Generate Python docs from pytorch/pytorch@834e8f0

Author: pytorchbot

docs/master/_dynamo.html

@@ -237,7 +237,7 @@
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@@ -608,7 +608,7 @@
 
 <dl class="py function">
 <dt class="sig sig-object py" id="torch._dynamo.list_backends">
-<span class="sig-prename descclassname"><span class="pre">torch._dynamo.</span></span><span class="sig-name descname"><span class="pre">list_backends</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/_dynamo/backends/registry.html#list_backends"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch._dynamo.list_backends" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">torch._dynamo.</span></span><span class="sig-name descname"><span class="pre">list_backends</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">exclude_tags</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">('debug',</span> <span class="pre">'experimental')</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/_dynamo/backends/registry.html#list_backends"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch._dynamo.list_backends" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return valid strings that can be passed to:</p>
 <blockquote>
 <div><p>torch.compile(…, backend=”name”)</p>

docs/master/_images/RReLU.png

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@@ -708,6 +708,11 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="fm">__int__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">int_</span><span class="p">()</span>
 
+    <span class="c1"># This is a hack, shouldn&#39;t be necessary.  Helps</span>
+    <span class="c1"># pyhpc_turbulent_kinetic_energy and vision_maskrcnn</span>
+    <span class="k">def</span> <span class="fm">__iadd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
+        <span class="k">return</span> <span class="bp">self</span> <span class="o">+</span> <span class="n">other</span>
+
     <span class="c1"># Magic methods installed by torch.fx.experimental.symbolic_shapes</span>
 
     <span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="nb">object</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">builtins</span><span class="o">.</span><span class="n">bool</span><span class="p">:</span>

docs/master/_modules/torch.html

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docs/master/_modules/torch/__config__.html

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docs/master/_modules/torch/_dynamo.html

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@@ -513,6 +513,12 @@ <h1>Source code for torch._dynamo.backends.registry</h1><div class="highlight"><
     <span class="k">return</span> <span class="n">compiler_fn</span></div>
 
 
+<span class="n">register_debug_backend</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">register_backend</span><span class="p">,</span> <span class="n">tags</span><span class="o">=</span><span class="p">(</span><span class="s2">&quot;debug&quot;</span><span class="p">,))</span>
+<span class="n">register_experimental_backend</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span>
+    <span class="n">register_backend</span><span class="p">,</span> <span class="n">tags</span><span class="o">=</span><span class="p">(</span><span class="s2">&quot;experimental&quot;</span><span class="p">,)</span>
+<span class="p">)</span>
+
+
 <span class="k">def</span> <span class="nf">lookup_backend</span><span class="p">(</span><span class="n">compiler_fn</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Expand backend strings to functions&quot;&quot;&quot;</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compiler_fn</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
@@ -522,14 +528,21 @@ <h1>Source code for torch._dynamo.backends.registry</h1><div class="highlight"><
     <span class="k">return</span> <span class="n">compiler_fn</span>
 
 
-<div class="viewcode-block" id="list_backends"><a class="viewcode-back" href="../../../../_dynamo.html#torch._dynamo.list_backends">[docs]</a><span class="k">def</span> <span class="nf">list_backends</span><span class="p">():</span>
+<div class="viewcode-block" id="list_backends"><a class="viewcode-back" href="../../../../_dynamo.html#torch._dynamo.list_backends">[docs]</a><span class="k">def</span> <span class="nf">list_backends</span><span class="p">(</span><span class="n">exclude_tags</span><span class="o">=</span><span class="p">(</span><span class="s2">&quot;debug&quot;</span><span class="p">,</span> <span class="s2">&quot;experimental&quot;</span><span class="p">)):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Return valid strings that can be passed to:</span>
 
 <span class="sd">        torch.compile(..., backend=&quot;name&quot;)</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">_lazy_import</span><span class="p">()</span>
-    <span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">_BACKENDS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></div>
+    <span class="n">exclude_tags</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">exclude_tags</span> <span class="ow">or</span> <span class="p">())</span>
+    <span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span>
+        <span class="p">[</span>
+            <span class="n">name</span>
+            <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">backend</span> <span class="ow">in</span> <span class="n">_BACKENDS</span><span class="o">.</span><span class="n">items</span><span class="p">()</span>
+            <span class="k">if</span> <span class="ow">not</span> <span class="n">exclude_tags</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">backend</span><span class="o">.</span><span class="n">_tags</span><span class="p">)</span>
+        <span class="p">]</span>
+    <span class="p">)</span></div>
 
 
 <span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>

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