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frgfm committed Jun 23, 2024
1 parent 952e7cb commit 65f5cf6
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4 changes: 1 addition & 3 deletions latest/_modules/holocron/models/classification/sknet.html
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Expand Up @@ -477,9 +477,7 @@ <h1>Source code for holocron.models.classification.sknet</h1><div class="highlig
<span class="n">b</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="n">paths</span><span class="o">.</span><span class="n">shape</span><span class="p">[:</span><span class="mi">3</span><span class="p">]</span>
<span class="n">z</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sa</span><span class="p">(</span><span class="n">paths</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">attention_factors</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">softmax</span><span class="p">(</span><span class="n">z</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">out</span> <span class="o">=</span> <span class="p">(</span><span class="n">attention_factors</span> <span class="o">*</span> <span class="n">paths</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

<span class="k">return</span> <span class="n">out</span>
<span class="k">return</span> <span class="p">(</span><span class="n">attention_factors</span> <span class="o">*</span> <span class="n">paths</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>


<span class="k">class</span> <span class="nc">SKBottleneck</span><span class="p">(</span><span class="n">_ResBlock</span><span class="p">):</span>
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4 changes: 1 addition & 3 deletions latest/_modules/holocron/models/classification/tridentnet.html
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Expand Up @@ -408,7 +408,7 @@ <h1>Source code for holocron.models.classification.tridentnet</h1><div class="hi
<span class="n">dilations</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_branches</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dilation</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span> <span class="k">else</span> <span class="p">[</span><span class="mi">1</span> <span class="o">+</span> <span class="n">idx</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">num_branches</span><span class="p">)]</span>

<span class="c1"># Use shared weight to apply the convolution</span>
<span class="n">out</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">(</span>
<span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">(</span>
<span class="p">[</span>
<span class="n">F</span><span class="o">.</span><span class="n">conv2d</span><span class="p">(</span>
<span class="n">_x</span><span class="p">,</span>
Expand All @@ -424,8 +424,6 @@ <h1>Source code for holocron.models.classification.tridentnet</h1><div class="hi
<span class="mi">1</span><span class="p">,</span>
<span class="p">)</span>

<span class="k">return</span> <span class="n">out</span>


<span class="k">class</span> <span class="nc">Tridentneck</span><span class="p">(</span><span class="n">_ResBlock</span><span class="p">):</span>
<span class="n">expansion</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span>
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4 changes: 1 addition & 3 deletions latest/_modules/holocron/models/detection/yolo.html
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Expand Up @@ -706,9 +706,7 @@ <h1>Source code for holocron.models.detection.yolo</h1><div class="highlight"><p
<span class="k">def</span> <span class="nf">_forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">backbone</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">block4</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
<span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="k">return</span> <span class="n">out</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">forward</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">target</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span>
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4 changes: 1 addition & 3 deletions latest/_modules/holocron/models/detection/yolov2.html
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Expand Up @@ -575,9 +575,7 @@ <h1>Source code for holocron.models.detection.yolov2</h1><div class="highlight">
<span class="n">out</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">((</span><span class="n">passthrough</span><span class="p">,</span> <span class="n">out</span><span class="p">),</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">block6</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="k">return</span> <span class="n">out</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">forward</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">target</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span>
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3 changes: 1 addition & 2 deletions latest/_modules/holocron/models/detection/yolov4.html
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Expand Up @@ -995,15 +995,14 @@ <h1>Source code for holocron.models.detection.yolov4</h1><div class="highlight">
<span class="n">y3</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">yolo3</span><span class="p">(</span><span class="n">o3</span><span class="p">,</span> <span class="n">target</span><span class="p">)</span>

<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">training</span><span class="p">:</span>
<span class="n">detections</span> <span class="o">=</span> <span class="p">[</span>
<span class="k">return</span> <span class="p">[</span>
<span class="p">{</span>
<span class="s2">&quot;boxes&quot;</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">((</span><span class="n">det1</span><span class="p">[</span><span class="s2">&quot;boxes&quot;</span><span class="p">],</span> <span class="n">det2</span><span class="p">[</span><span class="s2">&quot;boxes&quot;</span><span class="p">],</span> <span class="n">det3</span><span class="p">[</span><span class="s2">&quot;boxes&quot;</span><span class="p">]),</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="s2">&quot;scores&quot;</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">((</span><span class="n">det1</span><span class="p">[</span><span class="s2">&quot;scores&quot;</span><span class="p">],</span> <span class="n">det2</span><span class="p">[</span><span class="s2">&quot;scores&quot;</span><span class="p">],</span> <span class="n">det3</span><span class="p">[</span><span class="s2">&quot;scores&quot;</span><span class="p">]),</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="s2">&quot;labels&quot;</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">((</span><span class="n">det1</span><span class="p">[</span><span class="s2">&quot;labels&quot;</span><span class="p">],</span> <span class="n">det2</span><span class="p">[</span><span class="s2">&quot;labels&quot;</span><span class="p">],</span> <span class="n">det3</span><span class="p">[</span><span class="s2">&quot;labels&quot;</span><span class="p">]),</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="p">}</span>
<span class="k">for</span> <span class="n">det1</span><span class="p">,</span> <span class="n">det2</span><span class="p">,</span> <span class="n">det3</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">y1</span><span class="p">,</span> <span class="n">y2</span><span class="p">,</span> <span class="n">y3</span><span class="p">)</span>
<span class="p">]</span>
<span class="k">return</span> <span class="n">detections</span>

<span class="k">return</span> <span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">y1</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">y2</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">y3</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">y1</span><span class="p">}</span>

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6 changes: 2 additions & 4 deletions latest/_modules/holocron/models/segmentation/unet.html
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Expand Up @@ -590,8 +590,7 @@ <h1>Source code for holocron.models.segmentation.unet</h1><div class="highlight"
<span class="n">x</span> <span class="o">=</span> <span class="n">decoder</span><span class="p">(</span><span class="n">xs</span><span class="o">.</span><span class="n">pop</span><span class="p">(),</span> <span class="n">x</span><span class="p">)</span>

<span class="c1"># Classifier</span>
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="k">return</span> <span class="n">x</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>


<span class="k">class</span> <span class="nc">UBlock</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
Expand Down Expand Up @@ -735,8 +734,7 @@ <h1>Source code for holocron.models.segmentation.unet</h1><div class="highlight"
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">upsample</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>

<span class="c1"># Classifier</span>
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="k">return</span> <span class="n">x</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>


<span class="k">def</span> <span class="nf">_unet</span><span class="p">(</span><span class="n">arch</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">pretrained</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">progress</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">UNet</span><span class="p">:</span>
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3 changes: 1 addition & 2 deletions latest/_modules/holocron/models/segmentation/unet3p.html
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Expand Up @@ -522,8 +522,7 @@ <h1>Source code for holocron.models.segmentation.unet3p</h1><div class="highligh
<span class="n">xs</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">decoder</span><span class="p">[</span><span class="n">idx</span><span class="p">](</span><span class="n">xs</span><span class="p">[:</span><span class="n">idx</span><span class="p">],</span> <span class="n">xs</span><span class="p">[</span><span class="n">idx</span><span class="p">],</span> <span class="n">xs</span><span class="p">[</span><span class="n">idx</span> <span class="o">+</span> <span class="mi">1</span> <span class="p">:])</span>

<span class="c1"># Classifier</span>
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">xs</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="k">return</span> <span class="n">x</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">xs</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>


<span class="k">def</span> <span class="nf">_unet</span><span class="p">(</span><span class="n">arch</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">pretrained</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">progress</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">:</span>
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