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Diffstat (limited to 'delegate/src/test/ComparisonTestHelper.hpp')
-rw-r--r-- | delegate/src/test/ComparisonTestHelper.hpp | 238 |
1 files changed, 0 insertions, 238 deletions
diff --git a/delegate/src/test/ComparisonTestHelper.hpp b/delegate/src/test/ComparisonTestHelper.hpp deleted file mode 100644 index db337f9f8a..0000000000 --- a/delegate/src/test/ComparisonTestHelper.hpp +++ /dev/null @@ -1,238 +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> CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode, - tflite::TensorType tensorType, - const std::vector <int32_t>& input0TensorShape, - const std::vector <int32_t>& input1TensorShape, - const std::vector <int32_t>& outputTensorShape, - 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)); - - auto quantizationParameters = - CreateQuantizationParameters(flatBufferBuilder, - 0, - 0, - flatBufferBuilder.CreateVector<float>({ quantScale }), - flatBufferBuilder.CreateVector<int64_t>({ quantOffset })); - - std::array<flatbuffers::Offset<Tensor>, 3> tensors; - tensors[0] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), - input0TensorShape.size()), - tensorType, - 1, - flatBufferBuilder.CreateString("input_0"), - quantizationParameters); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(), - input1TensorShape.size()), - tensorType, - 2, - flatBufferBuilder.CreateString("input_1"), - quantizationParameters); - tensors[2] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), - outputTensorShape.size()), - ::tflite::TensorType_BOOL, - 3); - - // create operator - tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;; - flatbuffers::Offset<void> operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union(); - switch (comparisonOperatorCode) - { - case BuiltinOperator_EQUAL: - { - operatorBuiltinOptionsType = BuiltinOptions_EqualOptions; - operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union(); - break; - } - case BuiltinOperator_NOT_EQUAL: - { - operatorBuiltinOptionsType = BuiltinOptions_NotEqualOptions; - operatorBuiltinOptions = CreateNotEqualOptions(flatBufferBuilder).Union(); - break; - } - case BuiltinOperator_GREATER: - { - operatorBuiltinOptionsType = BuiltinOptions_GreaterOptions; - operatorBuiltinOptions = CreateGreaterOptions(flatBufferBuilder).Union(); - break; - } - case BuiltinOperator_GREATER_EQUAL: - { - operatorBuiltinOptionsType = BuiltinOptions_GreaterEqualOptions; - operatorBuiltinOptions = CreateGreaterEqualOptions(flatBufferBuilder).Union(); - break; - } - case BuiltinOperator_LESS: - { - operatorBuiltinOptionsType = BuiltinOptions_LessOptions; - operatorBuiltinOptions = CreateLessOptions(flatBufferBuilder).Union(); - break; - } - case BuiltinOperator_LESS_EQUAL: - { - operatorBuiltinOptionsType = BuiltinOptions_LessEqualOptions; - operatorBuiltinOptions = CreateLessEqualOptions(flatBufferBuilder).Union(); - break; - } - default: - break; - } - const std::vector<int32_t> operatorInputs{0, 1}; - const std::vector<int32_t> operatorOutputs{2}; - flatbuffers::Offset <Operator> comparisonOperator = - CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), - operatorBuiltinOptionsType, - operatorBuiltinOptions); - - const std::vector<int> subgraphInputs{0, 1}; - const std::vector<int> subgraphOutputs{2}; - 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(&comparisonOperator, 1)); - - flatbuffers::Offset <flatbuffers::String> modelDescription = - flatBufferBuilder.CreateString("ArmnnDelegate: Comparison Operator Model"); - flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, comparisonOperatorCode); - - 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 ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode, - tflite::TensorType tensorType, - std::vector<armnn::BackendId>& backends, - std::vector<int32_t>& input0Shape, - std::vector<int32_t>& input1Shape, - std::vector<int32_t>& outputShape, - std::vector<T>& input0Values, - std::vector<T>& input1Values, - std::vector<bool>& expectedOutputValues, - float quantScale = 1.0f, - int quantOffset = 0) -{ - using namespace tflite; - std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode, - tensorType, - input0Shape, - input1Shape, - outputShape, - 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 - 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 - auto tfLiteDelegateInput0Id = tfLiteInterpreter->inputs()[0]; - auto tfLiteDelageInput0Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput0Id); - for (unsigned int i = 0; i < input0Values.size(); ++i) - { - tfLiteDelageInput0Data[i] = input0Values[i]; - } - - auto tfLiteDelegateInput1Id = tfLiteInterpreter->inputs()[1]; - auto tfLiteDelageInput1Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput1Id); - for (unsigned int i = 0; i < input1Values.size(); ++i) - { - tfLiteDelageInput1Data[i] = input1Values[i]; - } - - auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0]; - auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput0Id); - for (unsigned int i = 0; i < input0Values.size(); ++i) - { - armnnDelegateInput0Data[i] = input0Values[i]; - } - - auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1]; - auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput1Id); - for (unsigned int i = 0; i < input1Values.size(); ++i) - { - armnnDelegateInput1Data[i] = input1Values[i]; - } - - // Run EnqueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - // Compare output data - auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteDelageOutputData = 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 , tfLiteDelageOutputData , expectedOutputValues.size()); - armnnDelegate::CompareData(tfLiteDelageOutputData, armnnDelegateOutputData, expectedOutputValues.size()); -} - -} // anonymous namespace
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