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Diffstat (limited to 'delegate/test/ReverseV2TestHelper.hpp')
| -rw-r--r-- | delegate/test/ReverseV2TestHelper.hpp | 148 |
1 files changed, 148 insertions, 0 deletions
diff --git a/delegate/test/ReverseV2TestHelper.hpp b/delegate/test/ReverseV2TestHelper.hpp new file mode 100644 index 0000000000..8c4acd1a7e --- /dev/null +++ b/delegate/test/ReverseV2TestHelper.hpp @@ -0,0 +1,148 @@ +// +// Copyright © 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TestUtils.hpp" + +#include <armnn_delegate.hpp> +#include <DelegateTestInterpreter.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/version.h> + +#include <schema_generated.h> + +#include <doctest/doctest.h> + +namespace +{ + std::vector<char> CreateReverseV2TfLiteModel(tflite::BuiltinOperator operatorCode, + tflite::TensorType inputTensorType, + const std::vector <int32_t>& inputTensorShape, + const std::vector <int32_t>& axisTensorData, + const std::vector <int32_t>& axisTensorShape, + const std::vector <int32_t>& outputTensorShape) + { + 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, + flatBufferBuilder.CreateVector( + reinterpret_cast<const uint8_t*>(axisTensorData.data()), + sizeof(int32_t) * axisTensorData.size()))); + buffers.push_back(CreateBuffer(flatBufferBuilder)); + + std::array<flatbuffers::Offset<Tensor>, 3> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), + inputTensorShape.size()), + inputTensorType, + 1, + flatBufferBuilder.CreateString("input_tensor")); + + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(axisTensorShape.data(), + axisTensorShape.size()), + TensorType_INT32, + 2, + flatBufferBuilder.CreateString("axis_input_tensor")); + + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + inputTensorType, + 3, + flatBufferBuilder.CreateString("output_tensor")); + + // Create Operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE; + flatbuffers::Offset<void> operatorBuiltinOption = 0; + + const std::vector<int> operatorInputs{0, 1}; + const std::vector<int> operatorOutputs{2}; + flatbuffers::Offset <Operator> reverseV2Operator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOption); + + 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(&reverseV2Operator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: ReverseV2 Operator Model"); + flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, operatorCode); + + flatbuffers::Offset <Model> flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&opCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); + + flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); + + return std::vector<char>(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); + } + + void ReverseV2FP32TestImpl(tflite::BuiltinOperator operatorCode, + std::vector<armnn::BackendId>& backends, + std::vector<float>& inputValues, + std::vector<int32_t> inputShape, + std::vector<int32_t> axisValues, + std::vector<int32_t> axisShapeDims, + std::vector<float>& expectedOutputValues, + std::vector<int32_t> expectedOutputShape) + { + using namespace delegateTestInterpreter; + + std::vector<char> modelBuffer = CreateReverseV2TfLiteModel(operatorCode, + ::tflite::TensorType_FLOAT32, + inputShape, + axisValues, + axisShapeDims, + expectedOutputShape); + + // Setup interpreter with just TFLite Runtime. + auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); + CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(tfLiteInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk); + CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(axisValues, 1) == kTfLiteOk); + CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); + std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0); + std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); + + // Setup interpreter with Arm NN Delegate applied. + auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); + CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(armnnInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk); + CHECK(armnnInterpreter.FillInputTensor<int32_t>(axisValues, 1) == kTfLiteOk); + CHECK(armnnInterpreter.Invoke() == kTfLiteOk); + std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0); + std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); + + armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); + armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape); + + tfLiteInterpreter.Cleanup(); + armnnInterpreter.Cleanup(); + } + +} // anonymous namespace |