IVGCVSW-5924 Update 21.08 Doxygen Documents

* Also updated latest symlink. Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com> Change-Id: If9b4e0e52464abdf797b9eb858ae19bcc64c2aea
author: Matthew Sloyan <matthew.sloyan@arm.com> 2021-08-24 16:27:15 +0100
committer: Matthew Sloyan <matthew.sloyan@arm.com> 2021-08-24 16:27:40 +0100
commit: f86be93b7492b381370cae7bf71eca8572a0cbae (patch)
tree: 2a16d9b1892db2305851b2d91850f1c1635390b0 /21.08/operator_list.xhtml
parent: ff4682943c0a64acb22643aac7793ad2ec2a1194 (diff)
download: armnn-f86be93b7492b381370cae7bf71eca8572a0cbae.tar.gz
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+<!-- Copyright (c) 2020 ARM Limited. -->
+<!--                                 -->
+<!-- SPDX-License-Identifier: MIT    -->
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+<title>ArmNN: Arm NN Operators</title>
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+  <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
+  <td style="padding-left: 0.5em;">
+   <div id="projectname">
+   &#160;<span id="projectnumber">21.08</span>
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+<div class="header">
+  <div class="headertitle">
+<div class="title">Arm NN Operators </div>  </div>
+</div><!--header-->
+<div class="contents">
+<div class="toc"><h3>Table of Contents</h3>
+<ul><li class="level1"><a href="#S5_1_operator_list">Arm NN Operators</a></li>
+</ul>
+</div>
+<div class="textblock"><h1><a class="anchor" id="S5_1_operator_list"></a>
+Arm NN Operators</h1>
+<p>Arm NN supports operators that are listed in below table.</p>
+<p>Arm NN supports a wide list of data-types. The main data-types that the Machine Learning functions support are the following: </p><ul>
+<li>
+<b>BFLOAT16:</b> 16-bit non-standard brain floating point </li>
+<li>
+<b>QASYMMU8:</b> 8-bit unsigned asymmetric quantized </li>
+<li>
+<b>QASYMMS8:</b> 8-bit signed asymmetric quantized </li>
+<li>
+<b>QUANTIZEDSYMM8PERAXIS:</b> 8-bit signed symmetric quantized </li>
+<li>
+<b>QSYMMS8:</b> 8-bit unsigned symmetric quantized </li>
+<li>
+<b>QSYMMS16:</b> 16-bit unsigned symmetric quantized </li>
+<li>
+<b>FLOAT32:</b> 32-bit single precision floating point </li>
+<li>
+<b>FLOAT16:</b> 16-bit half precision floating point </li>
+<li>
+<b>SIGNED32:</b> 32-bit signed integer </li>
+<li>
+<b>BOOLEAN:</b> 8-bit unsigned char </li>
+<li>
+<b>All:</b> Agnostic to any specific data type </li>
+</ul>
+<p>Arm NN supports the following data layouts (fast changing dimension from right to left): </p><ul>
+<li>
+<b>NHWC:</b> Layout where channels are in the fastest changing dimension </li>
+<li>
+<b>NCHW:</b> Layout where width is in the fastest changing dimension </li>
+<li>
+<b>All:</b> Agnostic to any specific data layout </li>
+</ul>
+<p>where N = batches, C = channels, H = height, W = width</p>
+<a class="anchor" id="multi_row"></a>
+<table class="doxtable">
+<caption></caption>
+<tr>
+<th>Operator </th><th>Description </th><th>Equivalent Android NNAPI Operator </th><th>Backends </th><th>Data Layouts </th><th>Data Types </th></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_abs_layer.xhtml">AbsLayer</a> </td><td rowspan="3"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform absolute operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ABS </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_activation_layer.xhtml" title="This layer represents an activation operation with the specified activation function. ">ActivationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to simulate an activation layer with the specified activation function. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ABS </li>
+<li>
+ANEURALNETWORKS_ELU </li>
+<li>
+ANEURALNETWORKS_HARD_SWISH </li>
+<li>
+ANEURALNETWORKS_LOGISTIC </li>
+<li>
+ANEURALNETWORKS_PRELU </li>
+<li>
+ANEURALNETWORKS_RELU </li>
+<li>
+ANEURALNETWORKS_RELU1 </li>
+<li>
+ANEURALNETWORKS_RELU6 </li>
+<li>
+ANEURALNETWORKS_SQRT </li>
+<li>
+ANEURALNETWORKS_TANH </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_addition_layer.xhtml" title="This layer represents an addition operation. ">AdditionLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to add 2 tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ADD </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_arg_min_max_layer.xhtml" title="This layer represents a ArgMinMax operation. ">ArgMinMaxLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to calculate the index of the minimum or maximum values in a tensor based on an axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ARGMAX </li>
+<li>
+ANEURALNETWORKS_ARGMIN </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>SIGNED64 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_batch_normalization_layer.xhtml" title="This layer represents a batch normalization operation. ">BatchNormalizationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform batch normalization. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_batch_to_space_nd_layer.xhtml" title="This layer represents a BatchToSpaceNd operation. ">BatchToSpaceNdLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform a batch to space transformation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_BATCH_TO_SPACE_ND </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_cast_layer.xhtml" title="This layer represents a cast operation. ">CastLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to cast a tensor to a type. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_CAST </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_comparison_layer.xhtml" title="This layer represents a comparison operation. ">ComparisonLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compare 2 tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_EQUAL </li>
+<li>
+ANEURALNETWORKS_GREATER </li>
+<li>
+ANEURALNETWORKS_GREATER_EQUAL </li>
+<li>
+ANEURALNETWORKS_LESS </li>
+<li>
+ANEURALNETWORKS_LESS_EQUAL </li>
+<li>
+ANEURALNETWORKS_NOT_EQUAL </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_concat_layer.xhtml" title="This layer represents a merge operation. ">ConcatLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to concatenate tensors along a given axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_CONCATENATION </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_constant_layer.xhtml" title="A layer that the constant data can be bound to. ">ConstantLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to provide a constant tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convert_bf16_to_fp32_layer.xhtml" title="This layer converts data type BFloat16 to Float32. ">ConvertBf16ToFp32Layer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to convert <a class="el" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a> tensor to Float32 tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convert_fp16_to_fp32_layer.xhtml" title="This layer converts data type Float 16 to Float 32. ">ConvertFp16ToFp32Layer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to convert Float16 tensor to Float32 tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml" title="This layer converts data type Float32 to BFloat16. ">ConvertFp32ToBf16Layer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to convert Float32 tensor to <a class="el" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a> tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convert_fp32_to_fp16_layer.xhtml" title="This layer converts data type Float 32 to Float 16. ">ConvertFp32ToFp16Layer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to convert Float32 tensor to Float16 tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convolution2d_layer.xhtml" title="This layer represents a convolution 2d operation. ">Convolution2dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute a convolution operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_CONV_2D </li>
+<li>
+ANEURALNETWORKS_GROUPED_CONV_2D </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_debug_layer.xhtml" title="This layer visualizes the data flowing through the network. ">DebugLayer</a> </td><td rowspan="1" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to print out inter layer tensor information. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_depth_to_space_layer.xhtml" title="This layer represents a DepthToSpace operation. ">DepthToSpaceLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform Depth to Space transformation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_DEPTH_TO_SPACE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml" title="This layer represents a depthwise convolution 2d operation. ">DepthwiseConvolution2dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute a deconvolution or transpose convolution. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_DEPTHWISE_CONV_2D </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_dequantize_layer.xhtml" title="This layer dequantizes the input tensor. ">DequantizeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to dequantize the values in a tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_DEQUANTIZE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="2"><a class="el" href="classarmnn_1_1_detection_post_process_layer.xhtml" title="This layer represents a detection postprocess operator. ">DetectionPostProcessLayer</a> </td><td rowspan="2" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression (NMS). </td><td rowspan="2"><ul>
+<li>
+ANEURALNETWORKS_DETECTION_POSTPROCESSING </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_division_layer.xhtml" title="This layer represents a division operation. ">DivisionLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to divide 2 tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_DIV </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_elementwise_base_layer.xhtml" title="NOTE: this is an abstract class to encapsulate the element wise operations, it does not implement: st...">ElementwiseBaseLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform Add - Div - Max - Min - Mul operations. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ADD </li>
+<li>
+ANEURALNETWORKS_DIV </li>
+<li>
+ANEURALNETWORKS_MAXIMUM </li>
+<li>
+ANEURALNETWORKS_MINIMUM </li>
+<li>
+ANEURALNETWORKS_MUL </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_elementwise_unary_layer.xhtml" title="This layer represents a elementwiseUnary operation. ">ElementwiseUnaryLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform Rsqrt - Exp - Neg - Log - Abs - Sin - Sqrt operations. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_ABS </li>
+<li>
+ANEURALNETWORKS_EXP </li>
+<li>
+ANEURALNETWORKS_LOG </li>
+<li>
+ANEURALNETWORKS_NEG </li>
+<li>
+ANEURALNETWORKS_RSQRT </li>
+<li>
+ANEURALNETWORKS_SIN </li>
+<li>
+ANEURALNETWORKS_SQRT </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_fake_quantization_layer.xhtml" title="This layer represents a fake quantization operation. ">FakeQuantizationLayer</a> </td><td rowspan="1" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to quantize float values and dequantize afterwards. The current implementation does not dequantize the values. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_fill_layer.xhtml" title="This layer represents a fill operation. ">FillLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to set the values of a tensor with a given value. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_FILL </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_floor_layer.xhtml" title="This layer represents a floor operation. ">FloorLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to round the value to the lowest whole number. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_FLOOR </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_fully_connected_layer.xhtml" title="This layer represents a fully connected operation. ">FullyConnectedLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform a fully connected / dense operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_FULLY_CONNECTED </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_gather_layer.xhtml" title="This layer represents a Gather operator. ">GatherLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform the gather operation along the chosen axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_GATHER </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_input_layer.xhtml" title="A layer user-provided data can be bound to (e.g. inputs, outputs). ">InputLayer</a> </td><td rowspan="1" style="width:200px;">Special layer used to provide input data to the computational network. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>All </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_instance_normalization_layer.xhtml" title="This layer represents an instance normalization operation. ">InstanceNormalizationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an instance normalization on a given axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_INSTANCE_NORMALIZATION </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_l2_normalization_layer.xhtml" title="This layer represents a L2 normalization operation. ">L2NormalizationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an L2 normalization on a given axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_L2_NORMALIZATION </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_log_softmax_layer.xhtml" title="This layer represents a log softmax operation. ">LogSoftmaxLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform the log softmax activations given logits. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_logical_binary_layer.xhtml" title="This layer represents a Logical Binary operation. ">LogicalBinaryLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform Logical AND - Logical NOT - Logical OR operations. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_LOGICAL_AND </li>
+<li>
+ANEURALNETWORKS_LOGICAL_NOT </li>
+<li>
+ANEURALNETWORKS_LOGICAL_OR </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_lstm_layer.xhtml" title="This layer represents a LSTM operation. ">LstmLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform a single time step in a Long Short-Term Memory (LSTM) operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_LSTM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_map_layer.xhtml" title="This layer represents a memory copy operation. ">MapLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform map operation on tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_maximum_layer.xhtml" title="This layer represents a maximum operation. ">MaximumLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an elementwise maximum of two tensors. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_mean_layer.xhtml" title="This layer represents a mean operation. ">MeanLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform reduce mean operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_MEAN </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_mem_copy_layer.xhtml" title="This layer represents a memory copy operation. ">MemCopyLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform memory copy operation. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_mem_import_layer.xhtml" title="This layer represents a memory import operation. ">MemImportLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform memory import operation. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_merge_layer.xhtml" title="This layer dequantizes the input tensor. ">MergeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to concatenate tensors along a given axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_CONCATENATION </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_minimum_layer.xhtml" title="This layer represents a minimum operation. ">MinimumLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an elementwise minimum of two tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_MINIMUM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_multiplication_layer.xhtml" title="This layer represents a multiplication operation. ">MultiplicationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an elementwise multiplication of two tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_MUL </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_normalization_layer.xhtml" title="This layer represents a normalization operation. ">NormalizationLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute normalization operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_output_layer.xhtml" title="A layer user-provided data can be bound to (e.g. inputs, outputs). ">OutputLayer</a> </td><td rowspan="1" style="width:200px;">A special layer providing access to a user supplied buffer into which the output of a network can be written. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>All </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_pad_layer.xhtml" title="This layer represents a pad operation. ">PadLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to pad a tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_PAD </li>
+<li>
+ANEURALNETWORKS_PAD_V2 </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_permute_layer.xhtml" title="This layer represents a permutation operation. ">PermuteLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to transpose an ND tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_TRANSPOSE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_pooling2d_layer.xhtml" title="This layer represents a pooling 2d operation. ">Pooling2dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform pooling with the specified pooling operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_AVERAGE_POOL_2D </li>
+<li>
+ANEURALNETWORKS_L2_POOL_2D </li>
+<li>
+ANEURALNETWORKS_MAX_POOL_2D </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_pre_compiled_layer.xhtml">PreCompiledLayer</a> </td><td rowspan="1" style="width:200px;">Opaque layer provided by a backend which provides an executable representation of a subgraph from the original network. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>N/A </td><td>N/A </td><td>N/A </td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_prelu_layer.xhtml">PreluLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute the activation layer with the PRELU activation function. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_PRELU </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_q_lstm_layer.xhtml" title="This layer represents a QLstm operation. ">QLstmLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform quantized LSTM (Long Short-Term Memory) operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_QUANTIZED_LSTM </li>
+<li>
+ANEURALNETWORKS_QUANTIZED_16BIT_LSTM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_quantize_layer.xhtml">QuantizeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform quantization operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_QUANTIZE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMM16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMM16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_quantized_lstm_layer.xhtml" title="This layer represents a QuantizedLstm operation. ">QuantizedLstmLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform quantized LSTM (Long Short-Term Memory) operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_QUANTIZED_LSTM </li>
+<li>
+ANEURALNETWORKS_QUANTIZED_16BIT_LSTM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_rank_layer.xhtml">RankLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform a rank operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_RANK </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_reduce_layer.xhtml" title="This layer represents a reduction operation. ">ReduceLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform reduce with the following operations - ARG_IDX_MAX: Index of the max value - ARG_IDX_MIN: Index of the min value - MEAN_SUM: Mean of sum - PROD: Product - SUM_SQUARE: Sum of squares - SUM: Sum - MIN: Min - MAX: Max </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_REDUCE_MAX </li>
+<li>
+ANEURALNETWORKS_REDUCE_MIN </li>
+<li>
+ANEURALNETWORKS_REDUCE_SUM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_reshape_layer.xhtml" title="This layer represents a reshape operation. ">ReshapeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to reshape a tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_RESHAPE </li>
+<li>
+ANEURALNETWORKS_SQUEEZE </li>
+<li>
+ANEURALNETWORKS_EXPAND_DIMS </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>BOOLEAN </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_resize_layer.xhtml" title="This layer represents a resize operation. ">ResizeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform resize of a tensor using one of the interpolation methods: - Bilinear - Nearest Neighbor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_RESIZE_BILINEAR </li>
+<li>
+ANEURALNETWORKS_RESIZE_NEAREST_NEIGHBOR </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_rsqrt_layer.xhtml">RsqrtLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform Rsqrt operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_RSQRT </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_shape_layer.xhtml">ShapeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to return the shape of the input tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_slice_layer.xhtml">SliceLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform tensor slicing. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_SLICE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_softmax_layer.xhtml" title="This layer represents a softmax operation. ">SoftmaxLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform softmax, log-softmax operation over the specified axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_LOG_SOFTMAX </li>
+<li>
+ANEURALNETWORKS_SOFTMAX </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_space_to_batch_nd_layer.xhtml" title="This layer represents a SpaceToBatchNd operation. ">SpaceToBatchNdLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to divide spatial dimensions of the tensor into a grid of blocks and interleaves these blocks with the batch dimension. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_SPACE_TO_BATCH_ND </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_space_to_depth_layer.xhtml" title="This layer represents a SpaceToDepth operation. ">SpaceToDepthLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to rearrange blocks of spatial data into depth. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_SPACE_TO_DEPTH </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_splitter_layer.xhtml" title="This layer represents a split operation. ">SplitterLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to split a tensor along a given axis. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_SPLIT </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_stack_layer.xhtml" title="This layer represents a stack operation. ">StackLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to stack tensors along an axis. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="1"><a class="el" href="classarmnn_1_1_stand_in_layer.xhtml" title="This layer represents an unknown operation in the input graph. ">StandInLayer</a> </td><td rowspan="1" style="width:200px;">A layer to represent "unknown" or "unsupported" operations in the input graph. It has a configurable number of input and output slots and an optional name. </td><td rowspan="1"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>N/A </td><td>N/A </td><td>N/A </td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_strided_slice_layer.xhtml" title="This layer represents a strided slice operation. ">StridedSliceLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to extract a strided slice of a tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_STRIDED_SLICE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_subtraction_layer.xhtml" title="This layer represents a subtraction operation. ">SubtractionLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform an elementwise subtract of 2 tensors. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_SUB </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml" title="This layer represents a 2D transpose convolution operation. ">TransposeConvolution2dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform 2D transpose convolution (deconvolution) operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_TRANSPOSE_CONV_2D </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_transpose_layer.xhtml" title="This layer represents a transpose operation. ">TransposeLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to transpose a tensor. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_TRANSPOSE </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>BFLOAT16 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QSYMMS16 </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3">UnidirectionalSquenceLstmLayer </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform unidirectional LSTM operation. </td><td rowspan="3"><ul>
+<li>
+ANEURALNETWORKS_UNIDIRECTIONAL_SEQUENCE_LSTM </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>SIGNED32 </td></tr>
+<tr>
+<td>FLOAT16 </td></tr>
+<tr>
+<td>FLOAT32 </td></tr>
+<tr>
+<td>QASYMMU8 </td></tr>
+<tr>
+<td>QASYMMS8 </td></tr>
+<tr>
+<td>QUANTIZEDSYMM8PERAXIS </td></tr>
+</table>
+</td></tr>
+<tr>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_unmap_layer.xhtml" title="This layer represents a memory copy operation. ">UnmapLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform unmap operation on tensor. </td><td rowspan="3"><ul>
+<li>
+N/A </li>
+</ul>
+</td><td>CpuRef </td><td><ul>
+<li>
+All </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>CpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+<tr>
+<td>GpuAcc </td><td><ul>
+<li>
+NHWC </li>
+<li>
+NCHW </li>
+</ul>
+</td><td><table class="doxtable">
+<tr>
+<th></th></tr>
+<tr>
+<td>All </td></tr>
+</table>
+</td></tr>
+</table>
+</div></div><!-- contents -->
+</div><!-- doc-content -->
+<!-- start footer part -->
+<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
+  <ul>
+    <li class="footer">Generated on Tue Aug 24 2021 16:18:47 for ArmNN by
+    <a href="http://www.doxygen.org/index.html">
+    <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li>
+  </ul>
+</div>
+</body>
+</html>
author	Matthew Sloyan <matthew.sloyan@arm.com>	2021-08-24 16:27:15 +0100
committer	Matthew Sloyan <matthew.sloyan@arm.com>	2021-08-24 16:27:40 +0100
commit	f86be93b7492b381370cae7bf71eca8572a0cbae (patch)
tree	2a16d9b1892db2305851b2d91850f1c1635390b0 /21.08/operator_list.xhtml
parent	ff4682943c0a64acb22643aac7793ad2ec2a1194 (diff)
download	armnn-f86be93b7492b381370cae7bf71eca8572a0cbae.tar.gz