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</details></li>
<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>
<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.inv.html">mlx.core.linalg.inv</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="metal.html">Metal</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="nn.html">Neural Networks</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.nn.value_and_grad.html">mlx.nn.value_and_grad</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="nn/module.html">Module</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-l2 has-children"><a class="reference internal" href="nn/layers.html">Layers</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.ALiBi.html">mlx.nn.ALiBi</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.CELU.html">mlx.nn.CELU</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.Conv1d.html">mlx.nn.Conv1d</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.GLU.html">mlx.nn.GLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.GroupNorm.html">mlx.nn.GroupNorm</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.LeakyReLU.html">mlx.nn.LeakyReLU</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.LSTM.html">mlx.nn.LSTM</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.MaxPool1d.html">mlx.nn.MaxPool1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.MaxPool2d.html">mlx.nn.MaxPool2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.Mish.html">mlx.nn.Mish</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.MultiHeadAttention.html">mlx.nn.MultiHeadAttention</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.QuantizedEmbedding.html">mlx.nn.QuantizedEmbedding</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.QuantizedLinear.html">mlx.nn.QuantizedLinear</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.RMSNorm.html">mlx.nn.RMSNorm</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.ReLU.html">mlx.nn.ReLU</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.Softshrink.html">mlx.nn.Softshrink</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.Softsign.html">mlx.nn.Softsign</a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary/mlx.nn.Tanh.html">mlx.nn.Tanh</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="nn/functions.html">Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.elu.html">mlx.nn.elu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.celu.html">mlx.nn.celu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.gelu.html">mlx.nn.gelu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.gelu_approx.html">mlx.nn.gelu_approx</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html">mlx.nn.gelu_fast_approx</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.glu.html">mlx.nn.glu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.hard_shrink.html">mlx.nn.hard_shrink</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.hard_tanh.html">mlx.nn.hard_tanh</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.hardswish.html">mlx.nn.hardswish</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.leaky_relu.html">mlx.nn.leaky_relu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.log_sigmoid.html">mlx.nn.log_sigmoid</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.log_softmax.html">mlx.nn.log_softmax</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.mish.html">mlx.nn.mish</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.prelu.html">mlx.nn.prelu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.relu.html">mlx.nn.relu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.relu6.html">mlx.nn.relu6</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.selu.html">mlx.nn.selu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.sigmoid.html">mlx.nn.sigmoid</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.silu.html">mlx.nn.silu</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.softmax.html">mlx.nn.softmax</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.softmin.html">mlx.nn.softmin</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.softplus.html">mlx.nn.softplus</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.softshrink.html">mlx.nn.softshrink</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.step.html">mlx.nn.step</a></li>
<li class="toctree-l3"><a class="reference internal" href="nn/_autosummary_functions/mlx.nn.tanh.html">mlx.nn.tanh</a></li>
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</details></li>
<li class="toctree-l2 has-children"><a class="reference internal" href="nn/losses.html">Loss 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>Random</h1>
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<section id="random">
<span id="id1"></span><h1>Random<a class="headerlink" href="#random" title="Link to this heading">#</a></h1>
<p>Random sampling functions in MLX use an implicit global PRNG state by default.
However, all function take an optional <code class="docutils literal notranslate"><span class="pre">key</span></code> keyword argument for when more
fine-grained control or explicit state management is needed.</p>
<p>For example, you can generate random numbers with:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">())</span>
</pre></div>
</div>
<p>which will print a sequence of unique pseudo random numbers. Alternatively you
can explicitly set the key:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">key</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">key</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="n">key</span><span class="o">=</span><span class="n">key</span><span class="p">))</span>
</pre></div>
</div>
<p>which will yield the same pseudo random number at each iteration.</p>
<p>Following <a class="reference external" href="https://jax.readthedocs.io/en/latest/jep/263-prng.html">JAX’s PRNG design</a>
we use a splittable version of Threefry, which is a counter-based PRNG.</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.core.random.bernoulli.html#mlx.core.random.bernoulli" title="mlx.core.random.bernoulli"><code class="xref py py-obj docutils literal notranslate"><span class="pre">bernoulli</span></code></a>([p, shape, key, stream])</p></td>
<td><p>Generate Bernoulli random values.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.categorical.html#mlx.core.random.categorical" title="mlx.core.random.categorical"><code class="xref py py-obj docutils literal notranslate"><span class="pre">categorical</span></code></a>(logits[, axis, shape, ...])</p></td>
<td><p>Sample from a categorical distribution.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.gumbel.html#mlx.core.random.gumbel" title="mlx.core.random.gumbel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">gumbel</span></code></a>([shape, dtype, key, stream])</p></td>
<td><p>Sample from the standard Gumbel distribution.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.key.html#mlx.core.random.key" title="mlx.core.random.key"><code class="xref py py-obj docutils literal notranslate"><span class="pre">key</span></code></a>(seed)</p></td>
<td><p>Get a PRNG key from a seed.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.normal.html#mlx.core.random.normal" title="mlx.core.random.normal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">normal</span></code></a>([shape, dtype, loc, scale, key, stream])</p></td>
<td><p>Generate normally distributed random numbers.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.multivariate_normal.html#mlx.core.random.multivariate_normal" title="mlx.core.random.multivariate_normal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">multivariate_normal</span></code></a>(mean, cov[, shape, ...])</p></td>
<td><p>Generate jointly-normal random samples given a mean and covariance.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.randint.html#mlx.core.random.randint" title="mlx.core.random.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a>(low, high[, shape, dtype, key, stream])</p></td>
<td><p>Generate random integers from the given interval.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.seed.html#mlx.core.random.seed" title="mlx.core.random.seed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">seed</span></code></a>(seed)</p></td>
<td><p>Seed the global PRNG.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.split.html#mlx.core.random.split" title="mlx.core.random.split"><code class="xref py py-obj docutils literal notranslate"><span class="pre">split</span></code></a>(key[, num, stream])</p></td>
<td><p>Split a PRNG key into sub keys.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.truncated_normal.html#mlx.core.random.truncated_normal" title="mlx.core.random.truncated_normal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">truncated_normal</span></code></a>(lower, upper[, shape, ...])</p></td>
<td><p>Generate values from a truncated normal distribution.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.uniform.html#mlx.core.random.uniform" title="mlx.core.random.uniform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">uniform</span></code></a>([low, high, shape, dtype, key, stream])</p></td>
<td><p>Generate uniformly distributed random numbers.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.laplace.html#mlx.core.random.laplace" title="mlx.core.random.laplace"><code class="xref py py-obj docutils literal notranslate"><span class="pre">laplace</span></code></a>([shape, dtype, loc, scale, key, stream])</p></td>
<td><p>Sample numbers from a Laplace distribution.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.random.permutation.html#mlx.core.random.permutation" title="mlx.core.random.permutation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">permutation</span></code></a>(x[, axis, key, stream])</p></td>
<td><p>Generate a random permutation or permute the entries of an array.</p></td>
</tr>
</tbody>
</table>
</div>
</section>
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<script defer src="../_static/scripts/bootstrap.js?digest=26a4bc78f4c0ddb94549"></script>
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<footer class="bd-footer">
</footer>
</body>
</html>
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