-340"></a> <span class="bp">self</span><span class="o">.</span><span class="n">feedforward_dim</span> <span class="o">=</span> <span class="n">feedforward_dim</span>
</span><span id="__span-0-341"><a id="__codelineno-0-341" name="__codelineno-0-341"></a>
</span><span id="__span-0-342"><a id="__codelineno-0-342" name="__codelineno-0-342"></a> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
</span><span id="__span-0-343"><a id="__codelineno-0-343" name="__codelineno-0-343"></a> <span class="n">fl</span><span class="o">.</span><span class="n">Concatenate</span><span class="p">(</span>
</span><span id="__span-0-344"><a id="__codelineno-0-344" name="__codelineno-0-344"></a> <span class="n">ClassToken</span><span class="p">(</span>
</span><span id="__span-0-345"><a id="__codelineno-0-345" name="__codelineno-0-345"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-346"><a id="__codelineno-0-346" name="__codelineno-0-346"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-347"><a id="__codelineno-0-347" name="__codelineno-0-347"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-348"><a id="__codelineno-0-348" name="__codelineno-0-348"></a> <span class="p">),</span>
</span><span id="__span-0-349"><a id="__codelineno-0-349" name="__codelineno-0-349"></a> <span class="n">PatchEncoder</span><span class="p">(</span>
</span><span id="__span-0-350"><a id="__codelineno-0-350" name="__codelineno-0-350"></a> <span class="n">in_channels</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
</span><span id="__span-0-351"><a id="__codelineno-0-351" name="__codelineno-0-351"></a> <span class="n">out_channels</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-352"><a id="__codelineno-0-352" name="__codelineno-0-352"></a> <span class="n">patch_size</span><span class="o">=</span><span class="n">patch_size</span><span class="p">,</span>
</span><span id="__span-0-353"><a id="__codelineno-0-353" name="__codelineno-0-353"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-354"><a id="__codelineno-0-354" name="__codelineno-0-354"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-355"><a id="__codelineno-0-355" name="__codelineno-0-355"></a> <span class="p">),</span>
</span><span id="__span-0-356"><a id="__codelineno-0-356" name="__codelineno-0-356"></a> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
</span><span id="__span-0-357"><a id="__codelineno-0-357" name="__codelineno-0-357"></a> <span class="p">),</span>
</span><span id="__span-0-358"><a id="__codelineno-0-358" name="__codelineno-0-358"></a> <span class="n">PositionalEncoder</span><span class="p">(</span>
</span><span id="__span-0-359"><a id="__codelineno-0-359" name="__codelineno-0-359"></a> <span class="n">PositionalEmbedding</span><span class="p">(</span>
</span><span id="__span-0-360"><a id="__codelineno-0-360" name="__codelineno-0-360"></a> <span class="n">sequence_length</span><span class="o">=</span><span class="n">num_patches</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span>
</span><span id="__span-0-361"><a id="__codelineno-0-361" name="__codelineno-0-361"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-362"><a id="__codelineno-0-362" name="__codelineno-0-362"></a> <span class="n">patch_size</span><span class="o">=</span><span class="n">patch_size</span><span class="p">,</span>
</span><span id="__span-0-363"><a id="__codelineno-0-363" name="__codelineno-0-363"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-364"><a id="__codelineno-0-364" name="__codelineno-0-364"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-365"><a id="__codelineno-0-365" name="__codelineno-0-365"></a> <span class="p">),</span>
</span><span id="__span-0-366"><a id="__codelineno-0-366" name="__codelineno-0-366"></a> <span class="n">fl</span><span class="o">.</span><span class="n">Chain</span><span class="p">(</span>
</span><span id="__span-0-367"><a id="__codelineno-0-367" name="__codelineno-0-367"></a> <span class="n">fl</span><span class="o">.</span><span class="n">Parallel</span><span class="p">(</span>
</span><span id="__span-0-368"><a id="__codelineno-0-368" name="__codelineno-0-368"></a> <span class="n">fl</span><span class="o">.</span><span class="n">Identity</span><span class="p">(),</span>
</span><span id="__span-0-369"><a id="__codelineno-0-369" name="__codelineno-0-369"></a> <span class="n">fl</span><span class="o">.</span><span class="n">UseContext</span><span class="p">(</span><span class="n">context</span><span class="o">=</span><span class="s2">&quot;dinov2_vit&quot;</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="s2">&quot;input&quot;</span><span class="p">),</span>
</span><span id="__span-0-370"><a id="__codelineno-0-370" name="__codelineno-0-370"></a> <span class="p">),</span>
</span><span id="__span-0-371"><a id="__codelineno-0-371" name="__codelineno-0-371"></a> <span class="n">InterpolateEmbedding</span><span class="p">(</span>
</span><span id="__span-0-372"><a id="__codelineno-0-372" name="__codelineno-0-372"></a> <span class="n">mode</span><span class="o">=</span><span class="n">interpolate_mode</span><span class="p">,</span>
</span><span id="__span-0-373"><a id="__codelineno-0-373" name="__codelineno-0-373"></a> <span class="n">antialias</span><span class="o">=</span><span class="n">interpolate_antialias</span><span class="p">,</span>
</span><span id="__span-0-374"><a id="__codelineno-0-374" name="__codelineno-0-374"></a> <span class="n">patch_size</span><span class="o">=</span><span class="n">patch_size</span><span class="p">,</span>
</span><span id="__span-0-375"><a id="__codelineno-0-375" name="__codelineno-0-375"></a> <span class="p">),</span>
</span><span id="__span-0-376"><a id="__codelineno-0-376" name="__codelineno-0-376"></a> <span class="p">),</span>
</span><span id="__span-0-377"><a id="__codelineno-0-377" name="__codelineno-0-377"></a> <span class="p">),</span>
</span><span id="__span-0-378"><a id="__codelineno-0-378" name="__codelineno-0-378"></a> <span class="n">Transformer</span><span class="p">(</span>
</span><span id="__span-0-379"><a id="__codelineno-0-379" name="__codelineno-0-379"></a> <span class="n">TransformerLayer</span><span class="p">(</span>
</span><span id="__span-0-380"><a id="__codelineno-0-380" name="__codelineno-0-380"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-381"><a id="__codelineno-0-381" name="__codelineno-0-381"></a> <span class="n">feedforward_dim</span><span class="o">=</span><span class="n">feedforward_dim</span><span class="p">,</span>
</span><span id="__span-0-382"><a id="__codelineno-0-382" name="__codelineno-0-382"></a> <span class="n">activation</span><span class="o">=</span><span class="n">activation</span><span class="p">,</span>
</span><span id="__span-0-383"><a id="__codelineno-0-383" name="__codelineno-0-383"></a> <span class="n">num_heads</span><span class="o">=</span><span class="n">num_heads</span><span class="p">,</span>
</span><span id="__span-0-384"><a id="__codelineno-0-384" name="__codelineno-0-384"></a> <span class="n">mlp_ratio</span><span class="o">=</span><span class="n">mlp_ratio</span><span class="p">,</span>
</span><span id="__span-0-385"><a id="__codelineno-0-385" name="__codelineno-0-385"></a> <span class="n">norm_eps</span><span class="o">=</span><span class="n">norm_eps</span><span class="p">,</span>
</span><span id="__span-0-386"><a id="__codelineno-0-386" name="__codelineno-0-386"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-387"><a id="__codelineno-0-387" name="__codelineno-0-387"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-388"><a id="__codelineno-0-388" name="__codelineno-0-388"></a> <span class="p">)</span>
</span><span id="__span-0-389"><a id="__codelineno-0-389" name="__codelineno-0-389"></a> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)</span>
</span><span id="__span-0-390"><a id="__codelineno-0-390" name="__codelineno-0-390"></a> <span class="p">),</span>
</span><span id="__span-0-391"><a id="__codelineno-0-391" name="__codelineno-0-391"></a> <span class="n">fl</span><span class="o">.</span><span class="n">LayerNorm</span><span class="p">(</span>
</span><span id="__span-0-392"><a id="__codelineno-0-392" name="__codelineno-0-392"></a> <span class="n">normalized_shape</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-393"><a id="__codelineno-0-393" name="__codelineno-0-393"></a> <span class="n">eps</span><span class="o">=</span><span class="n">norm_eps</span><span class="p">,</span>
</span><span id="__span-0-394"><a id="__codelineno-0-394" name="__codelineno-0-394"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-395"><a id="__codelineno-0-395" name="__codelineno-0-395"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-396"><a id="__codelineno-0-396" name="__codelineno-0-396"></a> <span class="p">),</span>
</span><span id="__span-0-397"><a id="__codelineno-0-397" name="__codelineno-0-397"></a> <span class="p">)</span>
</span><span id="__span-0-398"><a id="__codelineno-0-398" name="__codelineno-0-398"></a>
</span><span id="__span-0-399"><a id="__codelineno-0-399" name="__codelineno-0-399"></a> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_registers</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
</span><span id="__span-0-400"><a id="__codelineno-0-400" name="__codelineno-0-400"></a> <span class="n">registers</span> <span class="o">=</span> <span class="n">Registers</span><span class="p">(</span>
</span><span id="__span-0-401"><a id="__codelineno-0-401" name="__codelineno-0-401"></a> <span class="n">num_registers</span><span class="o">=</span><span class="n">num_registers</span><span class="p">,</span>
</span><span id="__span-0-402"><a id="__codelineno-0-402" name="__codelineno-0-402"></a> <span class="n">embedding_dim</span><span class="o">=</span><span class="n">embedding_dim</span><span class="p">,</span>
</span><span id="__span-0-403"><a id="__codelineno-0-403" name="__codelineno-0-403"></a> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
</span><span id="__span-0-404"><a id="__codelineno-0-404" name="__codelineno-0-404"></a> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
</span><span id="__span-0-405"><a id="__codelineno-0-405" name="__codelineno-0-405"></a> <span class="p">)</span>
</span><span id="__span-0-406"><a id="__codelineno-0-406" name="__codelineno-0-406"></a> <span class="bp">self</span><span class="o">.</span><span class="n">insert_before_type</span><span class="p">(</span><span class="n">Transformer</span><span class="p">,</span> <span class="n">registers</span><span class="p">)</span>
</span></code></pre></div></td></tr></table></div>
</details>
<div class="doc doc-children">
</div>
</div>
</div>
<div class="doc doc-object doc-function">
<h2 id="refiners.foundationals.dinov2.preprocess" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">preprocess</span>
<a href="#refiners.foundationals.dinov2.preprocess" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">preprocess</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n"><span title="PIL.Image.Image">Image</span></span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span> <span class="o">=</span> <span class="mi">224</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><span title="torch.Tensor">Tensor</span></span>
</span></code></pre></div>
<div class="doc doc-contents ">
<p>Preprocess an image for use with DINOv2. Uses ImageNet mean and standard deviation.
Note that this only resizes and normalizes the image, there is no center crop.</p>
<p><span class="doc-section-title">Parameters:</span></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td><code>img</code></td>
<td>
<code><span title="PIL.Image.Image">Image</span></code>
</td>
<td>
<div class="doc-md-description">
<p>The image.</p>
</div>
</td>
<td>
<em>required</em>
</td>
</tr>
<tr class="doc-section-item">
<td><code>dim</code></td>
<td>
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></code>
</td>
<td>
<div class="doc-md-description">
<p>The square dimension to resize the image. Typically 224 or 518.</p>
</div>
</td>
<td>
<code>224</code>
</td>
</tr>
</tbody>
</table>
<p><span class="doc-section-title">Returns:</span></p>
<table>
<thead>
<tr>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="doc-section-item">
<td>
<code><span title="torch.Tensor">Tensor</span></code>
</td>
<td>
<div class="doc-md-description">
<p>A float32 tensor with shape (3, dim, dim).</p>
</div>
</td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>src/refiners/foundationals/dinov2/dinov2.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-9"> 9</a></span>
<span class="normal"><a href="#__codelineno-0-10">10</a></span>
<span class="normal"><a href="#__codelineno-0-11">11</a></span>
<span class="normal"><a href="#__codelineno-0-12">12</a></span>
<span class="normal"><a href="#__codelineno-0-13">13</a></span>
<span class="normal"><a href="#__codelineno-0-14">14</a></span>
<span class="normal"><a href="#__codelineno-0-15">15</a></span>
<span class="normal"><a href="#__codelineno-0-16">16</a></span>
<span class="normal"><a href="#__codelineno-0-17">17</a></span>
<span class="normal"><a href="#__codelineno-0-18">18</a></span>
<span class="normal"><a href="#__codelineno-0-19">19</a></span>
<span class="normal"><a href="#__codelineno-0-20">20</a></span>
<span class="normal"><a href="#__codelineno-0-21">21</a></span>
<span class="normal"><a href="#__codelineno-0-22">22</a></span>
<span class="normal"><a href="#__codelineno-0-23">23</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-9"><a id="__codelineno-0-9" name="__codelineno-0-9"></a><span class="k">def</span> <span class="nf">preprocess</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n">Image</span><span class="o">.</span><span class="n">Image</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">224</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
</span><span id="__span-0-10"><a id="__codelineno-0-10" name="__codelineno-0-10"></a><span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
</span><span id="__span-0-11"><a id="__codelineno-0-11" name="__codelineno-0-11"></a><span class="sd"> Preprocess an image for use with DINOv2. Uses ImageNet mean and standard deviation.</span>
</span><span id="__span-0-12"><a id="__codelineno-0-12" name="__codelineno-0-12"></a><span class="sd"> Note that this only resizes and normalizes the image, there is no center crop.</span>
</span><span id="__span-0-13"><a id="__codelineno-0-13" name="__codelineno-0-13"></a>
</span><span id="__span-0-14"><a id="__codelineno-0-14" name="__codelineno-0-14"></a><span class="sd"> Args:</span>
</span><span id="__span-0-15"><a id="__codelineno-0-15" name="__codelineno-0-15"></a><span class="sd"> img: The image.</span>
</span><span id="__span-0-16"><a id="__codelineno-0-16" name="__codelineno-0-16"></a><span class="sd"> dim: The square dimension to resize the image. Typically 224 or 518.</span>
</span><span id="__span-0-17"><a id="__codelineno-0-17" name="__codelineno-0-17"></a>
</span><span id="__span-0-18"><a id="__codelineno-0-18" name="__codelineno-0-18"></a><span class="sd"> Returns:</span>
</span><span id="__span-0-19"><a id="__codelineno-0-19" name="__codelineno-0-19"></a><span class="sd"> A float32 tensor with shape (3, dim, dim).</span>
</span><span id="__span-0-20"><a id="__codelineno-0-20" name="__codelineno-0-20"></a><span class="sd"> &quot;&quot;&quot;</span>
</span><span id="__span-0-21"><a id="__codelineno-0-21" name="__codelineno-0-21"></a> <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">&quot;RGB&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="n">dim</span><span class="p">,</span> <span class="n">dim</span><span class="p">))</span> <span class="c1"># type: ignore</span>
</span><span id="__span-0-22"><a id="__codelineno-0-22" name="__codelineno-0-22"></a> <span class="n">t</span> <span class="o">=</span> <span class="n">image_to_tensor</span><span class="p">(</span><span class="n">img</span><span class="p">)</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span>
</span><span id="__span-0-23"><a id="__codelineno-0-23" name="__codelineno-0-23"></a> <span class="k">return</span> <span class="n">normalize</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="p">[</span><span class="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">],</span> <span class="n">std</span><span class="o">=</span><span class="p">[</span><span class="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">])</span>
</span></code></pre></div></td></tr></table></div>
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<script src="../../../assets/javascripts/bundle.56dfad97.min.js"></script>
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