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486 lines
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<title>Class Tensor
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<div class="article row grid-right">
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<div class="col-md-10">
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<article class="content wrap" id="_content" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor">
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<h1 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor" class="text-break">Class Tensor
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</h1>
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<div class="markdown level0 summary"><p>Various methods for creating and manipulating Tensor<T></p>
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</div>
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<div class="markdown level0 conceptual"></div>
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<div class="inheritance">
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<h5>Inheritance</h5>
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<div class="level0"><span class="xref">System.Object</span></div>
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<div class="level1"><span class="xref">Tensor</span></div>
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</div>
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<div class="inheritedMembers">
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<h5>Inherited Members</h5>
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<div>
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<span class="xref">System.Object.ToString()</span>
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<div>
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<span class="xref">System.Object.Equals(System.Object)</span>
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</div>
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<div>
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<span class="xref">System.Object.Equals(System.Object, System.Object)</span>
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<span class="xref">System.Object.ReferenceEquals(System.Object, System.Object)</span>
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<span class="xref">System.Object.GetHashCode()</span>
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<span class="xref">System.Object.MemberwiseClone()</span>
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<h6><strong>Namespace</strong>: <a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.html">Microsoft.ML.OnnxRuntime.Tensors</a></h6>
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<h6><strong>Assembly</strong>: cs.temp.dll.dll</h6>
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<h5 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_syntax">Syntax</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static class Tensor</code></pre>
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</div>
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<h3 id="methods">Methods
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</h3>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateFromDiagonal_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateFromDiagonal*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateFromDiagonal__1_Microsoft_ML_OnnxRuntime_Tensors_Tensor___0__" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateFromDiagonal``1(Microsoft.ML.OnnxRuntime.Tensors.Tensor{``0})">CreateFromDiagonal<T>(Tensor<T>)</h4>
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<div class="markdown level1 summary"><p>Creates a n+1-rank tensor using the specified n-rank diagonal. Values not on the diagonal will be filled with zeros.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static Tensor<T> CreateFromDiagonal<T>(Tensor<T> diagonal)</code></pre>
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</div>
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<h5 class="parameters">Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><span class="parametername">diagonal</span></td>
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<td><p>Tensor representing the diagonal to build the new tensor from.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="returns">Returns</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><p>A new tensor of the same layout and order as <code data-dev-comment-type="paramref" class="paramref">diagonal</code> of one higher rank, with the values of <code data-dev-comment-type="paramref" class="paramref">diagonal</code> along the diagonal and zeros elsewhere.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="typeParameters">Type Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="parametername">T</span></td>
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<td><p>type contained within the Tensor. Typically a value type such as int, double, float, etc.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateFromDiagonal_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateFromDiagonal*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateFromDiagonal__1_Microsoft_ML_OnnxRuntime_Tensors_Tensor___0__System_Int32_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateFromDiagonal``1(Microsoft.ML.OnnxRuntime.Tensors.Tensor{``0},System.Int32)">CreateFromDiagonal<T>(Tensor<T>, Int32)</h4>
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<div class="markdown level1 summary"><p>Creates a n+1-dimension tensor using the specified n-dimension diagonal at the specified offset
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from the center. Values not on the diagonal will be filled with zeros.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static Tensor<T> CreateFromDiagonal<T>(Tensor<T> diagonal, int offset)</code></pre>
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</div>
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<h5 class="parameters">Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><span class="parametername">diagonal</span></td>
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<td><p>Tensor representing the diagonal to build the new tensor from.</p>
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</td>
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</tr>
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<tr>
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<td><span class="xref">System.Int32</span></td>
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<td><span class="parametername">offset</span></td>
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<td><p>Offset of diagonal to set in returned tensor. 0 for the main diagonal,
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less than zero for diagonals below, greater than zero from diagonals above.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="returns">Returns</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><p>A new tensor of the same layout and order as <code data-dev-comment-type="paramref" class="paramref">diagonal</code> of one higher rank,
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with the values of <code data-dev-comment-type="paramref" class="paramref">diagonal</code> along the specified diagonal and zeros elsewhere.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="typeParameters">Type Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="parametername">T</span></td>
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<td><p>type contained within the Tensor. Typically a value type such as int, double, float, etc.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity__1_System_Int32_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity``1(System.Int32)">CreateIdentity<T>(Int32)</h4>
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<div class="markdown level1 summary"><p>Creates an identity tensor of the specified size. An identity tensor is a two dimensional tensor with 1s in the diagonal.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static Tensor<T> CreateIdentity<T>(int size)</code></pre>
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</div>
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<h5 class="parameters">Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="xref">System.Int32</span></td>
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<td><span class="parametername">size</span></td>
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<td><p>Width and height of the identity tensor to create.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="returns">Returns</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><p>a <code data-dev-comment-type="paramref" class="paramref">size</code> by <code data-dev-comment-type="paramref" class="paramref">size</code> with 1s along the diagonal and zeros elsewhere.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="typeParameters">Type Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="parametername">T</span></td>
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<td><p>type contained within the Tensor. Typically a value type such as int, double, float, etc.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity__1_System_Int32_System_Boolean_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity``1(System.Int32,System.Boolean)">CreateIdentity<T>(Int32, Boolean)</h4>
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<div class="markdown level1 summary"><p>Creates an identity tensor of the specified size and layout (row vs column major). An identity tensor is a two dimensional tensor with 1s in the diagonal.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static Tensor<T> CreateIdentity<T>(int size, bool columMajor)</code></pre>
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</div>
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<h5 class="parameters">Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="xref">System.Int32</span></td>
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<td><span class="parametername">size</span></td>
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<td><p>Width and height of the identity tensor to create.</p>
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</td>
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</tr>
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<tr>
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<td><span class="xref">System.Boolean</span></td>
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<td><span class="parametername">columMajor</span></td>
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<td><blockquote>
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<p>False to indicate that the first dimension is most minor (closest) and the last dimension is most major (farthest): row-major. True to indicate that the last dimension is most minor (closest together) and the first dimension is most major (farthest apart): column-major.</p>
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</blockquote>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="returns">Returns</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
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<td><p>a <code data-dev-comment-type="paramref" class="paramref">size</code> by <code data-dev-comment-type="paramref" class="paramref">size</code> with 1s along the diagonal and zeros elsewhere.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="typeParameters">Type Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="parametername">T</span></td>
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<td><p>type contained within the Tensor. Typically a value type such as int, double, float, etc.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_Tensor_CreateIdentity__1_System_Int32_System_Boolean___0_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.Tensor.CreateIdentity``1(System.Int32,System.Boolean,``0)">CreateIdentity<T>(Int32, Boolean, T)</h4>
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<div class="markdown level1 summary"><p>Creates an identity tensor of the specified size and layout (row vs column major) using the specified one value. An identity tensor is a two dimensional tensor with 1s in the diagonal. This may be used in case T is a type that doesn't have a known 1 value.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public static Tensor<T> CreateIdentity<T>(int size, bool columMajor, T oneValue)</code></pre>
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</div>
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<h5 class="parameters">Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Name</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><span class="xref">System.Int32</span></td>
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<td><span class="parametername">size</span></td>
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<td><p>Width and height of the identity tensor to create.</p>
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</td>
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</tr>
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<tr>
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<td><span class="xref">System.Boolean</span></td>
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<td><span class="parametername">columMajor</span></td>
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<td><blockquote>
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<p>False to indicate that the first dimension is most minor (closest) and the last dimension is most major (farthest): row-major. True to indicate that the last dimension is most minor (closest together) and the first dimension is most major (farthest apart): column-major.</p>
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</blockquote>
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</td>
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</tr>
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<tr>
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<td><span class="xref">T</span></td>
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<td><span class="parametername">oneValue</span></td>
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<td><p>Value of <code data-dev-comment-type="typeparamref" class="typeparamref">T</code> that is used along the diagonal.</p>
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="returns">Returns</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Type</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
|
|
<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
|
|
<td><p>a <code data-dev-comment-type="paramref" class="paramref">size</code> by <code data-dev-comment-type="paramref" class="paramref">size</code> with 1s along the diagonal and zeros elsewhere.</p>
|
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</td>
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</tr>
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</tbody>
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</table>
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<h5 class="typeParameters">Type Parameters</h5>
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<table class="table table-bordered table-striped table-condensed">
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<thead>
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<tr>
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<th>Name</th>
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<th>Description</th>
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</tr>
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|
</thead>
|
|
<tbody>
|
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<tr>
|
|
<td><span class="parametername">T</span></td>
|
|
<td><p>type contained within the Tensor. Typically a value type such as int, double, float, etc.</p>
|
|
</td>
|
|
</tr>
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</tbody>
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</table>
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