IVGCVSW-7555 Restructure Delegate

* New folders created:
  * common is for common code where TfLite API is not used
  * classic is for existing delegate implementations
  * opaque is for new opaque delegate implementation,
  * tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed

1 files changed, 0 insertions, 159 deletions

diff --git a/delegate/src/test/CastTestHelper.hpp b/delegate/src/test/CastTestHelper.hpp
deleted file mode 100644
index 0448e65856..0000000000
--- a/delegate/src/test/CastTestHelper.hpp
+++ /dev/null
@@ -1,159 +0,0 @@
-//
-// Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include "TestUtils.hpp"
-
-#include <armnn_delegate.hpp>
-
-#include <flatbuffers/flatbuffers.h>
-#include <tensorflow/lite/interpreter.h>
-#include <tensorflow/lite/kernels/register.h>
-#include <tensorflow/lite/model.h>
-#include <tensorflow/lite/schema/schema_generated.h>
-#include <tensorflow/lite/version.h>
-
-#include <doctest/doctest.h>
-
-namespace
-{
-std::vector<char> CreateCastTfLiteModel(tflite::TensorType inputTensorType,
-                                        tflite::TensorType outputTensorType,
-                                        const std::vector <int32_t>& tensorShape,
-                                        float quantScale = 1.0f,
-                                        int quantOffset = 0)
-{
-    using namespace tflite;
-    flatbuffers::FlatBufferBuilder flatBufferBuilder;
-
-    std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
-    buffers.push_back(CreateBuffer(flatBufferBuilder));
-    buffers.push_back(CreateBuffer(flatBufferBuilder));
-    buffers.push_back(CreateBuffer(flatBufferBuilder));
-
-    auto quantizationParameters =
-        CreateQuantizationParameters(flatBufferBuilder,
-                                     0,
-                                     0,
-                                     flatBufferBuilder.CreateVector<float>({quantScale}),
-                                     flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
-
-    std::array<flatbuffers::Offset<Tensor>, 2> tensors;
-    tensors[0] = CreateTensor(flatBufferBuilder,
-                              flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(),
-                                                                      tensorShape.size()),
-                              inputTensorType,
-                              1,
-                              flatBufferBuilder.CreateString("input"),
-                              quantizationParameters);
-    tensors[1] = CreateTensor(flatBufferBuilder,
-                              flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(),
-                                                                      tensorShape.size()),
-                              outputTensorType,
-                              2,
-                              flatBufferBuilder.CreateString("output"),
-                              quantizationParameters);
-
-    const std::vector<int32_t> operatorInputs({0});
-    const std::vector<int32_t> operatorOutputs({1});
-
-    flatbuffers::Offset<Operator> castOperator =
-        CreateOperator(flatBufferBuilder,
-                       0,
-                       flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
-                       flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
-                       BuiltinOptions_CastOptions,
-                       CreateCastOptions(flatBufferBuilder).Union());
-
-    flatbuffers::Offset<flatbuffers::String> modelDescription =
-        flatBufferBuilder.CreateString("ArmnnDelegate: CAST Operator Model");
-    flatbuffers::Offset<OperatorCode> operatorCode =
-        CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_CAST);
-
-    const std::vector<int32_t> subgraphInputs({0});
-    const std::vector<int32_t> subgraphOutputs({1});
-    flatbuffers::Offset<SubGraph> subgraph =
-        CreateSubGraph(flatBufferBuilder,
-                       flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
-                       flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
-                       flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
-                       flatBufferBuilder.CreateVector(&castOperator, 1));
-
-    flatbuffers::Offset<Model> flatbufferModel =
-        CreateModel(flatBufferBuilder,
-                    TFLITE_SCHEMA_VERSION,
-                    flatBufferBuilder.CreateVector(&operatorCode, 1),
-                    flatBufferBuilder.CreateVector(&subgraph, 1),
-                    modelDescription,
-                    flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
-
-    flatBufferBuilder.Finish(flatbufferModel);
-    return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
-                             flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
-}
-
-template<typename T, typename K>
-void CastTest(tflite::TensorType inputTensorType,
-              tflite::TensorType outputTensorType,
-              std::vector<armnn::BackendId>& backends,
-              std::vector<int32_t>& shape,
-              std::vector<T>& inputValues,
-              std::vector<K>& expectedOutputValues,
-              float quantScale = 1.0f,
-              int quantOffset = 0)
-{
-    using namespace tflite;
-    std::vector<char> modelBuffer = CreateCastTfLiteModel(inputTensorType,
-                                                          outputTensorType,
-                                                          shape,
-                                                          quantScale,
-                                                          quantOffset);
-
-    const Model* tfLiteModel = GetModel(modelBuffer.data());
-
-    // Create TfLite Interpreters
-    std::unique_ptr<Interpreter> armnnDelegate;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-              (&armnnDelegate) == kTfLiteOk);
-    CHECK(armnnDelegate != nullptr);
-    CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
-
-    std::unique_ptr<Interpreter> tfLiteDelegate;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-              (&tfLiteDelegate) == kTfLiteOk);
-    CHECK(tfLiteDelegate != nullptr);
-    CHECK(tfLiteDelegate->AllocateTensors() == kTfLiteOk);
-
-    // Create the ArmNN Delegate
-    armnnDelegate::DelegateOptions delegateOptions(backends);
-    std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
-        theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
-                         armnnDelegate::TfLiteArmnnDelegateDelete);
-    CHECK(theArmnnDelegate != nullptr);
-
-    // Modify armnnDelegateInterpreter to use armnnDelegate
-    CHECK(armnnDelegate->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
-
-    // Set input data
-    armnnDelegate::FillInput<T>(tfLiteDelegate, 0, inputValues);
-    armnnDelegate::FillInput<T>(armnnDelegate, 0, inputValues);
-
-    // Run EnqueWorkload
-    CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegate->Invoke() == kTfLiteOk);
-
-    // Compare output data
-    armnnDelegate::CompareOutputData<K>(tfLiteDelegate,
-                                        armnnDelegate,
-                                        shape,
-                                        expectedOutputValues,
-                                        0);
-
-    tfLiteDelegate.reset(nullptr);
-    armnnDelegate.reset(nullptr);
-}
-
-} // anonymous namespace