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<h1 class="cover"><span><span>svd</span></span></h1>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-depenent-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="../../../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="token punctuation">.</span><a href="svd.html"><span class="token function">svd</span></a><span class="token punctuation">(</span><span class="token punctuation">)</span><span class="token operator">: </span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-triple/index.html">Triple</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="../index.html#-1680022905%2FClasslikes%2F-1345790395">Tensor</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="token punctuation">, </span><span class="token keyword"></span><a href="../index.html#-1680022905%2FClasslikes%2F-1345790395">Tensor</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="token punctuation">, </span><span class="token keyword"></span><a href="../index.html#-1680022905%2FClasslikes%2F-1345790395">Tensor</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="token operator">&gt;</span><span class="top-right-position"><span class="copy-icon"></span><div class="copy-popup-wrapper popup-to-left"><span class="copy-popup-icon"></span><span>Content copied to clipboard</span></div></span></div><p class="paragraph">Singular Value Decomposition.</p><p class="paragraph">Computes the singular value decomposition of either a matrix or batch of matrices <code class="lang-kotlin">input</code>. The singular value decomposition is represented as a triple <code class="lang-kotlin">Triple(U, S, V)</code>, such that <code class="lang-kotlin">input = U dot diagonalEmbedding(S) dot VH</code>, where <code class="lang-kotlin">VH</code> is the conjugate transpose of V. If <code class="lang-kotlin">input</code> is a batch of tensors, then <code class="lang-kotlin">U</code>, <code class="lang-kotlin">S</code>, and <code class="lang-kotlin">VH</code> are also batched with the same batch dimensions as <code class="lang-kotlin">input</code>. For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd</p><h4 class="">Receiver</h4><p class="paragraph">the <code class="lang-kotlin">input</code>.</p><h4 class="">Return</h4><p class="paragraph">triple <code class="lang-kotlin">Triple(U, S, V)</code>.</p></div></div>
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<h2 class="">Sources</h2>
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