Update TfLite build guides

* Update path changes in building TF, CL
* Add option to switch off XNN package while building TFLite
* Remove obsolete links

Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ib2c932ceb8ef2be4e01ac77ac8f880f814d452cb

2 files changed, 19 insertions, 17 deletions

diff --git a/delegate/BuildGuideNative.md b/delegate/BuildGuideNative.md
index 932c74423a..4aa1af3ee9 100644
--- a/delegate/BuildGuideNative.md
+++ b/delegate/BuildGuideNative.md
@@ -65,7 +65,7 @@ found [here](https://docs.bazel.build/versions/master/install-compile-source.htm
 compile with CMake. Depending on your operating system and architecture there might be an easier way.
 ```bash
 wget -O cmake-3.16.0.tar.gz https://cmake.org/files/v3.16/cmake-3.16.0.tar.gz
-tar -xzf cmake-3.16.0.tar.gz -C $BASEDIR/cmake-3.16.0
+tar -xzf cmake-3.16.0.tar.gz -C $BASEDIR/
 
 # If you have an older CMake, remove installed in order to upgrade
 yes | sudo apt-get purge cmake
@@ -89,8 +89,10 @@ git checkout $(../armnn/scripts/get_tensorflow.sh -p) # Minimum version required
 Now the build process can be started. When calling "cmake", as below, you can specify a number of build
 flags. But if you have no need to configure your tensorflow build, you can follow the exact commands below:
 ```bash
-cmake $BASEDIR/tensorflow
-cmake --build $BASEDIR/tflite-output # This will be your DTFLITE_LIB_ROOT directory
+mkdir build # You are already inside $BASEDIR/tensorflow at this point
+cd build
+cmake $BASEDIR/tensorflow/tensorflow/lite -DTFLITE_ENABLE_XNNPACK=OFF
+cmake --build . # This will be your DTFLITE_LIB_ROOT directory
 ```
 
 ## Build Flatbuffers
@@ -123,7 +125,7 @@ To build the Arm Compute Library on your platform, download the Arm Compute Libr
 the version you want to use. Build it using `scons`.
 
 ```bash
-cd $HOME/armnn-devenv
+cd $BASEDIR
 git clone https://review.mlplatform.org/ml/ComputeLibrary 
 cd ComputeLibrary/
 git checkout $(../armnn/scripts/get_compute_library.sh -p) # e.g. v21.11
@@ -152,7 +154,7 @@ with the additional cmake arguments shown below
 cd $BASEDIR/armnn/delegate && mkdir build && cd build
 cmake .. -DCMAKE_BUILD_TYPE=release                               # A release build rather than a debug build.
          -DTENSORFLOW_ROOT=$BASEDIR/tensorflow \                  # The root directory where tensorflow can be found.
-         -DTFLITE_LIB_ROOT=$BASEDIR/tflite-output \               # Directory where tensorflow libraries can be found.
+         -DTFLITE_LIB_ROOT=$BASEDIR/tensorflow/build \               # Directory where tensorflow libraries can be found.
          -DFLATBUFFERS_ROOT=$BASEDIR/flatbuffers-1.12.0/install \ # Flatbuffers install directory.
          -DArmnn_DIR=$BASEDIR/armnn/build \                       # Directory where the Arm NN library can be found
          -DARMNN_SOURCE_DIR=$BASEDIR/armnn                        # The top directory of the Arm NN repository. 
@@ -199,7 +201,7 @@ cmake .. -DARMCOMPUTE_ROOT=$BASEDIR/ComputeLibrary \
          -DBUILD_UNIT_TESTS=0 \
          -DBUILD_ARMNN_TFLITE_DELEGATE=1 \
          -DTENSORFLOW_ROOT=$BASEDIR/tensorflow \
-         -DTFLITE_LIB_ROOT=$BASEDIR/tflite-output \
+         -DTFLITE_LIB_ROOT=$BASEDIR/tensorflow/build \
          -DFLATBUFFERS_ROOT=$BASEDIR/flatbuffers-1.12.0/install
 make
 ```
@@ -227,11 +229,11 @@ wget https://github.com/ARM-software/ML-zoo/blob/master/models/image_classificat
 ```
 
 ## Execute the benchmarking tool with the Arm NN delegate
+You are already at $BASEDIR/benchmarking from the previous stage.
 ```bash
-cd $BASEDIR/benchmarking
 LD_LIBRARY_PATH=../armnn/build ./benchmark_model --graph=mobilenet_v2_1.0_224_quantized_1_default_1.tflite --external_delegate_path="../armnn/build/delegate/libarmnnDelegate.so" --external_delegate_options="backends:CpuAcc;logging-severity:info"
 ```
-The "external_delegate_options" here are specific to the Arm NN delegate. They are used to specify a target Arm NN backend or to enable/disable various options in Arm NN. A full description can be found in the parameters of function [tflite_plugin_create_delegate](namespacetflite.xhtml).
+The "external_delegate_options" here are specific to the Arm NN delegate. They are used to specify a target Arm NN backend or to enable/disable various options in Arm NN. A full description can be found in the parameters of function tflite_plugin_create_delegate.
 
 # Integrate the Arm NN TfLite Delegate into your project
 
@@ -256,4 +258,4 @@ armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get());
 
 For further information on using TfLite Delegates please visit the [tensorflow website](https://www.tensorflow.org/lite/guide)
 
-For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function [tflite_plugin_create_delegate](namespacetflite.xhtml).
+For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function tflite_plugin_create_delegate.
diff --git a/delegate/DelegateQuickStartGuide.md b/delegate/DelegateQuickStartGuide.md
index b581bce62c..ce58624677 100644
--- a/delegate/DelegateQuickStartGuide.md
+++ b/delegate/DelegateQuickStartGuide.md
@@ -1,5 +1,5 @@
 # TfLite Delegate Quick Start Guide
-If you have downloaded the ArmNN Github binaries or built the TfLite delegate yourself, then this tutorial will show you how you can
+If you have downloaded the Arm NN Github binaries or built the TfLite delegate yourself, then this tutorial will show you how you can
 integrate it into TfLite to run models using python.
 
 Here is an example python script showing how to do this. In this script we are making use of the 
@@ -13,7 +13,7 @@ import tflite_runtime.interpreter as tflite
 # (if you are using the complete tensorflow package you can find load_delegate in tf.experimental.load_delegate)
 armnn_delegate = tflite.load_delegate( library="<path-to-armnn-binaries>/libarmnnDelegate.so",
                                        options={"backends": "CpuAcc,GpuAcc,CpuRef", "logging-severity":"info"})
-# Delegates/Executes all operations supported by ArmNN to/with ArmNN
+# Delegates/Executes all operations supported by Arm NN to/with Arm NN
 interpreter = tflite.Interpreter(model_path="<your-armnn-repo-dir>/delegate/python/test/test_data/mock_model.tflite", 
                                  experimental_delegates=[armnn_delegate])
 interpreter.allocate_tensors()
@@ -36,14 +36,14 @@ print(output_data)
 
 # Prepare the environment
 Pre-requisites:
- * Dynamically build Arm NN Delegate library or download the ArmNN binaries
+ * Dynamically build Arm NN Delegate library or download the Arm NN binaries
  * python3 (Depends on TfLite version)
  * virtualenv
  * numpy (Depends on TfLite version)
  * tflite_runtime (>=2.5, depends on Arm NN Delegate)
 
 If you haven't built the delegate yet then take a look at the [build guide](./BuildGuideNative.md). Otherwise, 
-you can download the binaries [here](https://github.com/ARM-software/armnn/releases/tag/v21.11)
+you can download the binaries [here](https://github.com/ARM-software/armnn/releases/)
 
 We recommend creating a virtual environment for this tutorial. For the following code to work python3 is needed. Please
 also check the documentation of the TfLite version you want to use. There might be additional prerequisites for the python
@@ -88,16 +88,16 @@ python ExternalDelegatePythonTutorial.py
 ```
 The output should look similar to this:
 ```bash
-Info: ArmNN v27.0.0
+Info: Arm NN v28.0.0
 
 Info: Initialization time: 0.56 ms
 
-INFO: TfLiteArmnnDelegate: Created TfLite ArmNN delegate.
+INFO: TfLiteArmnnDelegate: Created TfLite Arm NN delegate.
 [[ 12 123  16  12  11  14  20  16  20  12]]
 Info: Shutdown time: 0.28 ms
 ```
 
-For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function [tflite_plugin_create_delegate](namespacetflite.xhtml).
+For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function tflite_plugin_create_delegate.
 
 You can also test the functionality of the external delegate adaptor by running some unit tests:
 ```bash
@@ -105,4 +105,4 @@ pip install pytest
 cd armnn/delegate/python/test
 # You can deselect tests that require backends that your hardware doesn't support using markers e.g. -m "not GpuAccTest"
 pytest --delegate-dir="<path-to-armnn-binaries>/libarmnnDelegate.so" -m "not GpuAccTest"
-```
\ No newline at end of file
+```