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+
+  <section id="diffusion-models-losses-kl-divergence-gaussian-kl">
+<h1>diffusion_models.losses.kl_divergence.gaussian_kl<a class="headerlink" href="#diffusion-models-losses-kl-divergence-gaussian-kl" title="Link to this heading"></a></h1>
+<dl class="py function">
+<dt class="sig sig-object py" id="diffusion_models.losses.kl_divergence.gaussian_kl">
+<span class="sig-prename descclassname"><span class="pre">diffusion_models.losses.kl_divergence.</span></span><span class="sig-name descname"><span class="pre">gaussian_kl</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p_var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q_var</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#diffusion_models.losses.kl_divergence.gaussian_kl" title="Link to this definition"></a></dt>
+<dd><p>Calculate KL Divergence of 2 Gaussian distributions.</p>
+<p>KL divergence between two univariate Gaussians, as derived in [1], with k=1 (dimensionality).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>p_mean</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">Float[Tensor,</span> <span class="pre">'1']</span></code>) – mean value of first distribution</p></li>
+<li><p><strong>p_var</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">Float[Tensor,</span> <span class="pre">'1']</span></code>) – variance value of first distribution</p></li>
+<li><p><strong>q_mean</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">Float[Tensor,</span> <span class="pre">'1']</span></code>) – mean value of second distribution</p></li>
+<li><p><strong>q_var</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">Float[Tensor,</span> <span class="pre">'1']</span></code>) – variance value of second distribution</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>KL divergence of inputs</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>out</p>
+</dd>
+</dl>
+<p class="rubric">References</p>
+<aside class="footnote-list brackets">
+<aside class="footnote brackets" id="id1" role="note">
+<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
+<p><a class="reference external" href="https://mr-easy.github.io/2020-04-16-kl-divergence-between-2-gaussian-distributions/">https://mr-easy.github.io/2020-04-16-kl-divergence-between-2-gaussian-distributions/</a></p>
+</aside>
+</aside>
+</dd></dl>
+
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