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<section id="rbnet-util-to-log">
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<h1>rbnet.util.to_log<a class="headerlink" href="#rbnet-util-to-log" title="Link to this heading"></a></h1>
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<dl class="py function">
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<dt class="sig sig-object py" id="rbnet.util.to_log">
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<span class="sig-prename descclassname"><span class="pre">rbnet.util.</span></span><span class="sig-name descname"><span class="pre">to_log</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">t</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-12</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/rbnet/util.html#to_log"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#rbnet.util.to_log" title="Link to this definition"></a></dt>
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<dd><p>Transform tensor to log representation by computing <img class="math" src="../_images/math/d9f7031b1eb5d6072d47ba11ede7f0b6a5c6c336.svg" alt="\log(t + \epsilon)"/>.</p>
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<dl class="field-list simple">
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<dt class="field-odd">Parameters<span class="colon">:</span></dt>
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<dd class="field-odd"><ul class="simple">
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<li><p><strong>t</strong> – input tensor to transform</p></li>
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<li><p><strong>eps</strong> – small constant to avoid inf</p></li>
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</ul>
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</dd>
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<dt class="field-even">Returns<span class="colon">:</span></dt>
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<dd class="field-even"><p>log-transformed tensor</p>
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</dd>
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<section id="module-rbnet.autoencoder">
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<span id="rbnet-autoencoder"></span><h1>rbnet.autoencoder<a class="headerlink" href="#module-rbnet.autoencoder" title="Link to this heading"></a></h1>
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<p class="rubric">Classes</p>
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<table class="autosummary longtable docutils align-default">
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<tbody>
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<tr class="row-odd"><td><p><a class="reference internal" href="rbnet.autoencoder.AutoencoderCell.html#rbnet.autoencoder.AutoencoderCell" title="rbnet.autoencoder.AutoencoderCell"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AutoencoderCell</span></code></a>(variable, transition, *args, ...)</p></td>
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<td><p></p></td>
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</tr>
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<tr class="row-even"><td><p><a class="reference internal" href="rbnet.autoencoder.AutoencoderNonTermVar.html#rbnet.autoencoder.AutoencoderNonTermVar" title="rbnet.autoencoder.AutoencoderNonTermVar"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AutoencoderNonTermVar</span></code></a>(dim[, chart_type])</p></td>
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<td><p>A point-wise continuous non-terminal variable of dimensionality <code class="docutils literal notranslate"><span class="pre">dim</span></code>.</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="rbnet.autoencoder.AutoencoderPrior.html#rbnet.autoencoder.AutoencoderPrior" title="rbnet.autoencoder.AutoencoderPrior"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AutoencoderPrior</span></code></a>(*args, **kwargs)</p></td>
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<td><p></p></td>
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</tr>
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<tr class="row-even"><td><p><a class="reference internal" href="rbnet.autoencoder.AutoencoderTransition.html#rbnet.autoencoder.AutoencoderTransition" title="rbnet.autoencoder.AutoencoderTransition"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AutoencoderTransition</span></code></a>(terminal_encoder, ...)</p></td>
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<td><p>An autoencoder transition combining a deterministic binary non-terminal and unary terminal transition.</p></td>
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</tr>
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</tbody>
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</table>
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