Generate Python docs from pytorch/pytorch@e494487

Author: pytorchbot

docs/1.11/_images/RReLU.png

@@ -537,6 +537,7 @@ <h1>All modules for which code is available</h1>
 <li><a href="torch/jit.html">torch.jit</a></li>
 <ul><li><a href="torch/jit/_async.html">torch.jit._async</a></li>
 <li><a href="torch/jit/_freeze.html">torch.jit._freeze</a></li>
+<li><a href="torch/jit/_fuser.html">torch.jit._fuser</a></li>
 <li><a href="torch/jit/_script.html">torch.jit._script</a></li>
 <li><a href="torch/jit/_serialization.html">torch.jit._serialization</a></li>
 <li><a href="torch/jit/_trace.html">torch.jit._trace</a></li>

docs/1.11/_modules/index.html

@@ -434,7 +434,7 @@ <h1>Source code for torch.ao.quantization.qconfig</h1><div class="highlight"><pr
 <span class="kn">import</span> <span class="nn">warnings</span>
 
 
-<div class="viewcode-block" id="QConfig"><a class="viewcode-back" href="../../../../generated/torch.quantization.qconfig.QConfig.html#torch.quantization.qconfig.QConfig">[docs]</a><span class="k">class</span> <span class="nc">QConfig</span><span class="p">(</span><span class="n">namedtuple</span><span class="p">(</span><span class="s1">&#39;QConfig&#39;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;activation&#39;</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">])):</span>
+<span class="k">class</span> <span class="nc">QConfig</span><span class="p">(</span><span class="n">namedtuple</span><span class="p">(</span><span class="s1">&#39;QConfig&#39;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;activation&#39;</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">])):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Describes how to quantize a layer or a part of the network by providing</span>
 <span class="sd">    settings (observer classes) for activations and weights respectively.</span>
@@ -458,7 +458,7 @@ <h1>Source code for torch.ao.quantization.qconfig</h1><div class="highlight"><pr
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">activation</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">weight</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;QConfig received observer instance, please pass observer class instead. &quot;</span> <span class="o">+</span>
                              <span class="s2">&quot;Use MyObserver.with_args(x=1) to override arguments to constructor if needed&quot;</span><span class="p">)</span>
-        <span class="k">return</span> <span class="nb">super</span><span class="p">(</span><span class="n">QConfig</span><span class="p">,</span> <span class="bp">cls</span><span class="p">)</span><span class="o">.</span><span class="fm">__new__</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">activation</span><span class="p">,</span> <span class="n">weight</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="nb">super</span><span class="p">(</span><span class="n">QConfig</span><span class="p">,</span> <span class="bp">cls</span><span class="p">)</span><span class="o">.</span><span class="fm">__new__</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">activation</span><span class="p">,</span> <span class="n">weight</span><span class="p">)</span>
 
 
 <span class="k">class</span> <span class="nc">QConfigDynamic</span><span class="p">(</span><span class="n">namedtuple</span><span class="p">(</span><span class="s1">&#39;QConfigDynamic&#39;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;activation&#39;</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">])):</span>

docs/1.11/_modules/torch.html

@@ -499,7 +499,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
         <span class="n">module</span><span class="o">.</span><span class="n">_forward_hooks</span><span class="o">.</span><span class="n">move_to_end</span><span class="p">(</span><span class="n">handle</span><span class="o">.</span><span class="n">id</span><span class="p">,</span> <span class="n">last</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="add_observer_"><a class="viewcode-back" href="../../../../generated/torch.quantization.add_observer_.html#torch.quantization.add_observer_">[docs]</a><span class="k">def</span> <span class="nf">add_observer_</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">qconfig_propagation_list</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">non_leaf_module_list</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">custom_module_class_mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">add_observer_</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">qconfig_propagation_list</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">non_leaf_module_list</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">custom_module_class_mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Add observer for the leaf child of the module.</span>
 
 <span class="sd">    This function insert observer module to all leaf child module that</span>
@@ -583,7 +583,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
     <span class="c1"># the output of the module, for input QuantStub will observe them</span>
     <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">module</span><span class="o">.</span><span class="n">_modules</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">)</span> \
        <span class="ow">and</span> <span class="nb">type</span><span class="p">(</span><span class="n">module</span><span class="p">)</span> <span class="ow">in</span> <span class="n">qconfig_propagation_list</span><span class="p">:</span>
-        <span class="n">insert_activation_post_process</span><span class="p">(</span><span class="n">module</span><span class="p">)</span></div>
+        <span class="n">insert_activation_post_process</span><span class="p">(</span><span class="n">module</span><span class="p">)</span>
 
 <span class="k">def</span> <span class="nf">get_unique_devices_</span><span class="p">(</span><span class="n">module</span><span class="p">):</span>
     <span class="k">return</span> <span class="p">{</span><span class="n">p</span><span class="o">.</span><span class="n">device</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">module</span><span class="o">.</span><span class="n">parameters</span><span class="p">()}</span> <span class="o">|</span> \
@@ -704,7 +704,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
 
     <span class="n">_remove_activation_post_process</span><span class="p">(</span><span class="n">module</span><span class="p">)</span>
 
-<span class="k">def</span> <span class="nf">quantize</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">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>
+<div class="viewcode-block" id="quantize"><a class="viewcode-back" href="../../../../generated/torch.quantization.quantize.html#torch.quantization.quantize">[docs]</a><span class="k">def</span> <span class="nf">quantize</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">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="sa">r</span><span class="sd">&quot;&quot;&quot;Quantize the input float model with post training static quantization.</span>
 
 <span class="sd">    First it will prepare the model for calibration, then it calls</span>
@@ -730,9 +730,9 @@ <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">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">mapping</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">quantize_dynamic</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">qconfig_spec</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">qint8</span><span class="p">,</span>
+<div class="viewcode-block" id="quantize_dynamic"><a class="viewcode-back" href="../../../../generated/torch.quantization.quantize_dynamic.html#torch.quantization.quantize_dynamic">[docs]</a><span class="k">def</span> <span class="nf">quantize_dynamic</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">qconfig_spec</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">qint8</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="sa">r</span><span class="sd">&quot;&quot;&quot;Converts a float model to dynamic (i.e. weights-only) quantized model.</span>
 
@@ -815,7 +815,7 @@ <h1>Source code for torch.ao.quantization.quantize</h1><div class="highlight"><p
     <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
     <span class="n">propagate_qconfig_</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">qconfig_spec</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">mapping</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">prepare_qat</span><span class="p">(</span><span class="n">model</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="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
@@ -845,7 +845,7 @@ <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>
 
-<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>
@@ -865,7 +865,7 @@ <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>
@@ -944,7 +944,7 @@ <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>
 
@@ -984,7 +984,7 @@ <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>
 
 <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>