IVGCVSW-5720 Remove the Caffe Parser from ArmNN

Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ib00be204f549efa9aa5971ecf65c2dec4a10b10f

56 files changed, 26 insertions, 12030 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 8878065478..c02db3d014 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -99,34 +99,6 @@ list(APPEND armnnUtils_sources
 add_library_ex(armnnUtils STATIC ${armnnUtils_sources})
 target_include_directories(armnnUtils PRIVATE src/backends)
 
-if(BUILD_CAFFE_PARSER)
-    # ArmNN Parser source files required for all build options
-    set(armnn_caffe_parser_sources)
-    list(APPEND armnn_caffe_parser_sources
-        include/armnnCaffeParser/ICaffeParser.hpp
-        include/armnnCaffeParser/Version.hpp
-        src/armnnCaffeParser/RecordByRecordCaffeParser.hpp
-        src/armnnCaffeParser/RecordByRecordCaffeParser.cpp
-        src/armnnCaffeParser/CaffeParser.hpp
-        src/armnnCaffeParser/CaffeParser.cpp
-        ${CAFFE_GENERATED_SOURCES}/caffe/proto/caffe.pb.cc
-        )
-    # The generated Caffe protobuf .cc file is not warning clean and we can't fix them.
-    if(COMPILER_IS_GNU_LIKE)
-        set_source_files_properties(${CAFFE_GENERATED_SOURCES}/caffe/proto/caffe.pb.cc PROPERTIES COMPILE_FLAGS "-Wno-unused-variable -Wno-unused-parameter -Wno-conversion -Wno-sign-conversion")
-    endif()
-
-    add_library_ex(armnnCaffeParser SHARED ${armnn_caffe_parser_sources})
-    set_target_properties(armnnCaffeParser PROPERTIES COMPILE_FLAGS "${CAFFE_PARSER_ADDITIONAL_COMPILE_FLAGS}")
-
-    target_include_directories(armnnCaffeParser PRIVATE src/armnnUtils)
-
-    target_link_libraries(armnnCaffeParser armnn)
-    target_link_libraries(armnnCaffeParser ${PROTOBUF_LIBRARIES})
-    set_target_properties(armnnCaffeParser PROPERTIES VERSION ${CAFFE_PARSER_LIB_VERSION} SOVERSION ${CAFFE_PARSER_LIB_SOVERSION})
-
-endif()
-
 if(BUILD_ONNX_PARSER)
     set(armnn_onnx_parser_sources)
     list(APPEND armnn_onnx_parser_sources
@@ -629,11 +601,6 @@ endif()
 add_subdirectory(third-party/fmt)
 target_link_libraries(armnn fmt)
 
-if(BUILD_CAFFE_PARSER)
-    install(TARGETS armnnCaffeParser
-            LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}
-            RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR})
-endif()
 if(BUILD_ONNX_PARSER)
     install(TARGETS armnnOnnxParser
             LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}
@@ -872,21 +839,6 @@ if(BUILD_UNIT_TESTS)
         list(APPEND unittest_sources ${CMAKE_CURRENT_BINARY_DIR}/SchemaText.cpp)
     endif()
 
-    if(BUILD_CAFFE_PARSER AND ARMNNREF)
-        list(APPEND unittest_sources
-            src/armnnCaffeParser/test/TestAdd.cpp
-            src/armnnCaffeParser/test/TestConcat.cpp
-            src/armnnCaffeParser/test/TestConvolution.cpp
-            src/armnnCaffeParser/test/TestDropout.cpp
-            src/armnnCaffeParser/test/TestInputs.cpp
-            src/armnnCaffeParser/test/TestMul.cpp
-            src/armnnCaffeParser/test/TestPooling2d.cpp
-            src/armnnCaffeParser/test/TestInPlace.cpp
-            src/armnnCaffeParser/test/TestMultiInputsOutputs.cpp
-            src/armnnCaffeParser/test/TestSplit.cpp
-            )
-    endif()
-
     if(BUILD_ONNX_PARSER AND ARMNNREF)
         list(APPEND unittest_sources
             src/armnnOnnxParser/test/Addition.cpp
@@ -1026,10 +978,6 @@ if(BUILD_UNIT_TESTS)
         target_link_libraries(UnitTests armnnTfLiteParser)
     endif()
 
-    if(BUILD_CAFFE_PARSER)
-        target_link_libraries(UnitTests armnnCaffeParser)
-    endif()
-
     if(BUILD_ARMNN_SERIALIZER AND ARMNNREF)
         target_include_directories(UnitTests SYSTEM PRIVATE ${CMAKE_CURRENT_BINARY_DIR}/src/armnnSerializer)
         target_include_directories(UnitTests SYSTEM PRIVATE "${FLATBUFFERS_INCLUDE_PATH}")
@@ -1053,7 +1001,7 @@ if(BUILD_UNIT_TESTS)
     addDllCopyCommands(UnitTests)
 endif()
 
-if (BUILD_ARMNN_SERIALIZER AND (BUILD_TF_PARSER OR BUILD_TF_LITE_PARSER OR BUILD_ONNX_PARSER OR BUILD_CAFFE_PARSER) AND ARMNNREF)
+if (BUILD_ARMNN_SERIALIZER AND (BUILD_TF_PARSER OR BUILD_TF_LITE_PARSER OR BUILD_ONNX_PARSER) AND ARMNNREF)
     set(ArmnnConverter_sources
         src/armnnConverter/ArmnnConverter.cpp)
 
@@ -1061,10 +1009,6 @@ if (BUILD_ARMNN_SERIALIZER AND (BUILD_TF_PARSER OR BUILD_TF_LITE_PARSER OR BUILD
     target_include_directories(ArmnnConverter PRIVATE src/armnn)
     target_include_directories(ArmnnConverter PRIVATE src/armnnUtils)
 
-    if(BUILD_CAFFE_PARSER)
-        target_link_libraries(ArmnnConverter armnnCaffeParser)
-    endif()
-
     if(BUILD_ONNX_PARSER)
         target_link_libraries(ArmnnConverter armnnOnnxParser)
     endif()
diff --git a/cmake/AddDllCopyCommands.cmake b/cmake/AddDllCopyCommands.cmake
index ff57bb173d..6190170dbc 100644
--- a/cmake/AddDllCopyCommands.cmake
+++ b/cmake/AddDllCopyCommands.cmake
@@ -39,14 +39,6 @@ macro(addDllCopyCommands target)
             addDllCopyCommand(${target} "$<TARGET_FILE_DIR:armnn>/armnn.dll" "$<TARGET_FILE_DIR:armnn>/armnn.dll")
         endif()
 
-        # armnnCaffeParser.dll
-        if ("armnnCaffeParser" IN_LIST target_deps)
-            addDllCopyCommand(${target} "$<TARGET_FILE_DIR:armnnCaffeParser>/armnnCaffeParser.dll"
-                                        "$<TARGET_FILE_DIR:armnnCaffeParser>/armnnCaffeParser.dll")
-            addDllCopyCommand(${target} "${PROTOBUF_ROOT}/bin/libprotobufd.dll"
-                                        "${PROTOBUF_ROOT}/bin/libprotobuf.dll")
-       endif()
-
         # armnnTfParser.dll
         if ("armnnTfParser" IN_LIST target_deps)
             addDllCopyCommand(${target} "$<TARGET_FILE_DIR:armnnTfParser>/armnnTfParser.dll"
@@ -60,18 +52,5 @@ macro(addDllCopyCommands target)
             addDllCopyCommand(${target} "$<TARGET_FILE_DIR:armnnTfLiteParser>/armnnTfLiteParser.dll"
                                         "$<TARGET_FILE_DIR:armnnTfLiteParser>/armnnTfLiteParser.dll")
         endif()
-
-        # caffe.dll and its dependencies
-        listContainsRegex(includeCaffeDlls "${target_deps}" "caffe")
-        if (${includeCaffeDlls})
-            addDllCopyCommand(${target} "${CAFFE_BUILD_ROOT}/lib/caffe-d.dll"
-                                        "${CAFFE_BUILD_ROOT}/lib/caffe.dll")
-            addDllCopyCommand(${target} "${PROTOBUF_ROOT}/bin/libprotobufd.dll"
-                                        "${PROTOBUF_ROOT}/bin/libprotobuf.dll")
-            addDllCopyCommand(${target} "${BLAS_ROOT}/bin/libopenblas.dll"          "${BLAS_ROOT}/bin/libopenblas.dll")
-            addDllCopyCommand(${target} "${MINGW32_ROOT}/bin/libgfortran-3.dll"     "${MINGW32_ROOT}/bin/libgfortran-3.dll")
-            addDllCopyCommand(${target} "${MINGW32_ROOT}/bin/libgcc_s_dw2-1.dll"    "${MINGW32_ROOT}/bin/libgcc_s_dw2-1.dll")
-            addDllCopyCommand(${target} "${MINGW32_ROOT}/bin/libquadmath-0.dll"     "${MINGW32_ROOT}/bin/libquadmath-0.dll")
-        endif()
     endif()
 endmacro()
diff --git a/cmake/GlobalConfig.cmake b/cmake/GlobalConfig.cmake
index 8a7c9a1821..031974814b 100644
--- a/cmake/GlobalConfig.cmake
+++ b/cmake/GlobalConfig.cmake
@@ -3,7 +3,6 @@
 # Copyright 2020 NXP
 # SPDX-License-Identifier: MIT
 #
-option(BUILD_CAFFE_PARSER "Build Caffe parser" OFF)
 option(BUILD_TF_PARSER "Build Tensorflow parser" OFF)
 option(BUILD_ONNX_PARSER "Build Onnx parser" OFF)
 option(BUILD_UNIT_TESTS "Build unit tests" ON)
@@ -159,7 +158,7 @@ endif()
 find_dependency(Threads)
 
 # Favour the protobuf passed on command line
-if(BUILD_TF_PARSER OR BUILD_CAFFE_PARSER OR BUILD_ONNX_PARSER)
+if(BUILD_TF_PARSER OR BUILD_ONNX_PARSER)
     find_library(PROTOBUF_LIBRARY_DEBUG NAMES "protobufd"
         PATHS ${PROTOBUF_ROOT}/lib
         NO_DEFAULT_PATH NO_CMAKE_FIND_ROOT_PATH)
@@ -181,15 +180,6 @@ if(BUILD_TF_PARSER OR BUILD_CAFFE_PARSER OR BUILD_ONNX_PARSER)
     add_definitions(-DPROTOBUF_USE_DLLS)
 endif()
 
-# Caffe and its dependencies
-if(BUILD_CAFFE_PARSER)
-    add_definitions(-DARMNN_CAFFE_PARSER)
-
-    find_path(CAFFE_GENERATED_SOURCES "caffe/proto/caffe.pb.h"
-        HINTS ${CAFFE_BUILD_ROOT}/include)
-    include_directories(SYSTEM "${CAFFE_GENERATED_SOURCES}")
-endif()
-
 if(BUILD_TF_PARSER)
     add_definitions(-DARMNN_TF_PARSER)
 
@@ -416,9 +406,6 @@ else()
 endif()
 
 
-if(NOT BUILD_CAFFE_PARSER)
-    message(STATUS "Caffe parser support is disabled")
-endif()
 
 if(NOT BUILD_TF_PARSER)
     message(STATUS "Tensorflow parser support is disabled")
diff --git a/cmake/ParserVersion.cmake b/cmake/ParserVersion.cmake
index e7a5234506..2120bf7057 100644
--- a/cmake/ParserVersion.cmake
+++ b/cmake/ParserVersion.cmake
@@ -3,22 +3,6 @@
 # SPDX-License-Identifier: MIT
 #
 
-# Read the CaffeParser version components from file
-file(READ ${CMAKE_CURRENT_LIST_DIR}/../include/armnnCaffeParser/Version.hpp caffeVersion)
-
-# Parse the CaffeParser version components
-string(REGEX MATCH "#define CAFFE_PARSER_MAJOR_VERSION ([0-9]*)" _ ${caffeVersion})
-set(CAFFE_PARSER_MAJOR_VERSION ${CMAKE_MATCH_1})
-string(REGEX MATCH "#define CAFFE_PARSER_MINOR_VERSION ([0-9]*)" _ ${caffeVersion})
-set(CAFFE_PARSER_MINOR_VERSION ${CMAKE_MATCH_1})
-
-# Define LIB version
-set(CAFFE_PARSER_LIB_VERSION "${CAFFE_PARSER_MAJOR_VERSION}.${CAFFE_PARSER_MINOR_VERSION}")
-
-# Define LIB soversion
-set(CAFFE_PARSER_LIB_SOVERSION "${CAFFE_PARSER_MAJOR_VERSION}")
-
-
 # Read the OnnxParser version components from file
 file(READ ${CMAKE_CURRENT_LIST_DIR}/../include/armnnOnnxParser/Version.hpp onnxVersion)
 
diff --git a/docker/x86_64/Dockerfile b/docker/x86_64/Dockerfile
index c03a1d7407..684b5cf34b 100644
--- a/docker/x86_64/Dockerfile
+++ b/docker/x86_64/Dockerfile
@@ -105,10 +105,6 @@ RUN apt-get update && apt-get install -y \
     libatlas-base-dev 
 
 
-# Download caffe 1.0
-RUN cd $HOME && git clone https://github.com/BVLC/caffe.git && \
-    cd caffe && git checkout eeebdab16155d34ff8f5f42137da7df4d1c7eab0
-
 # Makefile update
 # To Do: Don't copy the Local Make file to docker
 # RUN cd $HOME/caffe/ && rm Makefile.config.example
@@ -123,15 +119,6 @@ RUN apt-get update && apt-get install -y \
 # ENV PATH=$HOME/armnn-devenv/google/x86_64_pb_install/bin/:$PATH
 # ENV LD_LIBRARY_PATH=$HOME/armnn-devenv/google/x86_64_pb_install/lib/:$LD_LIBRARY_PATH
 
-# Compile CAFFE
-RUN cd $HOME/caffe/ && mkdir build && cd build && \
-    export PATH=$HOME/armnn-devenv/google/x86_64_pb_install/bin/:$PATH && \
-    export LD_LIBRARY_PATH=$HOME/armnn-devenv/google/x86_64_pb_install/lib/:$LD_LIBRARY_PATH && \
-    ldconfig && \
-    cmake -DCMAKE_CXX_FLAGS=--std=c++11 ../ && \
-    make all -j$(nproc) && \
-    make test -j$(nproc) && \
-    make runtest -j$(nproc)
 
 # Build Boost library for arm64
 RUN cd $HOME && wget http://downloads.sourceforge.net/project/boost/boost/1.64.0/boost_1_64_0.tar.gz && \
@@ -211,8 +198,6 @@ RUN cd $HOME/armnn-devenv && \
     -DARMCOMPUTE_BUILD_DIR=$HOME/armnn-devenv/ComputeLibrary/build/ \
     -DBOOST_ROOT=$HOME/armnn-devenv/boost_arm64_install/ \
     -DARMCOMPUTENEON=1 -DARMCOMPUTECL=1 -DARMNNREF=1 \
-    -DCAFFE_GENERATED_SOURCES=$HOME/caffe/build/include \
-    -DBUILD_CAFFE_PARSER=1 \
     -DONNX_GENERATED_SOURCES=$HOME/armnn-devenv/onnx \
     -DBUILD_ONNX_PARSER=1 \
     -DTF_GENERATED_SOURCES=$HOME/armnn-devenv/tensorflow-protobuf \
diff --git a/include/armnnCaffeParser/ICaffeParser.hpp b/include/armnnCaffeParser/ICaffeParser.hpp
deleted file mode 100644
index 0e31ad4461..0000000000
--- a/include/armnnCaffeParser/ICaffeParser.hpp
+++ /dev/null
@@ -1,66 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#pragma once
-
-#include "armnn/Types.hpp"
-#include "armnn/NetworkFwd.hpp"
-#include "armnn/Tensor.hpp"
-#include "armnn/INetwork.hpp"
-
-#include <memory>
-#include <map>
-#include <vector>
-
-namespace armnnCaffeParser
-{
-
-using BindingPointInfo = armnn::BindingPointInfo;
-
-class ICaffeParser;
-using ICaffeParserPtr = std::unique_ptr<ICaffeParser, void(*)(ICaffeParser* parser)>;
-
-class ICaffeParser
-{
-public:
-    static ICaffeParser* CreateRaw();
-    static ICaffeParserPtr Create();
-    static void Destroy(ICaffeParser* parser);
-
-    /// Create the network from a protobuf text file on the disk.
-    armnn::INetworkPtr CreateNetworkFromTextFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// Create the network from a protobuf binary file on the disk.
-    armnn::INetworkPtr CreateNetworkFromBinaryFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// Create the network directly from protobuf text in a string. Useful for debugging/testin.g
-    armnn::INetworkPtr CreateNetworkFromString(
-        const char* protoText,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name.
-    BindingPointInfo GetNetworkInputBindingInfo(const std::string& name) const;
-
-    /// Retrieve binding info (layer id and tensor info) for the network output identified by the given layer name.
-    BindingPointInfo GetNetworkOutputBindingInfo(const std::string& name) const;
-
-private:
-    friend class CaffeParser;
-    friend class RecordByRecordCaffeParser;
-
-    ICaffeParser();
-    ~ICaffeParser();
-
-    class CaffeParserImpl;
-    std::unique_ptr<CaffeParserImpl> pCaffeParserImpl;
-};
-
-}
\ No newline at end of file
diff --git a/include/armnnCaffeParser/Version.hpp b/include/armnnCaffeParser/Version.hpp
deleted file mode 100644
index 6e7ce5a539..0000000000
--- a/include/armnnCaffeParser/Version.hpp
+++ /dev/null
@@ -1,29 +0,0 @@
-//
-// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-namespace armnnCaffeParser
-{
-
-/// Macro utils
-#define STRINGIFY_VALUE(s) STRINGIFY_MACRO(s)
-#define STRINGIFY_MACRO(s) #s
-
-// CaffeParser version components
-#define CAFFE_PARSER_MAJOR_VERSION 24
-#define CAFFE_PARSER_MINOR_VERSION 1
-#define CAFFE_PARSER_PATCH_VERSION 0
-
-/// CAFFE_PARSER_VERSION: "X.Y.Z"
-/// where:
-///   X = Major version number
-///   Y = Minor version number
-///   Z = Patch version number
-#define CAFFE_PARSER_VERSION STRINGIFY_VALUE(CAFFE_PARSER_MAJOR_VERSION) "." \
-                             STRINGIFY_VALUE(CAFFE_PARSER_MINOR_VERSION) "." \
-                             STRINGIFY_VALUE(CAFFE_PARSER_PATCH_VERSION)
-
-} //namespace armnnCaffeParser
\ No newline at end of file
diff --git a/python/pyarmnn/examples/image_classification/example_utils.py b/python/pyarmnn/examples/image_classification/example_utils.py
index f0ba91e981..bd43d60da5 100644
--- a/python/pyarmnn/examples/image_classification/example_utils.py
+++ b/python/pyarmnn/examples/image_classification/example_utils.py
@@ -72,7 +72,7 @@ def parse_command_line(desc: str = ""):
     parser.add_argument("-d", "--data-dir", help="Data directory which contains all the images.",
                         action="store", default="")
     parser.add_argument("-m", "--model-dir",
-                        help="Model directory which contains the model file (TF, TFLite, ONNX, Caffe).", action="store",
+                        help="Model directory which contains the model file (TF, TFLite, ONNX).", action="store",
                         default="")
     return parser.parse_args()
 
diff --git a/python/pyarmnn/setup.py b/python/pyarmnn/setup.py
index e1eba4b082..9d9f561ef9 100755
--- a/python/pyarmnn/setup.py
+++ b/python/pyarmnn/setup.py
@@ -283,7 +283,6 @@ if __name__ == '__main__':
         ext_list.append(pyarmnn_optional_module)
 
 
-    add_parsers_ext('CaffeParser', extensions_to_build)
     add_parsers_ext('OnnxParser', extensions_to_build)
     add_parsers_ext('TfParser', extensions_to_build)
     add_parsers_ext('TfLiteParser', extensions_to_build)
diff --git a/python/pyarmnn/src/pyarmnn/__init__.py b/python/pyarmnn/src/pyarmnn/__init__.py
index 19b14a4b09..410e66be11 100644
--- a/python/pyarmnn/src/pyarmnn/__init__.py
+++ b/python/pyarmnn/src/pyarmnn/__init__.py
@@ -7,18 +7,6 @@ import logging
 from ._generated.pyarmnn_version import GetVersion, GetMajorVersion, GetMinorVersion
 
 # Parsers
-try:
-    from ._generated.pyarmnn_caffeparser import ICaffeParser
-except ImportError as err:
-    logger = logging.getLogger(__name__)
-    message = "Your ArmNN library instance does not support Caffe models parser functionality. "
-    logger.warning("%s Skipped ICaffeParser import.", message)
-    logger.debug(str(err))
-
-
-    def ICaffeParser():
-        """In case people try importing without having Arm NN built with this parser."""
-        raise RuntimeError(message)
 
 try:
     from ._generated.pyarmnn_onnxparser import IOnnxParser
diff --git a/python/pyarmnn/src/pyarmnn/swig/armnn_caffeparser.i b/python/pyarmnn/src/pyarmnn/swig/armnn_caffeparser.i
deleted file mode 100644
index 538b486aad..0000000000
--- a/python/pyarmnn/src/pyarmnn/swig/armnn_caffeparser.i
+++ /dev/null
@@ -1,103 +0,0 @@
-//
-// Copyright © 2020 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-%module pyarmnn_caffeparser
-%{
-#define SWIG_FILE_WITH_INIT
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "armnn/INetwork.hpp"
-%}
-
-//typemap definitions and other common stuff
-%include "standard_header.i"
-
-namespace std {
-   %template(BindingPointInfo)     pair<int, armnn::TensorInfo>;
-   %template(MapStringTensorShape) map<std::string, armnn::TensorShape>;
-   %template(StringVector)         vector<string>;
-}
-
-namespace armnnCaffeParser
-{
-
-%feature("docstring",
-"
-Interface for creating a parser object using Caffe (http://caffe.berkeleyvision.org/) caffemodel files.
-
-Parsers are used to automatically construct Arm NN graphs from model files.
-
-") ICaffeParser;
-
-%nodefaultctor ICaffeParser;
-class ICaffeParser
-{
-public:
-    // Documentation
-    %feature("docstring",
-    "
-    Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name.
-
-    Args:
-        name (str): Name of the input.
-
-    Returns:
-        tuple: (`int`, `TensorInfo`)
-    ") GetNetworkInputBindingInfo;
-
-    %feature("docstring",
-    "
-    Retrieve binding info (layer id and `TensorInfo`) for the network output identified by the given layer name.
-
-    Args:
-        name (str): Name of the output.
-
-    Returns:
-        tuple: (`int`, `TensorInfo`)
-    ") GetNetworkOutputBindingInfo;
-
-    std::pair<int, armnn::TensorInfo> GetNetworkInputBindingInfo(const std::string& name);
-    std::pair<int, armnn::TensorInfo> GetNetworkOutputBindingInfo(const std::string& name);
-};
-
-%extend ICaffeParser {
-    // This is not a substitution of the default constructor of the Armnn class. It tells swig to create custom __init__
-    // method for ICaffeParser python object that will use static factory method to do the job.
-
-    ICaffeParser() {
-        return armnnCaffeParser::ICaffeParser::CreateRaw();
-    }
-
-    // The following does not replace a real destructor of the Armnn class.
-    // It creates a functions that will be called when swig object goes out of the scope to clean resources.
-    // so the user doesn't need to call ICaffeParser::Destroy himself.
-    // $self` is a pointer to extracted ArmNN ICaffeParser object.
-
-    ~ICaffeParser() {
-        armnnCaffeParser::ICaffeParser::Destroy($self);
-    }
-
-    %feature("docstring",
-    "
-    Create the network from a Caffe caffemodel binary file on disk.
-
-    Args:
-        graphFile: Path to the caffe model to be parsed.
-        inputShapes (tuple): (`string`, `TensorShape`) A tuple containing the input name and TensorShape information for the network.
-        requestedOutputs (list): A list of the output tensor names.
-
-    Returns:
-        INetwork: INetwork object for the parsed Caffe model.
-    ") CreateNetworkFromBinaryFile;
-
-    %newobject CreateNetworkFromBinaryFile;
-    armnn::INetwork* CreateNetworkFromBinaryFile(const char* graphFile,
-                                                 const std::map<std::string, armnn::TensorShape>& inputShapes,
-                                                 const std::vector<std::string>& requestedOutputs) {
-        return $self->CreateNetworkFromBinaryFile(graphFile, inputShapes, requestedOutputs).release();
-    }
-}
-}
-
-// Clear exception typemap.
-%exception;
diff --git a/python/pyarmnn/swig_generate.py b/python/pyarmnn/swig_generate.py
index 72bccbf49e..a2352c9063 100755
--- a/python/pyarmnn/swig_generate.py
+++ b/python/pyarmnn/swig_generate.py
@@ -107,7 +107,6 @@ if __name__ == "__main__":
 
     wrap_names = ['armnn_version',
         'armnn',
-        'armnn_caffeparser',
         'armnn_onnxparser',
         'armnn_tfparser',
         'armnn_tfliteparser',
diff --git a/python/pyarmnn/test/test_caffe_parser.py b/python/pyarmnn/test/test_caffe_parser.py
deleted file mode 100644
index d744b907d4..0000000000
--- a/python/pyarmnn/test/test_caffe_parser.py
+++ /dev/null
@@ -1,131 +0,0 @@
-# Copyright © 2020 Arm Ltd. All rights reserved.
-# SPDX-License-Identifier: MIT
-import os
-
-import pytest
-import pyarmnn as ann
-import numpy as np
-
-
-@pytest.fixture()
-def parser(shared_data_folder):
-    """
-    Parse and setup the test network to be used for the tests below
-    """
-
-    # Create caffe parser
-    parser = ann.ICaffeParser()
-
-    # Specify path to model
-    path_to_model = os.path.join(shared_data_folder, 'mock_model.caffemodel')
-
-    # Specify the tensor shape relative to the input [1, 1, 28, 28]
-    tensor_shape = {'Placeholder': ann.TensorShape((1, 1, 28, 28))}
-
-    # Specify the requested_outputs
-    requested_outputs = ["output"]
-
-    # Parse caffe binary & create network
-    parser.CreateNetworkFromBinaryFile(path_to_model, tensor_shape, requested_outputs)
-
-    yield parser
-
-
-def test_caffe_parser_swig_destroy():
-    assert ann.ICaffeParser.__swig_destroy__, "There is a swig python destructor defined"
-    assert ann.ICaffeParser.__swig_destroy__.__name__ == "delete_ICaffeParser"
-
-
-def test_check_caffe_parser_swig_ownership(parser):
-    # Check to see that SWIG has ownership for parser. This instructs SWIG to take
-    # ownership of the return value. This allows the value to be automatically
-    # garbage-collected when it is no longer in use
-    assert parser.thisown
-
-
-def test_get_network_input_binding_info(parser):
-    input_binding_info = parser.GetNetworkInputBindingInfo("Placeholder")
-
-    tensor = input_binding_info[1]
-    assert tensor.GetDataType() == 1
-    assert tensor.GetNumDimensions() == 4
-    assert tensor.GetNumElements() == 784
-
-
-def test_get_network_output_binding_info(parser):
-    output_binding_info1 = parser.GetNetworkOutputBindingInfo("output")
-
-    # Check the tensor info retrieved from GetNetworkOutputBindingInfo
-    tensor1 = output_binding_info1[1]
-
-    assert tensor1.GetDataType() == 1
-    assert tensor1.GetNumDimensions() == 2
-    assert tensor1.GetNumElements() == 10
-
-
-def test_filenotfound_exception(shared_data_folder):
-    parser = ann.ICaffeParser()
-
-    # path to model
-    path_to_model = os.path.join(shared_data_folder, 'some_unknown_network.caffemodel')
-
-    # generic tensor shape [1, 1, 1, 1]
-    tensor_shape = {'data': ann.TensorShape((1, 1, 1, 1))}
-
-    # requested_outputs
-    requested_outputs = [""]
-
-    with pytest.raises(RuntimeError) as err:
-        parser.CreateNetworkFromBinaryFile(path_to_model, tensor_shape, requested_outputs)
-
-    # Only check for part of the exception since the exception returns
-    # absolute path which will change on different machines.
-    assert 'Failed to open graph file' in str(err.value)
-
-
-def test_caffe_parser_end_to_end(shared_data_folder):
-    parser = ann.ICaffeParser = ann.ICaffeParser()
-
-    # Load the network specifying the inputs and outputs
-    input_name = "Placeholder"
-    tensor_shape = {input_name: ann.TensorShape((1, 1, 28, 28))}
-    requested_outputs = ["output"]
-
-    network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'mock_model.caffemodel'),
-                                                 tensor_shape, requested_outputs)
-
-    # Specify preferred backend
-    preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')]
-
-    input_binding_info = parser.GetNetworkInputBindingInfo(input_name)
-
-    options = ann.CreationOptions()
-    runtime = ann.IRuntime(options)
-
-    opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions())
-
-    assert 0 == len(messages)
-
-    net_id, messages = runtime.LoadNetwork(opt_network)
-
-    assert "" == messages
-
-    # Load test image data stored in input_caffe.npy
-    input_tensor_data = np.load(os.path.join(shared_data_folder, 'caffe_parser/input_caffe.npy')).astype(np.float32)
-    input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data])
-
-    # Load output binding info and
-    outputs_binding_info = []
-    for output_name in requested_outputs:
-        outputs_binding_info.append(parser.GetNetworkOutputBindingInfo(output_name))
-    output_tensors = ann.make_output_tensors(outputs_binding_info)
-
-    runtime.EnqueueWorkload(net_id, input_tensors, output_tensors)
-
-    output_vectors = ann.workload_tensors_to_ndarray(output_tensors)
-
-    # Load golden output file for result comparison.
-    expected_output = np.load(os.path.join(shared_data_folder, 'caffe_parser/golden_output_caffe.npy'))
-
-    # Check that output matches golden output to 4 decimal places (there are slight rounding differences after this)
-    np.testing.assert_almost_equal(output_vectors[0], expected_output, 4)
diff --git a/python/pyarmnn/test/test_generated.py b/python/pyarmnn/test/test_generated.py
index 0e1d663234..f27d565c2b 100644
--- a/python/pyarmnn/test/test_generated.py
+++ b/python/pyarmnn/test/test_generated.py
@@ -7,7 +7,6 @@ import pytest
 
 import pyarmnn._generated.pyarmnn as generated_armnn
 import pyarmnn._generated.pyarmnn as generated_deserializer
-import pyarmnn._generated.pyarmnn_caffeparser as generated_caffe
 import pyarmnn._generated.pyarmnn_onnxparser as generated_onnx
 import pyarmnn._generated.pyarmnn_tfliteparser as generated_tflite
 import pyarmnn._generated.pyarmnn_tfparser as generated_tf
@@ -28,7 +27,6 @@ def get_classes(swig_independent_classes: Tuple):
     return list(filter(lambda x: x[0] not in ignored_class_names,
                        inspect.getmembers(generated_armnn, inspect.isclass) +
                        inspect.getmembers(generated_deserializer, inspect.isclass) +
-                       inspect.getmembers(generated_caffe, inspect.isclass) +
                        inspect.getmembers(generated_tflite, inspect.isclass) +
                        inspect.getmembers(generated_onnx, inspect.isclass) +
                        inspect.getmembers(generated_tf, inspect.isclass)))
diff --git a/src/armnnCaffeParser/CaffeParser.cpp b/src/armnnCaffeParser/CaffeParser.cpp
deleted file mode 100644
index 6a744f7f23..0000000000
--- a/src/armnnCaffeParser/CaffeParser.cpp
+++ /dev/null
@@ -1,2271 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "CaffeParser.hpp"
-#include "RecordByRecordCaffeParser.hpp"
-
-#include "armnnCaffeParser/Version.hpp"
-
-#include "armnn/Descriptors.hpp"
-#include "armnn/INetwork.hpp"
-#include "armnn/Utils.hpp"
-#include "armnn/Exceptions.hpp"
-
-#include "GraphTopologicalSort.hpp"
-#include "VerificationHelpers.hpp"
-
-#include <armnn/utility/Assert.hpp>
-#include <armnn/utility/NumericCast.hpp>
-
-#include <fmt/format.h>
-
-// Caffe
-#include "caffe/proto/caffe.pb.h"
-
-// ProtoBuf
-#include <google/protobuf/io/coded_stream.h>
-#include <google/protobuf/io/zero_copy_stream.h>
-#include <google/protobuf/io/zero_copy_stream_impl.h>
-#include <google/protobuf/text_format.h>
-#include <google/protobuf/stubs/common.h>
-#include <google/protobuf/stubs/once.h>
-#include <google/protobuf/io/coded_stream.h>
-#include <google/protobuf/descriptor.h>
-#include <google/protobuf/generated_message_reflection.h>
-#include <google/protobuf/reflection_ops.h>
-#include <google/protobuf/wire_format.h>
-
-#include <cmath>
-#include <iostream>
-#include <sstream>
-#include <queue>
-#include <fcntl.h>
-
-/// Caffe networks are loaded from protobuf files (binary or text) using the protobuf library and the generated
-/// code from caffe.pb.h. This gives us a caffe::NetParameter which is an in-memory version of the file.
-/// This contains a flat list of Caffe 'layers' (e.g. convolution, pooling etc.).
-/// Each layer has inputs (called "bottoms") and outputs (called "tops"). Data flows from bottom to top.
-/// The bottoms of a layer refer to the tops of other layers, not their names.
-/// The names of layers seem to be arbitrary (you could rename a layer and the network wouldn't
-/// need any other changes).
-///
-/// Some layers (e.g. Relu) can be configured so that their top and bottom are both the same. This is called an
-/// "in-place" layer and is a Caffe runtime feature used to reduce memory usage by modifying tensors in-place.
-/// This isn't relevant to the parser and so we preprocess these layers to convert them to regular layers, to result
-/// in a consistent graph structure.
-
-namespace armnnCaffeParser
-{
-
-using namespace armnn;
-using namespace caffe;
-using namespace std;
-using namespace google::protobuf::io;
-
-ICaffeParser::ICaffeParser() : pCaffeParserImpl(new RecordByRecordCaffeParser()) {}
-
-ICaffeParser::~ICaffeParser() = default;
-
-ICaffeParser* ICaffeParser::CreateRaw()
-{
-    return new ICaffeParser();
-}
-
-ICaffeParserPtr ICaffeParser::Create()
-{
-    return ICaffeParserPtr(CreateRaw(), &ICaffeParser::Destroy);
-}
-
-void ICaffeParser::Destroy(ICaffeParser* parser)
-{
-    delete parser;
-}
-
-armnn::INetworkPtr ICaffeParser::CreateNetworkFromTextFile(
-    const char* graphFile,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    return pCaffeParserImpl->CreateNetworkFromTextFile(graphFile, inputShapes, requestedOutputs);
-}
-
-armnn::INetworkPtr ICaffeParser::CreateNetworkFromBinaryFile(
-    const char* graphFile,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    return pCaffeParserImpl->CreateNetworkFromBinaryFile(graphFile, inputShapes,requestedOutputs);
-}
-
-armnn::INetworkPtr ICaffeParser::CreateNetworkFromString(
-    const char* protoText,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    return pCaffeParserImpl->CreateNetworkFromString(protoText, inputShapes, requestedOutputs);
-}
-
-BindingPointInfo ICaffeParser::GetNetworkInputBindingInfo(const std::string& name) const
-{
-    return pCaffeParserImpl->GetNetworkInputBindingInfo(name);
-}
-
-BindingPointInfo ICaffeParser::GetNetworkOutputBindingInfo(const std::string& name) const
-{
-    return pCaffeParserImpl->GetNetworkOutputBindingInfo(name);
-}
-
-namespace
-{
-
-const float* GetArrayPtrFromBlob(const LayerParameter& layerParam, unsigned int blobIndex)
-{
-    auto nBlobs = layerParam.blobs_size();
-    if (blobIndex >= armnn::numeric_cast<unsigned int>(nBlobs))
-    {
-        throw ParseException(
-            fmt::format("Expected data blob at index {} in layer {} not found. nBlobs={}. {}",
-                        blobIndex,
-                        layerParam.name(),
-                        nBlobs,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    const BlobProto& blob = layerParam.blobs(armnn::numeric_cast<int>(blobIndex));
-
-    const float* arrayPtr = blob.data().data();
-    return arrayPtr;
-}
-
-void GetDataFromBlob(const LayerParameter& layerParam, vector<float>& outData, unsigned int blobIndex)
-{
-    auto nBlobs = layerParam.blobs_size();
-    if (blobIndex >= armnn::numeric_cast<unsigned int>(nBlobs))
-    {
-        throw ParseException(
-            fmt::format("Expected data blob at index {} in layer {} not found. {}",
-                        blobIndex,
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    const BlobProto& blob = layerParam.blobs(armnn::numeric_cast<int>(blobIndex));
-
-    size_t blobSize = armnn::numeric_cast<size_t>(blob.data_size());
-    if (blobSize != outData.size())
-    {
-        throw ParseException(
-            fmt::format("Data blob at index {} in layer {} has an unexpected size. "
-                        "Expected {} elements but got {} elements. {}",
-                        blobIndex,
-                        layerParam.name(),
-                        outData.size(),
-                        blobSize,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    int outSizeInt = armnn::numeric_cast<int>(outData.size());
-    for (int i = 0; i < outSizeInt; ++i)
-    {
-        outData[static_cast<size_t>(i)] = blob.data(i);
-    }
-}
-
-template <typename T>
-size_t SizeOfVectorData(const vector<T>& vec)
-{
-    return vec.size() * sizeof(T);
-}
-
-void ValidateNumInputsOutputs(const caffe::LayerParameter& layerParameter,
-                              unsigned int                 numInputs,
-                              unsigned int                 numOutputs)
-{
-    int numInputsActual = layerParameter.bottom_size();
-    if (numInputs != armnn::numeric_cast<unsigned int>(numInputsActual))
-    {
-        throw ParseException(
-            fmt::format("Invalid number of inputs requested {} for layer {} "
-                        "while only {} present. {}",
-                        numInputs,
-                        layerParameter.name(),
-                        numInputsActual,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    int numOutputsActual = layerParameter.top_size();
-    if (numOutputs != armnn::numeric_cast<unsigned int>(numOutputsActual))
-    {
-        throw ParseException(
-            fmt::format("Invalid number of outputs requested {} for layer {} "
-                        "while only {} present. {}",
-                        numOutputs,
-                        layerParameter.name(),
-                        numOutputsActual,
-                        CHECK_LOCATION().AsString()));
-    }
-}
-
-template <typename ParamType, typename ExtractOptional, typename ExtractFallback, typename ValueType>
-ValueType GetOptionalWithFallback(const ParamType& param,
-                                  ExtractOptional extractOptional,
-                                  ExtractFallback extractFallback,
-                                  ValueType defaultValue)
-{
-    auto optValue = extractOptional(param, defaultValue);
-    if (optValue.first)
-    {
-        return optValue.second;
-    }
-    auto fallbackValue = extractFallback(param, defaultValue);
-    return fallbackValue.second;
-}
-
-#define GET_OPTIONAL_WITH_VECTOR_FALLBACK(PARAM, \
-                                          PARAM_TYPE, \
-                                          OPTIONAL_VALUE, \
-                                          FALLBACK_VECTOR, \
-                                          VALUE_TYPE, \
-                                          DEFAULT_VALUE) \
-    GetOptionalWithFallback( \
-        PARAM, \
-        [](const PARAM_TYPE & param, VALUE_TYPE defaultValue) \
-        { \
-            if (param.has_##OPTIONAL_VALUE ()) \
-            { \
-                return std::make_pair(true, param.OPTIONAL_VALUE ()); \
-            } \
-            else \
-            { \
-                return std::make_pair(false, defaultValue); \
-            } \
-        }, \
-        [](const PARAM_TYPE & param, VALUE_TYPE defaultValue) \
-        { \
-            if (param.FALLBACK_VECTOR##_size() > 0) \
-            { \
-                return std::make_pair(true, (param.FALLBACK_VECTOR ()).Get(0)); \
-            } \
-            else \
-            { \
-                return std::make_pair(false, defaultValue); \
-            } \
-        }, \
-        DEFAULT_VALUE)
-
-#define GET_OPTIONAL_WITH_FALLBACK(PARAM, \
-                                   PARAM_TYPE, \
-                                   OPTIONAL_VALUE, \
-                                   FALLBACK_VALUE, \
-                                   VALUE_TYPE, \
-                                   DEFAULT_VALUE) \
-    GetOptionalWithFallback( \
-        PARAM, \
-        [](const PARAM_TYPE & param, VALUE_TYPE defaultValue) \
-        { \
-            if (param.has_##OPTIONAL_VALUE ()) \
-            { \
-                return std::make_pair(true, param.OPTIONAL_VALUE ()); \
-            } \
-            else \
-            { \
-                return std::make_pair(false, defaultValue); \
-            } \
-        }, \
-        [](const PARAM_TYPE & param, VALUE_TYPE defaultValue) \
-        { \
-            if (param.has_##FALLBACK_VALUE ()) \
-            { \
-                return std::make_pair(true, param.FALLBACK_VALUE ()); \
-            } \
-            else \
-            { \
-                return std::make_pair(false, defaultValue); \
-            } \
-        }, \
-        DEFAULT_VALUE)
-
-} // namespace <anonymous>
-
-const std::map<std::string, ICaffeParser::CaffeParserImpl::OperationParsingFunction>
-    ICaffeParser::CaffeParserImpl::ms_CaffeLayerNameToParsingFunctions = {
-    { "Input",        &CaffeParserImpl::ParseInputLayer },
-    { "Convolution",  &CaffeParserImpl::ParseConvLayer },
-    { "Deconvolution",&CaffeParserImpl::ParseDeconvLayer },
-    { "Pooling",      &CaffeParserImpl::ParsePoolingLayer },
-    { "ReLU",         &CaffeParserImpl::ParseReluLayer },
-    { "LRN",          &CaffeParserImpl::ParseLRNLayer },
-    { "InnerProduct", &CaffeParserImpl::ParseInnerProductLayer },
-    { "Softmax",      &CaffeParserImpl::ParseSoftmaxLayer },
-    { "Eltwise",      &CaffeParserImpl::ParseEltwiseLayer },
-    { "Concat",       &CaffeParserImpl::ParseConcatLayer },
-    { "BatchNorm",    &CaffeParserImpl::ParseBatchNormLayer },
-    { "Scale",        &CaffeParserImpl::ParseScaleLayer },
-    { "Split",        &CaffeParserImpl::ParseSplitLayer },
-    { "Dropout",      &CaffeParserImpl::ParseDropoutLayer},
-    { "ArgMax",       &CaffeParserImpl::ParseArgmaxLayer},
-};
-
-ICaffeParser::CaffeParserImpl::CaffeParserImpl()
-    : m_Network(nullptr, nullptr)
-{
-
-}
-
-CaffeParser::CaffeParser()
-: CaffeParserImpl()
-{
-
-}
-
-BindingPointInfo ICaffeParser::CaffeParserImpl::GetNetworkInputBindingInfo(const std::string& name) const
-{
-    return GetBindingInfo(name, "input", m_NetworkInputsBindingInfo);
-}
-
-BindingPointInfo ICaffeParser::CaffeParserImpl::GetNetworkOutputBindingInfo(const std::string& name) const
-{
-    return GetBindingInfo(name, "output", m_NetworkOutputsBindingInfo);
-}
-
-std::pair<armnn::LayerBindingId, armnn::TensorInfo> ICaffeParser::CaffeParserImpl::GetBindingInfo(
-    const std::string& layerName,
-    const char* bindingPointDesc,
-    const std::unordered_map<std::string, BindingPointInfo>& nameToBindingInfo)
-{
-    auto it = nameToBindingInfo.find(layerName);
-    if (it == nameToBindingInfo.end())
-    {
-        throw InvalidArgumentException(
-            fmt::format("Unknown binding {} for layer '{}'. {}",
-                        bindingPointDesc,
-                        layerName,
-                        CHECK_LOCATION().AsString()));
-    }
-    return it->second;
-}
-
-TensorInfo ICaffeParser::CaffeParserImpl::BlobShapeToTensorInfo(const caffe::BlobShape& blobShape) const
-{
-    std::vector<unsigned int> shape;
-    for (int j = 0; j < blobShape.dim_size(); ++j)
-    {
-        shape.push_back(static_cast<unsigned int>(blobShape.dim(j)));
-    }
-
-    return TensorInfo(armnn::numeric_cast<unsigned int>(shape.size()), shape.data(), DataType::Float32);
-}
-
-BlobShape TensorDescToBlobShape(const TensorInfo& desc)
-{
-    BlobShape ret;
-    for (unsigned int i = 0; i < desc.GetNumDimensions(); ++i)
-    {
-        ret.add_dim(i);
-        ret.set_dim(armnn::numeric_cast<int>(i), desc.GetShape()[i]);
-    }
-
-    return ret;
-}
-
-// Note: can move to CaffeParser when/if we optimise the text/string format
-//       to load on a layer by layer basis
-vector<const LayerParameter*> ICaffeParser::CaffeParserImpl::GetInputs(const LayerParameter& layerParam)
-{
-    std::vector<const caffe::LayerParameter*> ret;
-    ret.reserve(armnn::numeric_cast<size_t>(layerParam.bottom_size()));
-    for (int j = 0; j < layerParam.bottom_size(); ++j)
-    {
-        std::string inputName = layerParam.bottom(j);
-        auto inputIt = m_CaffeLayersByTopName.find(inputName);
-        if (inputIt == m_CaffeLayersByTopName.end())
-        {
-            throw ParseException(
-                fmt::format("Can't find Caffe layer with top called '{}', "
-                            "which is listed as an input of '{}'. {}",
-                            inputName,
-                            layerParam.name(),
-                            CHECK_LOCATION().AsString()));
-        }
-        ret.push_back(inputIt->second);
-    }
-
-    return ret;
-}
-
-void ICaffeParser::CaffeParserImpl::ParseInputLayer(const LayerParameter& layerParam)
-{
-    ARMNN_ASSERT(layerParam.type() == "Input");
-    ValidateNumInputsOutputs(layerParam, 0, 1);
-
-    const InputParameter& param = layerParam.input_param();
-
-    const armnn::LayerBindingId inputId = armnn::numeric_cast<armnn::LayerBindingId>(
-        m_NetworkInputsBindingInfo.size());
-    armnn::IConnectableLayer* const inputLayer = m_Network->AddInputLayer(inputId, layerParam.name().c_str());
-
-    // Decides the tensor info for this input. This can be specified in the Caffe network but can also
-    // be overriden by user input (m_inputShapes).
-    armnn::TensorInfo inputTensorInfo;
-
-    const BlobShape* originalShape = param.shape_size() > 0 && param.shape(0).dim_size() > 0 ?
-        &param.shape(0) : nullptr;
-    if (originalShape)
-    {
-        inputTensorInfo = BlobShapeToTensorInfo(*originalShape);
-    }
-
-    auto overrideIt = m_InputShapes.find(layerParam.name());
-    if (overrideIt != m_InputShapes.end())
-    {
-        const TensorShape& overrideShape = overrideIt->second;
-        if (originalShape &&
-            (    originalShape->dim(1) != overrideShape[1]
-              || originalShape->dim(2) != overrideShape[2]
-              || originalShape->dim(3) != overrideShape[3]))
-        {
-            throw ParseException(
-                fmt::format("Parsed input shape for '{}' is incompatible with the override provided. {}",
-                            layerParam.name(),
-                            CHECK_LOCATION().AsString()));
-        }
-        inputTensorInfo.SetShape(overrideShape);
-    }
-    else if (!originalShape)
-    {
-        throw ParseException(
-            fmt::format("No input descriptor given for '{}' and no input shape found in caffe model. {}",
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-    TrackInputBinding(inputLayer, inputId, inputTensorInfo);
-    inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), inputLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::AddConvLayerWithSplits(const caffe::LayerParameter& layerParam,
-                                                           const armnn::Convolution2dDescriptor& desc,
-                                                           unsigned int kernelW,
-                                                           unsigned int kernelH)
-{
-    ARMNN_ASSERT(layerParam.type() == "Convolution");
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    ConvolutionParameter convParam = layerParam.convolution_param();
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-    const unsigned int numGroups = convParam.has_group() ? convParam.group() : 1;
-
-    // asusme these were already verified by the caller ParseConvLayer() function
-    ARMNN_ASSERT(numGroups < inputShape.dim(1));
-    ARMNN_ASSERT(numGroups > 1);
-
-    // Handle grouping
-    armnn::IOutputSlot& inputConnection = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-
-    vector<string> convLayerNames(numGroups);
-    vector<armnn::IConnectableLayer*> convLayers(numGroups);
-    convLayerNames[0] = layerParam.name();
-
-    // This convolution is to be applied to chunks of the input data so add a splitter layer
-
-    // Redirect the convolution input to the splitter
-    unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape.dim(0)),
-                                        static_cast<unsigned int>(inputShape.dim(1)),
-                                        static_cast<unsigned int>(inputShape.dim(2)),
-                                        static_cast<unsigned int>(inputShape.dim(3))};
-
-    // Split dimension 1 of the splitter output shape and conv input shapes
-    // according to the number of groups
-
-    splitterDimSizes[1] /= numGroups;
-    inputShape.set_dim(1, splitterDimSizes[1]);
-
-    // This is used to describe how the input is to be split
-    ViewsDescriptor splitterDesc(numGroups);
-
-    // Create an output node for each group, giving each a unique name
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        // Work out the names of the splitter layers child convolutions
-        stringstream ss;
-        ss << layerParam.name() << "_" << g;
-        convLayerNames[g] = ss.str();
-
-        splitterDesc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g);
-
-        // Set the size of the views.
-        for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++)
-        {
-            splitterDesc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
-        }
-    }
-
-    const std::string splitterLayerName = std::string("splitter_") + layerParam.bottom(0);
-    armnn::IConnectableLayer* splitterLayer = m_Network->AddSplitterLayer(splitterDesc, splitterLayerName.c_str());
-
-    inputConnection.Connect(splitterLayer->GetInputSlot(0));
-    for (unsigned int i = 0; i < splitterLayer->GetNumOutputSlots(); i++)
-    {
-        splitterLayer->GetOutputSlot(i).SetTensorInfo(BlobShapeToTensorInfo(inputShape));
-    }
-
-    unsigned int numFilters = convParam.num_output();
-
-    // Populates convolution output tensor descriptor dimensions.
-    BlobShape outputShape;
-    outputShape.add_dim(0);
-    outputShape.set_dim(0, inputShape.dim(0));
-    outputShape.add_dim(1);
-    // Ensures that dimension 1 of the convolution output is split according to the number of groups.
-    outputShape.set_dim(1, numFilters / numGroups);
-    outputShape.add_dim(2);
-    outputShape.set_dim(
-        2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - (desc.m_DilationX * (kernelH - 1) + 1)) /
-                static_cast<float>(desc.m_StrideY)) + 1));
-    outputShape.add_dim(3);
-    outputShape.set_dim(
-        3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - (desc.m_DilationY * (kernelW - 1)  + 1)) /
-                static_cast<float>(desc.m_StrideX)) + 1));
-
-    // Load the weight data for ALL groups
-    vector<float> weightData(armnn::numeric_cast<size_t>(numGroups *
-                                                         inputShape.dim(1) *  // number of input channels
-                                                         outputShape.dim(1) * // number of output channels
-                                                         kernelH *
-                                                         kernelW));
-    GetDataFromBlob(layerParam, weightData, 0);
-
-    const unsigned int weightDimSizes[4] = {
-        static_cast<unsigned int>(outputShape.dim(1)),
-        static_cast<unsigned int>(inputShape.dim(1)),
-        kernelH,
-        kernelW};
-
-    TensorInfo biasInfo;
-    vector<float> biasData;
-
-    if (desc.m_BiasEnabled)
-    {
-        biasData.resize(armnn::numeric_cast<size_t>(numGroups * outputShape.dim(1)), 1.f);
-        GetDataFromBlob(layerParam, biasData, 1);
-
-        const unsigned int biasDimSizes[1] = {static_cast<unsigned int>(outputShape.dim(1))};
-        biasInfo = TensorInfo(1, biasDimSizes, DataType::Float32);
-    }
-
-    const unsigned int numWeightsPerGroup = armnn::numeric_cast<unsigned int>(weightData.size()) / numGroups;
-    const unsigned int numBiasesPerGroup  = armnn::numeric_cast<unsigned int>(biasData.size()) / numGroups;
-
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        // Sets the slot index, group 0 should be connected to the 0th output of the splitter
-        // group 1 should be connected to the 1st output of the splitter.
-
-        // Pulls out the weights for this group from that loaded from the model file earlier.
-        ConstTensor weights(TensorInfo(4, weightDimSizes, DataType::Float32),
-                            weightData.data() + numWeightsPerGroup * g);
-
-        IConnectableLayer* convLayer = nullptr;
-        Optional<ConstTensor> optionalBiases;
-        if (desc.m_BiasEnabled)
-        {
-            // Pulls out the biases for this group from that loaded from the model file earlier.
-            ConstTensor biases(biasInfo, biasData.data() + numBiasesPerGroup * g);
-            optionalBiases = Optional<ConstTensor>(biases);
-        }
-        convLayer = m_Network->AddConvolution2dLayer(desc,
-                                                     weights,
-                                                     optionalBiases,
-                                                     convLayerNames[g].c_str());
-        convLayers[g] = convLayer;
-
-        // If we have more than one group then the input to the nth convolution the splitter layer's nth output,
-        // otherwise it's the regular input to this layer.
-        armnn::IOutputSlot& splitterInputConnection =
-            splitterLayer ? splitterLayer->GetOutputSlot(g) : inputConnection;
-        splitterInputConnection.Connect(convLayer->GetInputSlot(0));
-        convLayer->GetOutputSlot(0).SetTensorInfo(BlobShapeToTensorInfo(outputShape));
-    }
-
-    // If the convolution was performed in chunks, add a layer to concatenate the results
-
-    // The merge input shape matches that of the convolution output
-    unsigned int concatDimSizes[4] = {static_cast<unsigned int>(outputShape.dim(0)),
-                                      static_cast<unsigned int>(outputShape.dim(1)),
-                                      static_cast<unsigned int>(outputShape.dim(2)),
-                                      static_cast<unsigned int>(outputShape.dim(3))};
-
-    // This is used to describe how the input is to be concatenated
-    OriginsDescriptor concatDesc(numGroups);
-
-    // Now create an input node for each group, using the name from
-    // the output of the corresponding convolution
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        concatDesc.SetViewOriginCoord(g, 1, concatDimSizes[1] * g);
-    }
-
-    // Make sure the output from the concat is the correct size to hold the data for all groups
-    concatDimSizes[1] *= numGroups;
-    outputShape.set_dim(1, concatDimSizes[1]);
-
-    // Finally add the concat layer
-    IConnectableLayer* concatLayer = m_Network->AddConcatLayer(concatDesc, layerParam.name().c_str());
-
-    if (!concatLayer)
-    {
-        throw ParseException(
-            fmt::format("Failed to create final concat layer for Split+Convolution+Concat. "
-                        "Layer={} #groups={} #filters={} {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        convLayers[g]->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(g));
-    }
-    concatLayer->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo(4, concatDimSizes, DataType::Float32));
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), concatLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::AddDeconvLayerWithSplits(const caffe::LayerParameter& layerParam,
-                                                             const armnn::TransposeConvolution2dDescriptor& desc,
-                                                             unsigned int kernelW,
-                                                             unsigned int kernelH)
-{
-    ARMNN_ASSERT(layerParam.type() == "Deconvolution");
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    ConvolutionParameter convParam = layerParam.convolution_param();
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-    const unsigned int numGroups = convParam.has_group() ? convParam.group() : 1;
-
-    // asusme these were already verified by the caller ParseDeconvLayer() function
-    ARMNN_ASSERT(numGroups <= inputShape.dim(1));
-    ARMNN_ASSERT(numGroups > 1);
-
-    // Handle grouping
-    armnn::IOutputSlot& inputConnection = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-
-    vector<string> convLayerNames(numGroups);
-    vector<armnn::IConnectableLayer*> convLayers(numGroups);
-    convLayerNames[0] = layerParam.name();
-
-    // This deconvolution is to be applied to chunks of the input data so add a splitter layer
-
-    // Redirect the deconvolution input to the splitter
-    unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape.dim(0)),
-                                        static_cast<unsigned int>(inputShape.dim(1)),
-                                        static_cast<unsigned int>(inputShape.dim(2)),
-                                        static_cast<unsigned int>(inputShape.dim(3))};
-
-    // Split dimension 1 of the splitter output shape and deconv input shapes
-    // according to the number of groups
-
-    splitterDimSizes[1] /= numGroups;
-    inputShape.set_dim(1, splitterDimSizes[1]);
-
-    // This is used to describe how the input is to be split
-    ViewsDescriptor splitterDesc(numGroups);
-
-    // Create an output node for each group, giving each a unique name
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        // Work out the names of the splitter layers child deconvolutions
-        stringstream ss;
-        ss << layerParam.name() << "_" << g;
-        convLayerNames[g] = ss.str();
-
-        splitterDesc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g);
-
-        // Set the size of the views.
-        for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++)
-        {
-            splitterDesc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
-        }
-    }
-
-    const std::string splitterLayerName = std::string("splitter_") + layerParam.bottom(0);
-    armnn::IConnectableLayer* splitterLayer = m_Network->AddSplitterLayer(splitterDesc, splitterLayerName.c_str());
-
-    inputConnection.Connect(splitterLayer->GetInputSlot(0));
-    for (unsigned int i = 0; i < splitterLayer->GetNumOutputSlots(); i++)
-    {
-        splitterLayer->GetOutputSlot(i).SetTensorInfo(BlobShapeToTensorInfo(inputShape));
-    }
-
-    unsigned int numFilters = convParam.num_output();
-
-    // Populates deconvolution output tensor descriptor dimensions.
-    BlobShape outputShape;
-    outputShape.add_dim(0);
-    outputShape.set_dim(0, inputShape.dim(0));
-    outputShape.add_dim(1);
-    // Ensures that dimension 1 of the deconvolution output is split according to the number of groups.
-    outputShape.set_dim(1, numFilters / numGroups);
-    outputShape.add_dim(2);
-    outputShape.set_dim(
-        2, (static_cast<int>(
-                desc.m_StrideY * (inputShape.dim(2) - 1) - 2 * desc.m_PadBottom + kernelH)));
-    outputShape.add_dim(3);
-    outputShape.set_dim(
-        3, (static_cast<int>(
-                desc.m_StrideX * (inputShape.dim(3) - 1) - 2 * desc.m_PadRight + kernelW)));
-
-    // Load the weight data for ALL groups
-    vector<float> weightData(armnn::numeric_cast<size_t>(numGroups *
-                                                         inputShape.dim(1) *  // number of input channels
-                                                         outputShape.dim(1) * // number of output channels
-                                                         kernelH *
-                                                         kernelW));
-    GetDataFromBlob(layerParam, weightData, 0);
-
-    const unsigned int weightDimSizes[4] = {
-        static_cast<unsigned int>(outputShape.dim(1)),
-        static_cast<unsigned int>(inputShape.dim(1)),
-        kernelH,
-        kernelW};
-
-    TensorInfo biasInfo;
-    vector<float> biasData;
-
-    if (desc.m_BiasEnabled)
-    {
-        biasData.resize(armnn::numeric_cast<size_t>(numGroups * outputShape.dim(1)), 1.f);
-        GetDataFromBlob(layerParam, biasData, 1);
-
-        const unsigned int biasDimSizes[1] = {static_cast<unsigned int>(outputShape.dim(1))};
-        biasInfo = TensorInfo(1, biasDimSizes, DataType::Float32);
-    }
-
-    const unsigned int numWeightsPerGroup = armnn::numeric_cast<unsigned int>(weightData.size()) / numGroups;
-    const unsigned int numBiasesPerGroup  = armnn::numeric_cast<unsigned int>(biasData.size()) / numGroups;
-
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        // Sets the slot index, group 0 should be connected to the 0th output of the splitter
-        // group 1 should be connected to the 1st output of the splitter.
-
-        // Pulls out the weights for this group from that loaded from the model file earlier.
-        ConstTensor weights(TensorInfo(4, weightDimSizes, DataType::Float32),
-                            weightData.data() + numWeightsPerGroup * g);
-
-        IConnectableLayer* deconvLayer = nullptr;
-        Optional<ConstTensor> optionalBiases;
-        if (desc.m_BiasEnabled)
-        {
-            // Pulls out the biases for this group from that loaded from the model file earlier.
-            ConstTensor biases(biasInfo, biasData.data() + numBiasesPerGroup * g);
-            optionalBiases = Optional<ConstTensor>(biases);
-        }
-        deconvLayer = m_Network->AddTransposeConvolution2dLayer(desc,
-                                                     weights,
-                                                     optionalBiases,
-                                                     convLayerNames[g].c_str());
-        convLayers[g] = deconvLayer;
-
-        // If we have more than one group then the input to the nth deconvolution the splitter layer's nth output,
-        // otherwise it's the regular input to this layer.
-        armnn::IOutputSlot& splitterInputConnection =
-            splitterLayer ? splitterLayer->GetOutputSlot(g) : inputConnection;
-        splitterInputConnection.Connect(deconvLayer->GetInputSlot(0));
-        deconvLayer->GetOutputSlot(0).SetTensorInfo(BlobShapeToTensorInfo(outputShape));
-    }
-
-    // If the deconvolution was performed in chunks, add a layer to concatenate the results
-
-    // The merge input shape matches that of the deconvolution output
-    unsigned int concatDimSizes[4] = {static_cast<unsigned int>(outputShape.dim(0)),
-                                      static_cast<unsigned int>(outputShape.dim(1)),
-                                      static_cast<unsigned int>(outputShape.dim(2)),
-                                      static_cast<unsigned int>(outputShape.dim(3))};
-
-    // This is used to describe how the input is to be concatenated
-    OriginsDescriptor concatDesc(numGroups);
-
-    // Now create an input node for each group, using the name from
-    // the output of the corresponding deconvolution
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        concatDesc.SetViewOriginCoord(g, 1, concatDimSizes[1] * g);
-    }
-
-    // Make sure the output from the concat is the correct size to hold the data for all groups
-    concatDimSizes[1] *= numGroups;
-    outputShape.set_dim(1, concatDimSizes[1]);
-
-    // Finally add the concat layer
-    IConnectableLayer* concatLayer = m_Network->AddConcatLayer(concatDesc, layerParam.name().c_str());
-
-    if (!concatLayer)
-    {
-        throw ParseException(
-            fmt::format("Failed to create final concat layer for Split+Deconvolution+Concat. "
-                        "Layer={} #groups={} #filters={} {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    for (unsigned int g = 0; g < numGroups; ++g)
-    {
-        convLayers[g]->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(g));
-    }
-    concatLayer->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo(4, concatDimSizes, DataType::Float32));
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), concatLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::AddConvLayerWithDepthwiseConv(const caffe::LayerParameter& layerParam,
-                                                                  const armnn::Convolution2dDescriptor& convDesc,
-                                                                  unsigned int kernelW,
-                                                                  unsigned int kernelH)
-{
-    ARMNN_ASSERT(layerParam.type() == "Convolution");
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    ConvolutionParameter convParam  = layerParam.convolution_param();
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-
-    DepthwiseConvolution2dDescriptor desc;
-    desc.m_PadLeft      = convDesc.m_PadLeft;
-    desc.m_PadRight     = convDesc.m_PadRight;
-    desc.m_PadTop       = convDesc.m_PadTop;
-    desc.m_PadBottom    = convDesc.m_PadBottom;
-    desc.m_StrideX      = convDesc.m_StrideX;
-    desc.m_StrideY      = convDesc.m_StrideY;
-    desc.m_DilationX    = convDesc.m_DilationX;
-    desc.m_DilationY    = convDesc.m_DilationY;
-    desc.m_BiasEnabled  = convDesc.m_BiasEnabled;
-
-    unsigned int numFilters = convParam.num_output();
-
-    BlobShape outputShape;
-    outputShape.add_dim(0);
-    outputShape.set_dim(0, inputShape.dim(0));
-    outputShape.add_dim(1);
-    outputShape.set_dim(1, numFilters);
-    outputShape.add_dim(2);
-    outputShape.set_dim(
-        2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - (desc.m_DilationX * (kernelH - 1) + 1)) /
-                static_cast<float>(desc.m_StrideY)) + 1));
-    outputShape.add_dim(3);
-    outputShape.set_dim(
-        3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - (desc.m_DilationY * (kernelW - 1) + 1)) /
-                static_cast<float>(desc.m_StrideX)) + 1));
-
-    // Load the weight data
-    size_t allWeightsSize = armnn::numeric_cast<size_t>(inputShape.dim(1) * kernelH * kernelW);
-    vector<float> weightData(allWeightsSize);
-
-    GetDataFromBlob(layerParam, weightData, 0);
-
-    // depth multiplier will be 1 for the depthwise convolution
-    const unsigned int weightDimSizes[4] = {
-        static_cast<unsigned int>(1),                 // depth multiplier
-        static_cast<unsigned int>(inputShape.dim(1)), // #channels
-        kernelH,
-        kernelW};
-
-    armnn::IConnectableLayer* returnLayer = nullptr;
-    ConstTensor weights(TensorInfo(4, weightDimSizes, DataType::Float32), weightData.data());
-    Optional<ConstTensor> optionalBiases;
-    vector<float> biasData;
-    if (desc.m_BiasEnabled)
-    {
-        TensorInfo biasInfo;
-
-        biasData.resize(armnn::numeric_cast<size_t>(outputShape.dim(1)), 1.f);
-        GetDataFromBlob(layerParam, biasData, 1);
-
-        const unsigned int biasDimSizes[1] = {static_cast<unsigned int>(outputShape.dim(1))};
-        biasInfo = TensorInfo(1, biasDimSizes, DataType::Float32);
-
-        ConstTensor biases(biasInfo, biasData.data());
-        optionalBiases = Optional<ConstTensor>(biases);
-    }
-    returnLayer = m_Network->AddDepthwiseConvolution2dLayer(desc,
-                                                            weights,
-                                                            optionalBiases,
-                                                            layerParam.name().c_str());
-
-    if (!returnLayer)
-    {
-        throw ParseException(
-            fmt::format("Failed to create depthwise convolution layer. "
-                        "Layer={} #filters={} {}",
-                        layerParam.name(),
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-    armnn::IOutputSlot& inputConnection = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-    inputConnection.Connect(returnLayer->GetInputSlot(0));
-    returnLayer->GetOutputSlot(0).SetTensorInfo(BlobShapeToTensorInfo(outputShape));
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), returnLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseConvLayer(const LayerParameter& layerParam)
-{
-    // Ignored Caffe Parameters
-    // * Weight Filler
-    // * Bias Filler
-    // * Engine
-    // * Force nd_im2col
-    // * Axis
-
-    // Not Available ArmNN Interface Parameters
-    // * Rounding policy;
-
-    ARMNN_ASSERT(layerParam.type() == "Convolution");
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    ConvolutionParameter convParam = layerParam.convolution_param();
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-    const unsigned int numGroups = convParam.has_group() ? convParam.group() : 1;
-    unsigned int numFilters = convParam.num_output();
-
-    const auto notFound = std::numeric_limits<unsigned int>::max();
-
-    unsigned int kernelH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             kernel_h, kernel_size, unsigned int, notFound);
-    unsigned int kernelW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             kernel_w, kernel_size, unsigned int, notFound);
-
-    unsigned int strideH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             stride_h, stride, unsigned int, 1u);
-    unsigned int strideW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             stride_w, stride, unsigned int, 1u);
-
-    unsigned int padH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                          pad_h, pad, unsigned int, 0u);
-    unsigned int padW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                          pad_w, pad, unsigned int, 0u);
-
-    unsigned int dilationH = convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
-    unsigned int dilationW = convParam.dilation_size() > 1 ? convParam.dilation(1) :
-        convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
-
-    Convolution2dDescriptor convolution2dDescriptor;
-    convolution2dDescriptor.m_PadLeft     = padW;
-    convolution2dDescriptor.m_PadRight    = padW;
-    convolution2dDescriptor.m_PadTop      = padH;
-    convolution2dDescriptor.m_PadBottom   = padH;
-    convolution2dDescriptor.m_StrideX     = strideW;
-    convolution2dDescriptor.m_StrideY     = strideH;
-    convolution2dDescriptor.m_DilationX   = dilationW;
-    convolution2dDescriptor.m_DilationY   = dilationH;
-    convolution2dDescriptor.m_BiasEnabled = convParam.has_bias_term() ? convParam.bias_term() : true;
-
-    if (numGroups > numFilters)
-    {
-        throw ParseException(
-            fmt::format("Error parsing Convolution: {}. "
-                        "The 'group'={} parameter cannot be larger than the "
-                        "number of filters supplied ='{}'. {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (inputShape.dim_size() != 4)
-    {
-        throw ParseException(
-            fmt::format("Convolution input shape is expected to have 4 dimensions. "
-                        "{}'s input has only {}. {}",
-                        layerParam.name(),
-                        inputShape.dim_size(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (numGroups > 1)
-    {
-        if (numGroups > inputShape.dim(1))
-        {
-            throw ParseException(
-                fmt::format("Error parsing Convolution: {}. "
-                            "The 'group'={} parameter cannot be larger than the "
-                            "channel of the input shape={} (in NCHW format). {}",
-                            layerParam.name(),
-                            numGroups,
-                            inputShape.dim(1),
-                            CHECK_LOCATION().AsString()));
-        }
-        else if (numGroups == inputShape.dim(1))
-        {
-            // we use a depthwise convolution here, because the number of groups equals to the
-            // input channels
-            AddConvLayerWithDepthwiseConv(layerParam, convolution2dDescriptor, kernelW, kernelH);
-            return;
-        }
-        else
-        {
-            // we split the input by channels into channels/groups separate convolutions
-            // and concatenate the results afterwards
-            AddConvLayerWithSplits(layerParam, convolution2dDescriptor, kernelW, kernelH);
-            return;
-        }
-    }
-
-    // NOTE: at this point we only need to handle #group=1 case, all other cases should be
-    //       handled by the AddConvLayer* helpers
-
-    // Populate convolution output tensor descriptor dimensions
-    BlobShape outputShape;
-    outputShape.add_dim(0);
-    outputShape.set_dim(0, inputShape.dim(0));
-    outputShape.add_dim(1);
-    outputShape.set_dim(1, numFilters);
-    outputShape.add_dim(2);
-    outputShape.set_dim(
-        2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * padH - (dilationH * (kernelH - 1) + 1)) /
-                static_cast<float>(strideH)) + 1));
-    outputShape.add_dim(3);
-    outputShape.set_dim(
-        3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * padW - (dilationW * (kernelW - 1) + 1)) /
-                static_cast<float>(strideW)) + 1));
-
-    // Load the weight data for ALL groups
-    vector<float> weightData(armnn::numeric_cast<size_t>(inputShape.dim(1) *
-                                                         outputShape.dim(1) *
-                                                         kernelH *
-                                                         kernelW));
-    GetDataFromBlob(layerParam, weightData, 0);
-
-    const unsigned int weightDimSizes[4] = {
-        static_cast<unsigned int>(outputShape.dim(1)), // output channels
-        static_cast<unsigned int>(inputShape.dim(1)),  // input channels
-        kernelH,
-        kernelW};
-
-    armnn::IConnectableLayer* returnLayer = nullptr;
-
-    // Pull out the weights for this group from that loaded from the model file earlier
-    ConstTensor weights(TensorInfo(4, weightDimSizes, DataType::Float32), weightData.data());
-    Optional<ConstTensor> optionalBiases;
-    vector<float> biasData;
-    if (convolution2dDescriptor.m_BiasEnabled)
-    {
-        TensorInfo biasInfo;
-
-        biasData.resize(armnn::numeric_cast<size_t>(outputShape.dim(1)), 1.f);
-        GetDataFromBlob(layerParam, biasData, 1);
-
-        const unsigned int biasDimSizes[1] = {static_cast<unsigned int>(outputShape.dim(1))};
-        biasInfo = TensorInfo(1, biasDimSizes, DataType::Float32);
-
-        // Pull out the biases for this group from that loaded from the model file earlier
-        ConstTensor biases(biasInfo, biasData.data());
-        optionalBiases = Optional<ConstTensor>(biases);
-    }
-    returnLayer = m_Network->AddConvolution2dLayer(convolution2dDescriptor,
-                                                   weights,
-                                                   optionalBiases,
-                                                   layerParam.name().c_str());
-
-    armnn::IOutputSlot& inputConnection = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-    inputConnection.Connect(returnLayer->GetInputSlot(0));
-    returnLayer->GetOutputSlot(0).SetTensorInfo(BlobShapeToTensorInfo(outputShape));
-
-    if (!returnLayer)
-    {
-        throw ParseException(
-            fmt::format("Failed to create Convolution layer. "
-                        "Layer={} #groups={} #filters={} {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), returnLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseDeconvLayer(const LayerParameter& layerParam)
-{
-    // Ignored Caffe Parameters
-    // * Weight Filler
-    // * Bias Filler
-    // * Engine
-    // * Force nd_im2col
-    // * Axis
-
-    // Not Available ArmNN Interface Parameters
-    // * Rounding policy;
-
-    ARMNN_ASSERT(layerParam.type() == "Deconvolution");
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    ConvolutionParameter convParam = layerParam.convolution_param();
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-    const unsigned int numGroups = convParam.has_group() ? convParam.group() : 1;
-    unsigned int numFilters = convParam.num_output();
-
-    const auto notFound = std::numeric_limits<unsigned int>::max();
-
-    unsigned int kernelH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             kernel_h, kernel_size, unsigned int, notFound);
-    unsigned int kernelW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             kernel_w, kernel_size, unsigned int, notFound);
-
-    unsigned int strideH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             stride_h, stride, unsigned int, 1u);
-    unsigned int strideW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                             stride_w, stride, unsigned int, 1u);
-
-    unsigned int padH = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                          pad_h, pad, unsigned int, 0u);
-    unsigned int padW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
-                                                          pad_w, pad, unsigned int, 0u);
-
-    unsigned int dilationH = convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
-    unsigned int dilationW = convParam.dilation_size() > 1 ? convParam.dilation(1) :
-        convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
-
-    if (dilationH != 1 || dilationW != 1) {
-        fmt::format("Dilated decnvolution is not supported. "
-                "{}'s input has dilation {} {}. {}",
-                layerParam.name(),
-                dilationW, dilationH,
-                CHECK_LOCATION().AsString());
-    }
-
-    TransposeConvolution2dDescriptor deconvolution2dDescriptor;
-    deconvolution2dDescriptor.m_PadLeft     = padW;
-    deconvolution2dDescriptor.m_PadRight    = padW;
-    deconvolution2dDescriptor.m_PadTop      = padH;
-    deconvolution2dDescriptor.m_PadBottom   = padH;
-    deconvolution2dDescriptor.m_StrideX     = strideW;
-    deconvolution2dDescriptor.m_StrideY     = strideH;
-    deconvolution2dDescriptor.m_BiasEnabled = convParam.has_bias_term() ? convParam.bias_term() : true;
-
-    if (numGroups > numFilters)
-    {
-        throw ParseException(
-            fmt::format("Error parsing Deconvolution: {}. "
-                        "The 'group'={} parameter cannot be larger than the "
-                        "number of filters supplied ='{}'. {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (inputShape.dim_size() != 4)
-    {
-        throw ParseException(
-            fmt::format("Deconvolution input shape is expected to have 4 dimensions. "
-                        "{}'s input has only {}. {}",
-                        layerParam.name(),
-                        inputShape.dim_size(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (numGroups > 1)
-    {
-        if (numGroups > inputShape.dim(1))
-        {
-            throw ParseException(
-                fmt::format("Error parsing Deconvolution: {}. "
-                            "The 'group'={} parameter cannot be larger than the "
-                            "channel of the input shape={} (in NCHW format). {}",
-                            layerParam.name(),
-                            numGroups,
-                            inputShape.dim(1),
-                            CHECK_LOCATION().AsString()));
-        }
-        else
-        {
-            // we split the input by channels into channels/groups separate convolutions
-            // and concatenate the results afterwards
-            AddDeconvLayerWithSplits(layerParam, deconvolution2dDescriptor, kernelW, kernelH);
-            return;
-        }
-    }
-
-    // NOTE: at this point we only need to handle #group=1 case, all other cases should be
-    //       handled by the AddDeconvLayer* helpers
-
-    // Populate deconvolution output tensor descriptor dimensions
-    BlobShape outputShape;
-    outputShape.add_dim(0);
-    outputShape.set_dim(0, inputShape.dim(0));
-    outputShape.add_dim(1);
-    outputShape.set_dim(1, numFilters);
-    outputShape.add_dim(2);
-    outputShape.set_dim(
-        2, (static_cast<int>(
-                strideH * (inputShape.dim(2) - 1) - 2 * padH + (dilationH * (kernelH - 1) + 1))));
-    outputShape.add_dim(3);
-    outputShape.set_dim(
-        3, (static_cast<int>(
-                strideW * (inputShape.dim(3) - 1) - 2 * padW + (dilationW * (kernelW - 1) + 1))));
-
-    // Load the weight data for ALL groups
-    vector<float> weightData(armnn::numeric_cast<size_t>(inputShape.dim(1) *
-                                                         outputShape.dim(1) *
-                                                         kernelH *
-                                                         kernelW));
-    GetDataFromBlob(layerParam, weightData, 0);
-
-    const unsigned int weightDimSizes[4] = {
-        static_cast<unsigned int>(outputShape.dim(1)), // output channels
-        static_cast<unsigned int>(inputShape.dim(1)),  // input channels
-        kernelH,
-        kernelW};
-
-    armnn::IConnectableLayer* returnLayer = nullptr;
-
-    // Pull out the weights for this group from that loaded from the model file earlier
-    ConstTensor weights(TensorInfo(4, weightDimSizes, DataType::Float32), weightData.data());
-    Optional<ConstTensor> optionalBiases;
-    vector<float> biasData;
-    if (deconvolution2dDescriptor.m_BiasEnabled)
-    {
-        TensorInfo biasInfo;
-
-        biasData.resize(armnn::numeric_cast<size_t>(outputShape.dim(1)), 1.f);
-        GetDataFromBlob(layerParam, biasData, 1);
-
-        const unsigned int biasDimSizes[1] = {static_cast<unsigned int>(outputShape.dim(1))};
-        biasInfo = TensorInfo(1, biasDimSizes, DataType::Float32);
-
-        // Pull out the biases for this group from that loaded from the model file earlier
-        ConstTensor biases(biasInfo, biasData.data());
-        optionalBiases = Optional<ConstTensor>(biases);
-    }
-    returnLayer = m_Network->AddTransposeConvolution2dLayer(deconvolution2dDescriptor,
-                                                   weights,
-                                                   optionalBiases,
-                                                   layerParam.name().c_str());
-
-    armnn::IOutputSlot& inputConnection = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-    inputConnection.Connect(returnLayer->GetInputSlot(0));
-    returnLayer->GetOutputSlot(0).SetTensorInfo(BlobShapeToTensorInfo(outputShape));
-
-    if (!returnLayer)
-    {
-        throw ParseException(
-            fmt::format("Failed to create Deconvolution layer. "
-                        "Layer={} #groups={} #filters={} {}",
-                        layerParam.name(),
-                        numGroups,
-                        numFilters,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), returnLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParsePoolingLayer(const LayerParameter& layerParam)
-{
-    // Ignored Caffe Parameters
-    //      Stochastic Pooling
-    //      Engine
-
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-    PoolingParameter param = layerParam.pooling_param();
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    const auto notFound = std::numeric_limits<unsigned int>::max();
-
-    unsigned int kernel_h = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                       kernel_h, kernel_size, unsigned int, notFound);
-    unsigned int kernel_w = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                       kernel_w, kernel_size, unsigned int, notFound);
-
-    if ((kernel_h == notFound || kernel_w == notFound) && param.has_global_pooling())
-    {
-        kernel_h = inputInfo.GetShape()[2];
-        kernel_w = inputInfo.GetShape()[3];
-    }
-
-    unsigned int stride_h = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                       stride_h, stride, unsigned int, notFound);
-    unsigned int stride_w = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                       stride_h, stride, unsigned int, notFound);
-
-    if ((stride_h == notFound || stride_w == notFound) && param.has_global_pooling())
-    {
-        stride_h = 1;
-        stride_w = 1;
-    }
-
-    unsigned int pad_h = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                    pad_h, pad, unsigned int, 0u);
-    unsigned int pad_w = GET_OPTIONAL_WITH_FALLBACK(param, PoolingParameter,
-                                                    pad_w, pad, unsigned int, 0u);
-
-    // Populate Weight and Bias Filter Descriptor
-    Pooling2dDescriptor pooling2dDescriptor;
-    if (param.has_pool())
-    {
-        PoolingParameter_PoolMethod p = param.pool();
-        switch (p)
-        {
-            case PoolingParameter_PoolMethod_MAX:
-            {
-                pooling2dDescriptor.m_PoolType = PoolingAlgorithm::Max;
-                break;
-            }
-            case PoolingParameter_PoolMethod_AVE:
-            {
-                pooling2dDescriptor.m_PoolType = PoolingAlgorithm::Average;
-                break;
-            }
-            case PoolingParameter_PoolMethod_STOCHASTIC:
-            {
-                throw ParseException(
-                    fmt::format("Pooling Layer: Stochastic Pooling Not Supported. Layer={} {}",
-                                layerParam.name(),
-                                CHECK_LOCATION().AsString()));
-            }
-            default:
-            {
-                throw ParseException(
-                    fmt::format("Pooling Layer: unknown pooling method: {} for layer: {} {}",
-                                p,
-                                layerParam.name(),
-                                CHECK_LOCATION().AsString()));
-            }
-        }
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("No Pooling Method Defined for {} {}",
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    pooling2dDescriptor.m_PadLeft     = pad_w;
-    pooling2dDescriptor.m_PadRight    = pad_w;
-    pooling2dDescriptor.m_PadTop      = pad_h;
-    pooling2dDescriptor.m_PadBottom   = pad_h;
-    pooling2dDescriptor.m_StrideX     = stride_w;
-    pooling2dDescriptor.m_StrideY     = stride_h;
-    pooling2dDescriptor.m_PoolWidth   = kernel_w;
-    pooling2dDescriptor.m_PoolHeight  = kernel_h;
-
-    pooling2dDescriptor.m_OutputShapeRounding = OutputShapeRounding::Ceiling;
-    pooling2dDescriptor.m_PaddingMethod  = PaddingMethod::IgnoreValue;
-
-    armnn::IConnectableLayer* poolingLayer = m_Network->AddPooling2dLayer(pooling2dDescriptor,
-        layerParam.name().c_str());
-
-    TensorInfo outputInfo(
-        { inputInfo.GetShape()[0],
-          inputInfo.GetShape()[1],
-          static_cast<unsigned int>(ceil(
-              static_cast<float>(inputInfo.GetShape()[2] + 2 * pad_h - kernel_h) /
-              armnn::numeric_cast<float>(stride_h))) + 1,
-          static_cast<unsigned int>(ceil(
-              static_cast<float>(inputInfo.GetShape()[3] + 2 * pad_w - kernel_w) /
-              armnn::numeric_cast<float>(stride_w))) + 1 },
-        DataType::Float32);
-
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(poolingLayer->GetInputSlot(0));
-    poolingLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), poolingLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseArgmaxLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-    ArgMaxParameter param = layerParam.argmax_param();
-
-    BlobShape inputShape = TensorDescToBlobShape(GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo());
-
-    const unsigned int topK = param.has_top_k() ? param.top_k() : 1;
-    if (topK != 1) {
-        throw ParseException(
-                fmt::format("ArgMaxLayer: Only support top_k equals to 1. Layer={} {}",
-                    layerParam.name(),
-                    CHECK_LOCATION().AsString()));
-    }
-
-    const unsigned int outMaxVal = param.has_out_max_val() ? param.out_max_val() : false;
-    if (outMaxVal) {
-        throw ParseException(
-                fmt::format("ArgMaxLayer: Does not support out_max_val. Layer={} {}",
-                    layerParam.name(),
-                    CHECK_LOCATION().AsString()));
-    }
-
-    int axis = param.has_axis() ? param.axis() : 1;
-    if (axis < 0) {
-        axis = inputShape.dim_size() - axis;
-    }
-    if ((axis < 0) || (axis >= inputShape.dim_size())) {
-        throw ParseException(
-            fmt::format("ArgMaxLayer: Invalid axis value which outside range of input dims. "
-                        "{}'s input has input dim_size {}, requested axis: {}. {}",
-                        layerParam.name(),
-                        inputShape.dim_size(),
-                        axis,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    ArgMinMaxDescriptor desc;
-    desc.m_Axis = axis;
-    desc.m_Function = ArgMinMaxFunction::Max;
-
-    armnn::IConnectableLayer* argmaxLayer = m_Network->AddArgMinMaxLayer(desc,
-        layerParam.name().c_str());
-
-    TensorShape outputShape(static_cast<unsigned int>(inputShape.dim_size() - 1));
-    int j = 0;
-    // remove the flatten axis
-    for (int i = 0; i < inputShape.dim_size(); ++i)
-    {
-        if (i == axis) continue;
-        outputShape[static_cast<unsigned int>(j++)] = static_cast<unsigned int>(inputShape.dim(i));
-    }
-    TensorInfo outputInfo(outputShape, DataType::Signed32);
-
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(argmaxLayer->GetInputSlot(0));
-    argmaxLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), argmaxLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseReluLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    const string& name = layerParam.name();
-    const ReLUParameter& param = layerParam.relu_param();
-
-    ActivationDescriptor activationDescriptor;
-    const float negativeSlope = param.negative_slope();
-    if (negativeSlope == 0.0f)
-    {
-        activationDescriptor.m_Function = ActivationFunction::ReLu;
-    }
-    else
-    {
-        activationDescriptor.m_Function = ActivationFunction::LeakyReLu;
-        activationDescriptor.m_A = negativeSlope;
-    }
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-    IConnectableLayer* const activationLayer = m_Network->AddActivationLayer(activationDescriptor, name.c_str());
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(activationLayer->GetInputSlot(0));
-    activationLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), activationLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseLRNLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    LRNParameter param = layerParam.lrn_param();
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    // Ignored BATCH NORMALIZATION Caffe Parameters.
-    // Ignored MVN Caffe Parameters.
-    // Ignored LRN Caffe Parameters.
-    //      Engine
-
-    NormalizationDescriptor normalizationDescriptor;
-    if (param.has_norm_region())
-    {
-        LRNParameter_NormRegion n = param.norm_region();
-        switch (n)
-        {
-            case LRNParameter_NormRegion_ACROSS_CHANNELS:
-            {
-                normalizationDescriptor.m_NormChannelType = NormalizationAlgorithmChannel::Across;
-                break;
-            }
-            case LRNParameter_NormRegion_WITHIN_CHANNEL:
-            {
-                normalizationDescriptor.m_NormChannelType = NormalizationAlgorithmChannel::Within;
-                break;
-            }
-            default:
-            {
-                throw ParseException(
-                    fmt::format("Unknown region {} for LRN layer {} {}",
-                                n,
-                                layerParam.name(),
-                                CHECK_LOCATION().AsString()));
-            }
-        }
-    }
-    else
-    {
-        // Caffe defaults to normalization across channels.
-        normalizationDescriptor.m_NormChannelType = NormalizationAlgorithmChannel::Across;
-    }
-
-    normalizationDescriptor.m_NormMethodType = NormalizationAlgorithmMethod::LocalBrightness;
-    if (param.has_local_size())
-    {
-        normalizationDescriptor.m_NormSize = param.local_size();
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("local_size not defined for LRN layer {} {}",
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (param.has_alpha())
-    {
-        normalizationDescriptor.m_Alpha = param.alpha();
-        normalizationDescriptor.m_Alpha /= armnn::numeric_cast<float>(param.local_size());
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("Alpha not defined for LRN layer {} {}",
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-    if (param.has_beta())
-    {
-        normalizationDescriptor.m_Beta = param.beta();
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("Beta not defined for LRN layer {} {}",
-                        layerParam.name(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    if (param.has_k())
-    {
-        normalizationDescriptor.m_K = param.k();
-    }
-    else
-    {
-        normalizationDescriptor.m_K = 1;
-    }
-
-    IConnectableLayer* const normLayer = m_Network->AddNormalizationLayer(normalizationDescriptor,
-        layerParam.name().c_str());
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(normLayer->GetInputSlot(0));
-    normLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), normLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseInnerProductLayer(const LayerParameter& layerParam)
-{
-    InnerProductParameter param = layerParam.inner_product_param();
-
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    unsigned int outputSize = param.num_output();
-
-    // Ignored Caffe Parameters:
-    // Weight Filler
-    // Bias Filler
-    // Engine
-    // Axis
-
-    FullyConnectedDescriptor tensorFullyConnectedDescriptor;
-
-    if (param.has_transpose())
-    {
-        // If true, assumes transposed weights.
-        tensorFullyConnectedDescriptor.m_TransposeWeightMatrix = param.transpose();
-    }
-    else
-    {
-        // Caffe defaults to transposed.
-        tensorFullyConnectedDescriptor.m_TransposeWeightMatrix = true;
-    }
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    TensorInfo weightInfo;
-    TensorInfo biasInfo;
-
-    // Allows implicit flattening of extra dimensions.
-    unsigned int inputSize = inputInfo.GetShape()[1];
-    for (unsigned int i = 2; i < inputInfo.GetNumDimensions(); ++i)
-    {
-        inputSize *= inputInfo.GetShape()[i];
-    }
-
-    const float* weightDataPtr = GetArrayPtrFromBlob(layerParam, 0);
-    const unsigned int swTD[2] = { outputSize, inputSize };
-    ConstTensor weights(TensorInfo(2, swTD, DataType::Float32), weightDataPtr);
-
-    tensorFullyConnectedDescriptor.m_BiasEnabled = true;
-    // Todo: check whether bias enabled.
-    armnn::IConnectableLayer* fullyConnectedLayer = nullptr;
-    if (tensorFullyConnectedDescriptor.m_BiasEnabled)
-    {
-        // BIAS VALUE
-        const float* biasDataPtr = GetArrayPtrFromBlob(layerParam, 1);
-
-        const unsigned int sbTD[1] = { outputSize };
-
-        ConstTensor biases(TensorInfo(1, sbTD, DataType::Float32), biasDataPtr);
-
-        fullyConnectedLayer = m_Network->AddFullyConnectedLayer(tensorFullyConnectedDescriptor,
-                                                                weights,
-                                                                Optional<ConstTensor>(biases),
-                                                                layerParam.name().c_str());
-    }
-    else
-    {
-        fullyConnectedLayer = m_Network->AddFullyConnectedLayer(tensorFullyConnectedDescriptor,
-                                                                weights,
-                                                                EmptyOptional(),
-                                                                layerParam.name().c_str());
-    }
-
-    TensorInfo outputInfo({ inputInfo.GetShape()[0], outputSize }, DataType::Float32);
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(fullyConnectedLayer->GetInputSlot(0));
-    fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), fullyConnectedLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseSoftmaxLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    SoftmaxParameter param = layerParam.softmax_param();
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    // Ignored Caffe Parameters:
-    //      axis
-    //      Engine
-
-    armnn::SoftmaxDescriptor softmaxDescriptor;
-    softmaxDescriptor.m_Axis = 1;
-    armnn::IConnectableLayer* const softmaxLayer = m_Network->AddSoftmaxLayer(
-        softmaxDescriptor,
-        layerParam.name().c_str());
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(softmaxLayer->GetInputSlot(0));
-    softmaxLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), softmaxLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseEltwiseLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 2, 1);
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    // Ignored Caffe Parameters:
-    //      coeff
-
-    EltwiseParameter_EltwiseOp operation = EltwiseParameter_EltwiseOp_SUM; // Defaults to sum as per caffe.
-
-    if (layerParam.has_eltwise_param() && layerParam.eltwise_param().has_operation())
-    {
-        operation = layerParam.eltwise_param().operation();
-    }
-
-    armnn::IConnectableLayer* newLayer = nullptr;
-    switch (operation)
-    {
-        case EltwiseParameter_EltwiseOp_SUM:
-        {
-            newLayer = m_Network->AddAdditionLayer(layerParam.name().c_str());
-            break;
-        }
-        case EltwiseParameter_EltwiseOp_PROD:
-        {
-            newLayer = m_Network->AddMultiplicationLayer(layerParam.name().c_str());
-            break;
-        }
-        default:
-        {
-            throw ParseException(
-                fmt::format("Unsupported operation {} in Eltwise layer {} {}",
-                            operation,
-                            layerParam.name(),
-                            CHECK_LOCATION().AsString()));
-        }
-    }
-
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(newLayer->GetInputSlot(0));
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(1)).Connect(newLayer->GetInputSlot(1));
-    newLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), newLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseConcatLayer(const LayerParameter& layerParam)
-{
-    unsigned int numInputs = static_cast<unsigned int>(layerParam.bottom_size());
-    // We assume concat happens along the channel dimension, which is 1 in (0, 1, 2, 3).
-    unsigned int concatDim = 1;
-    unsigned int numOfDims = 4;
-
-    // we only consider 4-D tensor here
-    OriginsDescriptor concatDescriptor(static_cast<uint32_t>(numInputs), numOfDims);
-    std::vector<unsigned int>mergeDimSizes(numOfDims, 0u);
-
-    unsigned int mergeDim = 0;
-    for (unsigned int viewIndex = 0; viewIndex < numInputs; ++viewIndex)
-    {
-        const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(
-            layerParam.bottom(armnn::numeric_cast<int>(viewIndex))).GetTensorInfo();
-        // Checks whether the dimensions of the input tensors are actually 4.
-        if (inputInfo.GetNumDimensions()!=4)
-        {
-            throw ParseException(
-                fmt::format("The number of dimensions for input tensors of "
-                            "the concatenation op should be 4. Inputs of {} has "
-                            "{} dimensions. {}",
-                            layerParam.name(),
-                            inputInfo.GetNumDimensions(),
-                            CHECK_LOCATION().AsString()));
-        }
-
-        mergeDimSizes[0] = inputInfo.GetShape()[0];
-        mergeDimSizes[1] = inputInfo.GetShape()[1];
-        mergeDimSizes[2] = inputInfo.GetShape()[2];
-        mergeDimSizes[3] = inputInfo.GetShape()[3];
-
-        for (unsigned int j = 0; j < concatDim; ++j)
-        {
-            concatDescriptor.SetViewOriginCoord(viewIndex, j, 0);
-        }
-
-        concatDescriptor.SetViewOriginCoord(viewIndex, concatDim, mergeDim);
-        mergeDim += mergeDimSizes[concatDim];
-
-        for (unsigned int j = concatDim+1; j < numOfDims; ++j)
-        {
-            concatDescriptor.SetViewOriginCoord(viewIndex, j, 0);
-        }
-    }
-    mergeDimSizes[concatDim] = mergeDim;
-
-    armnn::IConnectableLayer* concatlayer = m_Network->AddConcatLayer(concatDescriptor, layerParam.name().c_str());
-    for (unsigned int i = 0; i < numInputs; ++i)
-    {
-        armnn::IOutputSlot& outputSlot = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(armnn::numeric_cast<int>(i)));
-        outputSlot.Connect(concatlayer->GetInputSlot(i));
-    }
-
-    concatlayer->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo(numOfDims, mergeDimSizes.data(), DataType::Float32));
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), concatlayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseBatchNormLayer(const LayerParameter& layerParam)
-{
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    string name = layerParam.name();
-
-    BatchNormParameter param = layerParam.batch_norm_param();
-    // If use_global_stats is not explicitly set in the model, assume it to be true (its default value
-    // when the network is in the testing phase).
-    if (param.has_use_global_stats())
-    {
-        if (!param.use_global_stats())
-        {
-            throw ParseException(
-                fmt::format("Error parsing Batch Norm layer '{}': "
-                            "Parameter 'use_global_stats' is set to false, which is "
-                            "unsupported (value used for training). {}",
-                            name,
-                            CHECK_LOCATION().AsString()));
-        }
-    }
-
-    BatchNormalizationDescriptor desc;
-    desc.m_Eps = param.eps();
-
-    unsigned int channels = inputInfo.GetShape()[1];
-    unsigned int shape[]  = {channels};
-
-    vector<float> meanData(channels);
-    GetDataFromBlob(layerParam, meanData, 0);
-
-    vector<float> varianceData(channels);
-    GetDataFromBlob(layerParam, varianceData, 1);
-
-    // Reads moving average factor and applies scaling (if required).
-    const BlobProto& blob = layerParam.blobs(armnn::numeric_cast<int>(2));
-    const float movingAverageFactor = blob.data(armnn::numeric_cast<int>(0));
-    if(movingAverageFactor != 0.0f)
-    {
-        const float scaleFactor = 1.0f / movingAverageFactor;
-        auto scaleFunction = [scaleFactor](float f) -> float { return f * scaleFactor; };
-
-        std::transform(varianceData.begin(), varianceData.end(), varianceData.begin(), scaleFunction);
-        std::transform(meanData.begin(), meanData.end(), meanData.begin(), scaleFunction);
-    }
-
-    // Identifies scale operation.
-    vector<float> betaData(channels, 0.0f);
-    vector<float> gammaData(channels, 1.0f);
-
-    ConstTensor mean(TensorInfo(1, shape, armnn::DataType::Float32), meanData);
-    ConstTensor variance(TensorInfo(1, shape, armnn::DataType::Float32), varianceData);
-    ConstTensor beta(TensorInfo(1, shape, armnn::DataType::Float32), betaData);
-    ConstTensor gamma(TensorInfo(1, shape, armnn::DataType::Float32), gammaData);
-
-    armnn::IConnectableLayer* const batchNormLayer = m_Network->AddBatchNormalizationLayer(desc,
-        mean, variance, beta, gamma, name.c_str());
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(batchNormLayer->GetInputSlot(0));
-    batchNormLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), batchNormLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseScaleLayer(const LayerParameter& layerParam)
-{
-    // Current unoptimal solution: add a batchnormalization layer with 0 mean and 1 variance.
-    ValidateNumInputsOutputs(layerParam, 1, 1);
-
-    const TensorInfo& inputInfo = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).GetTensorInfo();
-
-    string name = layerParam.name();
-
-    ScaleParameter param = layerParam.scale_param();
-    if (param.axis() != 1)
-    {
-        // Would have to use something other than BatchNormalizationLayer in this case
-        throw ParseException(
-            fmt::format("Loading Scale Layer: Only axis 1 is supported currently. "
-                        "Layer={} Axis={} {}",
-                        layerParam.name(),
-                        param.axis(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    unsigned int     channels = inputInfo.GetShape()[1];
-    unsigned int     shape[]  = {channels};
-
-    BatchNormalizationDescriptor desc;
-    desc.m_Eps = 0.0f; // Don't need epsilon if variance is 1.
-    vector<float> meanData(channels, 0.0f);
-    vector<float> varianceData(channels, 1.0f);
-    vector<float> betaData(channels, 0.0f);
-    vector<float> gammaData(channels);
-
-    GetDataFromBlob(layerParam, gammaData, 0);
-
-    if(param.has_bias_term())
-    {
-        GetDataFromBlob(layerParam, betaData, 1);
-    }
-
-    ConstTensor mean(TensorInfo(1, shape, armnn::DataType::Float32), meanData);
-    ConstTensor variance(TensorInfo(1, shape, armnn::DataType::Float32), varianceData);
-    ConstTensor beta(TensorInfo(1, shape, armnn::DataType::Float32), betaData);
-    ConstTensor gamma(TensorInfo(1, shape, armnn::DataType::Float32), gammaData);
-
-    armnn::IConnectableLayer* const batchNormLayer = m_Network->AddBatchNormalizationLayer(desc,
-        mean, variance, beta, gamma, name.c_str());
-    GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)).Connect(batchNormLayer->GetInputSlot(0));
-    batchNormLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), batchNormLayer->GetOutputSlot(0));
-}
-
-void ICaffeParser::CaffeParserImpl::ParseSplitLayer(const caffe::LayerParameter& layerParam)
-{
-    // Used in caffe to duplicate memory - not necessary in armnn.
-    if (layerParam.bottom_size() != 1)
-    {
-        throw ParseException(
-            fmt::format("Split layer '{}' should have exactly 1 bottom. "
-                        "#bottoms={} {}",
-                        layerParam.name(),
-                        layerParam.bottom_size(),
-                        CHECK_LOCATION().AsString()));
-    }
-    armnn::IOutputSlot& outputSlot = GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0));
-    for (int i = 0; i < layerParam.top_size(); i++)
-    {
-        SetArmnnOutputSlotForCaffeTop(layerParam.top(i), outputSlot);
-    }
-}
-
-void ICaffeParser::CaffeParserImpl::ParseDropoutLayer(const caffe::LayerParameter& layerParam)
-{
-    // Ignored for inference, so patch the single input to its single output.
-    if (layerParam.bottom_size() != 1 || layerParam.top_size() != 1)
-    {
-        throw ParseException(
-            fmt::format("Dropout layer '{}' should have exactly 1 bottom and 1 top. "
-                        "#bottoms={} #tops={} {}",
-                        layerParam.name(),
-                        layerParam.bottom_size(),
-                        layerParam.top_size(),
-                        CHECK_LOCATION().AsString()));
-    }
-    SetArmnnOutputSlotForCaffeTop(layerParam.top(0), GetArmnnOutputSlotForCaffeTop(layerParam.bottom(0)));
-}
-
-void ICaffeParser::CaffeParserImpl::TrackInputBinding(armnn::IConnectableLayer* layer,
-    armnn::LayerBindingId id,
-    const armnn::TensorInfo& tensorInfo)
-{
-    return TrackBindingPoint(layer, id, tensorInfo, layer->GetName(), m_NetworkInputsBindingInfo);
-}
-
-void ICaffeParser::CaffeParserImpl::TrackOutputBinding(armnn::IConnectableLayer* layer,
-    armnn::LayerBindingId id,
-    const armnn::TensorInfo& tensorInfo)
-{
-    return TrackBindingPoint(layer, id, tensorInfo, layer->GetName(), m_NetworkOutputsBindingInfo);
-}
-
-void ICaffeParser::CaffeParserImpl::TrackBindingPoint(armnn::IConnectableLayer* layer,
-    armnn::LayerBindingId id,
-    const armnn::TensorInfo& tensorInfo,
-    const char* bindingPointDesc,
-    std::unordered_map<std::string, BindingPointInfo>& nameToBindingInfo)
-{
-    const std::string layerName = layer->GetName();
-    auto it = nameToBindingInfo.find(layerName);
-    if (it == nameToBindingInfo.end())
-    {
-        nameToBindingInfo[layerName] = std::make_pair(id, tensorInfo);
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("Id {} used by more than one {} layer {}",
-                        id,
-                        bindingPointDesc,
-                        CHECK_LOCATION().AsString()));
-    }
-}
-
-armnn::IOutputSlot& ICaffeParser::CaffeParserImpl::GetArmnnOutputSlotForCaffeTop(const std::string& caffeTopName) const
-{
-    auto it = m_ArmnnOutputSlotForCaffeTop.find(caffeTopName);
-    if (it != m_ArmnnOutputSlotForCaffeTop.end())
-    {
-        return *it->second;
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("Could not find armnn output slot for Caffe top '{}' {}",
-                        caffeTopName,
-                        CHECK_LOCATION().AsString()));
-    }
-}
-
-void ICaffeParser::CaffeParserImpl::SetArmnnOutputSlotForCaffeTop(
-    const std::string& caffeTopName, armnn::IOutputSlot& armnnOutputSlot)
-{
-    auto it = m_ArmnnOutputSlotForCaffeTop.find(caffeTopName);
-    if (it == m_ArmnnOutputSlotForCaffeTop.end())
-    {
-        m_ArmnnOutputSlotForCaffeTop[caffeTopName] = &armnnOutputSlot;
-    }
-    else
-    {
-        throw ParseException(
-            fmt::format("Attempting to add duplicate entry for Caffe top '{}' {}",
-                        caffeTopName,
-                        CHECK_LOCATION().AsString()));
-    }
-}
-
-// Note: can move to CaffeParser when/if we optimise the text/string format
-//       to load on a layer by layer basis
-void ICaffeParser::CaffeParserImpl::ResolveInPlaceLayers(caffe::NetParameter& netParameter)
-{
-    // Finds layers with the same top.
-    std::map<std::string, std::vector<caffe::LayerParameter*>> layersByTop;
-    for (int layerIdx = 0; layerIdx < netParameter.layer_size(); ++layerIdx)
-    {
-        caffe::LayerParameter& layer = *netParameter.mutable_layer(layerIdx);
-        std::string name = layer.name();
-        for (int i = 0; i < layer.top_size(); ++i)
-        {
-            layersByTop[layer.top(i)].push_back(&layer);
-        }
-    }
-
-    // For each set of layers with the same top, resolves them to a linear chain rather than in-place layers.
-    // Note that for 'regular' layers, there will be a single layer in each group and so this will be a no-op.
-    for (auto layersWithSameTopIt : layersByTop)
-    {
-        const std::string& top = layersWithSameTopIt.first;
-        const std::vector<caffe::LayerParameter*>& layersWithSameTop = layersWithSameTopIt.second;
-
-        // Chains the layers together in the order that they are listed in the prototxt (hopefully this is correct).
-        // Note that the last layer will not have its top modified so that other layers will continue to reference it.
-        for (unsigned int layerIdx = 0; layerIdx < layersWithSameTop.size() - 1; ++layerIdx)
-        {
-            caffe::LayerParameter& layer1 = *layersWithSameTop[layerIdx];
-            caffe::LayerParameter& layer2 = *layersWithSameTop[layerIdx+1];
-            if (layer1.top_size() != 1)
-            {
-                throw ParseException(
-                    fmt::format("Node '{}' is an in-place layer but doesn't have exactly one "
-                                "top. It has {} instead. {}",
-                                layer1.name(),
-                                layer1.top_size(),
-                                CHECK_LOCATION().AsString()));
-            }
-            std::string newTop = layer1.name() + "_top";
-            layer1.set_top(0, newTop);
-            if (layer2.bottom_size() != 1 || layer2.bottom(0) != top)
-            {
-                throw ParseException(
-                    fmt::format("Node '{}' is an in-place layer but "
-                                "doesn't have exactly one bottom, or it doesn't match its top. "
-                                "#bottoms={}, first bottom is {}, top is {} {}",
-                                layer2.name(),
-                                layer2.bottom(0),
-                                top,
-                                CHECK_LOCATION().AsString()));
-            }
-            layer2.set_bottom(0, newTop);
-        }
-    }
-}
-
-// Note: can move to CaffeParser when/if we optimise the text/string format
-//       to load on a layer by layer basis
-void ICaffeParser::CaffeParserImpl::LoadNetParam(NetParameter& netParameter)
-{
-    // Caffe models sometimes have an implicit input layer.
-    // In that case, add an explicit one.
-    if (netParameter.input_size() > 0)
-    {
-        LayerParameter* newLayer = netParameter.add_layer();
-
-        newLayer->set_type("Input");
-        newLayer->set_name(netParameter.input(0));
-        newLayer->add_top(netParameter.input(0));
-
-        InputParameter* inputParam = newLayer->mutable_input_param();
-        BlobShape* shape = inputParam->add_shape();
-
-        int dim_size = netParameter.input_dim_size();
-        for (int i = 0; i < dim_size; ++i)
-        {
-            shape->add_dim(netParameter.input_dim(i));
-        }
-    }
-
-    // Replaces in-place layers with regular ones to make the rest of the parsing easier.
-    ResolveInPlaceLayers(netParameter);
-
-    // Creates a lookup of Caffe layers by name.
-    for (int i = 0; i < netParameter.layer_size(); ++i)
-    {
-        const caffe::LayerParameter& layer = netParameter.layer(i);
-        for (int i = 0; i < layer.top_size(); ++i)
-        {
-            m_CaffeLayersByTopName[layer.top(i)] = &layer;
-        }
-    }
-
-    // Finds the output layers the user requested.
-    std::vector<const caffe::LayerParameter*> targetLayers;
-    for (const std::string& requestedOutputName : m_RequestedOutputs)
-    {
-        auto nodeIt = m_CaffeLayersByTopName.find(requestedOutputName);
-        if (nodeIt == m_CaffeLayersByTopName.end())
-        {
-            throw ParseException(
-                fmt::format("Couldn't find requested output layer '{}' in graph {}",
-                            requestedOutputName,
-                            CHECK_LOCATION().AsString()));
-        }
-        targetLayers.push_back(nodeIt->second);
-    }
-
-    // Sorts them into a linear ordering such that all inputs of a node are before the node itself.
-    std::vector<const caffe::LayerParameter*> sortedNodes;
-    if (!armnnUtils::GraphTopologicalSort<const caffe::LayerParameter*>(
-        targetLayers,
-        [this](const caffe::LayerParameter* node)
-        {
-            return GetInputs(*node);
-        },
-        sortedNodes))
-    {
-        throw ParseException(
-            fmt::format("Cycle detected in graph. #nodes: {} {}",
-                        sortedNodes.size(),
-                        CHECK_LOCATION().AsString()));
-    }
-
-    // Parses each node in order, knowing that all inputs of a node will be processed before the node itself.
-    for (const caffe::LayerParameter* current : sortedNodes)
-    {
-        auto it = ms_CaffeLayerNameToParsingFunctions.find(current->type());
-        if (it == ms_CaffeLayerNameToParsingFunctions.end())
-        {
-            throw ParseException(
-                fmt::format("Unsupported layer type: '{}' for layer {} {}",
-                            current->type(),
-                            current->name(),
-                            CHECK_LOCATION().AsString()));
-        }
-        auto func = it->second;
-        (this->*func)(*current);
-    }
-
-    // Adds ArmNN output layers connected to each requested output.
-    for (const std::string& requestedOutput : m_RequestedOutputs)
-    {
-        armnn::IOutputSlot& outputSlot = GetArmnnOutputSlotForCaffeTop(requestedOutput);
-
-        const armnn::LayerBindingId outputId = armnn::numeric_cast<armnn::LayerBindingId>(
-            m_NetworkOutputsBindingInfo.size());
-        armnn::IConnectableLayer* const outputLayer = m_Network->AddOutputLayer(outputId, requestedOutput.c_str());
-        outputSlot.Connect(outputLayer->GetInputSlot(0));
-
-        TrackOutputBinding(outputLayer, outputId, outputLayer->GetInputSlot(0).GetConnection()->GetTensorInfo());
-    }
-}
-
-INetworkPtr ICaffeParser::CaffeParserImpl::CreateNetworkFromTextFile(const char* graphFile,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    FILE* fd = fopen(graphFile, "r");
-
-    if (fd == nullptr)
-    {
-        throw FileNotFoundException(
-            fmt::format("Failed to open graph file: {} {}",
-                        graphFile,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    // Parses the file into a message.
-    NetParameter netParam;
-    auto         input   = new google::protobuf::io::FileInputStream(fileno(fd));
-    bool         success = google::protobuf::TextFormat::Parse(input, &netParam);
-    delete input;
-    fclose(fd);
-
-    if (!success)
-    {
-        throw ParseException(
-            fmt::format("Failed to parse graph file: {} {}",
-                        graphFile,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    return CreateNetworkFromNetParameter(netParam, inputShapes, requestedOutputs);
-}
-
-INetworkPtr ICaffeParser::CaffeParserImpl::CreateNetworkFromString(const char* protoText,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    // Parses the string into a message.
-    NetParameter netParam;
-    bool         success = google::protobuf::TextFormat::ParseFromString(protoText, &netParam);
-
-    if (!success)
-    {
-        throw ParseException(
-            fmt::format("Failed to parse graph string {}",
-                        CHECK_LOCATION().AsString()));
-    }
-
-    return CreateNetworkFromNetParameter(netParam, inputShapes, requestedOutputs);
-}
-
-INetworkPtr CaffeParser::CreateNetworkFromBinaryFile(const char* graphFile,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    FILE* fd = fopen(graphFile, "rb");
-
-    if (fd == nullptr)
-    {
-        throw FileNotFoundException(
-            fmt::format("Failed to open graph file at: {} {}",
-                        graphFile,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    // Parses the file into a message.
-    NetParameter netParam;
-
-    FileInputStream  inStream(fileno(fd));
-    CodedInputStream codedStream(&inStream);
-    codedStream.SetTotalBytesLimit(INT_MAX);
-    bool success = netParam.ParseFromCodedStream(&codedStream);
-    fclose(fd);
-
-    if (!success)
-    {
-        throw ParseException(
-            fmt::format("Failed to parse protobuf file: {} {}",
-                        graphFile,
-                        CHECK_LOCATION().AsString()));
-    }
-
-    return CreateNetworkFromNetParameter(netParam, inputShapes, requestedOutputs);
-}
-
-// Note: can move to CaffeParser when/if we optimise the text/string format
-//       to load on a layer by layer basis
-INetworkPtr ICaffeParser::CaffeParserImpl::CreateNetworkFromNetParameter(NetParameter& netParam,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-    m_NetworkInputsBindingInfo.clear();
-    m_NetworkOutputsBindingInfo.clear();
-
-    m_Network = INetwork::Create();
-
-    m_InputShapes = inputShapes;
-    if (requestedOutputs.size() == 0)
-    {
-        throw ParseException("requestedOutputs must have at least one entry");
-    }
-    m_RequestedOutputs = requestedOutputs;
-
-    try
-    {
-        LoadNetParam(netParam);
-    }
-    catch (const ParseException& e)
-    {
-        Cleanup();
-        throw e;
-    }
-
-    Cleanup();
-
-    return move(m_Network);
-}
-
-const std::string ICaffeParser::CaffeParserImpl::GetVersion()
-{
-    return CAFFE_PARSER_VERSION;
-}
-
-void ICaffeParser::CaffeParserImpl::Cleanup() {
-    // cleanup, in case we reuse this parser
-    m_InputShapes.clear();
-    m_RequestedOutputs.clear();
-    m_ArmnnOutputSlotForCaffeTop.clear();
-    // NOTE: when we get the text/string format
-    //       optimised for memory then this data structure can
-    //       also move to the CaffeParser class
-    m_CaffeLayersByTopName.clear();
-}
-
-}
diff --git a/src/armnnCaffeParser/CaffeParser.hpp b/src/armnnCaffeParser/CaffeParser.hpp
deleted file mode 100644
index 9f93569742..0000000000
--- a/src/armnnCaffeParser/CaffeParser.hpp
+++ /dev/null
@@ -1,189 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#pragma once
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-#include "armnn/Types.hpp"
-#include "armnn/NetworkFwd.hpp"
-#include "armnn/Tensor.hpp"
-
-#include <memory>
-#include <vector>
-#include <unordered_map>
-
-namespace caffe
-{
-class BlobShape;
-class LayerParameter;
-class NetParameter;
-}
-
-namespace armnnCaffeParser
-{
-
-class ICaffeParser::CaffeParserImpl
-{
-public:
-
-    // Because we haven't looked at reducing the memory usage when loading from Text/String
-    // have to retain these functions here for the moment.
-    /// Create the network from a protobuf text file on disk
-    armnn::INetworkPtr CreateNetworkFromTextFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// Create the network from a protobuf binary file on the disk.
-    virtual armnn::INetworkPtr CreateNetworkFromBinaryFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs) = 0;
-
-
-    /// Creates the network directly from protobuf text in a string. Useful for debugging/testing.
-    armnn::INetworkPtr CreateNetworkFromString(
-        const char* protoText,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// Retrieves binding info (layer id and tensor info) for the network input identified by the given layer name.
-    BindingPointInfo GetNetworkInputBindingInfo(const std::string& name) const;
-
-    /// Retrieves binding info (layer id and tensor info) for the network output identified by the given layer name.
-    BindingPointInfo GetNetworkOutputBindingInfo(const std::string& name) const;
-
-    /// Retrieve version in X.Y.Z form
-    static const std::string GetVersion();
-
-    CaffeParserImpl();
-    virtual ~CaffeParserImpl() = default;
-
-protected:
-    /// Adds an armnn layer to m_Network given a Caffe LayerParameter of the correct type
-    /// and is responsible for recording any newly created IOutputSlots using SetArmnnOutputSlotForCaffeTop().
-    /// @{
-    void ParseInputLayer(const caffe::LayerParameter& layerParam);
-    void ParseConvLayer(const caffe::LayerParameter& layerParam);
-    void ParseDeconvLayer(const caffe::LayerParameter& layerParam);
-    void ParsePoolingLayer(const caffe::LayerParameter& layerParam);
-    void ParseReluLayer(const caffe::LayerParameter& layerParam);
-    void ParseLRNLayer(const caffe::LayerParameter& layerParam);
-    void ParseInnerProductLayer(const caffe::LayerParameter& layerParam);
-    void ParseSoftmaxLayer(const caffe::LayerParameter& layerParam);
-    void ParseEltwiseLayer(const caffe::LayerParameter& layerParam);
-    void ParseConcatLayer(const caffe::LayerParameter& layerParam);
-    void ParseBatchNormLayer(const caffe::LayerParameter& layerParam);
-    void ParseScaleLayer(const caffe::LayerParameter& layerParam);
-    void ParseSplitLayer(const caffe::LayerParameter& layerParam);
-    void ParseDropoutLayer(const caffe::LayerParameter& layerParam);
-    void ParseArgmaxLayer(const caffe::LayerParameter& layerParam);
-    /// @}
-
-    /// ParseConv may use these helpers depending on the group parameter
-    /// @{
-    void AddConvLayerWithSplits(const caffe::LayerParameter& layerParam,
-                                const armnn::Convolution2dDescriptor & desc,
-                                unsigned int kernelW,
-                                unsigned int kernelH);
-    void AddConvLayerWithDepthwiseConv(const caffe::LayerParameter& layerParam,
-                                       const armnn::Convolution2dDescriptor & desc,
-                                       unsigned int kernelW,
-                                       unsigned int kernelH);
-    void AddDeconvLayerWithSplits(const caffe::LayerParameter& layerParam,
-                                const armnn::TransposeConvolution2dDescriptor& desc,
-                                unsigned int kernelW,
-                                unsigned int kernelH);
-    /// @}
-
-    /// Converts Caffe's protobuf tensor shape format to ArmNN's
-    armnn::TensorInfo BlobShapeToTensorInfo(const caffe::BlobShape& blobShape) const;
-
-    void TrackInputBinding(armnn::IConnectableLayer* layer,
-                           armnn::LayerBindingId id,
-                           const armnn::TensorInfo& tensorInfo);
-
-    static void TrackBindingPoint(armnn::IConnectableLayer* layer, armnn::LayerBindingId id,
-                                  const armnn::TensorInfo& tensorInfo,
-                                  const char* bindingPointDesc,
-                                  std::unordered_map<std::string, BindingPointInfo>& nameToBindingInfo);
-
-    void TrackOutputBinding(armnn::IConnectableLayer* layer,
-                            armnn::LayerBindingId id,
-                            const armnn::TensorInfo& tensorInfo);
-
-
-    void SetArmnnOutputSlotForCaffeTop(const std::string& caffeTopName, armnn::IOutputSlot& armnnOutputSlot);
-
-    /// Retrieves the Armnn IOutputSlot representing the given Caffe top.
-    /// Throws if it cannot be found (e.g. not parsed yet).
-    armnn::IOutputSlot& GetArmnnOutputSlotForCaffeTop(const std::string& caffeTopName) const;
-
-    static std::pair<armnn::LayerBindingId, armnn::TensorInfo> GetBindingInfo(
-        const std::string& layerName,
-        const char* bindingPointDesc,
-        const std::unordered_map<std::string, BindingPointInfo>& bindingInfos);
-
-
-    void Cleanup();
-
-    using OperationParsingFunction = void(CaffeParserImpl::*)(const caffe::LayerParameter& layerParam);
-
-    /// Maps Caffe layer names to parsing member functions.
-    static const std::map<std::string, OperationParsingFunction> ms_CaffeLayerNameToParsingFunctions;
-
-    /// maps input layer names to their corresponding ids and tensor infos
-    std::unordered_map<std::string, BindingPointInfo> m_NetworkInputsBindingInfo;
-
-    /// maps output layer names to their corresponding ids and tensor infos
-    std::unordered_map<std::string, BindingPointInfo> m_NetworkOutputsBindingInfo;
-
-    armnn::INetworkPtr m_Network;
-
-    std::map<std::string, armnn::TensorShape> m_InputShapes;
-
-    /// As we add armnn layers we store the armnn IOutputSlot which corresponds to the Caffe tops.
-    std::unordered_map<std::string, armnn::IOutputSlot*> m_ArmnnOutputSlotForCaffeTop;
-
-    std::vector<std::string> m_RequestedOutputs;
-
-
-    // Stuff which has gone to base class simply because we haven't done any
-    // memory optimisation on the text/string format. If we move this to a layer
-    // by layer parse as well these can move to the CaffeParser class.
-    std::map<std::string, const caffe::LayerParameter*> m_CaffeLayersByTopName;
-
-    /// Parses a NetParameter loaded into memory from one of the other CreateNetwork*
-    armnn::INetworkPtr CreateNetworkFromNetParameter(
-        caffe::NetParameter&     netParam,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs);
-
-    /// does the actual conversion from caffe::NetParameter to armnn::INetwork
-    void LoadNetParam(caffe::NetParameter& netParameter);
-
-    /// Find the Caffe layers listed as inputs (bottoms) for a given layer.
-    std::vector<const caffe::LayerParameter*> GetInputs(const caffe::LayerParameter& layerParam);
-
-    /// Modifies the Caffe network to replace "in-place" layers (whose top() and bottom() are both the same)
-    /// with regular layers. This simplifies further parsing.
-    void ResolveInPlaceLayers(caffe::NetParameter& netParameter);
-
-};
-
-class CaffeParser : public ICaffeParser::CaffeParserImpl
-{
-public:
-
-    /// Create the network from a protobuf binary file on disk
-    virtual armnn::INetworkPtr CreateNetworkFromBinaryFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs) override;
-
-public:
-    CaffeParser();
-
-};
-}
diff --git a/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp b/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp
deleted file mode 100644
index b7ff3d8731..0000000000
--- a/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp
+++ /dev/null
@@ -1,731 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "RecordByRecordCaffeParser.hpp"
-
-#include "armnn/Exceptions.hpp"
-#include "armnn/Utils.hpp"
-#include <armnn/utility/NumericCast.hpp>
-
-#include "GraphTopologicalSort.hpp"
-
-// Caffe
-#include <google/protobuf/wire_format.h>
-
-
-//#include <stdio.h>
-#include <limits.h>
-#include <sstream>
-//#include <iostream>
-#include <fstream>
-
-namespace armnnCaffeParser
-{
-// class which holds information on the absolute position in the stream
-// of the data and the length of the data record.
-class VarLenDataInfo
-{
-public:
-    VarLenDataInfo(std::streamoff positionOfData, size_t sizeOfData) :
-        m_PositionOfData(positionOfData), m_SizeOfData(sizeOfData) {}
-
-    VarLenDataInfo(const VarLenDataInfo& x) :
-        m_PositionOfData(x.PositionOfData()), m_SizeOfData (x.SizeOfData()) {}
-
-    VarLenDataInfo& operator=(const VarLenDataInfo& x)
-    {
-        // handle self assignment
-        if (this == &x) {
-            return *this;
-        }
-        m_PositionOfData = x.PositionOfData(); m_SizeOfData = x.SizeOfData(); return *this;
-    }
-
-    std::streamoff PositionOfData() const {return m_PositionOfData;}
-    size_t SizeOfData() const {return m_SizeOfData;}
-
-private:
-    std::streamoff m_PositionOfData;
-    size_t m_SizeOfData;
-
-};
-
-// class which holds enough information on a LayerParameter in the Caffe protobuf
-// format to allow it to be resolved for in place layering and sorted topologically
-// prior to the entire record being parsed into memory.
-//
-// NOTE: function naming follows that of the protobuf classes these proxies are standing in for
-class LayerParameterInfo : public VarLenDataInfo
-{
-public:
-    static const std::string INPUT;
-    LayerParameterInfo(const VarLenDataInfo& varLenDataInfo) :
-        VarLenDataInfo(varLenDataInfo.PositionOfData(), varLenDataInfo.SizeOfData()),
-        m_newTops(false), m_newBottoms(false) {}
-
-    LayerParameterInfo(std::streamoff positionOfData, size_t sizeOfData) :
-        VarLenDataInfo(positionOfData, sizeOfData), m_newTops(false), m_newBottoms(false) {}
-
-    LayerParameterInfo(const LayerParameterInfo& x) :
-        VarLenDataInfo(x.PositionOfData(), x.SizeOfData()),
-        m_name(x.m_name),
-        m_type(x.m_type),
-        m_tops(x.m_tops),
-        m_bottoms(x.m_bottoms),
-        m_newTops(x.m_newTops),
-        m_newBottoms(x.m_newBottoms) {}
-
-    LayerParameterInfo& operator=(const LayerParameterInfo& x)
-    {
-        if (this == &x) {
-            return *this;
-        }
-        VarLenDataInfo::operator=(x);
-        m_name = x.m_name;
-        m_type = x.m_type;
-        m_tops = x.m_tops;
-        m_bottoms = x.m_bottoms;
-        m_newTops = x.m_newTops;
-        m_newBottoms = x.m_newBottoms;
-        return *this;
-    }
-
-    const std::string name() const {return m_name;}
-    void set_name(const std::unique_ptr<char[]>& theName, size_t length)
-    {
-        m_name = std::string(theName.get(), length);
-    }
-    void set_name(const std::string& theName) {m_name = theName;}
-
-    const std::string type() const {return m_type;}
-    void set_type(const std::unique_ptr<char[]>& theType, size_t length)
-    {
-        m_type = std::string(theType.get(), length);
-    }
-    void set_type(const std::string& theType) {m_type = theType;}
-
-    void add_top(const std::unique_ptr<char[]>& top, size_t length)
-    {
-        std::string topName(top.get(), length);
-        m_tops.push_back(topName);
-    }
-    void add_top(const std::string& topName)
-    {
-        m_tops.push_back(topName);
-    }
-    const std::string top(unsigned long i) const {return m_tops[i];}
-    unsigned long top_size() const {return m_tops.size();}
-    void set_top(unsigned long i, const std::string& newName) {m_tops[i] = newName; m_newTops = true;}
-    bool new_tops() const {return m_newTops;}
-
-    void add_bottom(const std::unique_ptr<char[]>& bottom, size_t length)
-    {
-        std::string bottomName(bottom.get(), length);
-        m_bottoms.push_back(bottomName);
-    }
-    unsigned long bottom_size() const {return m_bottoms.size();}
-    const std::string bottom(unsigned long i) const {return m_bottoms[i];}
-    void set_bottom(unsigned long i, const std::string& newName) {m_bottoms[i] = newName; m_newBottoms = true;}
-    bool new_bottoms() const {return m_newBottoms;}
-
-    // if the position and size of the data is zero and the type is "Input" then this is an 'Implicit Input Layer'
-    // and needs to be handled differently from ordinary layers.
-    bool isImplicitInputLayer() const
-    {
-        if ((PositionOfData() == 0) && (SizeOfData() == 0) && INPUT.compare(type()) == 0)
-        {return true;} else {return false;}
-    }
-
-private:
-    std::string m_name;
-    std::string m_type;
-    std::vector<std::string> m_tops;
-    std::vector<std::string> m_bottoms;
-    // mark the layers whose topology was changed
-    // by the ResolveInPlaceLayers method.
-    bool m_newTops;
-    bool m_newBottoms;
-};
-
-// class which holds the field type (wire type) and field id (id from the .proto schema)
-// read from the protobuf messages as per the binary encoding described in
-// https://developers.google.com/protocol-buffers/docs/encoding
-//
-// NOTE: function naming follows that of the protobuf classes these proxies are standing in for
-class ProtobufFieldInfo
-{
-public:
-    ProtobufFieldInfo(int field_type, int field_id) :
-        m_eof(false), m_field_type(field_type), m_field_id(field_id) {}
-    ProtobufFieldInfo() : m_eof(true), m_field_type(0), m_field_id(0) {}
-
-    bool eof() {return m_eof;}
-    int field_type() {return m_field_type;}
-    int field_id() {return m_field_id;}
-
-private:
-    bool m_eof;
-    int m_field_type;
-    int m_field_id;
-};
-
-
-// There are some NetParameter level data which are required
-// to correctly processes some Caffe models. Specifically those which
-// have 'implicit' input layers. Also it is nice to have the name of the model.
-//
-// NOTE: function naming follows that of the protobuf classes these proxies are standing in for
-class NetParameterInfo
-{
-public:
-    const std::string name() const {return m_name;}
-    void set_name(const std::unique_ptr<char[]>&  theName, size_t length)
-    {
-        m_name = std::string(theName.get(), length);
-    }
-
-    void add_input(const std::unique_ptr<char[]>&  input, size_t length)
-    {
-        std::string inputName(input.get(), length);
-        m_inputs.push_back(inputName);
-    }
-    const std::string input(unsigned long i) const {return m_inputs[i];}
-    unsigned long input_size() const {return m_inputs.size();}
-
-    void add_input_dimension(int input_dimension) {
-        m_input_dimensions.push_back(input_dimension);
-    }
-    int input_dimension(unsigned long i) const {return m_input_dimensions[i];}
-    unsigned long input_dimensions_size() const {return m_input_dimensions.size();}
-
-    void add_blob_shape(caffe::BlobShape shape) {
-        m_blob_shapes.push_back(shape);
-    }
-    const caffe::BlobShape blob_shape(unsigned long i) const {return m_blob_shapes[i];}
-    unsigned long blob_shapes_size() const {return m_blob_shapes.size();}
-
-private:
-    std::string m_name;
-    std::vector<std::string> m_inputs;
-    std::vector<int> m_input_dimensions;
-    std::vector<caffe::BlobShape> m_blob_shapes;
-
-};
-
-}; // namespace armnnCaffeParser
-
-using namespace armnnCaffeParser;
-
-// Initialise the class const
-const std::string LayerParameterInfo::INPUT = "Input";
-
-namespace
-{
-
-ProtobufFieldInfo readFieldInfo(std::ifstream& ifs)
-{
-    unsigned char first_byte = static_cast<unsigned char>(ifs.get());
-    if (!ifs.good())
-    {
-        ProtobufFieldInfo eof;
-        return eof;
-    }
-    int field_type = first_byte&7;
-    int field_id = first_byte>>3;
-    if ((field_id & 16) == 16)
-    {
-        unsigned char second_byte = static_cast<unsigned char>(ifs.get());
-        if (!ifs.good())
-        {
-            ProtobufFieldInfo eof;
-            return eof;
-        }
-        field_id = (field_id-16) + ((second_byte&127)<<4);
-    }
-    ProtobufFieldInfo fieldInfo(field_type, field_id);
-    return fieldInfo;
-}
-
-const static int MAX_NUM_BYTES = 5;
-
-int ReadBase128(std::ifstream& ifs)
-{
-    int result = 0;
-    unsigned int shift_by = 0;
-    int bytesRead = 0;
-    while (true)
-    {
-        unsigned char a_byte = static_cast<unsigned char>(ifs.get());
-        ++bytesRead;
-        if (bytesRead > MAX_NUM_BYTES)
-        {
-            throw armnn::ParseException(
-                "ReadBase128 exceeded the maximum number of bytes expected for an integer representation");
-        }
-        result += (a_byte & 127) << shift_by;
-        shift_by += 7;
-        if ((a_byte & 128) != 128)
-        {
-            break;
-        }
-    }
-    return result;
-}
-
-
-std::unique_ptr<char[]> AllocateBuffer(std::ifstream& ifs, VarLenDataInfo& dataInfo)
-{
-    std::unique_ptr<char[]> ptr(new char[dataInfo.SizeOfData()]);
-    ifs.clear();
-    ifs.seekg(dataInfo.PositionOfData(), std::ios_base::beg);
-    ifs.read(ptr.get(), armnn::numeric_cast<std::streamsize>(dataInfo.SizeOfData()));
-    return ptr;
-}
-
-VarLenDataInfo CreateVarLenDataInfo(std::streamoff bufferStart, std::streamoff endOfLayer) {
-    std::streamoff sizeOfLayer = endOfLayer - bufferStart;
-    if (sizeOfLayer < 0)
-    {
-        std::stringstream ss;
-        ss << "error when determining buffer size, negative value [" << sizeOfLayer << "]";
-        throw armnn::ParseException(ss.str());
-    }
-    // NOTE: as some of the data being read in will be translated into strings (names of layers etc)
-    //       the maximum size we can deal with is the upper size limit of a string i.e. size_t
-    // on the platform in which I am currently compiling std::streamoff is signed long int and
-    // size_t is unsigned long int so there is no way this error condition can fire but this stuff
-    // is supposed to be portable so the check remains in place
-    if (armnn::numeric_cast<size_t>(sizeOfLayer) > SIZE_MAX) {
-        std::stringstream ss;
-        ss << "layer is greater than " << SIZE_MAX << " in size cannot process. layer size = [" << sizeOfLayer << "]";
-        throw armnn::ParseException(ss.str());
-    }
-    LayerParameterInfo info(bufferStart, armnn::numeric_cast<size_t>(sizeOfLayer));
-    return info;
-}
-
-void ReadTopologicalInfoForLayerParameter(LayerParameterInfo& layerInfo, std::ifstream& ifs)
-{
-    // position the file pointer to the start of the layer data
-    ifs.clear();
-    ifs.seekg(layerInfo.PositionOfData(), std::ios_base::beg);
-    std::streamoff endOfLayer = layerInfo.PositionOfData() +
-        armnn::numeric_cast<std::streamoff>(layerInfo.SizeOfData());
-    while(true)
-    {
-        // check to see if we have reached the end of the record
-        std::streamoff currentPosition = ifs.tellg();
-        if (currentPosition >= endOfLayer) {
-            return;
-        }
-        // read the information for the next field.
-        ProtobufFieldInfo fieldInfo = readFieldInfo(ifs);
-        if (fieldInfo.eof())
-        {
-            return;
-            // TODO: figure out whether this is an error condition or not...
-            //throw armnn::ParseException("failed to read field from LayerParameter data");
-        }
-        // process the field
-        switch (fieldInfo.field_type())
-        {
-            case 0:
-            {
-                ReadBase128(ifs);
-                break;
-            }
-            case 2:
-            {
-                int size = ReadBase128(ifs);
-                std::streamoff posStartOfData = ifs.tellg();
-                VarLenDataInfo dataInfo(posStartOfData, armnn::numeric_cast<size_t>(size));
-                //optional string name = 1; // the layer name
-                //optional string type = 2; // the layer type
-                //repeated string bottom = 3; // the name of each bottom blob
-                //repeated string top = 4; // the name of each top blob
-                if (fieldInfo.field_id() == 1)
-                {
-                    // read and set the name of the layer
-                    auto layerName = AllocateBuffer(ifs, dataInfo);
-                    layerInfo.set_name(layerName, dataInfo.SizeOfData());
-                }
-                else if (fieldInfo.field_id() == 2)
-                {
-                    // read and set the type of the layer
-                    auto layerType = AllocateBuffer(ifs, dataInfo);
-                    layerInfo.set_type(layerType, dataInfo.SizeOfData());
-                }
-                else if (fieldInfo.field_id() == 3)
-                {
-                    // read and add a bottom to the layer
-                    auto bottom = AllocateBuffer(ifs, dataInfo);
-                    layerInfo.add_bottom(bottom, dataInfo.SizeOfData());
-                }
-                else if (fieldInfo.field_id() == 4)
-                {
-                    // read and add a top to the layer
-                    auto top = AllocateBuffer(ifs, dataInfo);
-                    layerInfo.add_top(top, dataInfo.SizeOfData());
-                }
-                else
-                {
-                    ifs.seekg(size, std::ios_base::cur);
-                    if (!ifs.good())
-                    {
-                        // TODO: error out?
-                        return;
-                    }
-                }
-                break;
-            }
-            case 1:
-            {
-                // 64 bit
-                // advance by eight bytes
-                ifs.seekg(8, std::ios_base::cur);
-                if (!ifs.good())
-                {
-                    // TODO: error out?
-                    return;
-                }
-                break;
-            }
-            case 5:
-            {
-                // 32 bit
-                // advance by four bytes
-                ifs.seekg(4, std::ios_base::cur);
-                if (!ifs.good())
-                {
-                    // TODO: error out?
-                    return;
-                }
-                break;
-            }
-            default:
-            {
-                throw armnn::ParseException("Encounted an unknown field type");
-                break;
-            }
-        }
-    }
-}
-
-void ResolveInPlaceLayers(std::vector<LayerParameterInfo>& layerInfo)
-{
-    std::map<std::string, std::vector<LayerParameterInfo*>> layersByTop;
-    for (auto& info : layerInfo)
-    {
-        for (unsigned long i = 0; i < info.top_size(); ++i)
-        {
-            layersByTop[info.top(i)].push_back(&info);
-        }
-    }
-    // For each set of layers with the same top, resolve them to a linear chain rather than in-place layers.
-    // Note that for 'regular' layers, there will be a single layer in each group and so this will be a no-op.
-    for (auto& layersWithSameTopIterator : layersByTop)
-    {
-        const std::string& top = layersWithSameTopIterator.first;
-        const std::vector<LayerParameterInfo*> layersWithSameTop = layersWithSameTopIterator.second;
-
-        // Chain the layers together in the order that they are listed in the prototxt (hopefully this is correct).
-        // Note that the last layer will not have its top modified so that other layers will continue to reference it.
-        for (unsigned int layerIdx = 0; layerIdx < layersWithSameTop.size() - 1; ++layerIdx)
-        {
-            LayerParameterInfo* layer1 = layersWithSameTop[layerIdx];
-            LayerParameterInfo* layer2 = layersWithSameTop[layerIdx + 1];
-            if (layer1->top_size() != 1)
-            {
-                throw armnn::ParseException("Node '" + layer1->name() + "' is an in-place layer but "
-                                                                        "doesn't have exactly one top.");
-            }
-            std::string newTop = layer1->name() + "_top";
-            layer1->set_top(0, newTop);
-            if (layer2->bottom_size() != 1 || layer2->bottom(0) != top)
-            {
-                throw armnn::ParseException("Node '" + layer2->name() + "' is an in-place layer but "
-                    " doesn't have exactly one bottom, or it doesn't match its top.");
-            }
-            layer2->set_bottom(0, newTop);
-
-        }
-    }
-}
-
-} // anonymous namespace, can't be seen outside this source file
-
-RecordByRecordCaffeParser::RecordByRecordCaffeParser() : CaffeParserImpl()
-{}
-
-armnn::INetworkPtr RecordByRecordCaffeParser::CreateNetworkFromBinaryFile(
-    const char* graphFile,
-    const std::map<std::string, armnn::TensorShape>& inputShapes,
-    const std::vector<std::string>& requestedOutputs)
-{
-
-    m_InputShapes = inputShapes;
-    if (requestedOutputs.size() == 0)
-    {
-        throw armnn::ParseException("requestedOutputs must have at least one entry");
-    }
-    m_RequestedOutputs = requestedOutputs;
-
-    std::ifstream ifs(graphFile, std::ifstream::in|std::ifstream::binary);
-    if (ifs.fail())
-    {
-        throw armnn::FileNotFoundException("Failed to open graph file '" + std::string(graphFile) + "'");
-    }
-
-    std::vector<LayerParameterInfo> layerInfo;
-    NetParameterInfo netParameterInfo;
-    while(true)
-    {
-        ProtobufFieldInfo fieldInfo = readFieldInfo(ifs);
-        if (fieldInfo.eof())
-        {
-            break;
-        }
-        switch(fieldInfo.field_type())
-        {
-            case 0:
-            {
-                ReadBase128(ifs);
-                break;
-            }
-            case 2:
-            {
-                // The values of interest from the caffe.proto schema are:
-                // optional string name = 1; // consider giving the network a name
-                // DEPRECATED. See InputParameter. The input blobs to the network.
-                // repeated string input = 3;
-                // DEPRECATED. See InputParameter. The shape of the input blobs.
-                // repeated BlobShape input_shape = 8;
-
-                // 4D input dimensions -- deprecated.  Use "input_shape" instead.
-                // If specified, for each input blob there should be four
-                // values specifying the num, channels, height and width of the input blob.
-                // Thus, there should be a total of (4 * #input) numbers.
-                // repeated int32 input_dim = 4;
-
-                // The layers that make up the net.  Each of their configurations, including
-                // connectivity and behavior, is specified as a LayerParameter.
-                // repeated LayerParameter layer = 100;  // ID 100 so layers are printed last.
-
-                // The first four will (if present) be read into the NetParameterInfo
-                // the LayerParameters will be read into the LayerParameterInfo vector.
-
-                int size = ReadBase128(ifs);
-                std::streamoff posStartOfData = ifs.tellg();
-                ifs.seekg(size, std::ios_base::cur);
-                if(!ifs.good())
-                {
-                    throw armnn::ParseException("failed to seek ahead in binary caffe file");
-                }
-                std::streamoff endOfLayer = ifs.tellg();
-                if (fieldInfo.field_id() == 1)
-                {
-                    VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer);
-                    auto graphName = AllocateBuffer(ifs, dataInfo);
-                    netParameterInfo.set_name(graphName, dataInfo.SizeOfData());
-                }
-                if (fieldInfo.field_id() == 3)
-                {
-                    VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer);
-                    auto inputName = AllocateBuffer(ifs, dataInfo);
-                    netParameterInfo.add_input(inputName, dataInfo.SizeOfData());
-                }
-                if (fieldInfo.field_id() == 8)
-                {
-                    VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer);
-                    auto inputShape = AllocateBuffer(ifs, dataInfo);
-                    caffe::BlobShape blobShape;
-                    bool bRet = blobShape.ParseFromArray(inputShape.get(), static_cast<int>(dataInfo.SizeOfData()));
-                    if (!bRet)
-                    {
-                        throw armnn::ParseException("Failed to parse input shape");
-                    }
-                    netParameterInfo.add_blob_shape(blobShape);
-                }
-                if (fieldInfo.field_id() == 4)
-                {
-                    int input_dim = ReadBase128(ifs);
-                    netParameterInfo.add_input_dimension(input_dim);
-                }
-                if (fieldInfo.field_id() == 100)
-                {
-                    LayerParameterInfo info(CreateVarLenDataInfo(posStartOfData, endOfLayer));
-                    ReadTopologicalInfoForLayerParameter(info, ifs);
-                    layerInfo.push_back(info);
-                }
-                break;
-            }
-            default:
-            {
-                break;
-            }
-        }
-    }
-    std::vector<const LayerParameterInfo*> sortedNodes;
-    ProcessLayers(netParameterInfo, layerInfo, m_RequestedOutputs, sortedNodes);
-    armnn::INetworkPtr networkPtr = LoadLayers(ifs, sortedNodes, netParameterInfo);
-    return networkPtr;
-
-}
-
-void RecordByRecordCaffeParser::ProcessLayers(
-    const NetParameterInfo& netParameterInfo,
-    std::vector<LayerParameterInfo>& layerInfo,
-    const std::vector<std::string>& m_RequestedOutputs,
-    std::vector<const LayerParameterInfo*>& sortedNodes)
-{
-    // if there is an implicit input layer add it to the layerInfo list
-    if (netParameterInfo.input_size() > 0)
-    {
-        LayerParameterInfo implicitInputLayer(0, 0);
-        implicitInputLayer.set_type(LayerParameterInfo::INPUT);
-        implicitInputLayer.set_name(netParameterInfo.input(0));
-        implicitInputLayer.add_top(netParameterInfo.input(0));
-        layerInfo.push_back(implicitInputLayer);
-    }
-    ::ResolveInPlaceLayers(layerInfo);
-
-    for (LayerParameterInfo& info : layerInfo)
-    {
-        for (unsigned long i = 0; i < info.top_size(); ++i)
-        {
-            m_CaffeLayersByTopName[info.top(i)] = &info;
-        }
-    }
-
-    // Find the output layers the user requested
-    std::vector<const LayerParameterInfo*> targetLayers;
-    for (const std::string& requestedOutputName : m_RequestedOutputs)
-    {
-        auto nodeIt = m_CaffeLayersByTopName.find(requestedOutputName);
-        if (nodeIt == m_CaffeLayersByTopName.end())
-        {
-            throw armnn::ParseException(
-                "Couldn't find requested output layer '" + requestedOutputName + "' in graph");
-        }
-        targetLayers.push_back(nodeIt->second);
-    }
-
-    // Sort them into a linear ordering such that all inputs of a node are before the node itself
-    if (!armnnUtils::GraphTopologicalSort<const LayerParameterInfo*>(
-        targetLayers,
-        [this](const LayerParameterInfo* node)
-            {
-                return GetInputs(*node);
-            },
-        sortedNodes))
-    {
-        throw armnn::ParseException("Cycle detected in graph");
-    }
-}
-
-
-std::vector<const LayerParameterInfo*> RecordByRecordCaffeParser::GetInputs(
-    const LayerParameterInfo& layerParam)
-{
-    std::vector<const LayerParameterInfo*> ret;
-    ret.reserve(layerParam.bottom_size());
-    for (unsigned long j = 0; j < layerParam.bottom_size(); ++j)
-    {
-        std::string inputName = layerParam.bottom(j);
-        auto inputIt = m_CaffeLayersByTopName.find(inputName);
-        if (inputIt == m_CaffeLayersByTopName.end())
-        {
-            throw armnn::ParseException(
-                "Can't find Caffe layer with top called '" + inputName + "', which is listed as an input of '" +
-                layerParam.name() + "'");
-        }
-        ret.push_back(inputIt->second);
-    }
-
-    return ret;
-}
-
-armnn::INetworkPtr RecordByRecordCaffeParser::LoadLayers(std::ifstream& ifs,
-                                                         std::vector<const LayerParameterInfo *>& sortedNodes,
-                                                         const NetParameterInfo& netParameterInfo)
-{
-
-    m_NetworkInputsBindingInfo.clear();
-    m_NetworkOutputsBindingInfo.clear();
-
-    m_Network = armnn::INetwork::Create();
-
-    for (auto info : sortedNodes)
-    {
-        caffe::LayerParameter layer;
-        if (info->isImplicitInputLayer())
-        {
-            // create the matching Layer Parameter programatically from the data in the
-            // net parameter info which has been passed in...
-            layer.set_type(LayerParameterInfo::INPUT);
-            layer.set_name(netParameterInfo.input(0));
-            layer.add_top(netParameterInfo.input(0));
-
-            caffe::InputParameter* inputParam = layer.mutable_input_param();
-            caffe::BlobShape* shape = inputParam->add_shape();
-
-            long unsigned int dim_size = netParameterInfo.input_dimensions_size();
-            for (long unsigned int i = 0; i < dim_size; ++i)
-            {
-                shape->add_dim(netParameterInfo.input_dimension(i));
-            }
-        }
-        else
-        {
-            char *buffer = new char[info->SizeOfData()];
-            ifs.clear();
-            ifs.seekg(info->PositionOfData(), std::ios_base::beg);
-            ifs.read(buffer, armnn::numeric_cast<std::streamsize>(info->SizeOfData()));
-            bool bRet = layer.ParseFromArray(buffer, static_cast<int>(info->SizeOfData()));
-            delete[] buffer;
-            if (!bRet)
-            {
-                throw armnn::ParseException("Failed to parse layer [" + info->name() + "]");
-            }
-        }
-
-        if (info->new_tops())
-        {
-            //update the tops
-            layer.set_top(0, info->top(0));
-        }
-        if (info->new_bottoms())
-        {
-            //update the bottoms
-            layer.set_bottom(0, info->bottom(0));
-        }
-
-        auto it = ms_CaffeLayerNameToParsingFunctions.find(layer.type());
-        if (it == ms_CaffeLayerNameToParsingFunctions.end())
-        {
-            throw armnn::ParseException("Unsupported layer type '" + layer.type() + "'");
-        }
-        auto func = it->second;
-        (this->*func)(layer);
-    }
-    ifs.close();
-
-    // Add ArmNN output layers connected to each requested output
-    for (const std::string& requestedOutput : m_RequestedOutputs)
-    {
-        armnn::IOutputSlot& outputSlot = GetArmnnOutputSlotForCaffeTop(requestedOutput);
-
-        const armnn::LayerBindingId outputId = armnn::numeric_cast<armnn::LayerBindingId>(
-            m_NetworkOutputsBindingInfo.size());
-        armnn::IConnectableLayer* const outputLayer = m_Network->AddOutputLayer(outputId, requestedOutput.c_str());
-        outputSlot.Connect(outputLayer->GetInputSlot(0));
-
-        TrackOutputBinding(outputLayer, outputId, outputLayer->GetInputSlot(0).GetConnection()->GetTensorInfo());
-    }
-
-    Cleanup();
-
-    return move(m_Network);
-}
diff --git a/src/armnnCaffeParser/RecordByRecordCaffeParser.hpp b/src/armnnCaffeParser/RecordByRecordCaffeParser.hpp
deleted file mode 100644
index aab2fb025b..0000000000
--- a/src/armnnCaffeParser/RecordByRecordCaffeParser.hpp
+++ /dev/null
@@ -1,53 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include <string>
-#include <vector>
-#include <iostream>
-
-#include "caffe/proto/caffe.pb.h"
-
-#include "CaffeParser.hpp"
-
-
-
-namespace armnnCaffeParser
-{
-
-class NetParameterInfo;
-class LayerParameterInfo;
-
-
-class RecordByRecordCaffeParser : public ICaffeParser::CaffeParserImpl
-{
-public:
-
-    /// Create the network from a protobuf binary file on disk
-    virtual armnn::INetworkPtr CreateNetworkFromBinaryFile(
-        const char* graphFile,
-        const std::map<std::string, armnn::TensorShape>& inputShapes,
-        const std::vector<std::string>& requestedOutputs) override;
-
-    RecordByRecordCaffeParser();
-
-private:
-    void ProcessLayers(const NetParameterInfo& netParameterInfo,
-                       std::vector<LayerParameterInfo>& layerInfo,
-                       const std::vector<std::string>& m_RequestedOutputs,
-                       std::vector<const LayerParameterInfo*>& sortedNodes);
-    armnn::INetworkPtr LoadLayers(std::ifstream& ifs,
-                                  std::vector<const LayerParameterInfo *>& sortedNodes,
-                                  const NetParameterInfo& netParameterInfo);
-    std::vector<const LayerParameterInfo*> GetInputs(
-        const LayerParameterInfo& layerParam);
-
-    std::map<std::string, const LayerParameterInfo*> m_CaffeLayersByTopName;
-    std::vector<std::string> m_RequestedOutputs;
-};
-
-} // namespace armnnCaffeParser
-
diff --git a/src/armnnCaffeParser/test/TestAdd.cpp b/src/armnnCaffeParser/test/TestAdd.cpp
deleted file mode 100644
index ab087cbb89..0000000000
--- a/src/armnnCaffeParser/test/TestAdd.cpp
+++ /dev/null
@@ -1,70 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct AddFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    AddFixture()
-    {
-        m_Prototext = "name: \"MinimalAdd\"\n"
-                      "layer {\n"
-                      "  name: \"data\"\n"
-                      "  type: \"Input\"\n"
-                      "  top: \"data\"\n"
-                      "  input_param { shape: { dim: 1 dim: 1 dim: 4 dim: 4 } }\n"
-                      "}\n"
-                      "layer {\n"
-                      "    bottom: \"data\"\n"
-                      "    top: \"pool1\"\n"
-                      "    name: \"pool1\"\n"
-                      "    type: \"Pooling\"\n"
-                      "    pooling_param {\n"
-                      "        kernel_size: 2\n"
-                      "        stride: 2\n"
-                      "        pool: MAX\n"
-                      "    }\n"
-                      "}\n"
-                      "layer {\n"
-                      "    bottom: \"data\"\n"
-                      "    top: \"pool2\"\n"
-                      "    name: \"pool2\"\n"
-                      "    type: \"Pooling\"\n"
-                      "    pooling_param {\n"
-                      "        kernel_size: 2\n"
-                      "        stride: 2\n"
-                      "        pool: MAX\n"
-                      "    }\n"
-                      "}\n"
-                      "layer {\n"
-                      "    bottom: \"pool1\"\n"
-                      "    bottom: \"pool2\"\n"
-                      "    top: \"add\"\n"
-                      "    name: \"add\"\n"
-                      "    type: \"Eltwise\"\n"
-                      "}\n";
-        SetupSingleInputSingleOutput("data", "add");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseAdd, AddFixture)
-{
-    RunTest<4>(
-        {
-            0, 1, 0, 0,
-            0, 0, 0, 0,
-            0, 0, 1, 0,
-            1, 0, 1, 1
-        },
-        {
-            2, 0,
-            2, 2
-        });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestConcat.cpp b/src/armnnCaffeParser/test/TestConcat.cpp
deleted file mode 100644
index 2d952865f4..0000000000
--- a/src/armnnCaffeParser/test/TestConcat.cpp
+++ /dev/null
@@ -1,73 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct ConcatFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    ConcatFixture()
-    {
-        m_Prototext = "name: \"Concat\"\n"
-            "layer {\n"
-            "  name: \"data\"\n"
-            "  type: \"Input\"\n"
-            "  top: \"data\"\n"
-            "  input_param { shape: { dim: 1 dim: 1 dim: 4 dim: 4 } }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"pool1\"\n"
-            "    name: \"pool1\"\n"
-            "    type: \"Pooling\"\n"
-            "    pooling_param {\n"
-            "        kernel_size: 2\n"
-            "        stride: 2\n"
-            "        pool: MAX\n"
-            "    }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"pool2\"\n"
-            "    name: \"pool2\"\n"
-            "    type: \"Pooling\"\n"
-            "    pooling_param {\n"
-            "        kernel_size: 2\n"
-            "        stride: 2\n"
-            "        pool: MAX\n"
-            "    }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"pool1\"\n"
-            "    bottom: \"pool2\"\n"
-            "    top: \"concat\"\n"
-            "    name: \"concat\"\n"
-            "    type: \"Concat\"\n"
-            "}\n";
-        SetupSingleInputSingleOutput("data", "concat");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseConcat, ConcatFixture)
-{
-    RunTest<4>(
-        {
-            0, 1, 0, 0,
-            0, 0, 0, 0,
-            0, 0, 1, 0,
-            1, 0, 1, 1
-        },
-        {
-            1, 0,
-            1, 1,
-
-            1, 0,
-            1, 1
-        });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestConvolution.cpp b/src/armnnCaffeParser/test/TestConvolution.cpp
deleted file mode 100644
index b881f1f58f..0000000000
--- a/src/armnnCaffeParser/test/TestConvolution.cpp
+++ /dev/null
@@ -1,133 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-#include <sstream>
-#include <initializer_list>
-
-namespace
-{
-
-template <typename T>
-std::string TaggedSequence(const std::string & tag, const std::initializer_list<T> & data)
-{
-    bool first = true;
-    std::stringstream ss;
-    for (auto && d : data)
-    {
-        if (!first)
-        {
-            ss << " , ";
-        }
-        else
-        {
-            first = false;
-        }
-        ss << " " << tag << " : " << d << " ";
-    }
-    return ss.str();
-}
-
-template <typename T>
-std::string TaggedSequence(const std::string & tag, T data, unsigned int n)
-{
-    std::stringstream ss;
-    for (unsigned int i=0; i<n; ++i)
-    {
-        if (i>0)
-        {
-            ss << " , ";
-        }
-        ss << " " << tag << " : " << data << " ";
-    }
-    return ss.str();
-}
-
-} // namespace <anonymous>
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct ConvolutionFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    ConvolutionFixture(const std::initializer_list<unsigned int> & inputDims,
-                       const std::initializer_list<float> & filterData,
-                       unsigned int kernelSize,
-                       unsigned int numOutput=1,
-                       unsigned int group=1)
-    {
-        m_Prototext = R"(
-            name: "ConvolutionTest"
-            layer {
-                name: "input1"
-                type: "Input"
-                top: "input1"
-                input_param { shape: { )" + TaggedSequence("dim", inputDims) + R"( } }
-            }
-            layer {
-                name: "conv1"
-                type: "Convolution"
-                bottom: "input1"
-                top: "conv1"
-                blobs: { )" + TaggedSequence("data", filterData) + R"( }
-                blobs: { )" + TaggedSequence("data", 0, numOutput) + R"( }
-                convolution_param {
-                    num_output: )" + std::to_string(numOutput) + R"(
-                    pad: 0
-                    kernel_size: )" +  std::to_string(kernelSize) + R"(
-                    stride: 1
-                    group: )" +  std::to_string(group) + R"(
-                }
-            }
-        )";
-        SetupSingleInputSingleOutput("input1", "conv1");
-    }
-};
-
-struct SimpleConvolutionFixture : public ConvolutionFixture
-{
-    SimpleConvolutionFixture()
-    : ConvolutionFixture( {1, 1, 2, 2}, {1.0f, 1.0f, 1.0f, 1.0f}, 2)
-    {
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(SimpleConvolution, SimpleConvolutionFixture)
-{
-    RunTest<4>({ 1, 3, 5, 7 }, { 16 });
-}
-
-struct GroupConvolutionFixture : public ConvolutionFixture
-{
-    GroupConvolutionFixture()
-    : ConvolutionFixture(
-        {1, 2, 2, 2},
-        {
-            1.0f, 1.0f, 1.0f, 1.0f, // filter for channel #0
-            2.0f, 2.0f, 2.0f, 2.0f  // filter for channel #1
-        },
-        2, // kernel size is 2x2
-        2, // number of output channels is 2
-        2) // number of groups (separate filters)
-    {
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(GroupConvolution, GroupConvolutionFixture)
-{
-    RunTest<4>(
-        {
-            1, 2, 3, 4, // input channel #0
-            5, 6, 7, 8, // input channel #1
-        },
-        {
-            10, // convolution result for channel #0 applying filter #0
-            52  // same for channel #1 and filter #1
-        }
-    );
-}
-
-
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
diff --git a/src/armnnCaffeParser/test/TestDropout.cpp b/src/armnnCaffeParser/test/TestDropout.cpp
deleted file mode 100644
index 503766248b..0000000000
--- a/src/armnnCaffeParser/test/TestDropout.cpp
+++ /dev/null
@@ -1,53 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct DropoutFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    DropoutFixture()
-    {
-        m_Prototext = "name: \"DropoutFixture\"\n"
-            "layer {\n"
-            "    name: \"data\"\n"
-            "    type: \"Input\"\n"
-            "    top: \"data\"\n"
-            "    input_param { shape: { dim: 1 dim: 1 dim: 2 dim: 2 } }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"drop1\"\n"
-            "    name: \"drop1\"\n"
-            "    type: \"Dropout\"\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"drop1\"\n"
-            "    bottom: \"drop1\"\n"
-            "    top: \"add\"\n"
-            "    name: \"add\"\n"
-            "    type: \"Eltwise\"\n"
-            "}\n";
-        SetupSingleInputSingleOutput("data", "add");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseDropout, DropoutFixture)
-{
-    RunTest<4>(
-        {
-            1, 2,
-            3, 4,
-        },
-        {
-            2, 4,
-            6, 8
-        });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestInPlace.cpp b/src/armnnCaffeParser/test/TestInPlace.cpp
deleted file mode 100644
index 2495e2182e..0000000000
--- a/src/armnnCaffeParser/test/TestInPlace.cpp
+++ /dev/null
@@ -1,98 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-// The pooling layer should take its input from the relu, not the add directly.
-struct InPlaceFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    InPlaceFixture()
-    {
-        m_Prototext = R"(
-name: "InPlace"
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param { shape: { dim: 1 dim: 1 dim: 1 dim: 1 } }
-}
-layer {
-    bottom: "data"
-    bottom: "data"
-    top: "add"
-    name: "add"
-    type: "Eltwise"
-}
-layer {
-  name: "relu"
-  type: "ReLU"
-  bottom: "add"
-  top: "relu"
-  phase: TEST
-}
-layer {
-  name: "pool"
-  type: "Pooling"
-  bottom: "relu"
-  top: "pool"
-  phase: TEST
-  pooling_param {
-    pool: MAX
-    kernel_size: 1
-    stride: 1
-  }
-}
-        )";
-        SetupSingleInputSingleOutput("data", "pool");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseInPlace, InPlaceFixture)
-{
-    RunTest<1>({ -1.0f }, { 0.0f });
-}
-
-// The requested output of the network is a layer which has an activation attached.
-// The output of the network should therefore actually be the activation layer.
-struct InPlaceOutputFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    InPlaceOutputFixture()
-    {
-        m_Prototext = R"(
-name: "InPlace"
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param { shape: { dim: 1 dim: 1 dim: 1 dim: 1 } }
-}
-layer {
-    bottom: "data"
-    bottom: "data"
-    top: "add"
-    name: "add"
-    type: "Eltwise"
-}
-layer {
-  name: "relu"
-  type: "ReLU"
-  bottom: "add"
-  top: "add"
-  phase: TEST
-}
-        )";
-        SetupSingleInputSingleOutput("data", "add");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(InPlaceOutput, InPlaceOutputFixture)
-{
-    RunTest<1>({ -1.0f }, { 0.0f });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestInputs.cpp b/src/armnnCaffeParser/test/TestInputs.cpp
deleted file mode 100644
index 96d8e2b8af..0000000000
--- a/src/armnnCaffeParser/test/TestInputs.cpp
+++ /dev/null
@@ -1,122 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "armnn/IRuntime.hpp"
-#include "armnn/INetwork.hpp"
-#include "armnn/Exceptions.hpp"
-
-#include "test/TensorHelpers.hpp"
-
-#include <string>
-
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-
-BOOST_AUTO_TEST_CASE(InputShapes)
-{
-    std::string explicitInput = "name: \"Minimal\"\n"
-                                "layer {\n"
-                                "  name: \"data\"\n"
-                                "  type: \"Input\"\n"
-                                "  top: \"data\"\n"
-                                "  input_param { shape: { dim: 1 dim: 2 dim: 3 dim: 4 } }\n"
-                                "}";
-    std::string implicitInput = "name: \"Minimal\"\n"
-                                "input: \"data\" \n"
-                                "input_dim: 1 \n"
-                                "input_dim: 2 \n"
-                                "input_dim: 3 \n"
-                                "input_dim: 4 \n";
-    std::string implicitInputNoShape = "name: \"Minimal\"\n"
-                                       "input: \"data\" \n";
-
-    armnn::IRuntime::CreationOptions options;
-    armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
-    armnnCaffeParser::ICaffeParserPtr parser(armnnCaffeParser::ICaffeParser::Create());
-    armnn::INetworkPtr network(nullptr, nullptr);
-    armnn::NetworkId netId;
-
-    // Check everything works normally
-    std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
-    {
-        network = parser->CreateNetworkFromString(explicitInput.c_str(), {}, { "data" });
-        BOOST_TEST(network.get());
-        runtime->LoadNetwork(netId, Optimize(*network, backends, runtime->GetDeviceSpec()));
-
-        armnnCaffeParser::BindingPointInfo inputBindingInfo = parser->GetNetworkInputBindingInfo("data");
-        armnn::TensorInfo inputTensorInfo = inputBindingInfo.second;
-        BOOST_TEST((inputTensorInfo == runtime->GetInputTensorInfo(netId, inputBindingInfo.first)));
-
-        BOOST_TEST(inputTensorInfo.GetShape()[0] == 1);
-        BOOST_TEST(inputTensorInfo.GetShape()[1] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[2] == 3);
-        BOOST_TEST(inputTensorInfo.GetShape()[3] == 4);
-    }
-
-    // Checks everything works with implicit input.
-    {
-        network = parser->CreateNetworkFromString(implicitInput.c_str(), {}, { "data" });
-        BOOST_TEST(network.get());
-        runtime->LoadNetwork(netId, Optimize(*network, backends, runtime->GetDeviceSpec()));
-
-        armnnCaffeParser::BindingPointInfo inputBindingInfo = parser->GetNetworkInputBindingInfo("data");
-        armnn::TensorInfo inputTensorInfo = inputBindingInfo.second;
-        BOOST_TEST((inputTensorInfo == runtime->GetInputTensorInfo(netId, inputBindingInfo.first)));
-
-        BOOST_TEST(inputTensorInfo.GetShape()[0] == 1);
-        BOOST_TEST(inputTensorInfo.GetShape()[1] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[2] == 3);
-        BOOST_TEST(inputTensorInfo.GetShape()[3] == 4);
-    }
-
-    // Checks everything works with implicit and passing shape.
-    {
-        network = parser->CreateNetworkFromString(implicitInput.c_str(), { {"data", { 2, 2, 3, 4 } } }, { "data" });
-        BOOST_TEST(network.get());
-        runtime->LoadNetwork(netId, Optimize(*network, backends, runtime->GetDeviceSpec()));
-
-        armnnCaffeParser::BindingPointInfo inputBindingInfo = parser->GetNetworkInputBindingInfo("data");
-        armnn::TensorInfo inputTensorInfo = inputBindingInfo.second;
-        BOOST_TEST((inputTensorInfo == runtime->GetInputTensorInfo(netId, inputBindingInfo.first)));
-
-        BOOST_TEST(inputTensorInfo.GetShape()[0] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[1] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[2] == 3);
-        BOOST_TEST(inputTensorInfo.GetShape()[3] == 4);
-    }
-
-    // Checks everything works with implicit (no shape) and passing shape.
-    {
-        network = parser->CreateNetworkFromString(implicitInputNoShape.c_str(), {{"data", {2, 2, 3, 4} }}, { "data" });
-        BOOST_TEST(network.get());
-        runtime->LoadNetwork(netId, Optimize(*network, backends, runtime->GetDeviceSpec()));
-
-        armnnCaffeParser::BindingPointInfo inputBindingInfo = parser->GetNetworkInputBindingInfo("data");
-        armnn::TensorInfo inputTensorInfo = inputBindingInfo.second;
-        BOOST_TEST((inputTensorInfo == runtime->GetInputTensorInfo(netId, inputBindingInfo.first)));
-
-        BOOST_TEST(inputTensorInfo.GetShape()[0] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[1] == 2);
-        BOOST_TEST(inputTensorInfo.GetShape()[2] == 3);
-        BOOST_TEST(inputTensorInfo.GetShape()[3] == 4);
-    }
-
-    // Checks exception on incompatible shapes.
-    {
-        BOOST_CHECK_THROW(parser->CreateNetworkFromString(implicitInput.c_str(), {{"data",{ 2, 2, 3, 2 }}}, {"data"}),
-            armnn::ParseException);
-    }
-
-    // Checks exception when no shape available.
-    {
-        BOOST_CHECK_THROW(parser->CreateNetworkFromString(implicitInputNoShape.c_str(), {}, { "data" }),
-            armnn::ParseException);
-    }
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestMul.cpp b/src/armnnCaffeParser/test/TestMul.cpp
deleted file mode 100644
index 3b49015bce..0000000000
--- a/src/armnnCaffeParser/test/TestMul.cpp
+++ /dev/null
@@ -1,73 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct MulFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    MulFixture()
-    {
-        m_Prototext = "name: \"MinimalMul\"\n"
-            "layer {\n"
-            "  name: \"data\"\n"
-            "  type: \"Input\"\n"
-            "  top: \"data\"\n"
-            "  input_param { shape: { dim: 1 dim: 1 dim: 4 dim: 4 } }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"pool1\"\n"
-            "    name: \"pool1\"\n"
-            "    type: \"Pooling\"\n"
-            "    pooling_param {\n"
-            "        kernel_size: 2\n"
-            "        stride: 2\n"
-            "        pool: MAX\n"
-            "    }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"pool2\"\n"
-            "    name: \"pool2\"\n"
-            "    type: \"Pooling\"\n"
-            "    pooling_param {\n"
-            "        kernel_size: 2\n"
-            "        stride: 2\n"
-            "        pool: MAX\n"
-            "    }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"pool1\"\n"
-            "    bottom: \"pool2\"\n"
-            "    top: \"mul\"\n"
-            "    name: \"mul\"\n"
-            "    type: \"Eltwise\"\n"
-            "    eltwise_param {\n"
-            "        operation: 0\n"
-            "    }\n"
-            "}\n";
-        SetupSingleInputSingleOutput("data", "mul");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseMul, MulFixture)
-{
-    RunTest<4>(
-        {
-            0, 1, 0, 0,
-            0, 0, 0, 0,
-            0, 0, 1, 0,
-            1, 0, 1, 1
-        },
-        {
-            1, 0,
-            1, 1
-        });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestMultiInputsOutputs.cpp b/src/armnnCaffeParser/test/TestMultiInputsOutputs.cpp
deleted file mode 100644
index 82b75f400e..0000000000
--- a/src/armnnCaffeParser/test/TestMultiInputsOutputs.cpp
+++ /dev/null
@@ -1,54 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct MultiInputsOutputsFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    MultiInputsOutputsFixture()
-    {
-        m_Prototext = R"(
-name: "MultiInputsOutputs"
-layer {
-  name: "input1"
-  type: "Input"
-  top: "input1"
-  input_param { shape: { dim: 1 } }
-}
-layer {
-  name: "input2"
-  type: "Input"
-  top: "input2"
-  input_param { shape: { dim: 1 } }
-}
-layer {
-    bottom: "input1"
-    bottom: "input2"
-    top: "add1"
-    name: "add1"
-    type: "Eltwise"
-}
-layer {
-    bottom: "input2"
-    bottom: "input1"
-    top: "add2"
-    name: "add2"
-    type: "Eltwise"
-}
-        )";
-        Setup({ }, { "add1", "add2" });
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(MultiInputsOutputs, MultiInputsOutputsFixture)
-{
-    RunTest<1>({ { "input1",{ 12.0f } },{ "input2",{ 13.0f } } },
-        { { "add1",{ 25.0f } },{ "add2",{ 25.0f } } });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestPooling2d.cpp b/src/armnnCaffeParser/test/TestPooling2d.cpp
deleted file mode 100644
index 55517a0695..0000000000
--- a/src/armnnCaffeParser/test/TestPooling2d.cpp
+++ /dev/null
@@ -1,54 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct GlobalPoolingFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    GlobalPoolingFixture()
-    {
-        m_Prototext = "name: \"GlobalPooling\"\n"
-            "layer {\n"
-            "  name: \"data\"\n"
-            "  type: \"Input\"\n"
-            "  top: \"data\"\n"
-            "  input_param { shape: { dim: 1 dim: 3 dim: 2 dim: 2 } }\n"
-            "}\n"
-            "layer {\n"
-            "    bottom: \"data\"\n"
-            "    top: \"pool1\"\n"
-            "    name: \"pool1\"\n"
-            "    type: \"Pooling\"\n"
-            "    pooling_param {\n"
-            "        pool: AVE\n"
-            "        global_pooling: true\n"
-            "    }\n"
-            "}\n";
-        SetupSingleInputSingleOutput("data", "pool1");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(GlobalPooling, GlobalPoolingFixture)
-{
-    RunTest<4>(
-        {
-            1,3,
-            5,7,
-
-            2,2,
-            2,2,
-
-            4,4,
-            6,6
-        },
-        {
-            4, 2, 5
-        });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnCaffeParser/test/TestSplit.cpp b/src/armnnCaffeParser/test/TestSplit.cpp
deleted file mode 100644
index 048da424cf..0000000000
--- a/src/armnnCaffeParser/test/TestSplit.cpp
+++ /dev/null
@@ -1,47 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include <boost/test/unit_test.hpp>
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "ParserPrototxtFixture.hpp"
-
-BOOST_AUTO_TEST_SUITE(CaffeParser)
-
-struct SplitFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
-{
-    SplitFixture()
-    {
-        m_Prototext = R"(
-name: "Split"
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param { shape: { dim: 1 dim: 1 dim: 1 dim: 1 } }
-}
-layer {
-    name: "split"
-    type: "Split"
-    bottom: "data"
-    top: "split_top0"
-    top: "split_top1"
-}
-layer {
-    bottom: "split_top0"
-    bottom: "split_top1"
-    top: "add"
-    name: "add"
-    type: "Eltwise"
-}
-        )";
-        SetupSingleInputSingleOutput("data", "add");
-    }
-};
-
-BOOST_FIXTURE_TEST_CASE(Split, SplitFixture)
-{
-    RunTest<1>({ 1.0f }, { 2.0f });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnConverter/ArmnnConverter.cpp b/src/armnnConverter/ArmnnConverter.cpp
index b5d3256c3c..6f05325bba 100644
--- a/src/armnnConverter/ArmnnConverter.cpp
+++ b/src/armnnConverter/ArmnnConverter.cpp
@@ -4,9 +4,6 @@
 //
 #include <armnn/Logging.hpp>
 
-#if defined(ARMNN_CAFFE_PARSER)
-#include <armnnCaffeParser/ICaffeParser.hpp>
-#endif
 #if defined(ARMNN_ONNX_PARSER)
 #include <armnnOnnxParser/IOnnxParser.hpp>
 #endif
@@ -81,9 +78,6 @@ int ParseCommandLineArgs(int argc, char* argv[],
     try
     {
         std::string modelFormatDescription("Format of the model file");
-#if defined(ARMNN_CAFFE_PARSER)
-        modelFormatDescription += ", caffe-binary, caffe-text";
-#endif
 #if defined(ARMNN_ONNX_PARSER)
         modelFormatDescription += ", onnx-binary, onnx-text";
 #endif
@@ -336,11 +330,10 @@ private:
 int main(int argc, char* argv[])
 {
 
-#if (!defined(ARMNN_CAFFE_PARSER)     \
-       && !defined(ARMNN_ONNX_PARSER) \
+#if (!defined(ARMNN_ONNX_PARSER) \
        && !defined(ARMNN_TF_PARSER)   \
        && !defined(ARMNN_TF_LITE_PARSER))
-    ARMNN_LOG(fatal) << "Not built with any of the supported parsers, Caffe, Onnx, Tensorflow, or TfLite.";
+    ARMNN_LOG(fatal) << "Not built with any of the supported parsers Onnx, Tensorflow, or TfLite.";
     return EXIT_FAILURE;
 #endif
 
@@ -399,20 +392,7 @@ int main(int argc, char* argv[])
 
     try
     {
-        if (modelFormat.find("caffe") != std::string::npos)
-        {
-#if defined(ARMNN_CAFFE_PARSER)
-            if (!converter.CreateNetwork<armnnCaffeParser::ICaffeParser>())
-            {
-                ARMNN_LOG(fatal) << "Failed to load model from file";
-                return EXIT_FAILURE;
-            }
-#else
-            ARMNN_LOG(fatal) << "Not built with Caffe parser support.";
-            return EXIT_FAILURE;
-#endif
-        }
-        else if (modelFormat.find("onnx") != std::string::npos)
+        if (modelFormat.find("onnx") != std::string::npos)
         {
 #if defined(ARMNN_ONNX_PARSER)
             if (!converter.CreateNetwork<armnnOnnxParser::IOnnxParser>())
diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt
index 135f6497be..308b885230 100644
--- a/tests/CMakeLists.txt
+++ b/tests/CMakeLists.txt
@@ -16,70 +16,6 @@ target_include_directories(inferenceTest PRIVATE ../src/armnnUtils)
 target_include_directories(inferenceTest PRIVATE ../src/backends)
 target_include_directories(inferenceTest PRIVATE ../third-party/stb)
 
-if(BUILD_CAFFE_PARSER)
-    macro(CaffeParserTest testName sources)
-        add_executable_ex(${testName} ${sources})
-        target_include_directories(${testName} PRIVATE ../src/armnnUtils)
-        target_include_directories(${testName} PRIVATE ../src/backends)
-        set_target_properties(${testName} PROPERTIES COMPILE_FLAGS "${CAFFE_PARSER_TEST_ADDITIONAL_COMPILE_FLAGS}")
-
-        target_link_libraries(${testName} inferenceTest)
-        target_link_libraries(${testName} armnnCaffeParser)
-        target_link_libraries(${testName} armnn)
-        target_link_libraries(${testName} ${CMAKE_THREAD_LIBS_INIT})
-        addDllCopyCommands(${testName})
-    endmacro()
-
-    set(CaffeCifar10AcrossChannels-Armnn_sources
-        CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
-        Cifar10Database.hpp
-        Cifar10Database.cpp)
-    CaffeParserTest(CaffeCifar10AcrossChannels-Armnn "${CaffeCifar10AcrossChannels-Armnn_sources}")
-
-    set(CaffeMnist-Armnn_sources
-        CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
-        MnistDatabase.hpp
-        MnistDatabase.cpp)
-    CaffeParserTest(CaffeMnist-Armnn "${CaffeMnist-Armnn_sources}")
-
-    set(CaffeAlexNet-Armnn_sources
-        CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
-        CaffePreprocessor.hpp
-        CaffePreprocessor.cpp)
-    CaffeParserTest(CaffeAlexNet-Armnn "${CaffeAlexNet-Armnn_sources}")
-
-    set(MultipleNetworksCifar10_SRC
-        MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
-        Cifar10Database.hpp
-        Cifar10Database.cpp)
-    CaffeParserTest(MultipleNetworksCifar10 "${MultipleNetworksCifar10_SRC}")
-
-    set(CaffeResNet-Armnn_sources
-        CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
-        CaffePreprocessor.hpp
-        CaffePreprocessor.cpp)
-    CaffeParserTest(CaffeResNet-Armnn "${CaffeResNet-Armnn_sources}")
-
-    set(CaffeVGG-Armnn_sources
-        CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
-        CaffePreprocessor.hpp
-        CaffePreprocessor.cpp)
-    CaffeParserTest(CaffeVGG-Armnn "${CaffeVGG-Armnn_sources}")
-
-    set(CaffeInception_BN-Armnn_sources
-        CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
-        CaffePreprocessor.hpp
-        CaffePreprocessor.cpp)
-    CaffeParserTest(CaffeInception_BN-Armnn "${CaffeInception_BN-Armnn_sources}")
-
-    set(CaffeYolo-Armnn_sources
-        CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
-        YoloDatabase.hpp
-        YoloDatabase.cpp
-        YoloInferenceTest.hpp)
-    CaffeParserTest(CaffeYolo-Armnn "${CaffeYolo-Armnn_sources}")
-endif()
-
 if(BUILD_TF_PARSER)
     macro(TfParserTest testName sources)
         add_executable_ex(${testName} ${sources})
@@ -119,8 +55,8 @@ if(BUILD_TF_PARSER)
 
     set(TfResNext-Armnn_sources
         TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
-        CaffePreprocessor.hpp
-        CaffePreprocessor.cpp)
+        ImagePreprocessor.hpp
+        ImagePreprocessor.cpp)
     TfParserTest(TfResNext-Armnn "${TfResNext-Armnn_sources}")
 endif()
 
@@ -238,7 +174,7 @@ if (BUILD_ONNX_PARSER)
     OnnxParserTest(OnnxMobileNet-Armnn "${OnnxMobileNet-Armnn_sources}")
 endif()
 
-if (BUILD_ARMNN_SERIALIZER OR BUILD_CAFFE_PARSER OR BUILD_TF_PARSER OR BUILD_TF_LITE_PARSER OR BUILD_ONNX_PARSER)
+if (BUILD_ARMNN_SERIALIZER OR BUILD_TF_PARSER OR BUILD_TF_LITE_PARSER OR BUILD_ONNX_PARSER)
     set(ExecuteNetwork_sources
         ExecuteNetwork/ExecuteNetwork.cpp
         ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
@@ -257,9 +193,6 @@ if (BUILD_ARMNN_SERIALIZER OR BUILD_CAFFE_PARSER OR BUILD_TF_PARSER OR BUILD_TF_
     if (BUILD_ARMNN_SERIALIZER)
         target_link_libraries(ExecuteNetwork armnnSerializer)
     endif()
-    if (BUILD_CAFFE_PARSER)
-        target_link_libraries(ExecuteNetwork armnnCaffeParser)
-    endif()
     if (BUILD_TF_PARSER)
         target_link_libraries(ExecuteNetwork armnnTfParser)
     endif()
@@ -285,9 +218,6 @@ if(BUILD_ACCURACY_TOOL)
         if (BUILD_ARMNN_SERIALIZER)
             target_link_libraries(${executorName} armnnSerializer)
         endif()
-        if (BUILD_CAFFE_PARSER)
-            target_link_libraries(${executorName} armnnCaffeParser)
-        endif()
         if (BUILD_TF_PARSER)
             target_link_libraries(${executorName} armnnTfParser)
         endif()
diff --git a/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp b/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
deleted file mode 100644
index e14cd61e72..0000000000
--- a/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
+++ /dev/null
@@ -1,35 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        using DataType = float;
-        using DatabaseType = CaffePreprocessor;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                     argc, argv, "bvlc_alexnet_1.caffemodel", true, "data", "prob", { 0 },
-                     [](const char* dataDir, const ModelType &) {
-                         return DatabaseType(dataDir);
-                     });
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeAlexNet-Armnn: An error has occurred when running the "
-                     "classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeAlexNet-Armnn/Validation.txt b/tests/CaffeAlexNet-Armnn/Validation.txt
deleted file mode 100644
index cb95f050e2..0000000000
--- a/tests/CaffeAlexNet-Armnn/Validation.txt
+++ /dev/null
@@ -1,1000 +0,0 @@
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
diff --git a/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp b/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
deleted file mode 100644
index 7bd98f69da..0000000000
--- a/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
+++ /dev/null
@@ -1,36 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../Cifar10Database.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        using DataType = float;
-        using DatabaseType = Cifar10Database;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                    argc, argv, "cifar10_full_iter_60000.caffemodel", true, "data", "prob",
-                    { 0, 1, 2, 4, 7 },
-                    [](const char* dataDir, const ModelType&) {
-                        return DatabaseType(dataDir);
-                    });
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeCifar10AcrossChannels-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeCifar10AcrossChannels-Armnn/Validation.txt b/tests/CaffeCifar10AcrossChannels-Armnn/Validation.txt
deleted file mode 100644
index a7b59465eb..0000000000
--- a/tests/CaffeCifar10AcrossChannels-Armnn/Validation.txt
+++ /dev/null
@@ -1,1000 +0,0 @@
-3
-8
-8
-8
-6
-8
-5
-6
-3
-8
-0
-9
-5
-7
-9
-8
-5
-7
-8
-6
-7
-0
-8
-9
-4
-3
-3
-0
-9
-6
-6
-5
-8
-3
-9
-3
-7
-9
-9
-5
-0
-6
-7
-3
-0
-9
-3
-8
-7
-2
-9
-8
-5
-5
-8
-8
-7
-5
-5
-3
-7
-5
-2
-3
-6
-7
-8
-0
-3
-7
-0
-3
-8
-8
-0
-2
-0
-8
-5
-8
-8
-0
-1
-7
-3
-0
-3
-3
-8
-9
-0
-2
-8
-6
-7
-3
-6
-0
-0
-7
-8
-5
-6
-3
-1
-1
-3
-6
-8
-7
-5
-0
-2
-3
-0
-3
-0
-3
-7
-5
-8
-0
-1
-2
-8
-8
-8
-3
-6
-0
-4
-1
-8
-9
-1
-0
-9
-4
-2
-8
-3
-5
-6
-5
-8
-0
-6
-5
-5
-5
-8
-9
-5
-0
-0
-5
-0
-9
-5
-4
-0
-0
-0
-6
-0
-0
-8
-8
-5
-8
-9
-0
-8
-8
-9
-9
-3
-7
-5
-0
-0
-5
-2
-8
-0
-8
-5
-3
-3
-8
-5
-8
-0
-1
-7
-3
-8
-8
-7
-8
-5
-0
-8
-0
-1
-3
-8
-5
-7
-8
-7
-0
-5
-8
-8
-0
-7
-9
-8
-2
-7
-5
-8
-5
-5
-9
-8
-0
-3
-6
-5
-1
-7
-8
-8
-0
-4
-0
-5
-3
-1
-1
-8
-3
-0
-8
-1
-8
-2
-0
-5
-5
-9
-9
-2
-8
-3
-0
-8
-9
-8
-8
-3
-3
-0
-8
-8
-4
-7
-0
-0
-3
-6
-3
-8
-0
-0
-3
-2
-5
-9
-0
-6
-1
-0
-9
-8
-8
-7
-9
-8
-2
-6
-9
-3
-0
-6
-0
-0
-6
-6
-3
-3
-8
-8
-8
-8
-3
-1
-0
-8
-6
-0
-0
-8
-0
-7
-7
-5
-5
-3
-3
-2
-0
-5
-0
-7
-7
-3
-6
-1
-9
-3
-6
-6
-9
-3
-8
-0
-7
-0
-6
-2
-5
-8
-5
-7
-6
-8
-9
-9
-1
-8
-2
-3
-7
-5
-2
-8
-0
-9
-5
-8
-8
-9
-4
-0
-5
-8
-0
-0
-7
-9
-3
-2
-7
-3
-7
-8
-6
-6
-9
-0
-8
-5
-0
-7
-3
-5
-5
-1
-2
-6
-2
-3
-6
-2
-3
-0
-8
-9
-8
-7
-8
-8
-4
-0
-8
-8
-3
-5
-8
-3
-8
-1
-9
-0
-5
-5
-7
-4
-7
-8
-0
-0
-9
-3
-7
-0
-6
-3
-3
-8
-7
-3
-7
-8
-5
-3
-8
-1
-3
-9
-8
-8
-7
-3
-0
-0
-0
-2
-9
-7
-0
-8
-3
-4
-5
-3
-8
-5
-6
-8
-7
-3
-8
-4
-3
-7
-8
-5
-7
-8
-8
-3
-7
-4
-0
-5
-4
-3
-6
-0
-8
-5
-8
-9
-9
-8
-0
-0
-0
-0
-1
-8
-8
-0
-5
-2
-0
-4
-0
-5
-2
-9
-4
-7
-9
-0
-4
-5
-6
-8
-9
-5
-5
-8
-9
-3
-8
-5
-7
-0
-7
-0
-5
-0
-0
-0
-6
-8
-8
-9
-5
-6
-3
-6
-3
-9
-8
-1
-7
-0
-7
-5
-9
-0
-6
-5
-5
-3
-3
-8
-3
-9
-8
-6
-4
-3
-2
-0
-7
-6
-0
-2
-3
-9
-5
-8
-0
-6
-7
-8
-3
-6
-8
-8
-8
-7
-5
-4
-0
-8
-4
-0
-8
-3
-5
-8
-9
-6
-9
-2
-3
-0
-0
-7
-8
-8
-3
-8
-5
-0
-2
-1
-6
-3
-4
-3
-9
-6
-9
-8
-8
-5
-8
-6
-3
-2
-1
-7
-7
-1
-2
-7
-9
-9
-4
-4
-0
-8
-3
-2
-8
-7
-0
-8
-3
-0
-3
-3
-8
-0
-7
-9
-1
-8
-0
-4
-5
-3
-9
-3
-0
-8
-0
-1
-5
-4
-1
-8
-0
-7
-6
-3
-0
-9
-0
-8
-2
-6
-3
-2
-3
-0
-0
-3
-8
-0
-3
-9
-6
-8
-0
-9
-2
-8
-2
-3
-0
-3
-2
-2
-7
-8
-3
-8
-0
-7
-5
-7
-0
-4
-8
-7
-4
-8
-3
-8
-8
-6
-0
-8
-7
-4
-3
-3
-8
-4
-8
-7
-8
-8
-9
-8
-8
-1
-3
-3
-5
-5
-0
-7
-9
-8
-0
-8
-4
-1
-3
-5
-7
-8
-7
-8
-7
-4
-6
-2
-5
-8
-0
-8
-1
-2
-0
-6
-8
-2
-1
-3
-5
-6
-0
-1
-2
-0
-8
-3
-0
-5
-0
-6
-8
-0
-2
-7
-6
-0
-6
-9
-1
-7
-8
-7
-0
-3
-9
-7
-8
-0
-0
-3
-3
-7
-5
-4
-8
-8
-8
-7
-1
-2
-7
-4
-4
-8
-4
-7
-7
-3
-2
-7
-2
-0
-8
-8
-5
-8
-0
-8
-2
-0
-8
-7
-5
-0
-8
-5
-0
-0
-8
-2
-2
-2
-8
-9
-2
-7
-2
-7
-0
-7
-2
-1
-0
-0
-0
-8
-4
-7
-9
-8
-0
-0
-7
-7
-0
-7
-8
-4
-4
-3
-5
-0
-1
-3
-7
-0
-1
-8
-1
-4
-2
-3
-8
-4
-5
-0
-7
-8
-8
-3
-0
-8
-8
-8
-8
-8
-4
-3
-6
-7
-3
-1
-8
-3
-7
-7
-5
-5
-6
-6
-5
-8
-8
-1
-6
-8
-8
-3
-3
-3
-2
-0
-1
-8
-8
-8
-0
-0
-9
-9
-3
-3
-5
-8
-3
-0
-0
-4
-2
-3
-3
-7
-3
-0
-5
-8
-8
-9
-8
-5
-4
-8
-3
-0
-8
-7
-8
-3
-9
-2
-8
-4
-7
-8
-3
-7
-8
-8
-8
-8
-3
-6
-3
-3
-8
-1
-9
-9
-4
-6
-8
-0
-0
-0
-8
-8
-9
-2
-8
-8
-8
-7
-8
-3
-1
-7
-0
-1
-5
-8
-3
-3
-3
-8
-9
-3
-8
diff --git a/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp b/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
deleted file mode 100644
index c41d0443a9..0000000000
--- a/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
+++ /dev/null
@@ -1,42 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        // Coverity fix: The following code may throw an exception of type std::length_error.
-        std::vector<ImageSet> imageSet =
-        {
-            {"shark.jpg", 3694}
-        };
-
-        using DataType = float;
-        using DatabaseType = CaffePreprocessor;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                    argc, argv, "Inception-BN-batchsize1.caffemodel", true,
-                    "data", "softmax", { 0 },
-                    [&imageSet](const char* dataDir, const ModelType&) {
-                        return DatabaseType(dataDir, 224, 224, imageSet);
-                    });
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeInception_BN-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeInception_BN-Armnn/Validation.txt b/tests/CaffeInception_BN-Armnn/Validation.txt
deleted file mode 100644
index f6040137d8..0000000000
--- a/tests/CaffeInception_BN-Armnn/Validation.txt
+++ /dev/null
@@ -1,1000 +0,0 @@
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
-3694
diff --git a/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp b/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
deleted file mode 100644
index c79cb78703..0000000000
--- a/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
+++ /dev/null
@@ -1,36 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../MnistDatabase.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        using DataType = float;
-        using DatabaseType = MnistDatabase;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                    argc, argv, "lenet_iter_9000.caffemodel", true, "data", "prob",
-                    { 0, 1, 5, 8, 9 },
-                    [](const char* dataDir, const ModelType&) {
-                        return DatabaseType(dataDir);
-                    });
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeMnist-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeMnist-Armnn/Validation.txt b/tests/CaffeMnist-Armnn/Validation.txt
deleted file mode 100644
index 63cbca6c56..0000000000
--- a/tests/CaffeMnist-Armnn/Validation.txt
+++ /dev/null
@@ -1,1000 +0,0 @@
-7
-2
-1
-0
-4
-1
-4
-9
-5
-9
-0
-6
-9
-0
-1
-5
-9
-7
-3
-4
-9
-6
-6
-5
-4
-0
-7
-4
-0
-1
-3
-1
-3
-4
-7
-2
-7
-1
-2
-1
-1
-7
-4
-2
-3
-5
-1
-2
-4
-4
-6
-3
-5
-5
-6
-0
-4
-1
-9
-5
-7
-8
-9
-3
-7
-4
-6
-4
-3
-0
-7
-0
-2
-9
-1
-7
-3
-2
-9
-7
-7
-6
-2
-7
-8
-4
-7
-3
-6
-1
-3
-6
-9
-3
-1
-4
-1
-7
-6
-9
-6
-0
-5
-4
-9
-9
-2
-1
-9
-4
-8
-7
-3
-9
-7
-9
-4
-4
-9
-2
-5
-4
-7
-6
-7
-9
-0
-5
-8
-5
-6
-6
-5
-7
-8
-1
-0
-1
-6
-4
-6
-7
-3
-1
-7
-1
-8
-2
-0
-2
-9
-9
-5
-5
-1
-5
-6
-0
-3
-4
-4
-6
-5
-4
-6
-5
-4
-5
-1
-4
-4
-7
-2
-3
-2
-7
-1
-8
-1
-8
-1
-8
-5
-0
-8
-9
-2
-5
-0
-1
-1
-1
-0
-9
-0
-3
-1
-6
-4
-2
-3
-6
-1
-1
-1
-3
-9
-5
-2
-9
-4
-5
-9
-3
-9
-0
-3
-6
-5
-5
-7
-2
-2
-7
-1
-2
-8
-4
-1
-7
-3
-3
-8
-8
-7
-9
-2
-2
-4
-1
-5
-9
-8
-7
-2
-3
-0
-4
-4
-2
-4
-1
-9
-5
-7
-7
-2
-8
-2
-6
-8
-5
-7
-7
-9
-1
-8
-1
-8
-0
-3
-0
-1
-9
-9
-4
-1
-8
-2
-1
-2
-9
-7
-5
-9
-2
-6
-4
-1
-5
-8
-2
-9
-2
-0
-4
-0
-0
-2
-8
-4
-7
-1
-2
-4
-0
-2
-7
-4
-3
-3
-0
-0
-3
-1
-9
-6
-5
-2
-5
-9
-2
-9
-3
-0
-4
-2
-0
-7
-1
-1
-2
-1
-5
-3
-3
-9
-7
-8
-6
-3
-6
-1
-3
-8
-1
-0
-5
-1
-3
-1
-5
-5
-6
-1
-8
-5
-1
-7
-9
-4
-6
-2
-2
-5
-0
-6
-5
-6
-3
-7
-2
-0
-8
-8
-5
-4
-1
-1
-4
-0
-3
-3
-7
-6
-1
-6
-2
-1
-9
-2
-8
-6
-1
-9
-5
-2
-5
-4
-4
-2
-8
-3
-8
-2
-4
-5
-0
-3
-1
-7
-7
-5
-7
-9
-7
-1
-9
-2
-1
-4
-2
-9
-2
-0
-4
-9
-1
-4
-8
-1
-8
-4
-5
-9
-8
-8
-3
-7
-6
-0
-0
-3
-0
-2
-0
-6
-4
-9
-5
-3
-3
-2
-3
-9
-1
-2
-6
-8
-0
-5
-6
-6
-6
-3
-8
-8
-2
-7
-5
-8
-9
-6
-1
-8
-4
-1
-2
-5
-9
-1
-9
-7
-5
-4
-0
-8
-9
-9
-1
-0
-5
-2
-3
-7
-8
-9
-4
-0
-6
-3
-9
-5
-2
-1
-3
-1
-3
-6
-5
-7
-4
-2
-2
-6
-3
-2
-6
-5
-4
-8
-9
-7
-1
-3
-0
-3
-8
-3
-1
-9
-3
-4
-4
-6
-4
-2
-1
-8
-2
-5
-4
-8
-8
-4
-0
-0
-2
-3
-2
-7
-3
-0
-8
-7
-4
-4
-7
-9
-6
-9
-0
-9
-8
-0
-4
-6
-0
-6
-3
-5
-4
-8
-3
-3
-9
-3
-3
-3
-7
-8
-0
-2
-2
-1
-7
-0
-6
-5
-4
-3
-8
-0
-9
-6
-3
-8
-0
-9
-9
-6
-8
-6
-8
-5
-7
-8
-6
-0
-2
-4
-0
-2
-2
-3
-1
-9
-7
-5
-8
-0
-8
-4
-6
-2
-6
-7
-9
-3
-2
-9
-8
-2
-2
-9
-2
-7
-3
-5
-9
-1
-8
-0
-2
-0
-5
-2
-1
-3
-7
-6
-7
-1
-2
-5
-8
-0
-3
-7
-1
-4
-0
-9
-1
-8
-6
-7
-7
-4
-3
-4
-9
-1
-9
-5
-1
-7
-3
-9
-7
-6
-9
-1
-3
-3
-8
-3
-3
-6
-7
-2
-8
-5
-8
-5
-1
-1
-4
-4
-3
-1
-0
-7
-7
-0
-7
-9
-4
-4
-8
-5
-5
-4
-0
-8
-2
-7
-0
-8
-4
-8
-0
-4
-0
-6
-1
-7
-3
-2
-6
-7
-2
-6
-9
-3
-1
-4
-6
-2
-5
-4
-2
-0
-6
-2
-1
-7
-3
-4
-1
-0
-5
-4
-3
-1
-1
-7
-4
-9
-9
-4
-8
-4
-0
-2
-4
-5
-1
-1
-6
-4
-7
-1
-9
-4
-2
-4
-1
-5
-5
-3
-8
-3
-1
-4
-5
-6
-8
-9
-4
-1
-5
-3
-8
-0
-3
-2
-5
-1
-2
-8
-3
-4
-4
-0
-8
-8
-3
-3
-1
-7
-3
-5
-9
-6
-3
-2
-6
-1
-3
-6
-0
-7
-2
-1
-7
-1
-4
-2
-4
-2
-1
-7
-9
-6
-1
-1
-2
-4
-8
-1
-7
-7
-4
-8
-0
-9
-3
-1
-3
-1
-0
-7
-7
-0
-3
-5
-5
-2
-7
-6
-6
-9
-2
-8
-3
-5
-2
-2
-5
-6
-0
-8
-2
-9
-2
-8
-8
-8
-8
-7
-4
-9
-3
-0
-6
-6
-3
-2
-1
-3
-2
-2
-9
-3
-0
-0
-5
-7
-8
-3
-4
-4
-6
-0
-2
-9
-1
-4
-7
-4
-7
-3
-9
-8
-8
-4
-7
-1
-2
-1
-2
-2
-3
-2
-3
-2
-3
-9
-1
-7
-4
-0
-3
-5
-5
-8
-6
-3
-2
-6
-7
-6
-6
-3
-2
-7
-9
-1
-1
-7
-5
-6
-4
-9
-5
-1
-3
-3
-4
-7
-8
-9
-1
-1
-6
-9
-1
-4
-4
-5
-4
-0
-6
-2
-2
-3
-1
-5
-1
-2
-0
-3
-8
-1
-2
-6
-7
-1
-6
-2
-3
-9
-0
-1
-2
-2
-0
-8
-9
diff --git a/tests/CaffePreprocessor.cpp b/tests/CaffePreprocessor.cpp
deleted file mode 100644
index 54ce833b72..0000000000
--- a/tests/CaffePreprocessor.cpp
+++ /dev/null
@@ -1,44 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "InferenceTestImage.hpp"
-#include "CaffePreprocessor.hpp"
-
-#include <armnn/utility/NumericCast.hpp>
-
-#include <iostream>
-#include <fcntl.h>
-#include <array>
-
-const std::vector<ImageSet> g_DefaultImageSet =
-{
-    {"shark.jpg", 2}
-};
-
-CaffePreprocessor::CaffePreprocessor(const std::string& binaryFileDirectory, unsigned int width, unsigned int height,
-                                   const std::vector<ImageSet>& imageSet)
-:   m_BinaryDirectory(binaryFileDirectory)
-,   m_Height(height)
-,   m_Width(width)
-,   m_ImageSet(imageSet.empty() ? g_DefaultImageSet : imageSet)
-{
-}
-
-std::unique_ptr<CaffePreprocessor::TTestCaseData> CaffePreprocessor::GetTestCaseData(unsigned int testCaseId)
-{
-    testCaseId = testCaseId % armnn::numeric_cast<unsigned int>(m_ImageSet.size());
-    const ImageSet& imageSet = m_ImageSet[testCaseId];
-    const std::string fullPath = m_BinaryDirectory + imageSet.first;
-
-    InferenceTestImage image(fullPath.c_str());
-    image.Resize(m_Width, m_Height, CHECK_LOCATION());
-
-    // The model expects image data in BGR format.
-    std::vector<float> inputImageData = GetImageDataInArmNnLayoutAsFloatsSubtractingMean(ImageChannelLayout::Bgr,
-                                                                                         image, m_MeanBgr);
-
-    // List of labels: https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
-    const unsigned int label = imageSet.second;
-    return std::make_unique<TTestCaseData>(label, std::move(inputImageData));
-}
diff --git a/tests/CaffePreprocessor.hpp b/tests/CaffePreprocessor.hpp
deleted file mode 100644
index a57382e618..0000000000
--- a/tests/CaffePreprocessor.hpp
+++ /dev/null
@@ -1,40 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#pragma once
-
-#include "ClassifierTestCaseData.hpp"
-
-#include <array>
-#include <string>
-#include <vector>
-#include <memory>
-
-/// Caffe requires BGR images, not normalized, mean adjusted and  resized using smooth resize of STB library
-
-using ImageSet = std::pair<const std::string, unsigned int>;
-
-class CaffePreprocessor
-{
-public:
-    using DataType = float;
-    using TTestCaseData = ClassifierTestCaseData<DataType>;
-
-    explicit CaffePreprocessor(const std::string& binaryFileDirectory,
-        unsigned int width = 227,
-        unsigned int height = 227,
-        const std::vector<ImageSet>& imageSet = std::vector<ImageSet>());
-    std::unique_ptr<TTestCaseData> GetTestCaseData(unsigned int testCaseId);
-
-private:
-    unsigned int GetNumImageElements() const { return 3 * m_Width * m_Height; }
-    unsigned int GetNumImageBytes() const { return 4 * GetNumImageElements(); }
-
-    std::string m_BinaryDirectory;
-    unsigned int m_Height;
-    unsigned int m_Width;
-    // Mean value of the database [B, G, R].
-    const std::array<float, 3> m_MeanBgr = {{104.007965f, 116.669472f, 122.675102f}};
-    const std::vector<ImageSet> m_ImageSet;
-};
diff --git a/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp b/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
deleted file mode 100644
index aa814ff44b..0000000000
--- a/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
+++ /dev/null
@@ -1,45 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        // Coverity fix: The following code may throw an exception of type std::length_error.
-        std::vector<ImageSet> imageSet =
-        {
-            {"ILSVRC2012_val_00000018.JPEG",  21 },
-            {"shark.jpg", 2}
-        };
-
-        armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
-
-        using DataType = float;
-        using DatabaseType = CaffePreprocessor;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                    argc, argv, "ResNet_50_ilsvrc15_model.caffemodel", true,
-                    "data", "prob", { 0, 1 },
-                    [&imageSet](const char* dataDir, const ModelType&) {
-                        return DatabaseType(dataDir, 224, 224, imageSet);
-                    }, &inputTensorShape);
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeResNet-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeResNet-Armnn/Validation.txt b/tests/CaffeResNet-Armnn/Validation.txt
deleted file mode 100644
index b3c5de80b7..0000000000
--- a/tests/CaffeResNet-Armnn/Validation.txt
+++ /dev/null
@@ -1,2000 +0,0 @@
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
-21
-2
diff --git a/tests/CaffeSqueezeNet1_0-Armnn/CaffeSqueezeNet1_0-Armnn.cpp b/tests/CaffeSqueezeNet1_0-Armnn/CaffeSqueezeNet1_0-Armnn.cpp
deleted file mode 100644
index c19abefef8..0000000000
--- a/tests/CaffeSqueezeNet1_0-Armnn/CaffeSqueezeNet1_0-Armnn.cpp
+++ /dev/null
@@ -1,20 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    using DataType = float;
-    using DatabaseType = CaffePreprocessor;
-    using ParserType = armnnCaffeParser::ICaffeParser;
-    using ModelType = InferenceModel<ParserType, DataType>;
-
-    return armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-        argc, argv, "squeezenet.caffemodel", true,
-        "input", "prob", { 0 },
-        [](const char* dataDir, const ModelType &) { return CaffePreprocessor(dataDir); });
-}
diff --git a/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp b/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
deleted file mode 100644
index 733cc29b27..0000000000
--- a/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
+++ /dev/null
@@ -1,37 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-
-int main(int argc, char* argv[])
-{
-    armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        using DataType = float;
-        using DatabaseType = CaffePreprocessor;
-        using ParserType = armnnCaffeParser::ICaffeParser;
-        using ModelType = InferenceModel<ParserType, DataType>;
-
-        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
-        retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
-                    argc, argv, "VGG_CNN_S.caffemodel", true,
-                    "input", "prob", { 0 },
-                    [](const char* dataDir, const ModelType&) {
-                        return DatabaseType(dataDir, 224, 224);
-                    }, &inputTensorShape);
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeVGG-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/CaffeVGG-Armnn/Validation.txt b/tests/CaffeVGG-Armnn/Validation.txt
deleted file mode 100644
index cb95f050e2..0000000000
--- a/tests/CaffeVGG-Armnn/Validation.txt
+++ /dev/null
@@ -1,1000 +0,0 @@
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
diff --git a/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp b/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
deleted file mode 100644
index d563faaab2..0000000000
--- a/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
+++ /dev/null
@@ -1,58 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "../YoloInferenceTest.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#include "armnn/TypesUtils.hpp"
-
-int main(int argc, char* argv[])
-{
-    armnn::TensorShape inputTensorShape{ { 1, 3, YoloImageHeight, YoloImageWidth } };
-
-    using YoloInferenceModel = InferenceModel<armnnCaffeParser::ICaffeParser,
-        float>;
-
-    int retVal = EXIT_FAILURE;
-    try
-    {
-        // Coverity fix: InferenceTestMain() may throw uncaught exceptions.
-        retVal = InferenceTestMain(argc, argv, { 0 },
-            [&inputTensorShape]()
-            {
-                return make_unique<YoloTestCaseProvider<YoloInferenceModel>>(
-                    [&]
-                    (const InferenceTestOptions &commonOptions,
-                     typename YoloInferenceModel::CommandLineOptions modelOptions)
-                    {
-                        if (!ValidateDirectory(modelOptions.m_ModelDir))
-                        {
-                            return std::unique_ptr<YoloInferenceModel>();
-                        }
-
-                        typename YoloInferenceModel::Params modelParams;
-                        modelParams.m_ModelPath = modelOptions.m_ModelDir + "yolov1_tiny_voc2007_model.caffemodel";
-                        modelParams.m_InputBindings = { "data" };
-                        modelParams.m_OutputBindings = { "fc12" };
-                        modelParams.m_InputShapes = { inputTensorShape };
-                        modelParams.m_IsModelBinary = true;
-                        modelParams.m_ComputeDevices = modelOptions.GetComputeDevicesAsBackendIds();
-                        modelParams.m_VisualizePostOptimizationModel = modelOptions.m_VisualizePostOptimizationModel;
-                        modelParams.m_EnableFp16TurboMode = modelOptions.m_EnableFp16TurboMode;
-
-                        return std::make_unique<YoloInferenceModel>(modelParams,
-                                                                    commonOptions.m_EnableProfiling,
-                                                                    commonOptions.m_DynamicBackendsPath);
-                });
-            });
-    }
-    catch (const std::exception& e)
-    {
-        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
-        // exception of type std::length_error.
-        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
-        std::cerr << "WARNING: CaffeYolo-Armnn: An error has occurred when running "
-                     "the classifier inference tests: " << e.what() << std::endl;
-    }
-    return retVal;
-}
diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp
index f812e53e04..8ab286b16b 100644
--- a/tests/ExecuteNetwork/ExecuteNetwork.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp
@@ -13,9 +13,6 @@
 #if defined(ARMNN_SERIALIZER)
 #include "armnnDeserializer/IDeserializer.hpp"
 #endif
-#if defined(ARMNN_CAFFE_PARSER)
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#endif
 #if defined(ARMNN_TF_PARSER)
 #include "armnnTfParser/ITfParser.hpp"
 #endif
@@ -472,15 +469,6 @@ int main(int argc, const char* argv[])
         return EXIT_FAILURE;
     #endif
     }
-    else if (modelFormat.find("caffe") != std::string::npos)
-    {
-    #if defined(ARMNN_CAFFE_PARSER)
-        return MainImpl<armnnCaffeParser::ICaffeParser, float>(ProgramOptions.m_ExNetParams, runtime);
-    #else
-        ARMNN_LOG(fatal) << "Not built with Caffe parser support.";
-        return EXIT_FAILURE;
-    #endif
-    }
     else if (modelFormat.find("onnx") != std::string::npos)
     {
     #if defined(ARMNN_ONNX_PARSER)
@@ -526,7 +514,7 @@ int main(int argc, const char* argv[])
     else
     {
         ARMNN_LOG(fatal) << "Unknown model format: '" << modelFormat
-                         << "'. Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'";
+                         << "'. Please include 'tensorflow', 'tflite' or 'onnx'";
         return EXIT_FAILURE;
     }
 }
diff --git a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
index 890ab2a658..4e3b5e313d 100644
--- a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
@@ -41,14 +41,6 @@ void CheckModelFormat(const std::string& modelFormat)
                                               "built with serialization support.");
 #endif
     }
-    else if (modelFormat.find("caffe") != std::string::npos)
-    {
-#if defined(ARMNN_CAFFE_PARSER)
-#else
-        throw armnn::InvalidArgumentException("Can't run model in caffe format without a "
-                                              "built with Caffe parser support.");
-#endif
-    }
     else if (modelFormat.find("onnx") != std::string::npos)
     {
 #if defined(ARMNN_ONNX_PARSER)
@@ -83,7 +75,7 @@ void CheckModelFormat(const std::string& modelFormat)
     else
     {
         throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. "
-                                                          "Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'",
+                                                          "Please include 'tensorflow', 'tflite' or 'onnx'",
                                                           modelFormat));
     }
 }
diff --git a/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp b/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
index b52adaa325..7c1db61841 100644
--- a/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
@@ -173,12 +173,12 @@ ProgramOptions::ProgramOptions() : m_CxxOptions{"ExecuteNetwork",
                  cxxopts::value<std::vector<std::string>>())
 
                 ("f,model-format",
-                 "armnn-binary, caffe-binary, caffe-text, onnx-binary, onnx-text, tflite-binary, tensorflow-binary or "
+                 "armnn-binary, onnx-binary, onnx-text, tflite-binary, tensorflow-binary or "
                  "tensorflow-text.",
                  cxxopts::value<std::string>())
 
                 ("m,model-path",
-                 "Path to model file, e.g. .armnn, .caffemodel, .prototxt, .tflite, .onnx",
+                 "Path to model file, e.g. .armnn, , .prototxt, .tflite, .onnx",
                  cxxopts::value<std::string>(m_ExNetParams.m_ModelPath))
 
                 ("i,input-name",
diff --git a/tests/ImageTensorGenerator/ImageTensorGenerator.cpp b/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
index 754d980423..34dbe1e352 100644
--- a/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
+++ b/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
@@ -164,7 +164,7 @@ public:
                 ("f,model-format",
                     "Format of the intended model file that uses the images."
                     "Different formats have different image normalization styles."
-                    "Accepted values (caffe, tensorflow, tflite)",
+                    "Accepted values (tensorflow, tflite)",
                     cxxopts::value<std::string>(m_ModelFormat))
                 ("o,outfile",
                     "Output raw tensor file path",
@@ -235,11 +235,7 @@ public:
     unsigned int GetNewHeight() {return static_cast<unsigned int>(std::stoi(m_NewHeight));}
     SupportedFrontend GetModelFormat()
     {
-        if (m_ModelFormat == "caffe")
-        {
-            return SupportedFrontend::Caffe;
-        }
-        else if (m_ModelFormat == "tensorflow")
+        if (m_ModelFormat == "tensorflow")
         {
             return SupportedFrontend::TensorFlow;
         }
diff --git a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp b/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
index 4793f822fb..f2ee470a7a 100644
--- a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
+++ b/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
@@ -24,14 +24,13 @@ struct NormalizationParameters
 
 enum class SupportedFrontend
 {
-    Caffe      = 0,
-    TensorFlow = 1,
-    TFLite     = 2,
+    TensorFlow = 0,
+    TFLite     = 1,
 };
 
 /** Get normalization parameters.
  * Note that different flavours of models and different model data types have different normalization methods.
- * This tool currently only supports Caffe, TF and TFLite models
+ * This tool currently only supports TF and TFLite models
  *
  * @param[in] modelFormat   One of the supported frontends
  * @param[in] outputType    Output type of the image tensor, also the type of the intended model
@@ -46,8 +45,6 @@ NormalizationParameters GetNormalizationParameters(const SupportedFrontend& mode
     normParams.stddev = { 1.0, 1.0, 1.0 };
     switch (modelFormat)
     {
-        case SupportedFrontend::Caffe:
-            break;
         case SupportedFrontend::TensorFlow:
         case SupportedFrontend::TFLite:
         default:
diff --git a/tests/InferenceModel.hpp b/tests/InferenceModel.hpp
index dca3ab2788..cab594ed48 100644
--- a/tests/InferenceModel.hpp
+++ b/tests/InferenceModel.hpp
@@ -367,7 +367,7 @@ public:
         options
             .allow_unrecognised_options()
             .add_options()
-                ("m,model-dir", "Path to directory containing model files (.caffemodel/.prototxt/.tflite)",
+                ("m,model-dir", "Path to directory containing model files (.prototxt/.tflite)",
                  cxxopts::value<std::string>(cLineOptions.m_ModelDir))
                 ("c,compute", backendsMessage.c_str(),
                  cxxopts::value<std::vector<std::string>>(cLineOptions.m_ComputeDevices)->default_value("CpuRef"))
diff --git a/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
index f8337a5286..345a0fed98 100644
--- a/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
+++ b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
@@ -76,7 +76,7 @@ int main(int argc, char* argv[])
                     "Path to armnn format model file",
                     cxxopts::value<std::string>(modelPath))
                 ("f,model-format",
-                    "The model format. Supported values: caffe, tensorflow, tflite",
+                    "The model format. Supported values: tensorflow, tflite",
                     cxxopts::value<std::string>(modelFormat))
                 ("i,input-name",
                     "Identifier of the input tensors in the network separated by comma with no space.",
@@ -312,11 +312,7 @@ int main(int argc, char* argv[])
             const unsigned int batchSize = 1;
             // Get normalisation parameters
             SupportedFrontend modelFrontend;
-            if (modelFormat == "caffe")
-            {
-                modelFrontend = SupportedFrontend::Caffe;
-            }
-            else if (modelFormat == "tensorflow")
+            if (modelFormat == "tensorflow")
             {
                 modelFrontend = SupportedFrontend::TensorFlow;
             }
diff --git a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
index 456ff68e7c..9c51d3f0a7 100644
--- a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
+++ b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
@@ -6,7 +6,7 @@
 #include "armnn/ArmNN.hpp"
 #include "armnn/Utils.hpp"
 #include "armnn/INetwork.hpp"
-#include "armnnCaffeParser/ICaffeParser.hpp"
+#include "armnnTfParser/TfParser.hpp"
 #include "../Cifar10Database.hpp"
 #include "../InferenceTest.hpp"
 #include "../InferenceModel.hpp"
@@ -89,7 +89,7 @@ int main(int argc, char* argv[])
             return EXIT_FAILURE;
         }
 
-        fs::path modelPath = fs::path(modelDir + "/cifar10_full_iter_60000.caffemodel");
+        fs::path modelPath = fs::path(modelDir + "/cifar10_tf.prototxt");
 
         // Create runtime
         // This will also load dynamic backend in case that the dynamic backend path is specified
@@ -123,7 +123,7 @@ int main(int argc, char* argv[])
         };
         std::vector<Net> networks;
 
-        armnnCaffeParser::ICaffeParserPtr parser(armnnCaffeParser::ICaffeParser::Create());
+        armnnTfParser::ITfParserPtr parser(armnnTfParser::ITfParser::Create());
 
         const int networksCount = 4;
         for (int i = 0; i < networksCount; ++i)
diff --git a/tests/NetworkExecutionUtils/NetworkExecutionUtils.cpp b/tests/NetworkExecutionUtils/NetworkExecutionUtils.cpp
index d902d23d86..74c878304d 100644
--- a/tests/NetworkExecutionUtils/NetworkExecutionUtils.cpp
+++ b/tests/NetworkExecutionUtils/NetworkExecutionUtils.cpp
@@ -12,9 +12,6 @@
 #if defined(ARMNN_SERIALIZER)
 #include "armnnDeserializer/IDeserializer.hpp"
 #endif
-#if defined(ARMNN_CAFFE_PARSER)
-#include "armnnCaffeParser/ICaffeParser.hpp"
-#endif
 #if defined(ARMNN_TF_PARSER)
 #include "armnnTfParser/ITfParser.hpp"
 #endif
diff --git a/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp b/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
index c152c0f6c2..bec2771d4b 100644
--- a/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
+++ b/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
@@ -3,7 +3,7 @@
 // SPDX-License-Identifier: MIT
 //
 #include "../InferenceTest.hpp"
-#include "../CaffePreprocessor.hpp"
+#include "../ImagePreprocessor.hpp"
 #include "armnnTfParser/ITfParser.hpp"
 
 int main(int argc, char* argv[])
@@ -21,7 +21,7 @@ int main(int argc, char* argv[])
         armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
 
         using DataType = float;
-        using DatabaseType = CaffePreprocessor;
+        using DatabaseType = ImagePreprocessor<DataType>;;
         using ParserType = armnnTfParser::ITfParser;
         using ModelType = InferenceModel<ParserType, DataType>;