diff options
author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-14 12:10:28 +0000 |
---|---|---|
committer | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-28 11:41:55 +0100 |
commit | ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9 (patch) | |
tree | a5b8e1ad68a2437f007338f0b6195ca5ed2bddc3 /delegate/test/StridedSliceTestHelper.hpp | |
parent | 9cb3466b677a1048b8abb24661e92c4c83fdda04 (diff) | |
download | armnn-ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9.tar.gz |
IVGCVSW-7555 Restructure Delegate
* New folders created:
* common is for common code where TfLite API is not used
* classic is for existing delegate implementations
* opaque is for new opaque delegate implementation,
* tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed
Diffstat (limited to 'delegate/test/StridedSliceTestHelper.hpp')
-rw-r--r-- | delegate/test/StridedSliceTestHelper.hpp | 221 |
1 files changed, 221 insertions, 0 deletions
diff --git a/delegate/test/StridedSliceTestHelper.hpp b/delegate/test/StridedSliceTestHelper.hpp new file mode 100644 index 0000000000..fde7e16c72 --- /dev/null +++ b/delegate/test/StridedSliceTestHelper.hpp @@ -0,0 +1,221 @@ +// +// 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> CreateStridedSliceTfLiteModel(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; + + flatbuffers::Offset<tflite::Buffer> buffers[6] = { + 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*>(endTensorData.data()), + sizeof(int32_t) * endTensorData.size())), + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(strideTensorData.data()), + sizeof(int32_t) * strideTensorData.size())), + CreateBuffer(flatBufferBuilder) + }; + + std::array<flatbuffers::Offset<Tensor>, 5> 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>(endTensorShape.data(), + endTensorShape.size()), + ::tflite::TensorType_INT32, + 3, + flatBufferBuilder.CreateString("end_tensor")); + tensors[3] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(strideTensorShape.data(), + strideTensorShape.size()), + ::tflite::TensorType_INT32, + 4, + flatBufferBuilder.CreateString("stride_tensor")); + tensors[4] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 5, + 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, 6)); + + 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 = CreateStridedSliceTfLiteModel( + ::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
\ No newline at end of file |