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<span class="sd"> There are other circumstances where CUDA graphs are not applicable; use TORCH_LOG=perf_hints</span>
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<span class="k">def</span> <span class="nf">add_relu</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="n">Tensor</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">r</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">r</span>
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<span class="w"> </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Operation equivalent to ``torch.matmul(Tensor, Tensor)``&quot;&quot;&quot;</span>
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<span class="k">def</span> <span class="nf">matmul</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="n">Tensor</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
596+
<span class="n">r</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">r</span></div>
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<div class="viewcode-block" id="QFunctional"><a class="viewcode-back" href="../../../../../../generated/torch.ao.nn.quantized.QFunctional.html#torch.ao.nn.quantized.QFunctional">[docs]</a><span class="k">class</span> <span class="nc">QFunctional</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">Module</span><span class="p">):</span>
@@ -679,6 +690,13 @@ <h1>Source code for torch.ao.nn.quantized.modules.functional_modules</h1><div cl
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<span class="n">r</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">activation_post_process</span><span class="p">(</span><span class="n">r</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">r</span>
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693+
<span class="w"> </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Operation equivalent to ``torch.ops.quantized.matmul(Tensor, Tensor)``&quot;&quot;&quot;</span>
694+
<span class="k">def</span> <span class="nf">matmul</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="n">Tensor</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
695+
<span class="n">r</span> <span class="o">=</span> <span class="n">ops</span><span class="o">.</span><span class="n">quantized</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">,</span> <span class="n">zero_point</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">zero_point</span><span class="p">)</span>
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<span class="c1"># Note: this operation is not observed because the observation is not</span>
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<span class="c1"># needed for the quantized op.</span>
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<span class="k">return</span> <span class="n">r</span>
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<span class="nd">@classmethod</span>
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<span class="k">def</span> <span class="nf">from_float</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">mod</span><span class="p">):</span>
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<span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">mod</span><span class="p">)</span> <span class="o">==</span> <span class="n">FloatFunctional</span><span class="p">,</span>\

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