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<li class="toctree-l1 has-children"><a class="reference internal" href="../linalg.html">Linear Algebra</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 current active has-children"><a class="reference internal" href="../nn.html">Neural Networks</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul class="current">
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<li class="toctree-l2 current active has-children"><a class="current reference internal" href="#">Module</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2 has-children"><a class="reference internal" href="functions.html">Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<h1>Module</h1>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#mlx.nn.Module"><code class="docutils literal notranslate"><span class="pre">Module</span></code></a></li>
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<section id="module">
<h1>Module<a class="headerlink" href="#module" title="Link to this heading">#</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="mlx.nn.Module">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Module</span></span><a class="headerlink" href="#mlx.nn.Module" title="Link to this definition">#</a></dt>
<dd><p>Base class for building neural networks with MLX.</p>
<p>All the layers provided in <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.nn.layers</span></code> subclass this class and
your models should do the same.</p>
<p>A <code class="docutils literal notranslate"><span class="pre">Module</span></code> can contain other <code class="docutils literal notranslate"><span class="pre">Module</span></code> instances or <a class="reference internal" href="../_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a>
instances in arbitrary nesting of python lists or dicts. The <code class="docutils literal notranslate"><span class="pre">Module</span></code>
then allows recursively extracting all the <a class="reference internal" href="../_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a> instances
using <a class="reference internal" href="_autosummary/mlx.nn.Module.parameters.html#mlx.nn.Module.parameters" title="mlx.nn.Module.parameters"><code class="xref py py-meth docutils literal notranslate"><span class="pre">mlx.nn.Module.parameters()</span></code></a>.</p>
<p>In addition, the <code class="docutils literal notranslate"><span class="pre">Module</span></code> has the concept of trainable and non trainable
parameters (called “frozen”). When using <a class="reference internal" href="../_autosummary/mlx.nn.value_and_grad.html#mlx.nn.value_and_grad" title="mlx.nn.value_and_grad"><code class="xref py py-func docutils literal notranslate"><span class="pre">mlx.nn.value_and_grad()</span></code></a>
the gradients are returned only with respect to the trainable parameters.
All arrays in a module are trainable unless they are added in the “frozen”
set by calling <a class="reference internal" href="_autosummary/mlx.nn.Module.freeze.html#mlx.nn.Module.freeze" title="mlx.nn.Module.freeze"><code class="xref py py-meth docutils literal notranslate"><span class="pre">freeze()</span></code></a>.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">mlx.core</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">mx</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">mlx.nn</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">nn</span>
<span class="k">class</span><span class="w"> </span><span class="nc">MyMLP</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_dims</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">hidden_dims</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">in_proj</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">hidden_dims</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">out_proj</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">hidden_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">)</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">in_proj</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">maximum</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">out_proj</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">MyMLP</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="c1"># All the model parameters are created but since MLX is lazy by</span>
<span class="c1"># default, they are not evaluated yet. Calling `mx.eval` actually</span>
<span class="c1"># allocates memory and initializes the parameters.</span>
<span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">())</span>
<span class="c1"># Setting a parameter to a new value is as simply as accessing that</span>
<span class="c1"># parameter and assigning a new array to it.</span>
<span class="n">model</span><span class="o">.</span><span class="n">in_proj</span><span class="o">.</span><span class="n">weight</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">in_proj</span><span class="o">.</span><span class="n">weight</span> <span class="o">*</span> <span class="mi">2</span>
<span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">())</span>
</pre></div>
</div>
<p class="rubric">Attributes</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.training.html#mlx.nn.Module.training" title="mlx.nn.Module.training"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.training</span></code></a></p></td>
<td><p>Boolean indicating if the model is in training mode.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.state.html#mlx.nn.Module.state" title="mlx.nn.Module.state"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.state</span></code></a></p></td>
<td><p>The module's state dictionary</p></td>
</tr>
</tbody>
</table>
</div>
<p class="rubric">Methods</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.apply.html#mlx.nn.Module.apply" title="mlx.nn.Module.apply"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.apply</span></code></a>(map_fn[, filter_fn])</p></td>
<td><p>Map all the parameters using the provided <code class="docutils literal notranslate"><span class="pre">map_fn</span></code> and immediately update the module with the mapped parameters.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.apply_to_modules.html#mlx.nn.Module.apply_to_modules" title="mlx.nn.Module.apply_to_modules"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.apply_to_modules</span></code></a>(apply_fn)</p></td>
<td><p>Apply a function to all the modules in this instance (including this instance).</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.children.html#mlx.nn.Module.children" title="mlx.nn.Module.children"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.children</span></code></a>()</p></td>
<td><p>Return the direct descendants of this Module instance.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.eval.html#mlx.nn.Module.eval" title="mlx.nn.Module.eval"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.eval</span></code></a>()</p></td>
<td><p>Set the model to evaluation mode.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.filter_and_map.html#mlx.nn.Module.filter_and_map" title="mlx.nn.Module.filter_and_map"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.filter_and_map</span></code></a>(filter_fn[, map_fn, ...])</p></td>
<td><p>Recursively filter the contents of the module using <code class="docutils literal notranslate"><span class="pre">filter_fn</span></code>, namely only select keys and values where <code class="docutils literal notranslate"><span class="pre">filter_fn</span></code> returns true.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.freeze.html#mlx.nn.Module.freeze" title="mlx.nn.Module.freeze"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.freeze</span></code></a>(*[, recurse, keys, strict])</p></td>
<td><p>Freeze the Module's parameters or some of them.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.leaf_modules.html#mlx.nn.Module.leaf_modules" title="mlx.nn.Module.leaf_modules"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.leaf_modules</span></code></a>()</p></td>
<td><p>Return the submodules that do not contain other modules.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.load_weights.html#mlx.nn.Module.load_weights" title="mlx.nn.Module.load_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.load_weights</span></code></a>(file_or_weights[, strict])</p></td>
<td><p>Update the model's weights from a <code class="docutils literal notranslate"><span class="pre">.npz</span></code>, a <code class="docutils literal notranslate"><span class="pre">.safetensors</span></code> file, or a list.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.modules.html#mlx.nn.Module.modules" title="mlx.nn.Module.modules"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.modules</span></code></a>()</p></td>
<td><p>Return a list with all the modules in this instance.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.named_modules.html#mlx.nn.Module.named_modules" title="mlx.nn.Module.named_modules"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.named_modules</span></code></a>()</p></td>
<td><p>Return a list with all the modules in this instance and their name with dot notation.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.parameters.html#mlx.nn.Module.parameters" title="mlx.nn.Module.parameters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.parameters</span></code></a>()</p></td>
<td><p>Recursively return all the <a class="reference internal" href="../_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a> members of this Module as a dict of dicts and lists.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.save_weights.html#mlx.nn.Module.save_weights" title="mlx.nn.Module.save_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.save_weights</span></code></a>(file)</p></td>
<td><p>Save the model's weights to a file.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.set_dtype.html#mlx.nn.Module.set_dtype" title="mlx.nn.Module.set_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.set_dtype</span></code></a>(dtype[, predicate])</p></td>
<td><p>Set the dtype of the module's parameters.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.train.html#mlx.nn.Module.train" title="mlx.nn.Module.train"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.train</span></code></a>([mode])</p></td>
<td><p>Set the model in or out of training mode.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.trainable_parameters.html#mlx.nn.Module.trainable_parameters" title="mlx.nn.Module.trainable_parameters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.trainable_parameters</span></code></a>()</p></td>
<td><p>Recursively return all the non frozen <a class="reference internal" href="../_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a> members of this Module as a dict of dicts and lists.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.unfreeze.html#mlx.nn.Module.unfreeze" title="mlx.nn.Module.unfreeze"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.unfreeze</span></code></a>(*[, recurse, keys, strict])</p></td>
<td><p>Unfreeze the Module's parameters or some of them.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.update.html#mlx.nn.Module.update" title="mlx.nn.Module.update"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.update</span></code></a>(parameters)</p></td>
<td><p>Replace the parameters of this Module with the provided ones in the dict of dicts and lists.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.nn.Module.update_modules.html#mlx.nn.Module.update_modules" title="mlx.nn.Module.update_modules"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Module.update_modules</span></code></a>(modules)</p></td>
<td><p>Replace the child modules of this <a class="reference internal" href="#mlx.nn.Module" title="mlx.nn.Module"><code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code></a> instance with the provided ones in the dict of dicts and lists.</p></td>
</tr>
</tbody>
</table>
</div>
</dd></dl>
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