| // |
| // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include "TestUtils.hpp" |
| |
| #include <armnn_delegate.hpp> |
| #include <armnn/DescriptorsFwd.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> |
| |
| #include <string> |
| |
| namespace |
| { |
| |
| struct StridedSliceParams |
| { |
| StridedSliceParams(std::vector<int32_t>& inputTensorShape, |
| std::vector<int32_t>& beginTensorData, |
| std::vector<int32_t>& endTensorData, |
| std::vector<int32_t>& strideTensorData, |
| std::vector<int32_t>& outputTensorShape, |
| armnn::StridedSliceDescriptor& descriptor) |
| : m_InputTensorShape(inputTensorShape), |
| m_BeginTensorData(beginTensorData), |
| m_EndTensorData(endTensorData), |
| m_StrideTensorData(strideTensorData), |
| m_OutputTensorShape(outputTensorShape), |
| m_Descriptor (descriptor) {} |
| |
| std::vector<int32_t> m_InputTensorShape; |
| std::vector<int32_t> m_BeginTensorData; |
| std::vector<int32_t> m_EndTensorData; |
| std::vector<int32_t> m_StrideTensorData; |
| std::vector<int32_t> m_OutputTensorShape; |
| armnn::StridedSliceDescriptor m_Descriptor; |
| }; |
| |
| std::vector<char> CreateSliceTfLiteModel(tflite::TensorType tensorType, |
| const std::vector<int32_t>& inputTensorShape, |
| const std::vector<int32_t>& beginTensorData, |
| const std::vector<int32_t>& endTensorData, |
| const std::vector<int32_t>& strideTensorData, |
| const std::vector<int32_t>& beginTensorShape, |
| const std::vector<int32_t>& endTensorShape, |
| const std::vector<int32_t>& strideTensorShape, |
| const std::vector<int32_t>& outputTensorShape, |
| const int32_t beginMask, |
| const int32_t endMask, |
| const int32_t ellipsisMask, |
| const int32_t newAxisMask, |
| const int32_t ShrinkAxisMask, |
| const armnn::DataLayout& dataLayout) |
| { |
| using namespace tflite; |
| flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| |
| std::array<flatbuffers::Offset<tflite::Buffer>, 4> buffers; |
| buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); |
| buffers[1] = CreateBuffer(flatBufferBuilder, |
| flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(beginTensorData.data()), |
| sizeof(int32_t) * beginTensorData.size())); |
| buffers[2] = CreateBuffer(flatBufferBuilder, |
| flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(endTensorData.data()), |
| sizeof(int32_t) * endTensorData.size())); |
| buffers[3] = CreateBuffer(flatBufferBuilder, |
| flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(strideTensorData.data()), |
| sizeof(int32_t) * strideTensorData.size())); |
| |
| std::array<flatbuffers::Offset<Tensor>, 5> tensors; |
| tensors[0] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), |
| inputTensorShape.size()), |
| tensorType, |
| 0, |
| flatBufferBuilder.CreateString("input")); |
| tensors[1] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(beginTensorShape.data(), |
| beginTensorShape.size()), |
| ::tflite::TensorType_INT32, |
| 1, |
| flatBufferBuilder.CreateString("begin_tensor")); |
| tensors[2] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(endTensorShape.data(), |
| endTensorShape.size()), |
| ::tflite::TensorType_INT32, |
| 2, |
| flatBufferBuilder.CreateString("end_tensor")); |
| tensors[3] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(strideTensorShape.data(), |
| strideTensorShape.size()), |
| ::tflite::TensorType_INT32, |
| 3, |
| flatBufferBuilder.CreateString("stride_tensor")); |
| tensors[4] = CreateTensor(flatBufferBuilder, |
| flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| outputTensorShape.size()), |
| tensorType, |
| 0, |
| flatBufferBuilder.CreateString("output")); |
| |
| |
| // create operator |
| tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_StridedSliceOptions; |
| flatbuffers::Offset<void> operatorBuiltinOptions = CreateStridedSliceOptions(flatBufferBuilder, |
| beginMask, |
| endMask, |
| ellipsisMask, |
| newAxisMask, |
| ShrinkAxisMask).Union(); |
| |
| const std::vector<int> operatorInputs{ 0, 1, 2, 3 }; |
| const std::vector<int> operatorOutputs{ 4 }; |
| flatbuffers::Offset <Operator> sliceOperator = |
| 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, 2, 3 }; |
| const std::vector<int> subgraphOutputs{ 4 }; |
| 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(&sliceOperator, 1)); |
| |
| flatbuffers::Offset <flatbuffers::String> modelDescription = |
| flatBufferBuilder.CreateString("ArmnnDelegate: StridedSlice Operator Model"); |
| flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, |
| BuiltinOperator_STRIDED_SLICE); |
| |
| 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 StridedSliceTestImpl(std::vector<armnn::BackendId>& backends, |
| std::vector<T>& inputValues, |
| std::vector<T>& expectedOutputValues, |
| std::vector<int32_t>& beginTensorData, |
| std::vector<int32_t>& endTensorData, |
| std::vector<int32_t>& strideTensorData, |
| std::vector<int32_t>& inputTensorShape, |
| std::vector<int32_t>& beginTensorShape, |
| std::vector<int32_t>& endTensorShape, |
| std::vector<int32_t>& strideTensorShape, |
| std::vector<int32_t>& outputTensorShape, |
| const int32_t beginMask = 0, |
| const int32_t endMask = 0, |
| const int32_t ellipsisMask = 0, |
| const int32_t newAxisMask = 0, |
| const int32_t ShrinkAxisMask = 0, |
| const armnn::DataLayout& dataLayout = armnn::DataLayout::NHWC) |
| { |
| using namespace tflite; |
| std::vector<char> modelBuffer = CreateSliceTfLiteModel( |
| ::tflite::TensorType_FLOAT32, |
| inputTensorShape, |
| beginTensorData, |
| endTensorData, |
| strideTensorData, |
| beginTensorShape, |
| endTensorShape, |
| strideTensorShape, |
| outputTensorShape, |
| beginMask, |
| endMask, |
| ellipsisMask, |
| newAxisMask, |
| ShrinkAxisMask, |
| dataLayout); |
| |
| auto 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, |
| outputTensorShape, |
| expectedOutputValues); |
| |
| tfLiteDelegate.reset(nullptr); |
| armnnDelegate.reset(nullptr); |
| } // End of StridedSlice Test |
| |
| } // anonymous namespace |