From a4f45cf04de2ae108c21cc90cfe08caa47aa6aeb Mon Sep 17 00:00:00 2001
From: Colm Donelan <Colm.Donelan@arm.com>
Date: Thu, 14 May 2020 07:45:44 +0100
Subject: MLCE-193 README and FAQ updates.

* Add FAQ entry about ArmNN and ComputeLibrary mismatch
* Add documentation reference to README that dynamically referrs to
  gh branch on GitHub.
* Update ONNXSupport.mb to fix broken links.

Signed-off-by: Colm Donelan <Colm.Donelan@arm.com>
Change-Id: I6390d87443c57cc43e27ea0a27f830f8fc25244d
---
 README.md                          |  2 ++
 docs/FAQ.md                        | 19 +++++++++++++------
 src/armnnOnnxParser/OnnxSupport.md |  6 +++---
 3 files changed, 18 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index 9c404f885d..25dab0edf9 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,8 @@ There is a getting started guide here using ONNX: <https://developer.arm.com/sol
 
 There is a guide for backend development: [Backend development guide](src/backends/README.md)
 
+API Documentation is available at https://github.com/ARM-software/armnn/wiki/Documentation.
+
 ### Build Instructions
 
 Arm tests the build system of Arm NN with the following build environments:
diff --git a/docs/FAQ.md b/docs/FAQ.md
index 2f06df62bb..1df82e8a63 100644
--- a/docs/FAQ.md
+++ b/docs/FAQ.md
@@ -3,13 +3,20 @@ Frequently asked questions
 
 These are issues that have been commonly seen when using ArmNN.
 
+Problems seen when trying to build armnn and ComputeLibrary obtained from GitHub
+-----------------------------------------------------------------------------
+
+Some users have encountered difficulties when attempting to build armnn and ComputeLibrary obtained from GitHub. The build generally fails reporting missing dependencies or fields in aclCommon, backendsCommon, cl or neon. These errors can look like this:
+
+error: ‘HARD_SWISH’ is not a member of ‘AclActivationFunction {aka arm_compute::ActivationLayerInfo::ActivationFunction}’
+
+The most common reason for these errors are a mismatch between armnn and clframework revisions. For any version of ArmNN the coresponding version of ComputeLibrary is detailed in scripts/get_compute_library.sh as DEFAULT_CLFRAMEWORKREVISION
+
+On *nix like systems running this script will checkout ComputeLibrary, with the current default SHA, into ../../clframework/ relative to the location of the script.
+
 Segmentation fault following a failed call to armnn::Optimize using CpuRef backend.
 ---------------------------------------------------------
 
-In some error scenarios of calls to armnn::Optimize a null pointer may be
-returned. This contravenes the function documentation however, it can
-happen. Users are advised to check the value returned from the function as a
-precaution.
+In some error scenarios of calls to armnn::Optimize a null pointer may be returned. This contravenes the function documentation however, it can happen. Users are advised to check the value returned from the function as a precaution.
 
-If you encounter this problem and are able to isolate it consider contributing
-a solution.
+If you encounter this problem and are able to isolate it consider contributing a solution.
diff --git a/src/armnnOnnxParser/OnnxSupport.md b/src/armnnOnnxParser/OnnxSupport.md
index 4a9645d67a..051e2c908b 100644
--- a/src/armnnOnnxParser/OnnxSupport.md
+++ b/src/armnnOnnxParser/OnnxSupport.md
@@ -76,8 +76,8 @@ The parser only supports constant weights in a fully connected layer.
 
 Arm tested these operators with the following ONNX fp32 neural networks:
 
-* Simple MNIST. See the ONNX [MNIST documentation](https://github.com/onnx/models/tree/master/mnist) for more information.
+* Mobilenet_v2. See the ONNX [MobileNet documentation](https://github.com/onnx/models/tree/master/vision/classification/mobilenet) for more information.
 
-* Mobilenet_v2. See the ONNX [MobileNet documentation](https://github.com/onnx/models/tree/master/models/image_classification/mobilenet) for more information.
+* Simple MNIST. This is no longer directly documented by ONNX. The model and test data may be downloaded [from the ONNX model zoo](https://onnxzoo.blob.core.windows.net/models/opset_8/mnist/mnist.tar.gz).
 
-More machine learning operators will be supported in future releases.
\ No newline at end of file
+More machine learning operators will be supported in future releases as time allows. If you require specific operator support contribution are welcome.
-- 
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