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Diffstat (limited to 'delegate/src/test/BatchSpaceTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/BatchSpaceTestHelper.hpp | 216 |
1 files changed, 216 insertions, 0 deletions
diff --git a/delegate/src/test/BatchSpaceTestHelper.hpp b/delegate/src/test/BatchSpaceTestHelper.hpp new file mode 100644 index 0000000000..464a5d9cbe --- /dev/null +++ b/delegate/src/test/BatchSpaceTestHelper.hpp @@ -0,0 +1,216 @@ +// +// 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> CreateBatchSpaceTfLiteModel(tflite::BuiltinOperator batchSpaceOperatorCode, + tflite::TensorType tensorType, + std::vector<int32_t>& inputTensorShape, + std::vector <int32_t>& outputTensorShape, + std::vector<unsigned int>& blockData, + std::vector<std::pair<unsigned int, unsigned int>>& cropsPadData, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::array<flatbuffers::Offset<tflite::Buffer>, 3> buffers; + buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); + buffers[1] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(blockData.data()), + sizeof(int32_t) * blockData.size())); + buffers[2] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(cropsPadData.data()), + sizeof(int64_t) * cropsPadData.size())); + + auto quantizationParameters = + CreateQuantizationParameters(flatBufferBuilder, + 0, + 0, + flatBufferBuilder.CreateVector<float>({ quantScale }), + flatBufferBuilder.CreateVector<int64_t>({ quantOffset })); + + std::string cropsOrPadding = + batchSpaceOperatorCode == tflite::BuiltinOperator_BATCH_TO_SPACE_ND ? "crops" : "padding"; + + std::vector<int32_t> blockShape { 2 }; + std::vector<int32_t> cropsOrPaddingShape { 2, 2 }; + + std::array<flatbuffers::Offset<Tensor>, 4> 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>(blockShape.data(), + blockShape.size()), + ::tflite::TensorType_INT32, + 1, + flatBufferBuilder.CreateString("block"), + quantizationParameters); + + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(cropsOrPaddingShape.data(), + cropsOrPaddingShape.size()), + ::tflite::TensorType_INT32, + 2, + flatBufferBuilder.CreateString(cropsOrPadding), + quantizationParameters); + + // Create output tensor + tensors[3] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output"), + quantizationParameters); + + // Create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE; + flatbuffers::Offset<void> operatorBuiltinOptions = 0; + switch (batchSpaceOperatorCode) + { + case tflite::BuiltinOperator_BATCH_TO_SPACE_ND: + { + operatorBuiltinOptionsType = tflite::BuiltinOptions_BatchToSpaceNDOptions; + operatorBuiltinOptions = CreateBatchToSpaceNDOptions(flatBufferBuilder).Union(); + break; + } + case tflite::BuiltinOperator_SPACE_TO_BATCH_ND: + { + operatorBuiltinOptionsType = tflite::BuiltinOptions_SpaceToBatchNDOptions; + operatorBuiltinOptions = CreateSpaceToBatchNDOptions(flatBufferBuilder).Union(); + break; + } + default: + break; + } + + const std::vector<int> operatorInputs{ {0, 1, 2} }; + const std::vector<int> operatorOutputs{ 3 }; + flatbuffers::Offset <Operator> batchSpaceOperator = + 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(&batchSpaceOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: BatchSpace Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, batchSpaceOperatorCode); + + 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 BatchSpaceTest(tflite::BuiltinOperator controlOperatorCode, + tflite::TensorType tensorType, + std::vector<armnn::BackendId>& backends, + std::vector<int32_t>& inputShape, + std::vector<int32_t>& expectedOutputShape, + std::vector<T>& inputValues, + std::vector<unsigned int>& blockShapeValues, + std::vector<std::pair<unsigned int, unsigned int>>& cropsPaddingValues, + std::vector<T>& expectedOutputValues, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateBatchSpaceTfLiteModel(controlOperatorCode, + tensorType, + inputShape, + expectedOutputShape, + blockShapeValues, + cropsPaddingValues, + quantScale, + quantOffset); + + 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<T>(tfLiteInterpreter, + armnnDelegateInterpreter, + expectedOutputShape, + expectedOutputValues); + + armnnDelegateInterpreter.reset(nullptr); + tfLiteInterpreter.reset(nullptr); +} + +} // anonymous namespace
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