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<title>mlx.nn.GroupNorm — MLX 0.18.0 documentation</title>
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<title>mlx.nn.GroupNorm — MLX 0.18.1 documentation</title>
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<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.repeat.html">mlx.core.repeat</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.random.truncated_normal.html">mlx.core.random.truncated_normal</a></li>
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@@ -872,7 +874,7 @@ document.write(`
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<h1>mlx.nn.GroupNorm<a class="headerlink" href="#mlx-nn-groupnorm" title="Link to this heading">#</a></h1>
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<dl class="py class">
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<dt class="sig sig-object py" id="mlx.nn.GroupNorm">
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<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">GroupNorm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_groups</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">affine</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pytorch_compatible</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#mlx.nn.GroupNorm" title="Link to this definition">#</a></dt>
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<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">GroupNorm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_groups</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><span class="pre">float</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">affine</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pytorch_compatible</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#mlx.nn.GroupNorm" title="Link to this definition">#</a></dt>
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<dd><p>Applies Group Normalization [1] to the inputs.</p>
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<p>Computes the same normalization as layer norm, namely</p>
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<div class="math notranslate nohighlight">
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@@ -888,12 +890,12 @@ that precede it (except the first) are considered the spatial dimensions.</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>num_groups</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Number of groups to separate the features into</p></li>
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<li><p><strong>dims</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – The feature dimensions of the input to normalize over</p></li>
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<li><p><strong>eps</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – A small additive constant for numerical stability</p></li>
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<li><p><strong>affine</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – If True learn an affine transform to apply after the
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<li><p><strong>num_groups</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><em>int</em></a>) – Number of groups to separate the features into</p></li>
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<li><p><strong>dims</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><em>int</em></a>) – The feature dimensions of the input to normalize over</p></li>
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<li><p><strong>eps</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><em>float</em></a>) – A small additive constant for numerical stability</p></li>
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<li><p><strong>affine</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a>) – If True learn an affine transform to apply after the
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normalization.</p></li>
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<li><p><strong>pytorch_compatible</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – If True perform the group normalization in
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<li><p><strong>pytorch_compatible</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a>) – If True perform the group normalization in
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the same order/grouping as PyTorch.</p></li>
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</ul>
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</dd>
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