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* initial setup and rename "how to" to "setup" * move API to main nav * move api to main nav * add get starated, rework nav order * rename to install move mds out of install section * update api nav and home page * add install docs and python qs updates * python get started work * remove c and obj c for now * move java, python, and obj-c docs under api folder * move java api html to iframe (ugh) * remove api docs w/o details, move api text getstar * remove api docs wo detail updates get started * remvoe iframes * move eco system to main nav * fix api buttons * added more examples moved intro to ORT * fix links * fix get started titles * fix get started titles * fix more links * fix more links * more link fixes * fix nav remove inferencing and training subnav * fix top nav remove inference and training nav * fix title * fix tutorials nav hierarchy * fix python api button * add tenorflow keras example * fix quickstart toc * add imports fix spacing * fix links * update nav and python get started page * move ort training example, add coming soon for iot * update C# get started * fix spacing on quantization * Add some js get started content * fix formatting * fix typo * removed onnx-pytorch and onnx-tf * updated pip install torch and added links iot page * added pytorch tutorial heirarchy * updated web to docs soon added release blog link * add web link
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<h2 title="Class OnnxTensor" class="title">Class OnnxTensor</h2>
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<pre>public class <span class="typeNameLabel">OnnxTensor</span>
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extends java.lang.Object
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implements <a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></pre>
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<div class="block">A Java object wrapping an OnnxTensor. Tensors are the main input to the library,
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and can also be returned as outputs.</div>
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<h3>Nested classes/interfaces inherited from interface ai.onnxruntime.<a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></h3>
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<code><a href="../../ai/onnxruntime/OnnxValue.OnnxValueType.html" title="enum in ai.onnxruntime">OnnxValue.OnnxValueType</a></code></li>
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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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<tr>
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<th class="colFirst" scope="col">Modifier and Type</th>
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<th class="colLast" scope="col">Method and Description</th>
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<tr id="i0" class="altColor">
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<td class="colFirst"><code>void</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#close--">close</a></span>()</code>
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<div class="block">Closes the tensor, releasing it's underlying memory (if it's not backed by an NIO buffer).</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 <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.ByteBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.ByteBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct ByteBuffer.</div>
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</td>
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</tr>
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<tr id="i2" class="altColor">
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<td class="colFirst"><code>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.ByteBuffer-long:A-ai.onnxruntime.OnnxJavaType-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.ByteBuffer data,
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long[] shape,
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<a href="../../ai/onnxruntime/OnnxJavaType.html" title="enum in ai.onnxruntime">OnnxJavaType</a> type)</code>
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<div class="block">Create an OnnxTensor backed by a direct ByteBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.DoubleBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.DoubleBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct DoubleBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.FloatBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.FloatBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct FloatBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.IntBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.IntBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct IntBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.LongBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.LongBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct LongBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.lang.Object-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.lang.Object data)</code>
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<div class="block">Create a Tensor from a Java primitive or String multidimensional array.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.nio.ShortBuffer-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.ShortBuffer data,
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long[] shape)</code>
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<div class="block">Create an OnnxTensor backed by a direct ShortBuffer.</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>static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#createTensor-ai.onnxruntime.OrtEnvironment-java.lang.String:A-long:A-">createTensor</a></span>(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.lang.String[] data,
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long[] shape)</code>
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<div class="block">Create a tensor from a flattened string array.</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>java.nio.ByteBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getByteBuffer--">getByteBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as a ByteBuffer.</div>
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</td>
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</tr>
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<tr id="i11" class="rowColor">
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<td class="colFirst"><code>java.nio.DoubleBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getDoubleBuffer--">getDoubleBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as a DoubleBuffer if the underlying type is
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a double, otherwise it returns null.</div>
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</td>
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</tr>
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<tr id="i12" class="altColor">
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<td class="colFirst"><code>java.nio.FloatBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getFloatBuffer--">getFloatBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as a FloatBuffer
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if it can be losslessly converted into a float (i.e.</div>
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</td>
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</tr>
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<tr id="i13" class="rowColor">
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<td class="colFirst"><code><a href="../../ai/onnxruntime/TensorInfo.html" title="class in ai.onnxruntime">TensorInfo</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getInfo--">getInfo</a></span>()</code>
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<div class="block">Gets the type info object associated with this OnnxValue.</div>
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</td>
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</tr>
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<tr id="i14" class="altColor">
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<td class="colFirst"><code>java.nio.IntBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getIntBuffer--">getIntBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as an IntBuffer if
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the underlying type is int32 or uint32, otherwise it returns null.</div>
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</td>
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</tr>
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<tr id="i15" class="rowColor">
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<td class="colFirst"><code>java.nio.LongBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getLongBuffer--">getLongBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as a LongBuffer
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if the underlying type is int64 or uint64, otherwise it returns null.</div>
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</td>
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</tr>
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<tr id="i16" class="altColor">
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<td class="colFirst"><code>java.nio.ShortBuffer</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getShortBuffer--">getShortBuffer</a></span>()</code>
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<div class="block">Returns a copy of the underlying OnnxTensor as a ShortBuffer if the
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underlying type is int16 or uint16, otherwise it returns null.</div>
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</td>
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</tr>
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<tr id="i17" class="rowColor">
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<td class="colFirst"><code><a href="../../ai/onnxruntime/OnnxValue.OnnxValueType.html" title="enum in ai.onnxruntime">OnnxValue.OnnxValueType</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getType--">getType</a></span>()</code>
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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="i18" class="altColor">
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<td class="colFirst"><code>java.lang.Object</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#getValue--">getValue</a></span>()</code>
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<div class="block">Either returns a boxed primitive if the Tensor is a scalar, or a multidimensional array of
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primitives if it has multiple dimensions.</div>
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</td>
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<tr id="i19" class="rowColor">
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<td class="colFirst"><code>java.lang.String</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../ai/onnxruntime/OnnxTensor.html#toString--">toString</a></span>()</code> </td>
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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, wait, wait, wait</code></li>
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<h3>Methods inherited from interface ai.onnxruntime.<a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></h3>
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<code><a href="../../ai/onnxruntime/OnnxValue.html#close-java.lang.Iterable-">close</a>, <a href="../../ai/onnxruntime/OnnxValue.html#close-java.util.Map-">close</a></code></li>
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<pre>public <a href="../../ai/onnxruntime/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="../../ai/onnxruntime/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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<dl>
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<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OnnxValue.html#getType--">getType</a></code> in interface <code><a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></code></dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>The value type.</dd>
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<pre>public java.lang.Object getValue()
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Either returns a boxed primitive if the Tensor is a scalar, or a multidimensional array of
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primitives if it has multiple dimensions.
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<p>
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Java multidimensional arrays are quite slow for more than 2 dimensions, in that
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case it is recommended you use the java.nio.Buffer extractors below (e.g. <a href="../../ai/onnxruntime/OnnxTensor.html#getFloatBuffer--"><code>getFloatBuffer()</code></a>).</div>
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<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OnnxValue.html#getValue--">getValue</a></code> in interface <code><a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></code></dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A Java value.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - If the value could not be extracted as the Tensor is invalid, or if the native code encountered an error.</dd>
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<pre>public <a href="../../ai/onnxruntime/TensorInfo.html" title="class in ai.onnxruntime">TensorInfo</a> getInfo()</pre>
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<div class="block"><span class="descfrmTypeLabel">Description copied from interface: <code><a href="../../ai/onnxruntime/OnnxValue.html#getInfo--">OnnxValue</a></code></span></div>
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<div class="block">Gets the type info object associated with this OnnxValue.</div>
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<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OnnxValue.html#getInfo--">getInfo</a></code> in interface <code><a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></code></dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>The type information.</dd>
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<pre>public java.lang.String toString()</pre>
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<dt><span class="overrideSpecifyLabel">Overrides:</span></dt>
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<dd><code>toString</code> in class <code>java.lang.Object</code></dd>
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<pre>public void close()</pre>
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<div class="block">Closes the tensor, releasing it's underlying memory (if it's not backed by an NIO buffer).
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If it is backed by a buffer then the memory is released when the buffer is GC'd.</div>
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<dl>
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<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OnnxValue.html#close--">close</a></code> in interface <code><a href="../../ai/onnxruntime/OnnxValue.html" title="interface in ai.onnxruntime">OnnxValue</a></code></dd>
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<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
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<dd><code>close</code> in interface <code>java.lang.AutoCloseable</code></dd>
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<pre>public java.nio.ByteBuffer getByteBuffer()</pre>
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<div class="block">Returns a copy of the underlying OnnxTensor as a ByteBuffer.
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<p>
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This method returns null if the OnnxTensor contains Strings as they are stored externally to the OnnxTensor.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A ByteBuffer copy of the OnnxTensor.</dd>
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<pre>public java.nio.FloatBuffer getFloatBuffer()</pre>
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<div class="block">Returns a copy of the underlying OnnxTensor as a FloatBuffer
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if it can be losslessly converted into a float (i.e. it's a float or fp16), otherwise it
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returns null.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A FloatBuffer copy of the OnnxTensor.</dd>
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<pre>public java.nio.DoubleBuffer getDoubleBuffer()</pre>
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a double, otherwise it returns null.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A DoubleBuffer copy of the OnnxTensor.</dd>
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<pre>public java.nio.ShortBuffer getShortBuffer()</pre>
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<div class="block">Returns a copy of the underlying OnnxTensor as a ShortBuffer if the
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underlying type is int16 or uint16, otherwise it returns null.</div>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A ShortBuffer copy of the OnnxTensor.</dd>
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<pre>public java.nio.IntBuffer getIntBuffer()</pre>
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<div class="block">Returns a copy of the underlying OnnxTensor as an IntBuffer if
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the underlying type is int32 or uint32, otherwise it returns null.</div>
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<dl>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An IntBuffer copy of the OnnxTensor.</dd>
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<pre>public java.nio.LongBuffer getLongBuffer()</pre>
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<div class="block">Returns a copy of the underlying OnnxTensor as a LongBuffer
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if the underlying type is int64 or uint64, otherwise it returns null.</div>
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<dl>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>A LongBuffer copy of the OnnxTensor.</dd>
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<pre>public static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a> createTensor(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The data to store in a tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor storing the data.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - If the onnx runtime threw an error.</dd>
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<pre>public static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a> createTensor(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.lang.String[] data,
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Create a tensor from a flattened string array.
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<p>
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Requires the array to be flattened in row-major order. Uses the default allocator.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data</dd>
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<dd><code>shape</code> - the shape of the tensor</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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<pre>public static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a> createTensor(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.FloatBuffer data,
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<p>
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of the tensor. Uses the default allocator.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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of the tensor. Uses the default allocator.</div>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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of the tensor. Uses the default allocator. Tells the runtime it's <a href="../../ai/onnxruntime/OnnxJavaType.html#INT8"><code>OnnxJavaType.INT8</code></a>.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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java.nio.ByteBuffer data,
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long[] shape,
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<a href="../../ai/onnxruntime/OnnxJavaType.html" title="enum in ai.onnxruntime">OnnxJavaType</a> type)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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of the tensor. Uses the default allocator. Tells the runtime it's the specified type.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dd><code>type</code> - The type to use for the byte buffer elements.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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java.nio.ShortBuffer data,
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Create an OnnxTensor backed by a direct ShortBuffer. The buffer should be in nativeOrder.
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<p>
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If the supplied buffer is not a direct buffer, a direct copy is created tied to the lifetime
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of the tensor. Uses the default allocator.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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<pre>public static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a> createTensor(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.IntBuffer data,
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Create an OnnxTensor backed by a direct IntBuffer. The buffer should be in nativeOrder.
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<p>
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If the supplied buffer is not a direct buffer, a direct copy is created tied to the lifetime
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of the tensor. Uses the default allocator.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>env</code> - The current OrtEnvironment.</dd>
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<dd><code>data</code> - The tensor data.</dd>
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<dd><code>shape</code> - The shape of tensor.</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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</dl>
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</li>
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</ul>
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<a name="createTensor-ai.onnxruntime.OrtEnvironment-java.nio.LongBuffer-long:A-">
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<!-- -->
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<h4>createTensor</h4>
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<pre>public static <a href="../../ai/onnxruntime/OnnxTensor.html" title="class in ai.onnxruntime">OnnxTensor</a> createTensor(<a href="../../ai/onnxruntime/OrtEnvironment.html" title="class in ai.onnxruntime">OrtEnvironment</a> env,
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java.nio.LongBuffer data,
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long[] shape)
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throws <a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></pre>
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<div class="block">Create an OnnxTensor backed by a direct LongBuffer. The buffer should be in nativeOrder.
|
|
<p>
|
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If the supplied buffer is not a direct buffer, a direct copy is created tied to the lifetime
|
|
of the tensor. Uses the default allocator.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
|
|
<dd><code>env</code> - The current OrtEnvironment.</dd>
|
|
<dd><code>data</code> - The tensor data.</dd>
|
|
<dd><code>shape</code> - The shape of tensor.</dd>
|
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<dt><span class="returnLabel">Returns:</span></dt>
|
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<dd>An OnnxTensor of the required shape.</dd>
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<dt><span class="throwsLabel">Throws:</span></dt>
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<dd><code><a href="../../ai/onnxruntime/OrtException.html" title="class in ai.onnxruntime">OrtException</a></code> - Thrown if there is an onnx error or if the data and shape don't match.</dd>
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