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               <p class="caption"><span class="caption-text">Notes</span></p>
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 <li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">Automatic Mixed Precision examples</a></li>
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   <div class="section" id="module-torch.autograd">
 <span id="automatic-differentiation-package-torch-autograd"></span><h1>Automatic differentiation package - torch.autograd<a class="headerlink" href="#module-torch.autograd" title="Permalink to this headline">¶</a></h1>
 <p><code class="docutils literal notranslate"><span class="pre">torch.autograd</span></code> provides classes and functions implementing automatic
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 <span id="functional-api"></span><h2>Functional higher level API<a class="headerlink" href="#functional-higher-level-api" title="Permalink to this headline">¶</a></h2>
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 <p>This section contains the higher level API for the autograd that builds on the basic API above
 and allows you to compute jacobians, hessians, etc.</p>
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