diff options
Diffstat (limited to 'delegate/test/SliceTestHelper.hpp')
| -rw-r--r-- | delegate/test/SliceTestHelper.hpp | 183 |
1 files changed, 183 insertions, 0 deletions
diff --git a/delegate/test/SliceTestHelper.hpp b/delegate/test/SliceTestHelper.hpp new file mode 100644 index 0000000000..c938fad31b --- /dev/null +++ b/delegate/test/SliceTestHelper.hpp @@ -0,0 +1,183 @@ +// +// Copyright © 2022-2023 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 <schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +#include <string> + +namespace +{ + +std::vector<char> CreateSliceTfLiteModel(tflite::TensorType tensorType, + const std::vector<int32_t>& inputTensorShape, + const std::vector<int32_t>& beginTensorData, + const std::vector<int32_t>& sizeTensorData, + const std::vector<int32_t>& beginTensorShape, + const std::vector<int32_t>& sizeTensorShape, + const std::vector<int32_t>& outputTensorShape) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + flatbuffers::Offset<tflite::Buffer> buffers[5] = { + CreateBuffer(flatBufferBuilder), + CreateBuffer(flatBufferBuilder), + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(beginTensorData.data()), + sizeof(int32_t) * beginTensorData.size())), + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(sizeTensorData.data()), + sizeof(int32_t) * sizeTensorData.size())), + CreateBuffer(flatBufferBuilder) + }; + + std::array<flatbuffers::Offset<Tensor>, 4> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), + inputTensorShape.size()), + tensorType, + 1, + flatBufferBuilder.CreateString("input")); + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(beginTensorShape.data(), + beginTensorShape.size()), + ::tflite::TensorType_INT32, + 2, + flatBufferBuilder.CreateString("begin_tensor")); + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(sizeTensorShape.data(), + sizeTensorShape.size()), + ::tflite::TensorType_INT32, + 3, + flatBufferBuilder.CreateString("size_tensor")); + tensors[3] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 4, + flatBufferBuilder.CreateString("output")); + + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_SliceOptions; + flatbuffers::Offset<void> operatorBuiltinOptions = CreateSliceOptions(flatBufferBuilder).Union(); + + const std::vector<int> operatorInputs{ 0, 1, 2 }; + const std::vector<int> operatorOutputs{ 3 }; + 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 }; + const std::vector<int> subgraphOutputs{ 3 }; + 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: Slice Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, + BuiltinOperator_SLICE); + + flatbuffers::Offset <Model> flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&operatorCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers, 5)); + + flatBufferBuilder.Finish(flatbufferModel); + + return std::vector<char>(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); +} + +template <typename T> +void SliceTestImpl(std::vector<armnn::BackendId>& backends, + std::vector<T>& inputValues, + std::vector<T>& expectedOutputValues, + std::vector<int32_t>& beginTensorData, + std::vector<int32_t>& sizeTensorData, + std::vector<int32_t>& inputTensorShape, + std::vector<int32_t>& beginTensorShape, + std::vector<int32_t>& sizeTensorShape, + std::vector<int32_t>& outputTensorShape) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateSliceTfLiteModel( + ::tflite::TensorType_FLOAT32, + inputTensorShape, + beginTensorData, + sizeTensorData, + beginTensorShape, + sizeTensorShape, + outputTensorShape); + + 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 Slice Test + +} // anonymous namespace
\ No newline at end of file |