Generate Python docs from pytorch/pytorch@8439583

Author: pytorchbot

docs/master/__config__.html

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docs/master/_modules/torch/ao/ns/_numeric_suite.html

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docs/master/_modules/torch/ao/ns/_numeric_suite_fx.html

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     <div class="version">
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docs/master/_modules/torch/ao/ns/fx/utils.html

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     <div class="version">
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docs/master/_modules/torch/ao/quantization/fake_quantize.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
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@@ -1575,6 +1575,44 @@ <h1>Source code for torch.ao.quantization.observer</h1><div class="highlight"><p
         <span class="p">)</span></div>
 
 
+<span class="k">class</span> <span class="nc">FixedQParamsObserver</span><span class="p">(</span><span class="n">ObserverBase</span><span class="p">):</span>
+    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Observer that simulates quantize and dequantize with fixed</span>
+<span class="sd">    quantization parameters in training time. Only per tensor</span>
+<span class="sd">    quantization is supported.</span>
+
+<span class="sd">    Args:</span>
+<span class="sd">        `scale` (float): fixed scale for the observer</span>
+<span class="sd">        `zero_point` (int): fixed zero point for the observer</span>
+<span class="sd">        `dtype`, `qscheme`, `quant_min`, `quant_max`</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+
+    <span class="n">scale</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span>
+    <span class="n">zero_point</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</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">scale</span><span class="p">,</span>
+                 <span class="n">zero_point</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">quint8</span><span class="p">,</span>
+                 <span class="n">qscheme</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">per_tensor_affine</span><span class="p">,</span>
+                 <span class="n">quant_min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
+                 <span class="n">quant_max</span><span class="o">=</span><span class="mi">255</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">FixedQParamsObserver</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">quant_min</span> <span class="o">=</span> <span class="n">quant_min</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">quant_max</span> <span class="o">=</span> <span class="n">quant_max</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">register_buffer</span><span class="p">(</span><span class="s1">&#39;scale&#39;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="n">scale</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">float</span><span class="p">))</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">register_buffer</span><span class="p">(</span><span class="s1">&#39;zero_point&#39;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="n">zero_point</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">int</span><span class="p">))</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="n">dtype</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span> <span class="o">=</span> <span class="n">qscheme</span>
+
+    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
+        <span class="k">return</span> <span class="n">X</span>
+
+    <span class="nd">@torch</span><span class="o">.</span><span class="n">jit</span><span class="o">.</span><span class="n">export</span>
+    <span class="k">def</span> <span class="nf">calculate_qparams</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">scale</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">zero_point</span>
+
+
 <div class="viewcode-block" id="PlaceholderObserver"><a class="viewcode-back" href="../../../../generated/torch.quantization.observer.PlaceholderObserver.html#torch.quantization.fake_quantize.PlaceholderObserver">[docs]</a><span class="k">class</span> <span class="nc">PlaceholderObserver</span><span class="p">(</span><span class="n">ObserverBase</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Observer that doesn&#39;t do anything and just passes its configuration to the</span>
@@ -1798,6 +1836,16 @@ <h1>Source code for torch.ao.quantization.observer</h1><div class="highlight"><p
 <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">Default observer for a floating point zero-point and 4 bit activations.</span>
 <span class="sd">&quot;&quot;&quot;</span>
+
+<span class="c1"># TODO(future PR): remove these defaults and enforce activation functions</span>
+<span class="c1"># to explicitly specify their output range</span>
+<span class="n">default_symmetric_fixed_qparams_observer</span> <span class="o">=</span> <span class="n">FixedQParamsObserver</span><span class="o">.</span><span class="n">with_args</span><span class="p">(</span>
+    <span class="n">scale</span><span class="o">=</span><span class="mf">2.0</span> <span class="o">/</span> <span class="mf">256.0</span><span class="p">,</span> <span class="n">zero_point</span><span class="o">=</span><span class="mi">128</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">quint8</span><span class="p">,</span> <span class="n">quant_min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">quant_max</span><span class="o">=</span><span class="mi">255</span><span class="p">)</span>
+<span class="n">default_affine_fixed_qparams_observer</span> <span class="o">=</span> <span class="n">FixedQParamsObserver</span><span class="o">.</span><span class="n">with_args</span><span class="p">(</span>
+    <span class="n">scale</span><span class="o">=</span><span class="mf">1.0</span> <span class="o">/</span> <span class="mf">256.0</span><span class="p">,</span> <span class="n">zero_point</span><span class="o">=</span><span class="mi">0</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">quint8</span><span class="p">,</span> <span class="n">quant_min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">quant_max</span><span class="o">=</span><span class="mi">255</span><span class="p">)</span>
+<span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">Default observers for fixed qparams operations.</span>
+<span class="sd">&quot;&quot;&quot;</span>
 </pre></div>
 
              </article>

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     <div class="version">
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@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gite42361b ) &#x25BC</a>
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     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git8439583 ) &#x25BC</a>
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@@ -524,7 +524,7 @@ <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="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span></div>
 
 
-<span class="k">class</span> <span class="nc">enable_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
+<div class="viewcode-block" id="enable_grad"><a class="viewcode-back" href="../../../generated/torch.enable_grad.html#torch.enable_grad">[docs]</a><span class="k">class</span> <span class="nc">enable_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 enables gradient calculation.</span>
 
 <span class="sd">    Enables gradient calculation, if it has been disabled via :class:`~no_grad`</span>
@@ -564,7 +564,7 @@ <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="kc">True</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">_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="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></div>
 
 
 <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="nb">object</span><span class="p">):</span>

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+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git8439583 ) &#x25BC</a>
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docs/master/_modules/torch/autograd/profiler.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gite42361b ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git8439583 ) &#x25BC</a>
     </div>