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authorNikhil Raj <nikhil.raj@arm.com>2022-08-19 15:23:36 +0100
committerNikhil Raj <nikhil.raj@arm.com>2022-08-19 15:23:36 +0100
commit7bfd38a721360183f3392f9ab35db18a0dd7fef8 (patch)
tree5b4da2f2e88636c939afbafa2571170297114e40 /22.08/serializer.xhtml
parentd5d43d82c0137e08553e44345c609cdd1a7931c7 (diff)
downloadarmnn-7bfd38a721360183f3392f9ab35db18a0dd7fef8.tar.gz
Update Doxygen for 22.08 Release
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com> Change-Id: I4789fe868e0492839be1482e5cee3642ed90d756
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+<!-- Copyright (c) 2020 ARM Limited. -->
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+ &#160;<span id="projectnumber">22.08</span>
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+ <div class="headertitle">
+<div class="title">Serializer </div> </div>
+</div><!--header-->
+<div class="contents">
+<div class="toc"><h3>Table of Contents</h3>
+<ul><li class="level1"><a href="#serializersupport">Supported Layers</a><ul><li class="level2"><a href="#serializersupportflully">Fully supported</a></li>
+<li class="level2"><a href="#serializersupportdeprecated">Deprecated layers</a></li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="textblock"><p>The <code><a class="el" href="namespacearmnn_serializer.xhtml">armnnSerializer</a></code> is a library for serializing an Arm NN network to a stream.</p>
+<h1><a class="anchor" id="serializersupport"></a>
+Supported Layers</h1>
+<p>This reference guide provides a list of layers which can be serialized by the Arm NN SDK.</p>
+<h2><a class="anchor" id="serializersupportflully"></a>
+Fully supported</h2>
+<p>The Arm NN SDK Serializer currently supports the following layers:</p>
+<ul>
+<li>Activation</li>
+<li>Addition</li>
+<li>ArgMinMax</li>
+<li>BatchToSpaceNd</li>
+<li>BatchNormalization</li>
+<li>Cast</li>
+<li>ChannelShuffle</li>
+<li>Comparison</li>
+<li>Concat</li>
+<li>Constant</li>
+<li>Convolution2d</li>
+<li>Convolution3d</li>
+<li>DepthToSpace</li>
+<li>DepthwiseConvolution2d</li>
+<li>Dequantize</li>
+<li>DetectionPostProcess</li>
+<li>Division</li>
+<li>ElementwiseUnary</li>
+<li>Fill</li>
+<li>Floor</li>
+<li>FullyConnected</li>
+<li>Gather</li>
+<li>GatherNd</li>
+<li>Input</li>
+<li>InstanceNormalization</li>
+<li>L2Normalization</li>
+<li>Logical</li>
+<li>LogSoftmax</li>
+<li>Lstm</li>
+<li>Maximum</li>
+<li>Mean</li>
+<li>Merge</li>
+<li>Minimum</li>
+<li>Multiplication</li>
+<li>Normalization</li>
+<li>Output</li>
+<li>Pad (Constant, Symmetric, Reflect)</li>
+<li>Permute</li>
+<li>Pooling2d</li>
+<li>Pooling3d</li>
+<li>Prelu</li>
+<li>QLstm</li>
+<li>Quantize</li>
+<li>QuantizedLstm</li>
+<li>Rank</li>
+<li>Reduce</li>
+<li>Reshape</li>
+<li>Resize</li>
+<li>Shape</li>
+<li>Slice</li>
+<li>Softmax</li>
+<li>SpaceToBatchNd</li>
+<li>SpaceToDepth</li>
+<li>Splitter</li>
+<li>Stack</li>
+<li>StandIn</li>
+<li>StridedSlice</li>
+<li>Subtraction</li>
+<li>Switch</li>
+<li>Transpose</li>
+<li>TransposeConvolution2d</li>
+<li>UnidirectionalSequenceLstm</li>
+</ul>
+<p>More machine learning layers will be supported in future releases.</p>
+<h2><a class="anchor" id="serializersupportdeprecated"></a>
+Deprecated layers</h2>
+<p>Some layers have been deprecated and replaced by others layers. In order to maintain backward compatibility, serializations of these deprecated layers will deserialize to the layers that have replaced them, as follows:</p>
+<ul>
+<li>Abs will deserialize as ElementwiseUnary</li>
+<li>Equal will deserialize as Comparison</li>
+<li>Greater will deserialize as Comparison</li>
+<li>Merger will deserialize as Concat</li>
+<li>ResizeBilinear will deserialize as Resize</li>
+<li>Rsqrt will deserialize as ElementwiseUnary <br />
+<br />
+<br />
+<br />
+ </li>
+</ul>
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