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<title>Class DenseTensor<T>
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<article class="content wrap" id="_content" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1">
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<h1 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1" class="text-break">Class DenseTensor<T>
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</h1>
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<div class="markdown level0 summary"><p>Represents a multi-dimensional collection of objects of type T that can be accessed by indices.<br>
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DenseTensor stores values in a contiguous sequential block of memory where all values are represented.</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"><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.TensorBase.html">TensorBase</a></div>
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<div class="level2"><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></div>
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<div class="level3"><span class="xref">DenseTensor<T></span></div>
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</div>
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<div class="implements">
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<h5>Implements</h5>
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<div><span class="xref">IList</span></div>
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<div><span class="xref">IList</span><T></div>
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<div><span class="xref">IReadOnlyList</span><T></div>
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<div><span class="xref">IStructuralComparable</span></div>
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<div><span class="xref">IStructuralEquatable</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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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Length">Tensor<T>.Length</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Rank">Tensor<T>.Rank</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_IsReversedStride">Tensor<T>.IsReversedStride</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Dimensions">Tensor<T>.Dimensions</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Strides">Tensor<T>.Strides</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Fill__0_">Tensor<T>.Fill(T)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_CloneEmpty">Tensor<T>.CloneEmpty()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_CloneEmpty_ReadOnlySpan_System_Int32__">Tensor<T>.CloneEmpty(ReadOnlySpan<Int32>)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_CloneEmpty__1">Tensor<T>.CloneEmpty<TResult>()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetDiagonal">Tensor<T>.GetDiagonal()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetDiagonal_System_Int32_">Tensor<T>.GetDiagonal(Int32)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetTriangle">Tensor<T>.GetTriangle()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetTriangle_System_Int32_">Tensor<T>.GetTriangle(Int32)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetUpperTriangle">Tensor<T>.GetUpperTriangle()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetUpperTriangle_System_Int32_">Tensor<T>.GetUpperTriangle(Int32)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetTriangle_System_Int32_System_Boolean_">Tensor<T>.GetTriangle(Int32, Boolean)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Item_System_Int32___">Tensor<T>.Item[Int32[]]</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Item_ReadOnlySpan_System_Int32__">Tensor<T>.Item[ReadOnlySpan<Int32>]</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Compare_Microsoft_ML_OnnxRuntime_Tensors_Tensor__0__Microsoft_ML_OnnxRuntime_Tensors_Tensor__0__">Tensor<T>.Compare(Tensor<T>, Tensor<T>)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Equals_Microsoft_ML_OnnxRuntime_Tensors_Tensor__0__Microsoft_ML_OnnxRuntime_Tensors_Tensor__0__">Tensor<T>.Equals(Tensor<T>, Tensor<T>)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_IsFixedSize">Tensor<T>.IsFixedSize</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_IsReadOnly">Tensor<T>.IsReadOnly</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_Contains__0_">Tensor<T>.Contains(T)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_ToDenseTensor">Tensor<T>.ToDenseTensor()</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html#Microsoft_ML_OnnxRuntime_Tensors_Tensor_1_GetArrayString_System_Boolean_">Tensor<T>.GetArrayString(Boolean)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.TensorBase.html#Microsoft_ML_OnnxRuntime_Tensors_TensorBase_GetTypeInfo_Type_">TensorBase.GetTypeInfo(Type)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.TensorBase.html#Microsoft_ML_OnnxRuntime_Tensors_TensorBase_GetElementTypeInfo_Microsoft_ML_OnnxRuntime_Tensors_TensorElementType_">TensorBase.GetElementTypeInfo(TensorElementType)</a>
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</div>
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<div>
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<a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.TensorBase.html#Microsoft_ML_OnnxRuntime_Tensors_TensorBase_GetTypeInfo">TensorBase.GetTypeInfo()</a>
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</div>
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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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<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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</div>
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<div>
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<span class="xref">System.Object.ReferenceEquals(System.Object, System.Object)</span>
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</div>
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<div>
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<span class="xref">System.Object.GetHashCode()</span>
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</div>
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<div>
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<span class="xref">System.Object.GetType()</span>
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</div>
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<div>
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<span class="xref">System.Object.MemberwiseClone()</span>
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</div>
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</div>
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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_DenseTensor_1_syntax">Syntax</h5>
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<div class="codewrapper">
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<pre><code class="lang-csharp hljs">public class DenseTensor<T> : Tensor<T></code></pre>
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</div>
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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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<h3 id="constructors">Constructors
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</h3>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1__ctor_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1__ctor_Memory__0__ReadOnlySpan_System_Int32__System_Boolean_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor(Memory{`0},ReadOnlySpan{System.Int32},System.Boolean)">DenseTensor(Memory<T>, ReadOnlySpan<Int32>, Boolean)</h4>
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<div class="markdown level1 summary"><p>Constructs a new DenseTensor of the specified dimensions, wrapping existing backing memory for the contents.</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 DenseTensor(Memory<T> memory, ReadOnlySpan<int> dimensions, bool reverseStride = false)</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">Memory</span><T></td>
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<td><span class="parametername">memory</span></td>
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<td></td>
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</tr>
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<tr>
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<td><span class="xref">ReadOnlySpan</span><<span class="xref">System.Int32</span>></td>
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<td><span class="parametername">dimensions</span></td>
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<td><p>An span of integers that represent the size of each dimension of the DenseTensor 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">reverseStride</span></td>
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<td><p>False (default) to indicate that the first dimension is most major (farthest apart) and the last dimension
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is most minor (closest together): akin to row-major in a rank-2 tensor.<br>
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True to indicate that the last dimension is most major (farthest apart) and the first dimension is most
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minor (closest together): akin to column-major in a rank-2 tensor.</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_DenseTensor_1__ctor_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1__ctor_ReadOnlySpan_System_Int32__System_Boolean_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor(ReadOnlySpan{System.Int32},System.Boolean)">DenseTensor(ReadOnlySpan<Int32>, Boolean)</h4>
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<div class="markdown level1 summary"><p>Initializes a rank-n Tensor using the dimensions specified in <code data-dev-comment-type="paramref" class="paramref">dimensions</code>.</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 DenseTensor(ReadOnlySpan<int> dimensions, bool reverseStride = false)</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">ReadOnlySpan</span><<span class="xref">System.Int32</span>></td>
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<td><span class="parametername">dimensions</span></td>
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<td><p>An span of integers that represent the size of each dimension of the DenseTensor 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">reverseStride</span></td>
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<td><p>False (default) to indicate that the first dimension is most major (farthest apart) and the last dimension
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is most minor (closest together): akin to row-major in a rank-2 tensor.<br>
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True to indicate that the last dimension is most major (farthest apart) and the first dimension is most
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minor (closest together): akin to column-major in a rank-2 tensor.</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_DenseTensor_1__ctor_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1__ctor_System_Int32_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.#ctor(System.Int32)">DenseTensor(Int32)</h4>
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<div class="markdown level1 summary"><p>Initializes a rank-1 Tensor using the specified <code data-dev-comment-type="paramref" class="paramref">length</code>.</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 DenseTensor(int length)</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">length</span></td>
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<td><p>Size of the 1-dimensional tensor</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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<h3 id="properties">Properties
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</h3>
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<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Buffer_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Buffer*"></a>
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<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Buffer" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Buffer">Buffer</h4>
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<div class="markdown level1 summary"><p>Memory storing backing values of this tensor.</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 Memory<T> Buffer { get; }</code></pre>
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</div>
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<h5 class="propertyValue">Property Value</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><span class="xref">Memory</span><T></td>
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<td></td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h3 id="methods">Methods
|
|
</h3>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Clone_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Clone*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Clone" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Clone">Clone()</h4>
|
|
<div class="markdown level1 summary"><p>Creates a shallow copy of this tensor, with new backing storage.</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">public override Tensor<T> Clone()</code></pre>
|
|
</div>
|
|
<h5 class="returns">Returns</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
|
|
<td><p>A shallow copy of this tensor.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.Clone()</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_CloneEmpty_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.CloneEmpty*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_CloneEmpty__1_ReadOnlySpan_System_Int32__" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.CloneEmpty``1(ReadOnlySpan{System.Int32})">CloneEmpty<TResult>(ReadOnlySpan<Int32>)</h4>
|
|
<div class="markdown level1 summary"><p>Creates a new Tensor of a different type with the specified dimensions and the same layout as this tensor
|
|
with elements initialized to their default value.</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">public override Tensor<TResult> CloneEmpty<TResult>(ReadOnlySpan<int> dimensions)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">ReadOnlySpan</span><<span class="xref">System.Int32</span>></td>
|
|
<td><span class="parametername">dimensions</span></td>
|
|
<td><p>An span of integers that represent the size of each dimension of the DenseTensor to create.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="returns">Returns</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><TResult></td>
|
|
<td><p>A new tensor with the same layout as this tensor but different type and dimensions.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="typeParameters">Type Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="parametername">TResult</span></td>
|
|
<td><p>Type contained in the returned Tensor.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.CloneEmpty<TResult>(ReadOnlySpan<System.Int32>)</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_CopyTo_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.CopyTo*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_CopyTo__0___System_Int32_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.CopyTo(`0[],System.Int32)">CopyTo(T[], Int32)</h4>
|
|
<div class="markdown level1 summary"><p>Overrides Tensor.CopyTo(). Copies the content of the Tensor
|
|
to the specified array starting with arrayIndex</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">protected override void CopyTo(T[] array, int arrayIndex)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>T[]</td>
|
|
<td><span class="parametername">array</span></td>
|
|
<td><p>destination array</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td><span class="xref">System.Int32</span></td>
|
|
<td><span class="parametername">arrayIndex</span></td>
|
|
<td><p>start index</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.CopyTo(T[], System.Int32)</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_GetValue_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.GetValue*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_GetValue_System_Int32_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.GetValue(System.Int32)">GetValue(Int32)</h4>
|
|
<div class="markdown level1 summary"><p>Gets the value at the specified index, where index is a linearized version of n-dimension indices
|
|
using strides. For a scalar, use index = 0</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">public override T GetValue(int index)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">System.Int32</span></td>
|
|
<td><span class="parametername">index</span></td>
|
|
<td><p>An integer index computed as a dot-product of indices.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="returns">Returns</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">T</span></td>
|
|
<td><p>The value at the specified position in this Tensor.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.GetValue(System.Int32)</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_IndexOf_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.IndexOf*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_IndexOf__0_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.IndexOf(`0)">IndexOf(T)</h4>
|
|
<div class="markdown level1 summary"><p>Determines the index of a specific item in the Tensor<T>.</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">protected override int IndexOf(T item)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">T</span></td>
|
|
<td><span class="parametername">item</span></td>
|
|
<td><p>Object to locate</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="returns">Returns</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">System.Int32</span></td>
|
|
<td><p>The index of item if found in the tensor; otherwise, -1</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.IndexOf(T)</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Reshape_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Reshape*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_Reshape_ReadOnlySpan_System_Int32__" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.Reshape(ReadOnlySpan{System.Int32})">Reshape(ReadOnlySpan<Int32>)</h4>
|
|
<div class="markdown level1 summary"><p>Reshapes the current tensor to new dimensions, using the same backing storage.</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">public override Tensor<T> Reshape(ReadOnlySpan<int> dimensions)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">ReadOnlySpan</span><<span class="xref">System.Int32</span>></td>
|
|
<td><span class="parametername">dimensions</span></td>
|
|
<td><p>An span of integers that represent the size of each dimension of the DenseTensor to create.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="returns">Returns</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><a class="xref" href="Microsoft.ML.OnnxRuntime.Tensors.Tensor-1.html">Tensor</a><T></td>
|
|
<td><p>A new tensor that reinterprets backing Buffer of this tensor with different dimensions.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.Reshape(ReadOnlySpan<System.Int32>)</span></div>
|
|
|
|
|
|
<a id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_SetValue_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.SetValue*"></a>
|
|
<h4 id="Microsoft_ML_OnnxRuntime_Tensors_DenseTensor_1_SetValue_System_Int32__0_" data-uid="Microsoft.ML.OnnxRuntime.Tensors.DenseTensor`1.SetValue(System.Int32,`0)">SetValue(Int32, T)</h4>
|
|
<div class="markdown level1 summary"><p>Sets the value at the specified index, where index is a linearized version of n-dimension indices
|
|
using strides. For a scalar, use index = 0</p>
|
|
</div>
|
|
<div class="markdown level1 conceptual"></div>
|
|
<h5 class="decalaration">Declaration</h5>
|
|
<div class="codewrapper">
|
|
<pre><code class="lang-csharp hljs">public override void SetValue(int index, T value)</code></pre>
|
|
</div>
|
|
<h5 class="parameters">Parameters</h5>
|
|
<table class="table table-bordered table-striped table-condensed">
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Name</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td><span class="xref">System.Int32</span></td>
|
|
<td><span class="parametername">index</span></td>
|
|
<td><p>An integer index computed as a dot-product of indices.</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td><span class="xref">T</span></td>
|
|
<td><span class="parametername">value</span></td>
|
|
<td><p>The new value to set at the specified position in this Tensor.</p>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<h5 class="overrides">Overrides</h5>
|
|
<div><span class="xref">Microsoft.ML.OnnxRuntime.Tensors.Tensor<T>.SetValue(System.Int32, T)</span></div>
|
|
<h3 id="implements">Implements</h3>
|
|
<div>
|
|
<span class="xref">IList</span>
|
|
</div>
|
|
<div>
|
|
<span class="xref">IList<></span>
|
|
</div>
|
|
<div>
|
|
<span class="xref">IReadOnlyList<></span>
|
|
</div>
|
|
<div>
|
|
<span class="xref">IStructuralComparable</span>
|
|
</div>
|
|
<div>
|
|
<span class="xref">IStructuralEquatable</span>
|
|
</div>
|
|
</article>
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</div>
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