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<div class="pytorch-left-menu-search">

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Expand Down Expand Up @@ -2187,8 +2187,8 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
<span class="n">device_type</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="n">device_type</span><span class="p">)</span><span class="o">.</span><span class="n">type</span>
<span class="n">m</span> <span class="o">=</span> <span class="n">sys</span><span class="o">.</span><span class="n">modules</span><span class="p">[</span><span class="vm">__name__</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">device_type</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;The runtime module of &#39;</span><span class="si">{}</span><span class="s2">&#39; has already &quot;</span>
<span class="s2">&quot;been registered with &#39;</span><span class="si">{}</span><span class="s2">&#39;&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">device_type</span><span class="p">,</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">device_type</span><span class="p">)))</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;The runtime module of &#39;</span><span class="si">{</span><span class="n">device_type</span><span class="si">}</span><span class="s2">&#39; has already &quot;</span>
<span class="sa">f</span><span class="s2">&quot;been registered with &#39;</span><span class="si">{</span><span class="nb">getattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span><span class="w"> </span><span class="n">device_type</span><span class="p">)</span><span class="si">}</span><span class="s2">&#39;&quot;</span><span class="p">)</span>
<span class="nb">setattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">device_type</span><span class="p">,</span> <span class="n">module</span><span class="p">)</span>
<span class="n">torch_module_name</span> <span class="o">=</span> <span class="s1">&#39;.&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="vm">__name__</span><span class="p">,</span> <span class="n">device_type</span><span class="p">])</span>
<span class="n">sys</span><span class="o">.</span><span class="n">modules</span><span class="p">[</span><span class="n">torch_module_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">module</span>
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Expand Down Expand Up @@ -1073,8 +1073,8 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>

<span class="k">if</span> <span class="n">m</span> <span class="o">&lt;</span> <span class="mi">3</span> <span class="o">*</span> <span class="n">n</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;LPBPCG algorithm is not applicable when the number of A rows (=</span><span class="si">{}</span><span class="s2">)&quot;</span>
<span class="s2">&quot; is smaller than 3 x the number of requested eigenpairs (=</span><span class="si">{}</span><span class="s2">)&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">n</span><span class="p">)</span>
<span class="sa">f</span><span class="s2">&quot;LPBPCG algorithm is not applicable when the number of A rows (=</span><span class="si">{</span><span class="n">m</span><span class="si">}</span><span class="s2">)&quot;</span>
<span class="sa">f</span><span class="s2">&quot; is smaller than 3 x the number of requested eigenpairs (=</span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2">)&quot;</span>
<span class="p">)</span>

<span class="n">method</span> <span class="o">=</span> <span class="s2">&quot;ortho&quot;</span> <span class="k">if</span> <span class="n">method</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">method</span>
Expand Down Expand Up @@ -1610,9 +1610,7 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
<span class="k">assert</span> <span class="n">B</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;Overdetermined shape of U:&quot;</span>
<span class="s2">&quot; #B-cols(=</span><span class="si">{}</span><span class="s2">) &gt;= #U-cols(=</span><span class="si">{}</span><span class="s2">) + #V-cols(=</span><span class="si">{}</span><span class="s2">) must hold&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
<span class="n">B</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">U</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">V</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="p">)</span>
<span class="sa">f</span><span class="s2">&quot; #B-cols(=</span><span class="si">{</span><span class="n">B</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">) &gt;= #U-cols(=</span><span class="si">{</span><span class="n">U</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">) + #V-cols(=</span><span class="si">{</span><span class="n">V</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">) must hold&quot;</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ivars</span><span class="p">[</span><span class="s2">&quot;ortho_i&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">i</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ivars</span><span class="p">[</span><span class="s2">&quot;ortho_j&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">j</span>
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Expand Down Expand Up @@ -1027,9 +1027,14 @@ <h1>Source code for torch._logging._internal</h1><div class="highlight"><pre>
<span class="n">record</span><span class="o">.</span><span class="n">rankprefix</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">if</span> <span class="n">dist</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span> <span class="ow">and</span> <span class="n">dist</span><span class="o">.</span><span class="n">is_initialized</span><span class="p">():</span>
<span class="n">record</span><span class="o">.</span><span class="n">rankprefix</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;[rank</span><span class="si">{</span><span class="n">dist</span><span class="o">.</span><span class="n">get_rank</span><span class="p">()</span><span class="si">}</span><span class="s2">]:&quot;</span>
<span class="n">prefix</span> <span class="o">=</span> <span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">rankprefix</span><span class="si">}</span><span class="s2">[</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">asctime</span><span class="si">}</span><span class="s2">] </span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">: [</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">levelname</span><span class="si">}</span><span class="s2">]&quot;</span>
<span class="p">)</span>

<span class="n">record</span><span class="o">.</span><span class="n">compileid</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">if</span> <span class="p">(</span>
<span class="n">compile_id</span> <span class="o">:=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_guards</span><span class="o">.</span><span class="n">CompileContext</span><span class="o">.</span><span class="n">current_compile_id</span><span class="p">()</span>
<span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">record</span><span class="o">.</span><span class="n">compileid</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot; [</span><span class="si">{</span><span class="n">compile_id</span><span class="si">}</span><span class="s2">]&quot;</span>

<span class="n">prefix</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">rankprefix</span><span class="si">}</span><span class="s2">[</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">asctime</span><span class="si">}</span><span class="s2">]</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">compileid</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">: [</span><span class="si">{</span><span class="n">record</span><span class="o">.</span><span class="n">levelname</span><span class="si">}</span><span class="s2">]&quot;</span>
<span class="k">return</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">prefix</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">l</span><span class="si">}</span><span class="s2">&quot;</span> <span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">lines</span><span class="p">)</span>


Expand Down Expand Up @@ -1140,6 +1145,7 @@ <h1>Source code for torch._logging._internal</h1><div class="highlight"><pre>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="bp">self</span><span class="o">.</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">kwargs</span><span class="p">)</span>


<span class="kn">import</span> <span class="nn">torch._guards</span>
<span class="kn">import</span> <span class="nn">torch.distributed</span> <span class="k">as</span> <span class="nn">dist</span>
</pre></div>

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2 changes: 1 addition & 1 deletion docs/main/_modules/torch/ao/nn/quantizable/modules/activation.html
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