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author | Sadik Armagan <sadik.armagan@arm.com> | 2021-01-20 17:48:07 +0000 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2021-01-26 12:11:46 +0000 |
commit | 89c5a9e6ecfa169512c43e659b1833f9a3c41d90 (patch) | |
tree | ba7314e4cece46bfb1c879e3ac6303010ca234f0 /delegate/src/test/SpaceDepthTestHelper.hpp | |
parent | 4b227bb4e2d83f0e3125a2a8fcc6834b3b98b44d (diff) | |
download | armnn-89c5a9e6ecfa169512c43e659b1833f9a3c41d90.tar.gz |
IVGCVSW-5391 'ArmNN TfLiteDelegate: Implement the Space/Depth operators'
* Added DEPTH_TO_SPACE and SPACE_TO_DEPTH operators support
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I2595f759181bd7339127e7b114b850b534210dd5
Diffstat (limited to 'delegate/src/test/SpaceDepthTestHelper.hpp')
-rw-r--r-- | delegate/src/test/SpaceDepthTestHelper.hpp | 166 |
1 files changed, 166 insertions, 0 deletions
diff --git a/delegate/src/test/SpaceDepthTestHelper.hpp b/delegate/src/test/SpaceDepthTestHelper.hpp new file mode 100644 index 0000000000..d9a783c6a7 --- /dev/null +++ b/delegate/src/test/SpaceDepthTestHelper.hpp @@ -0,0 +1,166 @@ +// +// 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 |