Generate Python docs from pytorch/pytorch@2ec6094

Author: pytorchbot

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docs/master/_modules/torch/ao/quantization/qconfig.html

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@@ -885,7 +885,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
     <span class="n">prepare</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">observer_non_leaf_module_list</span><span class="o">=</span><span class="nb">set</span><span class="p">(</span><span class="n">mapping</span><span class="o">.</span><span class="n">values</span><span class="p">()),</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">model</span></div>
 
-<span class="k">def</span> <span class="nf">quantize_qat</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">run_fn</span><span class="p">,</span> <span class="n">run_args</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+<div class="viewcode-block" id="quantize_qat"><a class="viewcode-back" href="../../../../generated/torch.quantization.quantize_qat.html#torch.quantization.quantize_qat">[docs]</a><span class="k">def</span> <span class="nf">quantize_qat</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">run_fn</span><span class="p">,</span> <span class="n">run_args</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Do quantization aware training and output a quantized model</span>
 
 <span class="sd">    Args:</span>
@@ -905,7 +905,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
     <span class="n">prepare_qat</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="n">run_fn</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="o">*</span><span class="n">run_args</span><span class="p">)</span>
     <span class="n">convert</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-    <span class="k">return</span> <span class="n">model</span>
+    <span class="k">return</span> <span class="n">model</span></div>
 
 <span class="k">def</span> <span class="nf">convert</span><span class="p">(</span>
         <span class="n">module</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">remove_qconfig</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
@@ -986,7 +986,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
 
     <span class="k">return</span> <span class="n">module</span>
 
-<span class="k">def</span> <span class="nf">swap_module</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <span class="n">mapping</span><span class="p">,</span> <span class="n">custom_module_class_mapping</span><span class="p">):</span>
+<div class="viewcode-block" id="swap_module"><a class="viewcode-back" href="../../../../generated/torch.quantization.swap_module.html#torch.quantization.swap_module">[docs]</a><span class="k">def</span> <span class="nf">swap_module</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <span class="n">mapping</span><span class="p">,</span> <span class="n">custom_module_class_mapping</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Swaps the module if it has a quantized counterpart and it has an</span>
 <span class="sd">    `observer` attached.</span>
 
@@ -1034,7 +1034,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
             <span class="n">device</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="nb">iter</span><span class="p">(</span><span class="n">devices</span><span class="p">))</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">devices</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">None</span>
             <span class="k">if</span> <span class="n">device</span><span class="p">:</span>
                 <span class="n">new_mod</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
-    <span class="k">return</span> <span class="n">new_mod</span>
+    <span class="k">return</span> <span class="n">new_mod</span></div>
 
 <div class="viewcode-block" id="get_observer_dict"><a class="viewcode-back" href="../../../../generated/torch.quantization.get_observer_dict.html#torch.quantization.get_observer_dict">[docs]</a><span class="k">def</span> <span class="nf">get_observer_dict</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <span class="n">target_dict</span><span class="p">,</span> <span class="n">prefix</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Traverse the modules and save all observers into dict.</span>

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@@ -509,7 +509,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">()</span>
 
 
-<div class="viewcode-block" id="no_grad"><a class="viewcode-back" href="../../../generated/torch.no_grad.html#torch.no_grad">[docs]</a><span class="k">class</span> <span class="nc">no_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
+<span class="k">class</span> <span class="nc">no_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Context-manager that disabled gradient calculation.</span>
 
 <span class="sd">    Disabling gradient calculation is useful for inference, when you are sure</span>
@@ -558,7 +558,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
 
     <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="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span></div>
+        <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span>
 
 
 <span class="k">class</span> <span class="nc">enable_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
@@ -607,7 +607,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span>
 
 
-<span class="k">class</span> <span class="nc">set_grad_enabled</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
+<div class="viewcode-block" id="set_grad_enabled"><a class="viewcode-back" href="../../../generated/torch.set_grad_enabled.html#torch.set_grad_enabled">[docs]</a><span class="k">class</span> <span class="nc">set_grad_enabled</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Context-manager that sets gradient calculation to on or off.</span>
 
 <span class="sd">    ``set_grad_enabled`` will enable or disable grads based on its argument :attr:`mode`.</span>
@@ -660,7 +660,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">clone</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="vm">__class__</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="p">)</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="p">)</span></div>
 
 
 <span class="k">class</span> <span class="nc">inference_mode</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>

docs/master/_modules/torch/autograd/grad_mode.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2ec6094 ) &#x25BC</a>
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docs/master/_modules/torch/autograd/profiler.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git104f0bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2ec6094 ) &#x25BC</a>
     </div>