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<h2 title="Class OnnxSparseTensor" class="title">Class OnnxSparseTensor</h2>
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<li>java.lang.Object</li>
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<li><a href="OnnxTensorLike.html" title="class in ai.onnxruntime">ai.onnxruntime.OnnxTensorLike</a></li>
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<ul class="inheritance">
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<li>ai.onnxruntime.OnnxSparseTensor</li>
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<pre>public final class <span class="typeNameLabel">OnnxSparseTensor</span>
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extends <a href="OnnxTensorLike.html" title="class in ai.onnxruntime">OnnxTensorLike</a></pre>
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<div class="block">A Java object wrapping an OnnxSparseTensor.
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<p>Sparse tensors support a variety of formats, and the <a href="#getValue()"><code>getValue()</code></a> method returns a
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different static inner class representing each type.</div>
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<th class="colFirst" scope="col">Modifier and Type</th>
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<th class="colSecond" scope="col">Class</th>
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<th class="colLast" scope="col">Description</th>
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<tr class="altColor">
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<td class="colFirst"><code>static class </code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="OnnxSparseTensor.BlockSparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.BlockSparseTensor</a></span></code></th>
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<td class="colLast">
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<div class="block">The Java side representation of a block sparse tensor.</div>
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</td>
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</tr>
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<tr class="rowColor">
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<td class="colFirst"><code>static class </code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="OnnxSparseTensor.COOTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.COOTensor</a></span></code></th>
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<td class="colLast">
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<div class="block">The Java side representation of a COO sparse tensor.</div>
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</td>
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</tr>
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<tr class="altColor">
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<td class="colFirst"><code>static class </code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="OnnxSparseTensor.CSRCTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.CSRCTensor</a></span></code></th>
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<td class="colLast">
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<div class="block">The Java side representation of a CSRC sparse tensor.</div>
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</td>
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</tr>
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<tr class="rowColor">
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<td class="colFirst"><code>static class </code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="OnnxSparseTensor.SparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.SparseTensor</a><<a href="OnnxSparseTensor.SparseTensor.html" title="type parameter in OnnxSparseTensor.SparseTensor">T</a> extends java.nio.Buffer></span></code></th>
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<td class="colLast">
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<div class="block">Abstract base class for Java sparse tensors</div>
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</td>
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<tr class="altColor">
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<td class="colFirst"><code>static class </code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="OnnxSparseTensor.SparseTensorType.html" title="enum in ai.onnxruntime">OnnxSparseTensor.SparseTensorType</a></span></code></th>
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<td class="colLast">
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<div class="block">The type of the sparse tensor.</div>
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<h3>Nested classes/interfaces inherited from interface ai.onnxruntime.<a href="OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></h3>
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<code><a href="OnnxValue.OnnxValueType.html" title="enum in ai.onnxruntime">OnnxValue.OnnxValueType</a></code></li>
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<h3>Fields inherited from class ai.onnxruntime.<a href="OnnxTensorLike.html" title="class in ai.onnxruntime">OnnxTensorLike</a></h3>
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<code><a href="OnnxTensorLike.html#allocatorHandle">allocatorHandle</a>, <a href="OnnxTensorLike.html#info">info</a>, <a href="OnnxTensorLike.html#nativeHandle">nativeHandle</a></code></li>
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<h3>Method Summary</h3>
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<table class="memberSummary">
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<caption><span id="t0" class="activeTableTab"><span>All Methods</span><span class="tabEnd"> </span></span><span id="t1" class="tableTab"><span><a href="javascript:show(1);">Static Methods</a></span><span class="tabEnd"> </span></span><span id="t2" class="tableTab"><span><a href="javascript:show(2);">Instance Methods</a></span><span class="tabEnd"> </span></span><span id="t4" class="tableTab"><span><a href="javascript:show(8);">Concrete Methods</a></span><span class="tabEnd"> </span></span></caption>
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<th class="colFirst" scope="col">Modifier and Type</th>
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<th class="colSecond" scope="col">Method</th>
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<th class="colLast" scope="col">Description</th>
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<td class="colFirst"><code>void</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#close()">close</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Closes the OnnxValue, freeing it's native memory.</div>
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</td>
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</tr>
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<tr id="i1" class="rowColor">
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<td class="colFirst"><code>static <T extends java.nio.Buffer><br><a href="OnnxSparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor</a></code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#createSparseTensor(ai.onnxruntime.OrtEnvironment,ai.onnxruntime.OnnxSparseTensor.SparseTensor)">createSparseTensor</a></span>​(<a href="OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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<a href="OnnxSparseTensor.SparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.SparseTensor</a><T> tensor)</code></th>
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<td class="colLast">
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<div class="block">Creates a Sparse Tensor in ORT from the Java side representation.</div>
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</td>
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<tr id="i2" class="altColor">
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<td class="colFirst"><code>java.nio.Buffer</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getIndicesBuffer()">getIndicesBuffer</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets a copy of the indices.</div>
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</td>
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</tr>
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<tr id="i3" class="rowColor">
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<td class="colFirst"><code>long[]</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getIndicesShape()">getIndicesShape</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets the shape of the (outer) indices.</div>
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</td>
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</tr>
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<tr id="i4" class="altColor">
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<td class="colFirst"><code>java.nio.LongBuffer</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getInnerIndicesBuffer()">getInnerIndicesBuffer</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets a copy of the inner indices in a CSRC sparse tensor.</div>
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</td>
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</tr>
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<tr id="i5" class="rowColor">
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<td class="colFirst"><code>long[]</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getInnerIndicesShape()">getInnerIndicesShape</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets the shape of the inner indices in a CSRC sparse tensor.</div>
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</td>
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</tr>
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<tr id="i6" class="altColor">
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<td class="colFirst"><code><a href="OnnxSparseTensor.SparseTensorType.html" title="enum in ai.onnxruntime">OnnxSparseTensor.SparseTensorType</a></code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getSparseTensorType()">getSparseTensorType</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Returns the type of this OnnxSparseTensor.</div>
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</td>
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</tr>
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<tr id="i7" class="rowColor">
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<td class="colFirst"><code><a href="OnnxValue.OnnxValueType.html" title="enum in ai.onnxruntime">OnnxValue.OnnxValueType</a></code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getType()">getType</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets the type of this OnnxValue.</div>
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</td>
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</tr>
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<tr id="i8" class="altColor">
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<td class="colFirst"><code><a href="OnnxSparseTensor.SparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.SparseTensor</a><? extends java.nio.Buffer></code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getValue()">getValue</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Returns the value as a Java object copying it out of the native heap.</div>
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</td>
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</tr>
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<tr id="i9" class="rowColor">
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<td class="colFirst"><code>java.nio.Buffer</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getValuesBuffer()">getValuesBuffer</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets a copy of the data buffer.</div>
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</td>
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</tr>
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<tr id="i10" class="altColor">
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<td class="colFirst"><code>long[]</code></td>
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<th class="colSecond" scope="row"><code><span class="memberNameLink"><a href="#getValuesShape()">getValuesShape</a></span>()</code></th>
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<td class="colLast">
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<div class="block">Gets the shape of the values.</div>
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<h3>Methods inherited from class ai.onnxruntime.<a href="OnnxTensorLike.html" title="class in ai.onnxruntime">OnnxTensorLike</a></h3>
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<code><a href="OnnxTensorLike.html#getInfo()">getInfo</a></code></li>
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<h3>Methods inherited from class java.lang.Object</h3>
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<code>clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait</code></li>
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</ul>
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<h3>Method Detail</h3>
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<a id="createSparseTensor(ai.onnxruntime.OrtEnvironment,ai.onnxruntime.OnnxSparseTensor.SparseTensor)">
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<h4>createSparseTensor</h4>
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<pre class="methodSignature">public static <T extends java.nio.Buffer> <a href="OnnxSparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor</a> createSparseTensor​(<a href="OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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<a href="OnnxSparseTensor.SparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.SparseTensor</a><T> tensor)
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throws <a href="OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Creates a Sparse Tensor in ORT from the Java side representation.</div>
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<dl>
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<dt><span class="paramLabel">Type Parameters:</span></dt>
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<dd><code>T</code> - The buffer type.</dd>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The OrtEnvironment.</dd>
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<dd><code>tensor</code> - The Java side representation.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>The sparse tensor in ORT.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - If the tensor could not be created or was invalid.</dd>
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<pre class="methodSignature">public <a href="OnnxValue.OnnxValueType.html" title="enum in ai.onnxruntime">OnnxValue.OnnxValueType</a> getType()</pre>
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<div class="block"><span class="descfrmTypeLabel">Description copied from interface: <code><a href="OnnxValue.html#getType()">OnnxValue</a></code></span></div>
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<div class="block">Gets the type of this OnnxValue.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<pre class="methodSignature">public <a href="OnnxSparseTensor.SparseTensor.html" title="class in ai.onnxruntime">OnnxSparseTensor.SparseTensor</a><? extends java.nio.Buffer> getValue()
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throws <a href="OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block"><span class="descfrmTypeLabel">Description copied from interface: <code><a href="OnnxValue.html#getValue()">OnnxValue</a></code></span></div>
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<div class="block">Returns the value as a Java object copying it out of the native heap. This operation can be
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quite slow for high dimensional tensors, where you should prefer <a href="OnnxTensor.html#getByteBuffer()"><code>OnnxTensor.getByteBuffer()</code></a> etc.
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<p>Overridden by the subclasses with a more specific type if available.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>The value.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - If an error occurred reading the value.</dd>
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<pre class="methodSignature">public <a href="OnnxSparseTensor.SparseTensorType.html" title="enum in ai.onnxruntime">OnnxSparseTensor.SparseTensorType</a> getSparseTensorType()</pre>
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<dt><span class="returnLabel">Returns:</span></dt>
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<p>These are the outer indices if it's a CSRC sparse tensor.
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<p>It's a <code>LongBuffer</code> if COO or CSRC, and <code>IntBuffer</code> if Block Sparse.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>The indices.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<div class="block">Gets a copy of the data buffer.
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<p>As with <a href="OnnxTensor.html" title="class in ai.onnxruntime"><code>OnnxTensor</code></a> fp16 values are upcast into fp32 and returned as a <code>FloatBuffer</code>.</div>
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<div class="block">Gets the shape of the (outer) indices.</div>
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<div class="block">Gets the shape of the inner indices in a CSRC sparse tensor.</div>
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<div class="block">Gets the shape of the values.</div>
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