IVGCVSW-5744 Remove Tensorflow, Caffe and Quantizer from documentation

* Remove from .md files and Doxygen
* Remove from armnn/docker build
* Remove Tensorflow model format from ExecuteNetworkParams
* Remove Tensorflow model format from ImageTensorGenerator

Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: Id6ed4a7d90366c396e8e0395d0ce43a3bcddcee6

4 files changed, 3 insertions, 183 deletions

diff --git a/docs/01_00_software_tools.dox b/docs/01_00_software_tools.dox
index 9398b83ad8..e560f44882 100644
--- a/docs/01_00_software_tools.dox
+++ b/docs/01_00_software_tools.dox
@@ -16,7 +16,6 @@ other helpful information in each section.
  - @subpage md_python_pyarmnn_README
  - @subpage serializer
  - @subpage deserializer
- - @subpage md_src_armnnQuantizer_README
  - @subpage md_src_armnnConverter_README
  - @subpage md_tests_ImageCSVFileGenerator_README
  - @subpage md_tests_ImageTensorGenerator_README
@@ -34,8 +33,6 @@ namespace armnn
 
 @page md_python_pyarmnn_README PyArmNN
 
-@page md_src_armnnQuantizer_README Quantizer
-
 @page md_src_armnnConverter_README Converter
 
 @page md_tests_ModelAccuracyTool-Armnn_README ModelAccuracyTool
diff --git a/docs/01_01_parsers.dox b/docs/01_01_parsers.dox
index 6607921585..af87eba7af 100644
--- a/docs/01_01_parsers.dox
+++ b/docs/01_01_parsers.dox
@@ -10,67 +10,14 @@ namespace armnn
 
 @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 tensorflow format (<model_name>.pb) use our tensorflow-parser.
+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.
 
 If you would like to run a Tensorflow Lite (TfLite) model you probably also want to take a look at our @ref delegate.
 
 All parsers are written in C++ but it is also possible to use them in python. For more information on our python
 bindings take a look into the @ref md_python_pyarmnn_README section.
 
-
-
-@section S4_caffe_parser Arm NN Caffe Parser
-
-`armnnCaffeParser` is a library for loading neural networks defined in Caffe protobuf files into the Arm NN runtime.
-
-Please note that certain deprecated Caffe features are not supported by the armnnCaffeParser. If you think that Arm NN
-should be able to load your model according to the list of supported layers, but you are getting strange error
-messages, then try upgrading your model to the latest format using Caffe, either by saving it to a new file or using
-the upgrade utilities in `caffe/tools`.
-
-\b NOTE: The Arm NN Caffe Parser is deprecated in Arm NN 21.02 and will be removed in 21.05.
-
-## Caffe layers supported by the Arm NN SDK
-This reference guide provides a list of Caffe layers the Arm NN SDK currently supports.
-
-### Although some other neural networks might work, Arm tests the Arm NN SDK with Caffe implementations of the following neural networks:
-
-- AlexNet.
-- Cifar10.
-- Inception-BN.
-- Resnet_50, Resnet_101 and Resnet_152.
-- VGG_CNN_S, VGG_16 and VGG_19.
-- Yolov1_tiny.
-- Lenet.
-- MobileNetv1.
-- SqueezeNet v1.0 and SqueezeNet v1.1
-
-### The Arm NN SDK supports the following machine learning layers for Caffe networks:
-
-- Argmax, excluding the top_k and out_max_val parameters.
-- BatchNorm, in inference mode.
-- Convolution, excluding Weight Filler, Bias Filler, Engine, Force nd_im2col, and Axis parameters.
-- Deconvolution, excluding the Dilation Size, Weight Filler, Bias Filler, Engine, Force nd_im2col, and Axis parameters.
-
-  Caffe doesn't support depthwise convolution, the equivalent layer is implemented through the notion of groups. ArmNN supports groups this way:
-  - when group=1, it is a normal conv2d
-  - when group=#input_channels, we can replace it by a depthwise convolution
-  - when group>1 && group<#input_channels, we need to split the input into the given number of groups, apply a separate convolution and then merge the results
-- Concat, along the channel dimension only.
-- Dropout, in inference mode.
-- Eltwise, excluding the coeff parameter.
-- Inner Product, excluding the Weight Filler, Bias Filler, Engine, and Axis parameters.
-- Input.
-- LRN, excluding the Engine parameter.
-- Pooling, excluding the Stochastic Pooling and Engine parameters.
-- ReLU.
-- Scale.
-- Softmax, excluding the Axis and Engine parameters.
-- Split.
-
-More machine learning layers will be supported in future releases.
-
-<br/><br/><br/><br/>
+<br/><br/>
 
 
 
@@ -229,125 +176,6 @@ Arm tested these operators with the following TensorFlow Lite neural network:
 - Quantized Yolo v3 (CpuRef)
 
 More machine learning operators will be supported in future releases.
-<br/><br/><br/><br/>
-
-
-
-
-@section S7_tf_parser ArmNN Tensorflow Parser
-
-`armnnTfParser` is a library for loading neural networks defined by TensorFlow protobuf files into the Arm NN runtime.
-
-\b NOTE: The Arm NN Tensorflow Parser is deprecated in Arm NN 21.02 and will be removed in 21.05.
-
-## TensorFlow operators that the Arm NN SDK supports
-
-This reference guide provides a list of TensorFlow operators the Arm NN SDK currently supports.
-
-The Arm NN SDK TensorFlow parser currently only supports fp32 operators.
-
-### Fully supported
-
-- avg_pool
-  - See the TensorFlow [avg_pool documentation](https://www.tensorflow.org/api_docs/python/tf/nn/avg_pool) for more information.
-- bias_add
-  - See the TensorFlow [bias_add documentation](https://www.tensorflow.org/api_docs/python/tf/nn/bias_add) for more information.
-- conv2d
-  - See the TensorFlow [conv2d documentation](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d) for more information.
-- expand_dims
-  - See the TensorFlow [expand_dims documentation](https://www.tensorflow.org/api_docs/python/tf/expand_dims) for more information.
-- gather
-  - See the TensorFlow [gather documentation](https://www.tensorflow.org/api_docs/python/tf/gather) for more information.
-- identity
-  - See the TensorFlow [identity documentation](https://www.tensorflow.org/api_docs/python/tf/identity) for more information.
-- local_response_normalization
-  - See the TensorFlow [local_response_normalization documentation](https://www.tensorflow.org/api_docs/python/tf/nn/local_response_normalization)  for more information.
-- max_pool
-  - See the TensorFlow [max_pool documentation](https://www.tensorflow.org/api_docs/python/tf/nn/max_pool) for more information.
-- placeholder
-  - See the TensorFlow [placeholder documentation](https://www.tensorflow.org/api_docs/python/tf/placeholder) for more information.
-- reduce_mean
-  - See the TensorFlow [reduce_mean documentation](https://www.tensorflow.org/api_docs/python/tf/reduce_mean) for more information.
-- relu
-  - See the TensorFlow [relu documentation](https://www.tensorflow.org/api_docs/python/tf/nn/relu) for more information.
-- relu6
-  - See the TensorFlow [relu6 documentation](https://www.tensorflow.org/api_docs/python/tf/nn/relu6) for more information.
-- rsqrt
-  - See the TensorFlow [rsqrt documentation](https://www.tensorflow.org/api_docs/python/tf/math/rsqrt) for more information.
-- shape
-  - See the TensorFlow [shape documentation](https://www.tensorflow.org/api_docs/python/tf/shape) for more information.
-- sigmoid
-  - See the TensorFlow [sigmoid documentation](https://www.tensorflow.org/api_docs/python/tf/sigmoid) for more information.
-- softplus
-  - See the TensorFlow [softplus documentation](https://www.tensorflow.org/api_docs/python/tf/nn/softplus) for more information.
-- squeeze
-  - See the TensorFlow [squeeze documentation](https://www.tensorflow.org/api_docs/python/tf/squeeze) for more information.
-- tanh
-  - See the TensorFlow [tanh documentation](https://www.tensorflow.org/api_docs/python/tf/tanh) for more information.
-- transpose
-  - See the TensorFlow [transpose documentation](https://www.tensorflow.org/api_docs/python/tf/transpose) for more information.
-
-### Partially supported
-
-- add
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [add operator documentation](https://www.tensorflow.org/api_docs/python/tf/add) for more information.
-- add_n
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [add operator documentation](https://www.tensorflow.org/api_docs/python/tf/add_n) for more information.
-- concat
-  - Arm NN supports concatenation along the channel dimension for data formats NHWC and NCHW.
-- constant
-  - The parser does not support the optional `shape` argument. It always infers the shape of the output tensor from `value`. See the TensorFlow [constant documentation](https://www.tensorflow.org/api_docs/python/tf/constant) for further information.
-- depthwise_conv2d_native
-  - The parser only supports a dilation rate of (1,1,1,1). See the TensorFlow [depthwise_conv2d_native documentation](https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d_native) for more information.
-- equal
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [equal operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/equal) for more information.
-- fused_batch_norm
-  - The parser does not support training outputs. See the TensorFlow [fused_batch_norm documentation](https://www.tensorflow.org/api_docs/python/tf/nn/fused_batch_norm) for more information.
-- greater
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [greater operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/greater) for more information.
-- matmul
-  - The parser only supports constant weights in a fully connected layer. See the TensorFlow [matmul documentation](https://www.tensorflow.org/api_docs/python/tf/matmul) for more information.
-- maximum
-  where maximum is used in one of the following ways
-  - max(mul(a, x), x)
-  - max(mul(x, a), x)
-  - max(x, mul(a, x))
-  - max(x, mul(x, a)
-  This is interpreted as a ActivationLayer with a LeakyRelu activation function. Any other usage of max will result in the insertion of a simple maximum layer. The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting). See the TensorFlow [maximum documentation](https://www.tensorflow.org/api_docs/python/tf/maximum) for more information.
-- minimum
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [minimum operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/minimum) for more information.
-- multiply
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [multiply documentation](https://www.tensorflow.org/api_docs/python/tf/multiply) for more information.
-- pack/stack
-  - See the TensorFlow [stack documentation](https://www.tensorflow.org/api_docs/python/tf/stack) for more information.
-- pad
-  - Only supports tf.pad function with mode = 'CONSTANT' and constant_values = 0. See the TensorFlow [pad documentation](https://www.tensorflow.org/api_docs/python/tf/pad) for more information.
-- realdiv
-  - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [realdiv documentation](https://www.tensorflow.org/api_docs/python/tf/realdiv) for more information.
-- reshape
-  - The parser does not support reshaping to or from 4D. See the TensorFlow [reshape documentation](https://www.tensorflow.org/api_docs/python/tf/reshape) for more information.
-- resize_images
-  - The parser only supports `ResizeMethod.BILINEAR` with `align_corners=False`. See the TensorFlow [resize_images documentation](https://www.tensorflow.org/api_docs/python/tf/image/resize_images) for more information.
-- softmax
-  - The parser only supports 2D inputs and does not support selecting the `softmax` dimension. See the TensorFlow [softmax documentation](https://www.tensorflow.org/api_docs/python/tf/nn/softmax) for more information.
-- split
-  - Arm NN supports split along the channel dimension for data formats NHWC and NCHW.
-- strided_slice
-  - See the TensorFlow [strided_slice documentation](https://www.tensorflow.org/api_docs/python/tf/strided_slice) for more information.
-- subtract
-  - The parser does not support all forms of broadcasting [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [subtract documentation](https://www.tensorflow.org/api_docs/python/tf/math/subtract) for more information.
-
-
-## Tested networks
-
-Arm tests these operators with the following TensorFlow fp32 neural networks:
-- Lenet
-- mobilenet_v1_1.0_224. The Arm NN SDK only supports the non-quantized version of the network. See the [MobileNet_v1 documentation](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md) for more information on quantized networks.
-- inception_v3. The Arm NN SDK only supports the official inception_v3 transformed model. See the TensorFlow documentation on [preparing models for mobile deployment](https://www.tensorflow.org/mobile/prepare_models) for more information on how to transform the inception_v3 network.
-- Simple MNIST. For more information check out the [tutorial](https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/deploying-a-tensorflow-mnist-model-on-arm-nn) on the Arm Developer portal.
-- ResNet v2 50 implementation from the [TF Slim model zoo](https://github.com/tensorflow/models/tree/master/research/slim)
-
-More machine learning operators will be supported in future releases.
 
 **/
 }
diff --git a/docs/Doxyfile b/docs/Doxyfile
index 31f06f70a5..d405e28a86 100644
--- a/docs/Doxyfile
+++ b/docs/Doxyfile
@@ -827,7 +827,6 @@ INPUT                  = ./docs/01_00_software_tools.dox \
                          ./python/pyarmnn/README.md \
                          ./include/ \
                          ./src/ \
-                         ./src/armnnQuantizer/README.md \
                          ./src/armnnConverter/README.md \
                          ./src/backends/README.md \
                          ./src/dynamic/README.md \
diff --git a/docs/FAQ.md b/docs/FAQ.md
index 273ef92168..4070541d52 100644
--- a/docs/FAQ.md
+++ b/docs/FAQ.md
@@ -45,8 +45,4 @@ This problem has previously been reported to the boostorg GitHub project. The so
 
 ArmNN fails to build on Ubuntu 20.04
 ---------------------------------------------------------
-The compiler version update on Ubuntu 20.04 resulted in build errors in Flat buffers 1.10.0. Update to Flatbuffers 1.12.0 to resolve this problem. In addition when building flatbuffers specify -fPIC CXX flag to allow the libraries to be used in our shared objects. Without this the the ArmNN build can fail with libflatbuffers.a(util.cpp.o): relocation R_X86_64_PC32 against symbol `_ZN11flatbuffers9DirExistsEPKc' can not be used when making a shared object; recompile with -fPIC
-
-Caffe fails to build on Ubuntu 20.04
----------------------------------------------------------
-The default version of OpenCV on Ubuntu 20.04 is 4.2. This appears to be incomatible with Caffe. Building results in missing definitions of "CV_LOAD_IMAGE_COLOR". When building Caffe to use with ArmNN you can disable OpenCV. In the Makefile.config uncomment "# USE_OPENCV := 0".
+The compiler version update on Ubuntu 20.04 resulted in build errors in Flat buffers 1.10.0. Update to Flatbuffers 1.12.0 to resolve this problem. In addition when building flatbuffers specify -fPIC CXX flag to allow the libraries to be used in our shared objects. Without this the the ArmNN build can fail with libflatbuffers.a(util.cpp.o): relocation R_X86_64_PC32 against symbol `_ZN11flatbuffers9DirExistsEPKc' can not be used when making a shared object; recompile with -fPIC
\ No newline at end of file