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<li class="toctree-l1 current active has-children"><a class="reference internal" href="../quantization.html">Quantization</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul class="current">
<li class="toctree-l2 current active has-children"><a class="reference internal" href="../quantization-support.html">Quantization API Reference</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul class="current">
<li class="toctree-l3"><a class="reference internal" href="torch.ao.quantization.quantize.html">quantize</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.quantization.qconfig.per_channel_dynamic_qconfig.html">per_channel_dynamic_qconfig</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.quantization.qconfig.default_qat_qconfig.html">default_qat_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.quantization.qconfig.default_weight_only_qconfig.html">default_weight_only_qconfig</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.quantization.qconfig.default_qat_qconfig_v2.html">default_qat_qconfig_v2</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvReLU1d.html">ConvReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvReLU3d.html">ConvReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.LinearReLU.html">LinearReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBn1d.html">ConvBn1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBn2d.html">ConvBn2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBn3d.html">ConvBn3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBnReLU1d.html">ConvBnReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBnReLU2d.html">ConvBnReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.ConvBnReLU3d.html">ConvBnReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.BNReLU2d.html">BNReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.BNReLU3d.html">BNReLU3d</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBn1d.html">ConvBn1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBnReLU1d.html">ConvBnReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBn2d.html">ConvBn2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBnReLU2d.html">ConvBnReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBn3d.html">ConvBn3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvBnReLU3d.html">ConvBnReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.ConvReLU3d.html">ConvReLU3d</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.qat.freeze_bn_stats.html">freeze_bn_stats</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.BNReLU2d.html">BNReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.BNReLU3d.html">BNReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.ConvReLU1d.html">ConvReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.ConvReLU3d.html">ConvReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.intrinsic.quantized.LinearReLU.html">LinearReLU</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.qat.dynamic.Linear.html">Linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.quantized.ReLU6.html">ReLU6</a></li>
<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.quantized.Hardswish.html">Hardswish</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.quantized.functional.conv2d.html">conv2d</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.quantized.functional.interpolate.html">interpolate</a></li>
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<li class="toctree-l3"><a class="reference internal" href="torch.ao.nn.quantizable.LSTM.html">LSTM</a></li>
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</ul>
</details></li>
<li class="toctree-l2"><a class="reference internal" href="../quantization-backend-configuration.html">Quantization Backend Configuration</a></li>
<li class="toctree-l2"><a class="reference internal" href="../quantization-accuracy-debugging.html">Quantization Accuracy Debugging</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="../rpc.html">Distributed RPC Framework</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="../rpc/rref.html">Remote Reference Protocol</a></li>
<li class="toctree-l2"><a class="reference internal" href="../rpc/distributed_autograd.html">Distributed Autograd Design</a></li>
</ul>
</details></li>
<li class="toctree-l1"><a class="reference internal" href="../random.html">torch.random</a></li>
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<div class="section" id="fuse-modules">
<h1>fuse_modules<a class="headerlink" href="#fuse-modules" title="Permalink to this heading">#</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="torch.ao.quantization.fuse_modules.fuse_modules">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torch.ao.quantization.fuse_modules.</span></span><span class="sig-name descname"><span class="pre">fuse_modules</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">modules_to_fuse</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace=False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fuser_func=<function</span> <span class="pre">fuse_known_modules></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fuse_custom_config_dict=None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/8dbe1ff34b8d4e2ef9bc2334069782b53d91678f/torch/ao/quantization/fuse_modules.py#L130"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.ao.quantization.fuse_modules.fuse_modules" title="Permalink to this definition">#</a></dt>
<dd><p>Fuse a list of modules into a single module.</p>
<p>Fuses only the following sequence of modules:
conv, bn
conv, bn, relu
conv, relu
linear, relu
bn, relu
All other sequences are left unchanged.
For these sequences, replaces the first item in the list
with the fused module, replacing the rest of the modules
with identity.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>model</strong> – Model containing the modules to be fused</p></li>
<li><p><strong>modules_to_fuse</strong> – list of list of module names to fuse. Can also be a list
of strings if there is only a single list of modules to fuse.</p></li>
<li><p><strong>inplace</strong> – bool specifying if fusion happens in place on the model, by default
a new model is returned</p></li>
<li><p><strong>fuser_func</strong> – Function that takes in a list of modules and outputs a list of fused modules
of the same length. For example,
fuser_func([convModule, BNModule]) returns the list [ConvBNModule, nn.Identity()]
Defaults to torch.ao.quantization.fuse_known_modules</p></li>
<li><p><strong>fuse_custom_config_dict</strong> – custom configuration for fusion</p></li>
</ul>
</dd>
</dl>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Example of fuse_custom_config_dict</span>
<span class="n">fuse_custom_config_dict</span> <span class="o">=</span> <span class="p">{</span>
<span class="c1"># Additional fuser_method mapping</span>
<span class="s2">"additional_fuser_method_mapping"</span><span class="p">:</span> <span class="p">{</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">Conv2d</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">BatchNorm2d</span><span class="p">):</span> <span class="n">fuse_conv_bn</span>
<span class="p">},</span>
<span class="p">}</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>model with fused modules. A new copy is created if inplace=True.</p>
</dd>
</dl>
<p>Examples:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">m</span> <span class="o">=</span> <span class="n">M</span><span class="p">()</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
<span class="gp">>>> </span><span class="c1"># m is a module containing the sub-modules below</span>
<span class="gp">>>> </span><span class="n">modules_to_fuse</span> <span class="o">=</span> <span class="p">[</span> <span class="p">[</span><span class="s1">'conv1'</span><span class="p">,</span> <span class="s1">'bn1'</span><span class="p">,</span> <span class="s1">'relu1'</span><span class="p">],</span> <span class="p">[</span><span class="s1">'submodule.conv'</span><span class="p">,</span> <span class="s1">'submodule.relu'</span><span class="p">]]</span>
<span class="gp">>>> </span><span class="n">fused_m</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ao</span><span class="o">.</span><span class="n">quantization</span><span class="o">.</span><span class="n">fuse_modules</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">modules_to_fuse</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">output</span> <span class="o">=</span> <span class="n">fused_m</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">m</span> <span class="o">=</span> <span class="n">M</span><span class="p">()</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
<span class="gp">>>> </span><span class="c1"># Alternately provide a single list of modules to fuse</span>
<span class="gp">>>> </span><span class="n">modules_to_fuse</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'conv1'</span><span class="p">,</span> <span class="s1">'bn1'</span><span class="p">,</span> <span class="s1">'relu1'</span><span class="p">]</span>
<span class="gp">>>> </span><span class="n">fused_m</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ao</span><span class="o">.</span><span class="n">quantization</span><span class="o">.</span><span class="n">fuse_modules</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">modules_to_fuse</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">output</span> <span class="o">=</span> <span class="n">fused_m</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span>
</pre></div>
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