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Diffstat (limited to 'delegate/src/test/ShapeTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/ShapeTestHelper.hpp | 171 |
1 files changed, 171 insertions, 0 deletions
diff --git a/delegate/src/test/ShapeTestHelper.hpp b/delegate/src/test/ShapeTestHelper.hpp new file mode 100644 index 0000000000..854c5084aa --- /dev/null +++ b/delegate/src/test/ShapeTestHelper.hpp @@ -0,0 +1,171 @@ +// +// Copyright © 2021 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> CreateShapeTfLiteModel(tflite::TensorType inputTensorType, + tflite::TensorType outputTensorType, + const std::vector<int32_t>& inputTensorShape, + 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, flatBufferBuilder.CreateVector({}))); + + 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>(inputTensorShape.data(), + inputTensorShape.size()), + inputTensorType, + 0, + flatBufferBuilder.CreateString("input"), + quantizationParameters); + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + outputTensorType, + 0, + flatBufferBuilder.CreateString("output"), + quantizationParameters); + + const std::vector<int32_t> operatorInputs({ 0 }); + const std::vector<int32_t> operatorOutputs({ 1 }); + + flatbuffers::Offset<Operator> shapeOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), + operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), + operatorOutputs.size()), + BuiltinOptions_ShapeOptions, + CreateShapeOptions(flatBufferBuilder, outputTensorType).Union()); + + flatbuffers::Offset<flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: SHAPE Operator Model"); + + flatbuffers::Offset<OperatorCode> operatorCode = + CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_SHAPE); + + 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(&shapeOperator, 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 ShapeTest(tflite::TensorType inputTensorType, + tflite::TensorType outputTensorType, + std::vector<armnn::BackendId>& backends, + std::vector<int32_t>& inputShape, + std::vector<T>& inputValues, + std::vector<K>& expectedOutputValues, + std::vector<int32_t>& expectedOutputShape, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateShapeTfLiteModel(inputTensorType, + outputTensorType, + inputShape, + expectedOutputShape, + 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, + expectedOutputShape, + expectedOutputValues, + 0); + + tfLiteDelegate.reset(nullptr); + armnnDelegate.reset(nullptr); +} + +} // anonymous namespace |