IVGCVSW-7255 Update Doxygen Documentation and publish on GitHub.

* Updating Doxygen documentation for 23.02 release. Signed-off-by: David Monahan <david.monahan@arm.com> Change-Id: I545574ff7664b4595d2fe6a91a3c35d2ad55df82
author: David Monahan <david.monahan@arm.com> 2023-03-22 16:48:58 +0000
committer: David Monahan <david.monahan@arm.com> 2023-03-22 16:48:58 +0000
commit: ae050524109f1ce827962665436ef7430f2ac479 (patch)
tree: a087fe0c77570971dd7979f2757426c24e91afc7 /23.02/operator_list.xhtml
parent: 8d2ca734165a068478df7cffa46185680b05cd20 (diff)
download: armnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz
1 files changed, 80 insertions, 75 deletions
diff --git a/23.02/operator_list.xhtml b/23.02/operator_list.xhtml
index 163f58c3d6..a7105c7347 100644
--- a/23.02/operator_list.xhtml
+++ b/23.02/operator_list.xhtml
@@ -8,7 +8,7 @@
 <head>
 <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
 <meta http-equiv="X-UA-Compatible" content="IE=9"/>
-<meta name="generator" content="Doxygen 1.8.13"/>
+<meta name="generator" content="Doxygen 1.8.17"/>
 <meta name="robots" content="NOINDEX, NOFOLLOW" />
 <meta name="viewport" content="width=device-width, initial-scale=1"/>
 <title>ArmNN: Arm NN Operators</title>
@@ -19,9 +19,6 @@
 <script type="text/javascript" src="resize.js"></script>
 <script type="text/javascript" src="navtreedata.js"></script>
 <script type="text/javascript" src="navtree.js"></script>
-<script type="text/javascript">
-  $(document).ready(initResizable);
-</script>
 <link href="search/search.css" rel="stylesheet" type="text/css"/>
 <script type="text/javascript" src="search/searchdata.js"></script>
 <script type="text/javascript" src="search/search.js"></script>
@@ -30,7 +27,8 @@
     extensions: ["tex2jax.js"],
     jax: ["input/TeX","output/HTML-CSS"],
 });
-</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
+</script>
+<script type="text/javascript" async="async" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
 <link href="doxygen.css" rel="stylesheet" type="text/css" />
 <link href="stylesheet.css" rel="stylesheet" type="text/css"/>
 </head>
@@ -51,18 +49,21 @@
 </table>
 </div>
 <!-- end header part -->
-<!-- Generated by Doxygen 1.8.13 -->
+<!-- Generated by Doxygen 1.8.17 -->
 <script type="text/javascript">
+/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
 var searchBox = new SearchBox("searchBox", "search",false,'Search');
+/* @license-end */
 </script>
 <script type="text/javascript" src="menudata.js"></script>
 <script type="text/javascript" src="menu.js"></script>
 <script type="text/javascript">
+/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
 $(function() {
   initMenu('',true,false,'search.php','Search');
   $(document).ready(function() { init_search(); });
 });
-</script>
+/* @license-end */</script>
 <div id="main-nav"></div>
 </div><!-- top -->
 <div id="side-nav" class="ui-resizable side-nav-resizable">
@@ -76,7 +77,9 @@ $(function() {
   </div>
 </div>
 <script type="text/javascript">
-$(document).ready(function(){initNavTree('operator_list.xhtml','');});
+/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
+$(document).ready(function(){initNavTree('operator_list.xhtml',''); initResizable(); });
+/* @license-end */
 </script>
 <div id="doc-content">
 <!-- window showing the filter options -->
@@ -93,7 +96,7 @@ $(document).ready(function(){initNavTree('operator_list.xhtml','');});
 </iframe>
 </div>
 
-<div class="header">
+<div class="PageDoc"><div class="header">
   <div class="headertitle">
 <div class="title">Arm NN Operators </div>  </div>
 </div><!--header-->
@@ -202,7 +205,7 @@ All </li>
 </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>
+<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>
@@ -286,7 +289,7 @@ All </li>
 </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>
+<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>
@@ -358,7 +361,7 @@ All </li>
 </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>
+<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>
@@ -480,7 +483,7 @@ All </li>
 </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>
+<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>
@@ -538,7 +541,7 @@ NCHW </li>
 </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>
+<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>
@@ -592,7 +595,7 @@ NCHW </li>
 </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>
+<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>
@@ -722,7 +725,7 @@ All </li>
 </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>
+<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>
@@ -786,7 +789,7 @@ All </li>
 </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>
+<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>
@@ -848,7 +851,7 @@ All </li>
 </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>
+<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>
@@ -902,7 +905,7 @@ All </li>
 </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>
+<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>
@@ -948,7 +951,7 @@ All </li>
 </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>
+<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>
@@ -994,7 +997,7 @@ All </li>
 </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>
+<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>
@@ -1070,7 +1073,7 @@ NCHW </li>
 </table>
 </td></tr>
 <tr>
-<td rowspan="3"><a class="el" href="classarmnn_1_1_convolution3d_layer.xhtml" title="This layer represents a convolution 3d operation. ">Convolution3dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute a 3D convolution operation. </td><td rowspan="3"><ul>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_convolution3d_layer.xhtml" title="This layer represents a convolution 3d operation.">Convolution3dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to compute a 3D convolution operation. </td><td rowspan="3"><ul>
 <li>
 N/A </li>
 </ul>
@@ -1118,7 +1121,7 @@ N/A </li>
 </ul>
 </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>
+<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>
@@ -1148,7 +1151,7 @@ All </li>
 </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>
+<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>
@@ -1202,7 +1205,7 @@ NCHW </li>
 </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>
+<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>
@@ -1278,7 +1281,7 @@ NCHW </li>
 </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>
+<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>
@@ -1348,7 +1351,7 @@ All </li>
 </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>
+<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>
@@ -1390,7 +1393,7 @@ All </li>
 </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>
+<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>
@@ -1526,7 +1529,7 @@ All </li>
 </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>
+<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>
@@ -1594,7 +1597,7 @@ All </li>
 </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>
+<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>
@@ -1610,7 +1613,7 @@ All </li>
 </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>
+<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>
@@ -1654,7 +1657,7 @@ All </li>
 </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>
+<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>
@@ -1702,7 +1705,7 @@ All </li>
 </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>
+<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>
@@ -1772,7 +1775,7 @@ NCHW </li>
 </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>
+<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>
@@ -1824,7 +1827,7 @@ All </li>
 </table>
 </td></tr>
 <tr>
-<td rowspan="3"><a class="el" href="classarmnn_1_1_gather_nd_layer.xhtml" title="This layer represents a GatherNd operator. ">GatherNdLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform the gatherNd operation. </td><td rowspan="3"><ul>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_gather_nd_layer.xhtml" title="This layer represents a GatherNd operator.">GatherNdLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform the gatherNd operation. </td><td rowspan="3"><ul>
 <li>
 N/A </li>
 </ul>
@@ -1900,7 +1903,7 @@ All </li>
 </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>
+<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>
@@ -1916,7 +1919,7 @@ All </li>
 </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>
+<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>
@@ -1968,7 +1971,7 @@ NCHW </li>
 </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>
+<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>
@@ -2026,7 +2029,7 @@ NCHW </li>
 </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>
+<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>
@@ -2082,7 +2085,7 @@ All </li>
 </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>
+<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>
@@ -2126,7 +2129,7 @@ All </li>
 </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>
+<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>
@@ -2174,7 +2177,7 @@ All </li>
 </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>
+<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>
@@ -2214,7 +2217,7 @@ All </li>
 </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>
+<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>
@@ -2284,7 +2287,7 @@ All </li>
 </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>
+<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>
@@ -2346,7 +2349,7 @@ All </li>
 </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>
+<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>
@@ -2398,7 +2401,7 @@ All </li>
 </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>
+<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>
@@ -2438,7 +2441,7 @@ All </li>
 </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>
+<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>
@@ -2500,7 +2503,7 @@ All </li>
 </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>
+<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>
@@ -2570,7 +2573,7 @@ All </li>
 </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>
+<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>
@@ -2644,7 +2647,7 @@ All </li>
 </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>
+<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>
@@ -2702,7 +2705,7 @@ NCHW </li>
 </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>
+<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>
@@ -2718,7 +2721,7 @@ All </li>
 </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>
+<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>
@@ -2774,7 +2777,7 @@ NCHW </li>
 </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>
+<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>
@@ -2828,7 +2831,7 @@ NCHW </li>
 </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 2D pooling with the specified pooling operation. </td><td rowspan="3"><ul>
+<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 2D pooling with the specified pooling operation. </td><td rowspan="3"><ul>
 <li>
 ANEURALNETWORKS_AVERAGE_POOL_2D </li>
 <li>
@@ -2898,7 +2901,7 @@ NCHW </li>
 </table>
 </td></tr>
 <tr>
-<td rowspan="3"><a class="el" href="classarmnn_1_1_pooling3d_layer.xhtml" title="This layer represents a pooling 3d operation. ">Pooling3dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform 3D pooling with the specified pooling operation. </td><td rowspan="3"><ul>
+<td rowspan="3"><a class="el" href="classarmnn_1_1_pooling3d_layer.xhtml" title="This layer represents a pooling 3d operation.">Pooling3dLayer</a> </td><td rowspan="3" style="width:200px;"><a class="el" href="classarmnn_1_1_layer.xhtml">Layer</a> to perform 3D pooling with the specified pooling operation. </td><td rowspan="3"><ul>
 <li>
 ANEURALNETWORKS_AVERAGE_POOL_3D </li>
 <li>
@@ -2942,9 +2945,10 @@ NDHWC </li>
 <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>
+</li>
 </ul>
-</td><td>N/A </td><td>N/A </td><td>N/A </td></tr>
+<br  />
+ N/A  </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>
@@ -3008,7 +3012,7 @@ All </li>
 </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>
+<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>
@@ -3130,7 +3134,7 @@ All </li>
 </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>
+<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>
@@ -3220,7 +3224,7 @@ All </li>
 </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>
+<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>
@@ -3294,7 +3298,7 @@ All </li>
 </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>
+<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>
@@ -3352,7 +3356,7 @@ All </li>
 </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>
+<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>
@@ -3566,7 +3570,7 @@ All </li>
 </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>
+<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>
@@ -3632,7 +3636,7 @@ All </li>
 </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>
+<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>
@@ -3686,7 +3690,7 @@ NCHW </li>
 </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>
+<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>
@@ -3740,7 +3744,7 @@ NCHW </li>
 </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>
+<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>
@@ -3790,7 +3794,7 @@ All </li>
 </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>
+<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>
@@ -3840,13 +3844,13 @@ All </li>
 </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>
+<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>
+<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>
@@ -3894,7 +3898,7 @@ All </li>
 </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>
+<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>
@@ -3966,7 +3970,7 @@ All </li>
 </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>
+<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>
@@ -4042,7 +4046,7 @@ NCHW </li>
 </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>
+<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>
@@ -4148,7 +4152,7 @@ All </li>
 </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>
+<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>
@@ -4193,13 +4197,14 @@ NCHW </li>
 </td></tr>
 </table>
 </div></div><!-- contents -->
+</div><!-- PageDoc -->
 </div><!-- doc-content -->
 <!-- start footer part -->
 <div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
   <ul>
-    <li class="footer">Generated on Fri Feb 24 2023 10:24:28 for ArmNN by
+    <li class="footer">Generated on Wed Mar 22 2023 15:53:03 for ArmNN by
     <a href="http://www.doxygen.org/index.html">
-    <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li>
+    <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.17 </li>
   </ul>
 </div>
 </body>
author	David Monahan <david.monahan@arm.com>	2023-03-22 16:48:58 +0000
committer	David Monahan <david.monahan@arm.com>	2023-03-22 16:48:58 +0000
commit	ae050524109f1ce827962665436ef7430f2ac479 (patch)
tree	a087fe0c77570971dd7979f2757426c24e91afc7 /23.02/operator_list.xhtml
parent	8d2ca734165a068478df7cffa46185680b05cd20 (diff)
download	armnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz