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docs/build/html/python/linalg.html
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docs/build/html/python/linalg.html
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@@ -8,7 +8,7 @@
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
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<title>Linear Algebra — MLX 0.16.1 documentation</title>
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<title>Linear Algebra — MLX 0.16.2 documentation</title>
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<link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
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<script src="../_static/documentation_options.js?v=179565df"></script>
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<img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.16.1 documentation - Home"/>
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<script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.16.1 documentation - Home"/>`);</script>
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<img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.16.2 documentation - Home"/>
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<script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.16.2 documentation - Home"/>`);</script>
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</a></div>
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</li>
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<li class="toctree-l1 current active has-children"><a class="current reference internal" href="#">Linear Algebra</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-9" name="toctree-checkbox-9" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-9"><i class="fa-solid fa-chevron-down"></i></label><ul>
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<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-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.tri_inv.html">mlx.core.linalg.tri_inv</a></li>
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<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.norm.html">mlx.core.linalg.norm</a></li>
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<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.cholesky.html">mlx.core.linalg.cholesky</a></li>
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<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.cholesky_inv.html">mlx.core.linalg.cholesky_inv</a></li>
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<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.qr.html">mlx.core.linalg.qr</a></li>
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<li class="toctree-l2"><a class="reference internal" href="_autosummary/mlx.core.linalg.svd.html">mlx.core.linalg.svd</a></li>
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</ul>
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@@ -839,12 +841,18 @@ document.write(`
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<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.inv.html#mlx.core.linalg.inv" title="mlx.core.linalg.inv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">inv</span></code></a>(a, *[, stream])</p></td>
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<td><p>Compute the inverse of a square matrix.</p></td>
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</tr>
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<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.norm.html#mlx.core.linalg.norm" title="mlx.core.linalg.norm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">norm</span></code></a>(a, /[, ord, axis, keepdims, stream])</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.tri_inv.html#mlx.core.linalg.tri_inv" title="mlx.core.linalg.tri_inv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tri_inv</span></code></a>(a[, upper, stream])</p></td>
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<td><p>Compute the inverse of a triangular square matrix.</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.norm.html#mlx.core.linalg.norm" title="mlx.core.linalg.norm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">norm</span></code></a>(a, /[, ord, axis, keepdims, stream])</p></td>
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<td><p>Matrix or vector norm.</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.cholesky.html#mlx.core.linalg.cholesky" title="mlx.core.linalg.cholesky"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cholesky</span></code></a>(a[, upper, stream])</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.cholesky.html#mlx.core.linalg.cholesky" title="mlx.core.linalg.cholesky"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cholesky</span></code></a>(a[, upper, stream])</p></td>
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<td><p>Compute the Cholesky decomposition of a real symmetric positive semi-definite matrix.</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.cholesky_inv.html#mlx.core.linalg.cholesky_inv" title="mlx.core.linalg.cholesky_inv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cholesky_inv</span></code></a>(L[, upper, stream])</p></td>
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<td><p>Compute the inverse of a real symmetric positive semi-definite matrix using it's Cholesky decomposition L.</p></td>
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</tr>
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<tr class="row-even"><td><p><a class="reference internal" href="_autosummary/mlx.core.linalg.qr.html#mlx.core.linalg.qr" title="mlx.core.linalg.qr"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qr</span></code></a>(a, *[, stream])</p></td>
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<td><p>The QR factorization of the input matrix.</p></td>
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</tr>
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