Generate Python docs from pytorch/pytorch@1c152f8

Author: pytorchbot

docs/master/__config__.html

@@ -214,7 +214,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 

docs/master/_images/RReLU.png

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/index.html

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch.html

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/__config__.html

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 
@@ -879,7 +879,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
         <span class="s2">&quot;if this method is not scripted, copy the python method onto the scripted model&quot;</span>
 
 
-<div class="viewcode-block" id="export"><a class="viewcode-back" href="../../jit.html#torch.jit.export">[docs]</a><span class="k">def</span> <span class="nf">export</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">export</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates that a method on an ``nn.Module`` is used as an entry point into a</span>
 <span class="sd">    :class:`ScriptModule` and should be compiled.</span>
@@ -922,10 +922,10 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
 <span class="sd">        m = torch.jit.script(MyModule())</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">EXPORT</span>
-    <span class="k">return</span> <span class="n">fn</span></div>
+    <span class="k">return</span> <span class="n">fn</span>
 
 
-<span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
+<div class="viewcode-block" id="unused"><a class="viewcode-back" href="../../generated/torch.jit.unused.html#torch.jit.unused">[docs]</a><span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates to the compiler that a function or method should</span>
 <span class="sd">    be ignored and replaced with the raising of an exception. This allows you</span>
@@ -972,7 +972,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">prop</span>
 
     <span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">UNUSED</span>
-    <span class="k">return</span> <span class="n">fn</span>
+    <span class="k">return</span> <span class="n">fn</span></div>
 
 <span class="c1"># No op context manager from python side</span>
 <span class="k">class</span> <span class="nc">_IgnoreContextManager</span><span class="p">(</span><span class="n">contextlib</span><span class="o">.</span><span class="n">AbstractContextManager</span><span class="p">):</span>
@@ -982,7 +982,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exc_type</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">exc_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">traceback</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
         <span class="k">pass</span>
 
-<span class="k">def</span> <span class="nf">ignore</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+<div class="viewcode-block" id="ignore"><a class="viewcode-back" href="../../generated/torch.jit.ignore.html#torch.jit.ignore">[docs]</a><span class="k">def</span> <span class="nf">ignore</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates to the compiler that a function or method should</span>
 <span class="sd">    be ignored and left as a Python function. This allows you to leave code in</span>
@@ -1073,7 +1073,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
         <span class="k">else</span><span class="p">:</span>
             <span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">IGNORE</span>
         <span class="k">return</span> <span class="n">fn</span>
-    <span class="k">return</span> <span class="n">decorator</span>
+    <span class="k">return</span> <span class="n">decorator</span></div>
 
 
 <span class="k">def</span> <span class="nf">_copy_to_script_wrapper</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
@@ -1371,7 +1371,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="nb">globals</span><span class="p">()[</span><span class="sa">f</span><span class="s2">&quot;BroadcastingList</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">BroadcastingList1</span>
 
 
-<div class="viewcode-block" id="is_scripting"><a class="viewcode-back" href="../../jit_language_reference.html#torch.jit.is_scripting">[docs]</a><span class="k">def</span> <span class="nf">is_scripting</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+<span class="k">def</span> <span class="nf">is_scripting</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Function that returns True when in compilation and False otherwise. This</span>
 <span class="sd">    is useful especially with the @unused decorator to leave code in your</span>
@@ -1390,7 +1390,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
 <span class="sd">           else:</span>
 <span class="sd">              return unsupported_linear_op(x)</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="kc">False</span></div>
+    <span class="k">return</span> <span class="kc">False</span>
 
 
 <span class="c1"># Retrieves a fully-qualified name (module hierarchy + classname) for a given obj.</span>

docs/master/_modules/torch/_jit_internal.html

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>
 
 
@@ -1069,17 +1069,16 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
 <span class="sd">    &quot;&quot;&quot;</span>
 
     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
-                 <span class="n">A</span><span class="p">,</span>        <span class="c1"># type: Optional[Tensor]</span>
-                 <span class="n">B</span><span class="p">,</span>        <span class="c1"># type: Optional[Tensor]</span>
-                 <span class="n">X</span><span class="p">,</span>        <span class="c1"># type: Tensor</span>
-                 <span class="n">iK</span><span class="p">,</span>       <span class="c1"># type: Optional[Tensor]</span>
-                 <span class="n">iparams</span><span class="p">,</span>  <span class="c1"># type: Dict[str, int]</span>
-                 <span class="n">fparams</span><span class="p">,</span>  <span class="c1"># type: Dict[str, float]</span>
-                 <span class="n">bparams</span><span class="p">,</span>  <span class="c1"># type: Dict[str, bool]</span>
-                 <span class="n">method</span><span class="p">,</span>   <span class="c1"># type: str</span>
-                 <span class="n">tracker</span>   <span class="c1"># type: None</span>
-                 <span class="p">):</span>
-        <span class="c1"># type: (...) -&gt; None</span>
+                 <span class="n">A</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">],</span>
+                 <span class="n">B</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</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">iK</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">],</span>
+                 <span class="n">iparams</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="nb">int</span><span class="p">],</span>
+                 <span class="n">fparams</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="nb">float</span><span class="p">],</span>
+                 <span class="n">bparams</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="nb">bool</span><span class="p">],</span>
+                 <span class="n">method</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
+                 <span class="n">tracker</span><span class="p">:</span> <span class="kc">None</span>
+                 <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
 
         <span class="c1"># constant parameters</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">A</span> <span class="o">=</span> <span class="n">A</span>
@@ -1098,10 +1097,10 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="o">.</span><span class="n">E</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">n</span><span class="p">,</span> <span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">device</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">R</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</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="n">dtype</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">device</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">S</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">m</span><span class="p">,</span> <span class="mi">3</span> <span class="o">*</span> <span class="n">n</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">X</span><span class="o">.</span><span class="n">device</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">tvars</span> <span class="o">=</span> <span class="p">{}</span>               <span class="c1"># type: Dict[str, Tensor]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">ivars</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;istep&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span>     <span class="c1"># type: Dict[str, int]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">fvars</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;_&#39;</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">}</span>       <span class="c1"># type: Dict[str, float]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">bvars</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;_&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">}</span>     <span class="c1"># type: Dict[str, bool]</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">tvars</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="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">ivars</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="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;istep&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">fvars</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="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;_&#39;</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">bvars</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="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;_&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">}</span>
 
     <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="n">lines</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;LOPBCG:&#39;</span><span class="p">]</span>
@@ -1364,11 +1363,10 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">Rinv</span> <span class="o">*</span> <span class="n">d_col</span>
 
     <span class="k">def</span> <span class="nf">_get_svqb</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
-                  <span class="n">U</span><span class="p">,</span>     <span class="c1"># Tensor</span>
-                  <span class="n">drop</span><span class="p">,</span>  <span class="c1"># bool</span>
-                  <span class="n">tau</span>    <span class="c1"># float</span>
-                  <span class="p">):</span>
-        <span class="c1"># type: (Tensor, bool, float) -&gt; Tensor</span>
+                  <span class="n">U</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>     <span class="c1"># Tensor</span>
+                  <span class="n">drop</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span>  <span class="c1"># bool</span>
+                  <span class="n">tau</span><span class="p">:</span> <span class="nb">float</span>    <span class="c1"># float</span>
+                  <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
         <span class="sd">&quot;&quot;&quot;Return B-orthonormal U.</span>
 
 <span class="sd">        .. note:: When `drop` is `False` then `svqb` is based on the</span>

docs/master/_modules/torch/_lobpcg.html

@@ -213,7 +213,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git943085f ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git1c152f8 ) &#x25BC</a>
     </div>