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, 189 deletions

diff --git a/delegate/src/test/ElementwiseUnaryTestHelper.hpp b/delegate/src/test/ElementwiseUnaryTestHelper.hpp
deleted file mode 100644
index 230d0fcca5..0000000000
--- a/delegate/src/test/ElementwiseUnaryTestHelper.hpp
+++ /dev/null
@@ -1,189 +0,0 @@
-//
-// Copyright © 2020, 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> CreateElementwiseUnaryTfLiteModel(tflite::BuiltinOperator unaryOperatorCode,
-                                                    tflite::TensorType tensorType,
-                                                    const std::vector <int32_t>& tensorShape)
-{
-    using namespace tflite;
-    flatbuffers::FlatBufferBuilder flatBufferBuilder;
-
-    std::array<flatbuffers::Offset<tflite::Buffer>, 1> buffers;
-    buffers[0] = CreateBuffer(flatBufferBuilder);
-
-    std::array<flatbuffers::Offset<Tensor>, 2> tensors;
-    tensors[0] = CreateTensor(flatBufferBuilder,
-                              flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
-                              tensorType);
-    tensors[1] = CreateTensor(flatBufferBuilder,
-                              flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
-                              tensorType);
-
-    // create operator
-    const std::vector<int> operatorInputs{0};
-    const std::vector<int> operatorOutputs{1};
-    flatbuffers::Offset <Operator> unaryOperator =
-        CreateOperator(flatBufferBuilder,
-                       0,
-                       flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
-                       flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
-
-    const std::vector<int> subgraphInputs{0};
-    const std::vector<int> 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(&unaryOperator, 1));
-
-    flatbuffers::Offset <flatbuffers::String> modelDescription =
-        flatBufferBuilder.CreateString("ArmnnDelegate: Elementwise Unary Operator Model");
-    flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, unaryOperatorCode);
-
-    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());
-}
-
-void ElementwiseUnaryFP32Test(tflite::BuiltinOperator unaryOperatorCode,
-                              std::vector<armnn::BackendId>& backends,
-                              std::vector<float>& inputValues,
-                              std::vector<float>& expectedOutputValues)
-{
-    using namespace tflite;
-    std::vector<int32_t> inputShape  { { 3, 1, 2} };
-    std::vector<char> modelBuffer = CreateElementwiseUnaryTfLiteModel(unaryOperatorCode,
-                                                                      ::tflite::TensorType_FLOAT32,
-                                                                      inputShape);
-
-    const Model* tfLiteModel = GetModel(modelBuffer.data());
-    // Create TfLite Interpreters
-    std::unique_ptr<Interpreter> armnnDelegateInterpreter;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-              (&armnnDelegateInterpreter) == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter != nullptr);
-    CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
-
-    std::unique_ptr<Interpreter> tfLiteInterpreter;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-              (&tfLiteInterpreter) == kTfLiteOk);
-    CHECK(tfLiteInterpreter != nullptr);
-    CHECK(tfLiteInterpreter->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(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
-
-    // Set input data
-    armnnDelegate::FillInput(armnnDelegateInterpreter, 0, inputValues);
-    armnnDelegate::FillInput(tfLiteInterpreter, 0, inputValues);
-
-    // Run EnqueWorkload
-    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data
-    armnnDelegate::CompareOutputData(tfLiteInterpreter, armnnDelegateInterpreter, inputShape, expectedOutputValues);
-
-    armnnDelegateInterpreter.reset(nullptr);
-    tfLiteInterpreter.reset(nullptr);
-}
-
-void ElementwiseUnaryBoolTest(tflite::BuiltinOperator unaryOperatorCode,
-                              std::vector<armnn::BackendId>& backends,
-                              std::vector<int32_t>& inputShape,
-                              std::vector<bool>& inputValues,
-                              std::vector<bool>& expectedOutputValues)
-{
-    using namespace tflite;
-    std::vector<char> modelBuffer = CreateElementwiseUnaryTfLiteModel(unaryOperatorCode,
-                                                                      ::tflite::TensorType_BOOL,
-                                                                      inputShape);
-
-    const Model* tfLiteModel = GetModel(modelBuffer.data());
-    // Create TfLite Interpreters
-    std::unique_ptr<Interpreter> armnnDelegateInterpreter;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-                  (&armnnDelegateInterpreter) == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter != nullptr);
-    CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
-
-    std::unique_ptr<Interpreter> tfLiteInterpreter;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-                  (&tfLiteInterpreter) == kTfLiteOk);
-    CHECK(tfLiteInterpreter != nullptr);
-    CHECK(tfLiteInterpreter->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(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
-
-    // Set input data
-    armnnDelegate::FillInput(armnnDelegateInterpreter, 0, inputValues);
-    armnnDelegate::FillInput(tfLiteInterpreter, 0, inputValues);
-
-    // Run EnqueWorkload
-    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data, comparing Boolean values is handled differently and needs to call the CompareData function
-    // directly instead. This is because Boolean types get converted to a bit representation in a vector.
-    auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
-    auto tfLiteDelegateOutputData = tfLiteInterpreter->typed_tensor<bool>(tfLiteDelegateOutputId);
-    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
-    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<bool>(armnnDelegateOutputId);
-
-    armnnDelegate::CompareData(expectedOutputValues, armnnDelegateOutputData, expectedOutputValues.size());
-    armnnDelegate::CompareData(expectedOutputValues, tfLiteDelegateOutputData, expectedOutputValues.size());
-    armnnDelegate::CompareData(tfLiteDelegateOutputData, armnnDelegateOutputData, expectedOutputValues.size());
-
-    armnnDelegateInterpreter.reset(nullptr);
-    tfLiteInterpreter.reset(nullptr);
-}
-
-} // anonymous namespace
-
-
-
-