<divclass="platform-hinted "data-platform-hinted="data-platform-hinted"><divclass="content sourceset-dependent-content"data-active=""data-togglable=":kmath-tensors:dokkaHtmlPartial/commonMain"><divclass="symbol monospace"><spanclass="token keyword">abstract </span><spanclass="token keyword"></span><spanclass="token keyword">fun </span><ahref="svd.html"><spanclass="token function">svd</span></a><spanclass="token punctuation">(</span><spanclass="parameters "><spanclass="parameter ">structureND<spanclass="token operator">: </span><ahref="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><spanclass="token operator"><</span><spanclass="token keyword"></span><ahref="index.html">T</a><spanclass="token operator">></span></span></span><spanclass="token punctuation">)</span><spanclass="token operator">: </span><ahref="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-triple/index.html">Triple</a><spanclass="token operator"><</span><spanclass="token keyword"></span><ahref="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><spanclass="token operator"><</span><spanclass="token keyword"></span><ahref="index.html">T</a><spanclass="token operator">></span><spanclass="token punctuation">, </span><spanclass="token keyword"></span><ahref="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><spanclass="token operator"><</span><spanclass="token keyword"></span><ahref="index.html">T</a><spanclass="token operator">></span><spanclass="token punctuation">, </span><spanclass="token keyword"></span><ahref="../../../kmath-core/space.kscience.kmath.nd/-structure-n-d/index.html">StructureND</a><spanclass="token operator"><</span><spanclass="token keyword"></span><ahref="index.html">T</a><spanclass="token operator">></span><spanclass="token operator">></span><spanclass="clearfix"><spanclass="floating-right">(<ahref="https://github.com/SciProgCentre/kmath/tree/master/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt#L94">source</a>)</span></span></div><pclass="paragraph">Singular Value Decomposition.</p><pclass="paragraph">Computes the singular value decomposition of either a matrix or batch of matrices <codeclass="lang-kotlin">input</code>. The singular value decomposition is represented as a triple <codeclass="lang-kotlin">Triple(U, S, V)</code>, such that <codeclass="lang-kotlin">input = U dot diagonalEmbedding(S) dot VH</code>, where <codeclass="lang-kotlin">VH</code> is the conjugate transpose of V. If <codeclass="lang-kotlin">input</code> is a batch of tensors, then <codeclass="lang-kotlin">U</code>, <codeclass="lang-kotlin">S</code>, and <codeclass="lang-kotlin">VH</code> are also batched with the same batch dimensions as <codeclass="lang-kotlin">input</code>. For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd</p><spanclass="kdoc-tag"><h4class="">Receiver</h4><pclass="paragraph">the <codeclass="lang-kotlin">input</code>.</p></span><spanclass="kdoc-tag"><h4class="">Return</h4><pclass="paragraph">triple <codeclass="lang-kotlin">Triple(U, S, V)</code>.</p></span></div></div>