IVGCVSW-7701 Update docu with new ops in 23.08

* Add supported ops in SupportLibrary
* Removed tableofcontents which was never used
* Separated pages for serializer and deserializer
* Removed link to delegate/IntegrateDelegateIntoPython.md which was removed
* Arranged components in alphabetical order

Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ic7a62d0af092f97c49f8ace1a8f8f31d9152b3f8

12 files changed, 489 insertions, 211 deletions

diff --git a/docs/02_operator_list.dox b/docs/02_operator_list.dox
index d7b2bb5bb8..e3c9f8c1f2 100644
--- a/docs/02_operator_list.dox
+++ b/docs/02_operator_list.dox
@@ -8,7 +8,6 @@ namespace armnn
 /**
 @page operator_list Arm NN Operators
 
-@tableofcontents
 
 @section S5_1_operator_list Arm NN Operators
 
diff --git a/docs/03_build_guides.dox b/docs/03_build_guides.dox
index f2697d81c0..3671c17844 100644
--- a/docs/03_build_guides.dox
+++ b/docs/03_build_guides.dox
@@ -7,7 +7,6 @@ namespace armnn
 {
 /**
 @page buildguides Build Guides
-@tableofcontents
 
 This page links all guides to build and/or install Arm NN tools hosted in our repository.
 You can find additional tutorials on
diff --git a/docs/04_contributor.dox b/docs/04_contributor.dox
index 5cbb6c3b8c..a12b73f10d 100644
--- a/docs/04_contributor.dox
+++ b/docs/04_contributor.dox
@@ -8,7 +8,6 @@ namespace armnn
 /**
 
 @page contribguides Contribution Guides
-@tableofcontents
 
 This is a collection of guides that should help you contribute code to Arm NN. Before you get started, please
 take a look into our /ref md_Contributor_Guide section.
diff --git a/docs/05_00_software_components.dox b/docs/05_00_software_components.dox
index 756f336416..0663599a96 100644
--- a/docs/05_00_software_components.dox
+++ b/docs/05_00_software_components.dox
@@ -11,14 +11,15 @@ namespace armnn
 On this page you can find all software components contained in the Arm NN repository. You will find links to how-to guides and
 other helpful information in each section.
 
- - @subpage delegate
+ - @subpage md_src_armnnConverter_README
+ - @subpage deserializer
  - @subpage supportlibrary
- - @subpage runtimeoptions
  - @subpage parsers
  - @subpage md_python_pyarmnn_README
+ - @subpage runtimeoptions
  - @subpage serializer
- - @subpage deserializer
- - @subpage md_src_armnnConverter_README
+ - @subpage delegate
+ 
 **/
 }
 
diff --git a/docs/05_01_parsers.dox b/docs/05_01_parsers.dox
index 6050d65953..f92504b389 100644
--- a/docs/05_01_parsers.dox
+++ b/docs/05_01_parsers.dox
@@ -8,7 +8,7 @@ namespace armnn
 /**
 @page parsers Parsers
 
-@tableofcontents
+
 Execute models from different machine learning platforms efficiently with our parsers. Simply choose a parser according
 to the model you want to run e.g. If you've got a model in onnx format (<model_name>.onnx) use our onnx-parser.
 
diff --git a/docs/05_02_deserializer_serializer.dox b/docs/05_02_deserializer_serializer.dox
deleted file mode 100644
index ab821b8d66..0000000000
--- a/docs/05_02_deserializer_serializer.dox
+++ /dev/null
@@ -1,192 +0,0 @@
-/// Copyright (c) 2021-2023 ARM Limited and Contributors. All rights reserved.
-///
-/// SPDX-License-Identifier: MIT
-///
-
-namespace armnn
-{
-/**
-@page serializer Serializer
-@tableofcontents
-
-The `armnnSerializer` is a library for serializing an Arm NN network to a stream.
-
-@section serializersupport Supported Layers
-
-This reference guide provides a list of layers which can be serialized by the Arm NN SDK.
-
-@subsection serializersupportflully Fully supported
-
-The Arm NN SDK Serializer currently supports the following layers:
-
-- Activation
-- Addition
-- ArgMinMax
-- BatchMatMul
-- BatchToSpaceNd
-- BatchNormalization
-- Cast
-- ChannelShuffle
-- Comparison
-- Concat
-- Constant
-- Convolution2d
-- Convolution3d
-- DepthToSpace
-- DepthwiseConvolution2d
-- Dequantize
-- DetectionPostProcess
-- Division
-- ElementwiseUnary
-- Fill
-- Floor
-- FullyConnected
-- Gather
-- GatherNd
-- Input
-- InstanceNormalization
-- L2Normalization
-- Logical
-- LogSoftmax
-- Lstm
-- Maximum
-- Mean
-- Merge
-- Minimum
-- Multiplication
-- Normalization
-- Output
-- Pad (Constant, Symmetric, Reflect)
-- Permute
-- Pooling2d
-- Pooling3d
-- Prelu
-- QLstm
-- Quantize
-- QuantizedLstm
-- Rank
-- Reduce
-- Reshape
-- Resize
-- ReverseV2
-- Shape
-- Slice
-- Softmax
-- SpaceToBatchNd
-- SpaceToDepth
-- Splitter
-- Stack
-- StandIn
-- StridedSlice
-- Subtraction
-- Switch
-- Transpose
-- TransposeConvolution2d
-- UnidirectionalSequenceLstm
-
-More machine learning layers will be supported in future releases.
-
-@subsection serializersupportdeprecated Deprecated layers
-
-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:
-
-- Abs will deserialize as ElementwiseUnary
-- Equal will deserialize as Comparison
-- Greater will deserialize as Comparison
-- Merger will deserialize as Concat
-- ResizeBilinear will deserialize as Resize
-- Rsqrt will deserialize as ElementwiseUnary
-<br/><br/><br/><br/>
-
-@page deserializer Deserializer
-@tableofcontents
-
-The `armnnDeserializer` is a library for loading neural networks defined by Arm NN FlatBuffers files
-into the Arm NN runtime.
-
-@section deserializersupport Supported Layers
-
-This reference guide provides a list of layers which can be deserialized by the Arm NN SDK.
-
-@subsection deserializersupportfully Fully supported
-
-The Arm NN SDK Deserialize parser currently supports the following layers:
-
-- Abs
-- Activation
-- Addition
-- ArgMinMax
-- BatchMatMul
-- BatchToSpaceNd
-- BatchNormalization
-- Cast
-- ChannelShuffle
-- Concat
-- Comparison
-- Constant
-- Convolution2d
-- DepthToSpace
-- DepthwiseConvolution2d
-- Dequantize
-- DetectionPostProcess
-- Division
-- ElementwiseUnary
-- Fill
-- Floor
-- FullyConnected
-- Gather
-- GatherNd
-- Input
-- InstanceNormalization
-- L2Normalization
-- Logical
-- LogSoftmax
-- Lstm
-- Maximum
-- Mean
-- Merge
-- Minimum
-- Multiplication
-- Normalization
-- Output
-- Pad
-- Permute
-- Pooling2d
-- Pooling3d
-- Prelu
-- Quantize
-- QLstm
-- QuantizedLstm
-- Rank
-- Reduce
-- Reshape
-- Resize
-- ResizeBilinear
-- ReverseV2
-- Slice
-- Softmax
-- SpaceToBatchNd
-- SpaceToDepth
-- Splitter
-- Stack
-- StandIn
-- StridedSlice
-- Subtraction
-- Switch
-- Transpose
-- TransposeConvolution2d
-- UnidirectionalSequenceLstm
-
-More machine learning layers will be supported in future releases.
-
-@subsection deserializersupportdeprecated Deprecated layers
-
-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:
-
-- Equal will deserialize as Comparison
-- Merger will deserialize as Concat
-- Greater will deserialize as Comparison
-- ResizeBilinear will deserialize as Resize
-
-**/
-}
diff --git a/docs/05_02_serializer.dox b/docs/05_02_serializer.dox
new file mode 100644
index 0000000000..a31917846e
--- /dev/null
+++ b/docs/05_02_serializer.dox
@@ -0,0 +1,162 @@
+/// Copyright (c) 2021-2023 ARM Limited and Contributors. All rights reserved.
+///
+/// SPDX-License-Identifier: MIT
+///
+
+namespace armnn
+{
+/**
+@page serializer Serializer
+
+The `armnnSerializer` is a library for serializing an Arm NN network to a stream.
+
+@section serializersupport Supported Layers
+
+This reference guide provides a list of layers which can be serialized by the Arm NN SDK.
+
+The Arm NN SDK Serializer currently supports the following layers:
+
+- Activation
+
+- Addition
+
+- ArgMinMax
+
+- BatchMatMul
+
+- BatchToSpaceNd
+
+- BatchNormalization
+
+- Cast
+
+- ChannelShuffle
+
+- Comparison
+
+- Concat
+
+- Constant
+
+- Convolution2d
+
+- Convolution3d
+
+- DepthToSpace
+
+- DepthwiseConvolution2d
+
+- Dequantize
+
+- DetectionPostProcess
+
+- Division
+
+- ElementwiseUnary
+
+- Fill
+
+- Floor
+
+- FullyConnected
+
+- Gather
+
+- GatherNd
+
+- Input
+
+- InstanceNormalization
+
+- L2Normalization
+
+- Logical
+
+- LogSoftmax
+
+- Lstm
+
+- Maximum
+
+- Mean
+
+- Merge
+
+- Minimum
+
+- Multiplication
+
+- Normalization
+
+- Output
+
+- Pad (Constant, Symmetric, Reflect)
+
+- Permute
+
+- Pooling2d
+
+- Pooling3d
+
+- Prelu
+
+- QLstm
+
+- Quantize
+
+- QuantizedLstm
+
+- Rank
+
+- Reduce
+
+- Reshape
+
+- Resize
+
+- ReverseV2
+
+- Shape
+
+- Slice
+
+- Softmax
+
+- SpaceToBatchNd
+
+- SpaceToDepth
+
+- Splitter
+
+- Stack
+
+- StandIn
+
+- StridedSlice
+
+- Subtraction
+
+- Switch
+
+- Transpose
+
+- TransposeConvolution2d
+
+- UnidirectionalSequenceLstm
+
+
+More machine learning layers will be supported in future releases.
+
+@section serializersupportdeprecated Deprecated layers
+
+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:
+
+- Abs will deserialize as ElementwiseUnary
+- Equal will deserialize as Comparison
+- Greater will deserialize as Comparison
+- Merger will deserialize as Concat
+- ResizeBilinear will deserialize as Resize
+- Rsqrt will deserialize as ElementwiseUnary
+
+**/
+}
diff --git a/docs/05_03_delegate.dox b/docs/05_03_delegate.dox
index 153d1eb4ca..624f06f7c2 100644
--- a/docs/05_03_delegate.dox
+++ b/docs/05_03_delegate.dox
@@ -7,7 +7,6 @@ namespace armnn
 {
 /**
 @page delegate TfLite Delegate
-@tableofcontents
 
 
 @section delegateintro About the delegate
@@ -22,14 +21,12 @@ words, every TfLite model can be executed and every operation in your model that
 That is the reason why the armnnDelegate is our recommended way to accelerate TfLite models.
 
 If you need help building the armnnDelegate, please take a look at our [build guide](delegate/BuildGuideNative.md).
-An example how to setup TfLite to integrate the armnnDelegate can be found in this
-guide: [Integrate the delegate into python](delegate/IntegrateDelegateIntoPython.md)
 
 
 @section delegatesupport Supported Operators
 This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports.
 
-@subsection delegatefullysupported Fully supported
+@section delegatefullysupported Fully supported
 
 The Arm NN SDK TensorFlow Lite delegate currently supports the following operators:
 
diff --git a/docs/05_04_supportlibrary.dox b/docs/05_04_supportlibrary.dox
index 689b8af018..c96c6f00d6 100644
--- a/docs/05_04_supportlibrary.dox
+++ b/docs/05_04_supportlibrary.dox
@@ -7,21 +7,175 @@ namespace armnn
 {
 /**
 @page supportlibrary NNAPI Support Library
-@tableofcontents
 
 
 @section supportlibraryintro About the NNAPI Support Library
 
 If you need help building the Arm NN NNAPI Support Library, please take a look at our [build guide](shim/BuildGuideShimSupportLibrary.md).
 
+@section sloptions Support Library Options
 
-@section slsupport Supported Operators
-This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports.
+The general list of runtime options are described in @subpage runtimeoptions
 
+@section slfullysupported Supported Operators
 
-@section sloptions Support Library Options
+The NNAPI Support Library currently supports the following operators:
 
-The general list of runtime options are described in @subpage runtimeoptions
+- ABS
+
+- ADD
+
+- ARGMAX
+
+- ARGMIN
+
+- AVERAGE_POOL_2D
+
+- BATCH_MATMUL
+
+- BATCH_TO_SPACE_ND
+
+- CAST
+
+- CONCATENATION
+
+- CONV_2D
+
+- DEPTH_TO_SPACE
+
+- DEPTHWISE_CONV_2D
+
+- DEQUANTIZE
+
+- DIV
+
+- ELU
+
+- EQUAL
+
+- EXP
+
+- EXPAND_DIMS
+
+- FILL
+
+- FLOOR
+
+- FULLY_CONNECTED
+
+- GATHER
+
+- GREATER
+
+- GREATER_EQUAL
+
+- GROUPED_CONV_2D
+
+- HARD_SWISH
+
+- INSTANCE_NORMALIZATION
+
+- L2_NORMALIZATION
+
+- L2_POOL_2D
+
+- LESS
+
+- LESS_EQUAL
+
+- LOCAL_RESPONSE_NORMALIZATION
+
+- LOG
+
+- LOGICAL_AND
+
+- LOGICAL_NOT
+
+- LOGICAL_OR
+
+- LOGISTIC
+
+- LOG_SOFTMAX
+
+- LSTM
+
+- MAX_POOL_2D
+
+- MAXIMUM
+
+- MEAN
+
+- MINIMUM
+
+- MUL
+
+- NEG
+
+- NOT_EQUAL
+
+- PAD
+
+- PADV2
+
+- PRELU
+
+- POW
+
+- QUANTIZE
+
+- QUANTIZED_LSTM
+
+- QUANTIZED_16BIT_LSTM
+
+- RANK
+
+- REDUCE_MAX
+
+- REDUCE_MIN
+
+- REDUCE_PROD
+
+- REDUCE_SUM
+
+- RELU
+
+- RELU1
+
+- RELU6
+
+- RESHAPE
+
+- RESIZE_BILINEAR
+
+- RESIZE_NEAREST_NEIGHBOR
+
+- REVERSE
+
+- RSQRT
+
+- SIN
+
+- SOFTMAX
+
+- SPACE_TO_BATCH_ND
+
+- SPACE_TO_DEPTH
+
+- SQRT
+
+- SQUEEZE
+
+- STRIDED_SLICE
+
+- SUB
+
+- TILE
+
+- TRANSPOSE
+
+- TRANSPOSE_CONV_2D
+
+- TANH
 
 **/
 }
\ No newline at end of file
diff --git a/docs/05_05_runtimeoptions.dox b/docs/05_05_runtimeoptions.dox
index b5888eed60..cdb9a04768 100644
--- a/docs/05_05_runtimeoptions.dox
+++ b/docs/05_05_runtimeoptions.dox
@@ -7,7 +7,6 @@ namespace armnn
 {
 /**
 @page runtimeoptions Runtime options for Arm NN
-@tableofcontents
 
 Across all software interfaces to Arm NN there are a set of common
 configuration parameters. These parameters control how a model is loaded or
diff --git a/docs/05_06_deserializer.dox b/docs/05_06_deserializer.dox
new file mode 100644
index 0000000000..bf44dbf966
--- /dev/null
+++ b/docs/05_06_deserializer.dox
@@ -0,0 +1,159 @@
+/// Copyright (c) 2021-2023 ARM Limited and Contributors. All rights reserved.
+///
+/// SPDX-License-Identifier: MIT
+///
+
+namespace armnn
+{
+/**
+
+@page deserializer Deserializer
+
+The `armnnDeserializer` is a library for loading neural networks defined by Arm NN FlatBuffers files
+into the Arm NN runtime.
+
+@section deserializersupport Supported Layers
+
+The Arm NN SDK Deserialize parser currently supports the following layers:
+
+- Abs
+
+- Activation
+
+- Addition
+
+- ArgMinMax
+
+- BatchMatMul
+
+- BatchToSpaceNd
+
+- BatchNormalization
+
+- Cast
+
+- ChannelShuffle
+
+- Concat
+
+- Comparison
+
+- Constant
+
+- Convolution2d
+
+- DepthToSpace
+
+- DepthwiseConvolution2d
+
+- Dequantize
+
+- DetectionPostProcess
+
+- Division
+
+- ElementwiseUnary
+
+- Fill
+
+- Floor
+
+- FullyConnected
+
+- Gather
+
+- GatherNd
+
+- Input
+
+- InstanceNormalization
+
+- L2Normalization
+
+- Logical
+
+- LogSoftmax
+
+- Lstm
+
+- Maximum
+
+- Mean
+
+- Merge
+
+- Minimum
+
+- Multiplication
+
+- Normalization
+
+- Output
+
+- Pad
+
+- Permute
+
+- Pooling2d
+
+- Pooling3d
+
+- Prelu
+
+- Quantize
+
+- QLstm
+
+- QuantizedLstm
+
+- Rank
+
+- Reduce
+
+- Reshape
+
+- Resize
+
+- ResizeBilinear
+
+- ReverseV2
+
+- Slice
+
+- Softmax
+
+- SpaceToBatchNd
+
+- SpaceToDepth
+
+- Splitter
+
+- Stack
+
+- StandIn
+
+- StridedSlice
+
+- Subtraction
+
+- Switch
+
+- Transpose
+
+- TransposeConvolution2d
+
+- UnidirectionalSequenceLstm
+
+More machine learning layers will be supported in future releases.
+
+@section deserializersupportdeprecated Deprecated layers
+
+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:
+
+- Equal will deserialize as Comparison
+- Merger will deserialize as Concat
+- Greater will deserialize as Comparison
+- ResizeBilinear will deserialize as Resize
+
+**/
+}
diff --git a/docs/Doxyfile b/docs/Doxyfile
index 40761cd658..b163241624 100644
--- a/docs/Doxyfile
+++ b/docs/Doxyfile
@@ -819,10 +819,11 @@ INPUT                  = ./docs/01_00_quick_start.dox \
                          ./docs/04_contributor.dox \
                          ./docs/05_00_software_components.dox \
                          ./docs/05_01_parsers.dox \
-                         ./docs/05_02_deserializer_serializer.dox \
+                         ./docs/05_02_serializer.dox \
                          ./docs/05_03_delegate.dox \
                          ./docs/05_04_supportlibrary.dox \
                          ./docs/05_05_runtimeoptions.dox \
+                         ./docs/05_06_deserializer.dox \
                          ./docs/FAQ.md \
                          ./tests/ImageCSVFileGenerator/README.md \
                          ./tests/ImageTensorGenerator/README.md \