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Diffstat (limited to 'delegate/src/test/RoundTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/RoundTestHelper.hpp | 163 |
1 files changed, 0 insertions, 163 deletions
diff --git a/delegate/src/test/RoundTestHelper.hpp b/delegate/src/test/RoundTestHelper.hpp deleted file mode 100644 index 6638607dcf..0000000000 --- a/delegate/src/test/RoundTestHelper.hpp +++ /dev/null @@ -1,163 +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> CreateRoundTfLiteModel(tflite::BuiltinOperator roundOperatorCode, - 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)); - - 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, - 1, - flatBufferBuilder.CreateString("input"), - quantizationParameters); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), - tensorShape.size()), - tensorType, - 2, - flatBufferBuilder.CreateString("output"), - quantizationParameters); - - const std::vector<int32_t> operatorInputs({0}); - const std::vector<int32_t> operatorOutputs({1}); - - flatbuffers::Offset<Operator> roundOperator; - flatbuffers::Offset<flatbuffers::String> modelDescription; - flatbuffers::Offset<OperatorCode> operatorCode; - - switch (roundOperatorCode) - { - case tflite::BuiltinOperator_FLOOR: - default: - roundOperator = - CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size())); - modelDescription = flatBufferBuilder.CreateString("ArmnnDelegate: Floor Operator Model"); - operatorCode = CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_FLOOR); - break; - } - 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(&roundOperator, 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 RoundTest(tflite::BuiltinOperator roundOperatorCode, - tflite::TensorType tensorType, - std::vector<armnn::BackendId>& backends, - std::vector<int32_t>& shape, - std::vector<T>& inputValues, - std::vector<T>& expectedOutputValues, - float quantScale = 1.0f, - int quantOffset = 0) -{ - using namespace tflite; - std::vector<char> modelBuffer = CreateRoundTfLiteModel(roundOperatorCode, - tensorType, - 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<T>(tfLiteDelegate, - armnnDelegate, - shape, - expectedOutputValues, - 0); - - tfLiteDelegate.reset(nullptr); - armnnDelegate.reset(nullptr); -} - -} // anonymous namespace |