| // |
| // 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> CreateSpaceDepthTfLiteModel(tflite::BuiltinOperator spaceDepthOperatorCode, |
| tflite::TensorType tensorType, |
| const std::vector <int32_t>& inputTensorShape, |
| const std::vector <int32_t>& outputTensorShape, |
| int32_t blockSize) |
| { |
| using namespace tflite; |
| flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| |
| auto quantizationParameters = |
| CreateQuantizationParameters(flatBufferBuilder, |
| 0, |
| 0, |
| flatBufferBuilder.CreateVector<float>({ 1.0f }), |
| flatBufferBuilder.CreateVector<int64_t>({ 0 })); |
| |
| std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; |
| buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}))); |
| |
| std::array<flatbuffers::Offset<Tensor>, 2> tensors; |
| tensors[0] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), |
| inputTensorShape.size()), |
| tensorType, |
| 0, |
| flatBufferBuilder.CreateString("input"), |
| quantizationParameters); |
| tensors[1] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| outputTensorShape.size()), |
| tensorType, |
| 0, |
| flatBufferBuilder.CreateString("output"), |
| quantizationParameters); |
| |
| const std::vector<int32_t> operatorInputs({0}); |
| const std::vector<int32_t> operatorOutputs({1}); |
| |
| flatbuffers::Offset<Operator> spaceDepthOperator; |
| flatbuffers::Offset<flatbuffers::String> modelDescription; |
| flatbuffers::Offset<OperatorCode> operatorCode; |
| |
| switch (spaceDepthOperatorCode) |
| { |
| case tflite::BuiltinOperator_SPACE_TO_DEPTH: |
| spaceDepthOperator = |
| CreateOperator(flatBufferBuilder, |
| 0, |
| flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| BuiltinOptions_SpaceToDepthOptions, |
| CreateSpaceToDepthOptions(flatBufferBuilder, blockSize).Union()); |
| modelDescription = flatBufferBuilder.CreateString("ArmnnDelegate: SPACE_TO_DEPTH Operator Model"); |
| operatorCode = CreateOperatorCode(flatBufferBuilder, |
| tflite::BuiltinOperator_SPACE_TO_DEPTH); |
| break; |
| case tflite::BuiltinOperator_DEPTH_TO_SPACE: |
| spaceDepthOperator = |
| CreateOperator(flatBufferBuilder, |
| 0, |
| flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| BuiltinOptions_DepthToSpaceOptions, |
| CreateDepthToSpaceOptions(flatBufferBuilder, blockSize).Union()); |
| flatBufferBuilder.CreateString("ArmnnDelegate: DEPTH_TO_SPACE Operator Model"); |
| operatorCode = CreateOperatorCode(flatBufferBuilder, |
| tflite::BuiltinOperator_DEPTH_TO_SPACE); |
| break; |
| default: |
| 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(&spaceDepthOperator, 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 SpaceDepthTest(tflite::BuiltinOperator spaceDepthOperatorCode, |
| tflite::TensorType tensorType, |
| std::vector<armnn::BackendId>& backends, |
| std::vector<int32_t>& inputShape, |
| std::vector<int32_t>& outputShape, |
| std::vector<T>& inputValues, |
| std::vector<T>& expectedOutputValues, |
| int32_t blockSize = 2) |
| { |
| using namespace tflite; |
| std::vector<char> modelBuffer = CreateSpaceDepthTfLiteModel(spaceDepthOperatorCode, |
| tensorType, |
| inputShape, |
| outputShape, |
| blockSize); |
| |
| 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 |
| armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, inputValues); |
| armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, inputValues); |
| |
| // Run EnqueWorkload |
| CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); |
| CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); |
| |
| // Compare output data |
| armnnDelegate::CompareOutputData(tfLiteInterpreter, armnnDelegateInterpreter, outputShape, expectedOutputValues); |
| } |
| |
| } // anonymous namespace |