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<title>mlx.optimizers.SGD — MLX 0.0.4 documentation</title>
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<title>mlx.optimizers.SGD — MLX 0.0.5 documentation</title>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../../quick_start.html">Quick Start Guide</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.gelu_approx.html">mlx.nn.gelu_approx</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.relu.html">mlx.nn.relu</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html">mlx.nn.losses.binary_cross_entropy</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.losses.l1_loss.html">mlx.nn.losses.l1_loss</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.losses.mse_loss.html">mlx.nn.losses.mse_loss</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.losses.nll_loss.html">mlx.nn.losses.nll_loss</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../_autosummary_functions/mlx.nn.losses.kl_div_loss.html">mlx.nn.losses.kl_div_loss</a></li>
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</ul>
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<li class="toctree-l1 current active has-children"><a class="reference internal" href="../optimizers.html">Optimizers</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-8" name="toctree-checkbox-8" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-8"><i class="fa-solid fa-chevron-down"></i></label><ul class="current">
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<h1>mlx.optimizers.SGD<a class="headerlink" href="#mlx-optimizers-sgd" title="Permalink 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.optimizers.SGD">
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<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">mlx.optimizers.</span></span><span class="sig-name descname"><span class="pre">SGD</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">learning_rate</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></em>, <em class="sig-param"><span class="n"><span class="pre">momentum</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">0.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#mlx.optimizers.SGD" title="Permalink 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-prename descclassname"><span class="pre">mlx.optimizers.</span></span><span class="sig-name descname"><span class="pre">SGD</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">learning_rate</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></em>, <em class="sig-param"><span class="n"><span class="pre">momentum</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">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weight_decay</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">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dampening</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">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nesterov</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.optimizers.SGD" title="Permalink to this definition">#</a></dt>
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<dd><p>Stochastic gradient descent optimizer.</p>
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<p>Updates a parameter <span class="math notranslate nohighlight">\(w\)</span> with a gradient <span class="math notranslate nohighlight">\(g\)</span> as follows</p>
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<div class="math notranslate nohighlight">
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\[\begin{split}v_{t+1} &= \mu v_t + (1 - \mu) g_t \\
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\[\begin{split}v_{t+1} &= \mu v_t + g_t \\
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w_{t+1} &= w_t - \lambda v_{t+1}\end{split}\]</div>
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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>learning_rate</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – The learning <span class="math notranslate nohighlight">\(\lambda\)</span> for the update</p></li>
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<li><p><strong>momentum</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – The momentum strength <span class="math notranslate nohighlight">\(\mu\)</span></p></li>
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<li><p><strong>momentum</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – The momentum strength <span class="math notranslate nohighlight">\(\mu\)</span> (default: 0)</p></li>
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<li><p><strong>weight_decay</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – The weight decay (L2 penalty) (default: 0)</p></li>
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<li><p><strong>dampening</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – Dampening for momentum <span class="math notranslate nohighlight">\(\tau\)</span> (default: 0)</p></li>
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<li><p><strong>nesterov</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Enables Nesterov momentum (default: False)</p></li>
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</ul>
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</dd>
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</dl>
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<p class="rubric">Methods</p>
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<table class="autosummary longtable table autosummary">
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<tbody>
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<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code>(learning_rate[, momentum])</p></td>
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<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code>(learning_rate[, momentum, ...])</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><code class="xref py py-obj docutils literal notranslate"><span class="pre">apply_single</span></code>(gradient, parameter, state)</p></td>
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