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Diffstat (limited to 'delegate/src/test/DelegateOptionsTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/DelegateOptionsTestHelper.hpp | 344 |
1 files changed, 0 insertions, 344 deletions
diff --git a/delegate/src/test/DelegateOptionsTestHelper.hpp b/delegate/src/test/DelegateOptionsTestHelper.hpp deleted file mode 100644 index 00a3d95904..0000000000 --- a/delegate/src/test/DelegateOptionsTestHelper.hpp +++ /dev/null @@ -1,344 +0,0 @@ -// -// Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#pragma once - -#include <armnn_delegate.hpp> - -#include "ConvolutionTestHelper.hpp" -#include "TestUtils.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 -{ - -struct StreamRedirector -{ -public: - StreamRedirector(std::ostream &stream, std::streambuf *newStreamBuffer) - : m_Stream(stream), m_BackupBuffer(m_Stream.rdbuf(newStreamBuffer)) {} - - ~StreamRedirector() { m_Stream.rdbuf(m_BackupBuffer); } - -private: - std::ostream &m_Stream; - std::streambuf *m_BackupBuffer; -}; - -std::vector<char> CreateAddDivTfLiteModel(tflite::TensorType tensorType, - 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)); - 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>, 5> tensors; - tensors[0] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 1, - flatBufferBuilder.CreateString("input_0"), - quantizationParameters); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 2, - flatBufferBuilder.CreateString("input_1"), - quantizationParameters); - tensors[2] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 3, - flatBufferBuilder.CreateString("input_2"), - quantizationParameters); - tensors[3] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 4, - flatBufferBuilder.CreateString("add"), - quantizationParameters); - tensors[4] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 5, - flatBufferBuilder.CreateString("output"), - quantizationParameters); - - // create operator - tflite::BuiltinOptions addBuiltinOptionsType = tflite::BuiltinOptions_AddOptions; - flatbuffers::Offset<void> addBuiltinOptions = - CreateAddOptions(flatBufferBuilder, ActivationFunctionType_NONE).Union(); - - tflite::BuiltinOptions divBuiltinOptionsType = tflite::BuiltinOptions_DivOptions; - flatbuffers::Offset<void> divBuiltinOptions = - CreateAddOptions(flatBufferBuilder, ActivationFunctionType_NONE).Union(); - - std::array<flatbuffers::Offset<Operator>, 2> operators; - const std::vector<int32_t> addInputs{0, 1}; - const std::vector<int32_t> addOutputs{3}; - operators[0] = CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(addInputs.data(), addInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(addOutputs.data(), addOutputs.size()), - addBuiltinOptionsType, - addBuiltinOptions); - const std::vector<int32_t> divInputs{3, 2}; - const std::vector<int32_t> divOutputs{4}; - operators[1] = CreateOperator(flatBufferBuilder, - 1, - flatBufferBuilder.CreateVector<int32_t>(divInputs.data(), divInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(divOutputs.data(), divOutputs.size()), - divBuiltinOptionsType, - divBuiltinOptions); - - const std::vector<int> subgraphInputs{0, 1, 2}; - const std::vector<int> subgraphOutputs{4}; - 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(operators.data(), operators.size())); - - flatbuffers::Offset<flatbuffers::String> modelDescription = - flatBufferBuilder.CreateString("ArmnnDelegate: Add and Div Operator Model"); - - std::array<flatbuffers::Offset<OperatorCode>, 2> codes; - codes[0] = CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_ADD); - codes[1] = CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_DIV); - - flatbuffers::Offset<Model> flatbufferModel = - CreateModel(flatBufferBuilder, - TFLITE_SCHEMA_VERSION, - flatBufferBuilder.CreateVector(codes.data(), codes.size()), - flatBufferBuilder.CreateVector(&subgraph, 1), - modelDescription, - flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); - - flatBufferBuilder.Finish(flatbufferModel); - - return std::vector<char>(flatBufferBuilder.GetBufferPointer(), - flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); -} - -std::vector<char> CreateCeilTfLiteModel(tflite::TensorType tensorType, - 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)); - - 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()), - tensorType, - 0, - flatBufferBuilder.CreateString("input"), - quantizationParameters); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 0, - flatBufferBuilder.CreateString("output"), - quantizationParameters); - - const std::vector<int32_t> operatorInputs({0}); - const std::vector<int32_t> operatorOutputs({1}); - - flatbuffers::Offset<Operator> ceilOperator = - CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), - BuiltinOptions_NONE); - - flatbuffers::Offset<flatbuffers::String> modelDescription = - flatBufferBuilder.CreateString("ArmnnDelegate: CEIL Operator Model"); - flatbuffers::Offset<OperatorCode> operatorCode = - CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_CEIL); - - 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(&ceilOperator, 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> -void DelegateOptionTest(tflite::TensorType tensorType, - const std::vector<armnn::BackendId>& backends, - std::vector<int32_t>& tensorShape, - std::vector<T>& input0Values, - std::vector<T>& input1Values, - std::vector<T>& input2Values, - std::vector<T>& expectedOutputValues, - const armnnDelegate::DelegateOptions& delegateOptions, - float quantScale = 1.0f, - int quantOffset = 0) -{ - using namespace tflite; - std::vector<char> modelBuffer = CreateAddDivTfLiteModel(tensorType, - tensorShape, - quantScale, - quantOffset); - - 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 - 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(tfLiteInterpreter, 0, input0Values); - armnnDelegate::FillInput(tfLiteInterpreter, 1, input1Values); - armnnDelegate::FillInput(tfLiteInterpreter, 2, input2Values); - - armnnDelegate::FillInput(armnnDelegateInterpreter, 0, input0Values); - armnnDelegate::FillInput(armnnDelegateInterpreter, 1, input1Values); - armnnDelegate::FillInput(armnnDelegateInterpreter, 2, input2Values); - - // Run EnqueueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, armnnDelegateInterpreter, tensorShape, expectedOutputValues); - - armnnDelegateInterpreter.reset(nullptr); -} - -template <typename T> -void DelegateOptionNoFallbackTest(tflite::TensorType tensorType, - const std::vector<armnn::BackendId>& backends, - std::vector<int32_t>& tensorShape, - std::vector<T>& inputValues, - std::vector<T>& expectedOutputValues, - const armnnDelegate::DelegateOptions& delegateOptions, - float quantScale = 1.0f, - int quantOffset = 0) -{ - using namespace tflite; - std::vector<char> modelBuffer = CreateCeilTfLiteModel(tensorType, - tensorShape, - quantScale, - quantOffset); - - 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 - std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> - theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), - armnnDelegate::TfLiteArmnnDelegateDelete); - CHECK(theArmnnDelegate != nullptr); - // Modify armnnDelegateInterpreter to use armnnDelegate - try - { - armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()); - } - catch (const armnn::Exception& e) - { - // Forward the exception message to std::cout - std::cout << e.what() << std::endl; - } - - // Set input data - armnnDelegate::FillInput(tfLiteInterpreter, 0, inputValues); - armnnDelegate::FillInput(armnnDelegateInterpreter, 0, inputValues); - - // Run EnqueueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, armnnDelegateInterpreter, tensorShape, expectedOutputValues); - - armnnDelegateInterpreter.reset(nullptr); -} - -} // anonymous namespace
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