Make samples visible in doxygen

 * uses the @example doxygen command to add all our simple examples
   into an 'Examples' tab in the doxygen documentation

Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: Ie8ae19ca471a0616eeea7f708d547388c8ee860e
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>

3 files changed, 45 insertions, 3 deletions

diff --git a/docs/01_01_parsers.dox b/docs/01_01_parsers.dox
index 3ac5b27735..97497fe016 100644
--- a/docs/01_01_parsers.dox
+++ b/docs/01_01_parsers.dox
@@ -22,7 +22,7 @@ bindings take a look into the @ref md_python_pyarmnn_README section.
 
 
 
-@section S5_onnx_parser ArmNN Onnx Parser
+@section S5_onnx_parser Arm NN Onnx Parser
 
 `armnnOnnxParser` is a library for loading neural networks defined in ONNX protobuf files into the Arm NN runtime.
 
@@ -92,7 +92,7 @@ More machine learning operators will be supported in future releases.
 
 
 
-@section S6_tf_lite_parser ArmNN Tf Lite Parser
+@section S6_tf_lite_parser Arm NN Tf Lite Parser
 
 `armnnTfLiteParser` is a library for loading neural networks defined by TensorFlow Lite FlatBuffers files
 into the Arm NN runtime.
diff --git a/docs/Doxyfile b/docs/Doxyfile
index 16510041cf..3fc872eda2 100644
--- a/docs/Doxyfile
+++ b/docs/Doxyfile
@@ -840,7 +840,8 @@ INPUT                  = ./docs/01_00_software_tools.dox \
                          ./InstallationViaAptRepository.md \
                          ./ContributorGuide.md \
                          ./BuildGuideAndroidNDK.md \
-                         ./BuildGuideCrossCompilation.md
+                         ./BuildGuideCrossCompilation.md \
+                         ./samples/examples.dox
 
 # This tag can be used to specify the character encoding of the source files
 # that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses
diff --git a/samples/examples.dox b/samples/examples.dox
new file mode 100644
index 0000000000..e0b0ea345e
--- /dev/null
+++ b/samples/examples.dox
@@ -0,0 +1,41 @@
+/// Copyright (c) 2021 ARM Limited and Contributors. All rights reserved.
+///
+/// SPDX-License-Identifier: MIT
+///
+
+namespace armnn
+{
+/**
+This is a very simple example which uses the Arm NN SDK API to create a neural network which consists of
+nothing else but a single fully connected layer with a single weights value. It's as minimalistic as it can get.
+
+@note Most of our users won't use our API to create a network manually. Usually you would use one of our software
+      tools like the @ref S6_tf_lite_parser "TfLite Parser" that will translate a TfLite model into Arm NN for you.
+      Still it's a very nice example to see how an Arm NN network is created, optimized and executed.
+
+      (You can find more complex examples using the TfLite Parser in samples/ObjectDetection and
+       samples/SpeechRecognition. And another example using @ref md_python_pyarmnn_README "PyArmnn" in
+       samples/ImageClassification)
+@example SimpleSample.cpp
+**/
+
+/**
+This is simple example that shows how to use a dynamic backend. Dynamic Backends can be compiled as standalone
+against Arm NN and can be loaded by Arm NN dynamically at runtime. This way you can quickly integrate new backends
+without having to worry or recompile Arm NN.
+
+This example makes use of a very simplistic dynamic backend called 'SampleDynamic'. There is a guide that tells you
+more about dynamic backends and how this particular backend was created so you can create a dynamic backend
+yourself @ref md_src_dynamic_README.
+@example DynamicSample.cpp
+**/
+
+/**
+This example is basically a copy of the SimpleSample example. But it makes use of a CustomAllocator to allocate
+memory for the inputs, outputs and inter layer memory.
+
+@note This is currently an experimental interface
+@example CustomMemoryAllocatorSample.cpp
+**/
+
+}