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<h1 class="cover"><span><span>cholesky</span></span></h1>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-dependent-content" data-active="" data-togglable=":kmath-tensors:dokkaHtmlPartial/commonMain"><div class="symbol monospace"><span class="token keyword">abstract </span><span class="token keyword"></span><span class="token keyword">fun </span><a href="cholesky.html"><span class="token function">cholesky</span></a><span class="token punctuation">(</span><span class="parameters "><span class="parameter ">structureND<span class="token operator">: </span><a href="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="index.html">T</a><span class="token operator">&gt;</span></span></span><span class="token punctuation">)</span><span class="token operator">: </span><a href="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="index.html">T</a><span class="token operator">&gt;</span><span class="clearfix"><span class="floating-right">(<a href="https://github.com/SciProgCentre/kmath/tree/master/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt#L50">source</a>)</span></span></div><p class="paragraph">Cholesky decomposition.</p><p class="paragraph">Computes the Cholesky decomposition of a Hermitian (or symmetric for real-valued matrices) positive-definite matrix or the Cholesky decompositions for a batch of such matrices. Each decomposition has the form: Given a tensor <code class="lang-kotlin">input</code>, return the tensor <code class="lang-kotlin">L</code> satisfying <code class="lang-kotlin">input = L dot LH</code>, where <code class="lang-kotlin">L</code> is a lower-triangular matrix and <code class="lang-kotlin">LH</code> is the conjugate transpose of <code class="lang-kotlin">L</code>, which is just a transpose for the case of real-valued input matrices. For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.cholesky</p><span class="kdoc-tag"><h4 class="">Receiver</h4><p class="paragraph">the <code class="lang-kotlin">input</code>.</p></span><span class="kdoc-tag"><h4 class="">Return</h4><p class="paragraph">the batch of <code class="lang-kotlin">L</code> matrices.</p></span></div></div>
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